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--- en:drones:platforms:navigation [2021/01/21 10:00] – oleg
+++ en:drones:platforms:navigation [Unknown date] (current) – external edit (Unknown date) 127.0.0.1
@@ Line 7: / Line 7: @@
 ==== Introduction to the GNSS ====
 Global Navigation Satellite Systems (short GNSS) are useful to position an object (here drone) in 3D space, mostly outdoors.\\
-Actually, 2D, planar (longitude/latitude) positioning is quite good and in most applications suitable, vertical positioning used to be inaccurate, so most drones use a different strategy to check their altitude, mostly measuring atmospheric pressure changes (using barometer). UAVs usually operate on long distances (some meter to even thousands of kilometres), so satellite-based positioning seems to be a reasonable choice. As receivers became cheaper, they appeared in almost all drones that operate in autonomous mode and in many of those that are manually controlled, to smoothen operations, provide rescue features (i.e. Return to Home function) to ensure basic and advanced features like, i.e. geofencing, collision avoidance and so on. \\ Current, modern GNSS receivers operate with multiple constellations parallel, delivering even better accuracy of the planar positioning. Still to get reliable positioning with high accuracy, one needs to ensure good satellite visibility. \\
+Actually, 2D, planar (longitude/latitude) positioning is quite good, and in most applications suitable, vertical positioning used to be inaccurate, so most drones use a different strategy to check their altitude, mostly measuring atmospheric pressure changes (using barometer). UAVs usually operate on long distances (some meters to even thousands of kilometers), so satellite-based positioning seems to be a reasonable choice. As receivers became cheaper, they appeared in almost all drones that operate in autonomous mode and in many of those that are manually controlled, to smoothen operations, provide rescue features (i.e. Return to Home function) to ensure basic and advanced features like, i.e. geofencing, collision avoidance and so on. \\ Current, modern GNSS receivers operate with multiple constellations parallel, delivering even better accuracy of the planar positioning. Still to get reliable positioning with high accuracy, one needs to ensure good satellite visibility. \\
-<note important>There is several factors, decreasing positioning that every UAV operator should be aware.</note>
+<note important>There are several factors, decreasing positioning that every UAV operator should be aware.</note>
-There is a number of factors, decreasing positioning that every UAV operator should be aware, as they may lead to incidents and accidents:
+There is a number of factors, decreasing positioning that every UAV operator should be aware of, as they may lead to incidents and accidents:
-  * Time synchronisation - it is crucial to have common time-base for both sender and receiver. Time synchronisation occurs during so-called "obtaining fix" and in short is based on error minimisation between position estimation based on at least four (usually much more) satellites. Time synchronisation is also performed periodically, as satellite time-base is considered as a reference one, but receiver implementation varies in quality. Thus you may observe periodical degradation of the accuracy in reference conditions, because of the de-synchronisation of the receiver.
+  * Time synchronization - it is crucial to have a common time-base for both sender and receiver. Time synchronization occurs during the so-called "obtaining fix" and in short is based on error minimization between position estimation based on at least four (usually much more) satellites. Time synchronization is also performed periodically, as satellite time-base is considered as a reference one, but receiver implementation varies in quality. Thus you may observe periodical degradation of the accuracy in reference conditions, because of the de-synchronization of the receiver.
-  * Selected Availability (SA) - as introduced by the constellation owner to interfere radio signal of the satellites, thus decrease the accuracy the controlled way. This was widely used in case of the American GPS (Navstar) until the first war in the Persian Gulf when US Army had to switch to the commercial receivers (affected by SA) because of lacks of delivery of the military products (that had SA corrected internally). Since then, GPS positioning became much more useful because of the increased accuracy of the positioning, once SA was disabled or at least reduced.
+  * Selected Availability (SA) - as introduced by the constellation owner to interfere radio signal of the satellites, thus decrease the accuracy of the controlled way. This was widely used in the case of the American GPS (Navstar) until the first war in the Persian Gulf when US Army had to switch to the commercial receivers (affected by SA) because of lack of delivery of the military products (that had SA corrected internally). Since then, GPS positioning became much more useful because of the increased accuracy of the positioning, once SA was disabled or at least reduced.
-  * Ionosphere delay - as solar radiation has a strong impact on the ionic sphere of the Earth, radio signal passing through it may experience deflection (thus delays). That is the second, natural phenomena, decreasing accuracy. Solar radiation is given by the KP Index that can be read close to realtime and is related to solar activity. With KP over 3, flying UAV is not advised, or at least try to avoid flying in a tight environment when filming, i.e. northern lights as you may experience sudden shifts of your drone even some dozen of meters. You can read the current KP index and forecast, i.e. here: [[http://www.aurora-service.eu/aurora-school/all-about-the-kp-index/|Aurora Service]].
+  * Ionosphere delay - as solar radiation has a strong impact on the ionic sphere of the Earth, radio signal passing through it may experience deflection (thus delays). That is the second, natural phenomenon, decreasing accuracy. Solar radiation is given by the KP Index that can be read close to real-time and is related to solar activity. With KP over 3, flying UAV is not advised, or at least try to avoid flying in a tight environment when filming, i.e. northern lights as you may experience sudden shifts of your drone even some dozen of meters. You can read the current KP index and forecast, i.e. here: [[http://www.aurora-service.eu/aurora-school/all-about-the-kp-index/|Aurora Service]].
   * Troposphere - has some minor impact (comparing to the mentioned above) yet it does exist. The troposphere is relatively thin, comparing, i.e. to the ionosphere. Advanced GPS receivers may use a built-in calendar to provide thermal compensation, based on the time and current position as using average temperature for the obtained location.
   * Ephemeris error - sometimes, satellite orbit is altered and satellite is not where it is intended to be, so the distance between satellite and receiver is affected. GPS receiver is unaware of the position deviation; thus, it has an impact on the positioning accuracy.
-Some of those phenomena can be handled tricky way (i.e. ionosphere deflection impacts different way signals with different frequency thus Glonass system can handle this issue almost real-time by calculating error, differential-based way) while others can be applied post-factum or live using corrections sent via other channels.\\
+Some of those phenomena can be handled in a tricky way (i.e. ionosphere deflection impacts different way signals with different frequency thus Glonass system can handle this issue almost real-time by calculating error, differential-based way) while others can be applied post-factum or live using corrections sent via other channels.\\
-The detailed description of the impact of the aforementioned factors for accuracy and performance is presented below in section **GNSS Performance and Accuracy**.
+A detailed description of the impact of the aforementioned factors for accuracy and performance is presented below in section **GNSS Performance and Accuracy**.
 ==== GNSS History ====
@@ Line 28: / Line 28: @@
   * In the early 1970s, the Department of Defense (DoD) wanted to ensure a robust, stable satellite navigation system would be available. Embracing previous ideas from Navy scientists, the DoD decided to use satellites to support their proposed navigation system. DoD then followed through and launched its first Navigation System with Timing and Ranging (NAVSTAR) satellite in 1978.
   * The 24 satellite system became fully operational in 1993. When selective availability was lifted in 2000, GPS had about a five-meter (16 ft) accuracy.
-  * The latest stage of accuracy enhancement uses the L5 band and is now fully deployed. GPS receivers released in 2018 that use the L5 band can have much higher accuracy, pinpointing to within 30 centimetres or 11.8 inches.
+  * The latest stage of accuracy enhancement uses the L5 band and is now fully deployed. GPS receivers released in 2018 that use the L5 band can have much higher accuracy, pinpointing to within 30 centimeters or 11.8 inches.
 <figure label>
-{{ :en:drones:platforms:gps.gif?direct&536 | title}}
+{{ :en:drones:platforms:gps_constellation.jpg?direct&400 | title}}
 <caption>GPS Constellation in space</caption>
 </figure>
@@ Line 37: / Line 37: @@
 === RF GLONASS ===
 {{ :en:drones:platforms:glonass.png}}
-  * The first proposal to use satellites for navigation was made by V.S.Shebashevich in 1957. This idea was born during the investigation of the possible application of radio-astronomy technologies for aeronavigation. Further investigations were conducted in a number of the Soviet institutions to increase the accuracy of navigation definitions, global support, daily application and independence from weather conditions. The research results were used in 1963 for an R&D project on the first Soviet low-orbit “Cicada” system.
+  * The first proposal to use satellites for navigation was made by V.S.Shebashevich in 1957. This idea was born during the investigation of the possible application of radio-astronomy technologies for aeronavigation. Further investigations were conducted in a number of the Soviet institutions to increase the accuracy of navigation definitions, global support, daily application, and independence from weather conditions. The research results were used in 1963 for an R&D project on the first Soviet low-orbit “Cicada” system.
   * In 1967 the first navigation Soviet satellite "Cosmos-192" was launched. The navigation satellite provided continuous radio navigation signal transmission on 150 and 400 MHz during its active lifetime.
   * he “Cicada” system of four satellites was commissioned in 1979.  The GLONASS system was formally declared operational in 1993. In 1995 it was brought to a fully operational constellation (24 GLONASS satellites of the first generation).
-  * In 2008 “Cicada” and “Cicada-M” users started to use GLONASS system and the operation of those systems was halted. The low-orbit systems couldn't meet the requirements of a great number of users.
+  * In 2008 “Cicada” and “Cicada-M” users started to use the GLONASS system and the operation of those systems was halted. The low-orbit systems couldn't meet the requirements of a great number of users.
 <figure label>
-{{ :en:drones:platforms:glonass.gif?direct&536 | title}}
+{{ :en:drones:platforms:glo_constellation.jpg?direct&400 | title}}
 <caption> Glonass Constellation in space</caption>
 </figure>
@@ Line 48: / Line 48: @@
 === EU GALILEO ===
 {{ :en:drones:platforms:galileo.png}}
-  * The first Galileo test satellite, the GIOVE-A, was launched 28 December 2005, while the first satellite to be part of the operating system was launched on 21 October 2011.
+  * The first Galileo test satellite, the GIOVE-A, was launched on 28 December 2005, while the first satellite to be part of the operating system was launched on 21 October 2011.
   * As of July 2018, 26 of the planned 30 active satellites are in orbit. Galileo started offering Early Operational Capability (EOC) on 15 December 2016, providing initial services with a weak signal and is expected to reach Full Operational Capability (FOC) in 2019.
   * The complete 30-satellite Galileo system (24 operational and 6 active spares) is expected by 2020.
   * It is expected that the next generation of satellites will begin to become operational by 2025 to replace older equipment. Older systems can then be used for backup capabilities.
 <figure label>
-{{ :en:drones:platforms:galileo.gif?direct&536 | title}}
+{{ :en:drones:platforms:gal_constellation.jpg?direct&400 | title}}
 <caption> Galileo Constellation in space</caption>
 </figure>
@@ Line 59: / Line 60: @@
 === CHINA BeiDou (BDS) ===
 {{ :en:drones:platforms:beidou.png}}
-  * It consists of two separate satellite constellations. The first BeiDou system, officially called the BeiDou Satellite Navigation Experimental System and also known as BeiDou-1, consists of three satellites which since 2000 has offered limited coverage and navigation services, mainly for users in China and neighbouring regions. Beidou-1 was decommissioned at the end of 2012.
+  * It consists of two separate satellite constellations. The first BeiDou system, officially called the BeiDou Satellite Navigation Experimental System and also known as BeiDou-1, consists of three satellites which since 2000 has offered limited coverage and navigation services, mainly for users in China and neighboring regions. Beidou-1 was decommissioned at the end of 2012.
   * The second generation of the system, officially called the BeiDou Navigation Satellite System (BDS) and also known as COMPASS or BeiDou-2, became operational in China in December 2011 with a partial constellation of 10 satellites in orbit.
   * Since December 2012, it has been offering services to customers in the Asia-Pacific region.
@@ Line 69: / Line 70: @@
 ==== GNSS SEGMENTS ====
-GNSS satellite systems consist of three major components or “segments”: **space segment**, **control segment** and **user segment**.
+GNSS satellite systems consist of three major components or “segments”: **space segment**, **control segment**, and **user segment**.
 **Space Segment**
-The space segment consists of GNSS satellites, orbiting about 20,000 km above the earth. Each GNSS has its own “constellation” of satellites, arranged in orbits to provide the desired coverage. Each satellite in a GNSS constellation broadcasts a signal that identifies it and provides its time, orbit and status.
+The space segment consists of GNSS satellites, orbiting about 20,000 km above the earth. Each GNSS has its own “constellation” of satellites, arranged in orbits to provide the desired coverage. Each satellite in a GNSS constellation broadcasts a signal that identifies it and provides its time, orbit, and status.
 **Control Segment**
-The control segment comprises a ground-based network of master control stations, data uploading stations and monitor stations; in the case of GPS, two master control stations (one primary and one backup), four data uploading stations and 16 monitor stations, located throughout the world. In each GNSS system, the master control station adjusts the satellites’ orbit parameters and onboard high-precision clocks when necessary to maintain accuracy. Monitor stations, usually installed over a broad geographic area, monitor the satellites’ signals and status and relay this information to the master control station. The master control station analyses the signals then transmits orbit and time corrections to the satellites through data uploading stations.
+The control segment comprises a ground-based network of master control stations, data uploading stations, and monitor stations; in the case of GPS, two master control stations (one primary and one backup), four data uploading stations, and 16 monitor stations, located throughout the world. In each GNSS system, the master control station adjusts the satellites’ orbit parameters and onboard high-precision clocks when necessary to maintain accuracy. Monitor stations, usually installed over a broad geographic area, monitor the satellites’ signals and status and relay this information to the master control station. The master control station analyses the signals then transmits orbit and time corrections to the satellites through data uploading stations.
 **User Segment**
@@ Line 81: / Line 82: @@
 **GNSS Antennas**
-GNSS antennas receive the radio signals that are transmitted by the GNSS satellites and send these signals to the receivers. GNSS antennas are available in a range of shapes, sizes and performances. The antenna is selected based on the application. While a large antenna may be appropriate for a base station, a lightweight, low-profile aerodynamic antenna may be more suitable for aircraft or Unmanned Aerial Vehicles (UAV) installations. Figure 8 presents a sampling of GNSS antennas.
+GNSS antennas receive the radio signals that are transmitted by the GNSS satellites and send these signals to the receivers. GNSS antennas are available in a range of shapes, sizes, and performances. The antenna is selected based on the application. While a large antenna may be appropriate for a base station, a lightweight, low-profile aerodynamic antenna may be more suitable for aircraft or Unmanned Aerial Vehicles (UAV) installations. Figure 8 presents a sampling of GNSS antennas.
 **GNSS Receivers**
@@ Line 87: / Line 88: @@
 **GNSS Augmentation**
-Positioning based on standalone GNSS service is accurate to within a few metres. The accuracy of standalone GNSS, and the number of available satellites, may not be adequate for the needs of some users. Techniques and equipment have been developed to improve the accuracy and availability of GNSS position and time information.
+Positioning based on standalone GNSS service is accurate to within a few meters. The accuracy of standalone GNSS, and the number of available satellites, may not be adequate for the needs of some users. Techniques and equipment have been developed to improve the accuracy and availability of GNSS position and time information.
 <figure label>
-{{ :en:drones:platforms:gnss_segments.png?direct&500 | title}}
+{{ :en:drones:platforms:gnss_segments.png?direct&400 | title}}
 <caption>GNSS Segments</caption>
 </figure>
@@ Line 147: / Line 148: @@
 === GNSS systems comparison ===
-All modern and operating GNSS systems like GPS, GLONASS, Galileo or BeiDou which were developed by different countries and organizations use terrestrial segment containing satellites orbiting over the Earth. Each satellite constellation occupies their own unique orbit segments. The entire view of GNSS constellation is present in the picture above. Modern positioning and timing modules have evolved to take advantage of multiple GNSS constellations at once. Combining multiple satellite systems improves the availability of signals, gives operators more access and increases accuracy.
+All modern and operating GNSS systems like GPS, GLONASS, Galileo, or BeiDou which were developed by different countries and organizations use terrestrial segment containing satellites orbiting over the Earth. Each satellite constellation occupies its own unique orbit segments. The entire view of the GNSS constellation is present in the picture above. Modern positioning and timing modules have evolved to take advantage of multiple GNSS constellations at once. Combining multiple satellite systems improves the availability of signals, gives operators more access, and increases accuracy.
 <figure label>
-{{ :en:drones:platforms:gnss_comparation.png?direct&300 | title}}
+{{ :en:drones:platforms:gnss_comparation.png?direct&300 |}}
 <caption>GNSS Systems</caption>
 </figure>
 ==== GPS Signals ====
-The generated signals onboard the satellites are based or derived from generation of a fundamental frequency ƒo=10.23 MHZ. The signal is controlled by an atomic clock and has stability in the range of 10−13 over one day. Two carrier signals in the L-band, denoted L1 and L2, are generated by integer multiplications of ƒo. The carriers L1 and L2 are biphase modulated by codes to provide satellite clock readings to the receiver and transmit information such as the orbital parameters. The codes consist of a sequence with the states +1 or -1, corresponding to the binary values 0 or 1. It contains information on the satellite orbits, orbit perturbations, GPS time, satellite clock, ionospheric parameters, and system status messages. The modulation of L1 by Pcode, C/A-code and navigation message (D), is done using the quadrature phase-shift keying (QPSK) scheme. The C/A-code is placed on the LI carrier with 90° offset from the P-code since they have the same bit transition epochs. For the L1 and L2 we have:
+The generated signals onboard the satellites are based or derived from the generation of a fundamental frequency ƒo=10.23 MHZ. The signal is controlled by an atomic clock and has stability in the range of 10−13 over one day. Two carrier signals in the L-band, denoted L1 and L2, are generated by integer multiplications of ƒo. The carriers L1 and L2 are biphase modulated by codes to provide satellite clock readings to the receiver and transmit information such as the orbital parameters. The codes consist of a sequence with the states +1 or -1, corresponding to the binary values 0 or 1. It contains information on the satellite orbits, orbit perturbations, GPS time, satellite clock, ionospheric parameters, and system status messages. The modulation of L1 by P-code, C/A-code, and navigation message (D), is done using the quadrature phase-shift keying (QPSK) scheme. The C/A-code is placed on the LI carrier with 90° offset from the P-code since they have the same bit transition epochs. For the L1 and L2 we have:
 	L1(t) = a1P(t)W(t)cos(2πf1t)+a1C/A(t)D(t)sin(2πf1t)
 	L2(t) = a2P(t)W(t)cos(2πf2t)
 <figure label>
-{{ :en:drones:platforms:gps_modulation.png?direct&400 | title}}
+{{ :en:drones:platforms:gps_modulation.png?direct&400 |}}
 <caption>GPS signal modulation</caption>
 </figure>
 **GPS signals in Space**
-The signal broadcast by the satellite is a spread spectrum signal, which makes it less prone to jamming. The basic concept of the spread spectrum technique is that the information waveform with small bandwidth is converted by modulating it with a large-bandwidth waveform. The navigation message consists of 25 frames with each frame containing 1500 bit, and each frame is subdivided into 5 sub-frames with 300 bit. The control segment periodically updates the information transmitted by the navigation message. It is well known that the presence of dual-frequency measurements (L1 and L2) has good advantages to eliminate the effect of the ionosphere and enhance the ambiguity resolution, especially for the high precision measurements.
+The signal broadcast by the satellite is a spread spectrum signal, which makes it less prone to jamming. The basic concept of the spread spectrum technique is that the information waveform with small bandwidth is converted by modulating it with a large-bandwidth waveform. The navigation message consists of 25 frames with each frame containing 1500 bits, and each frame is subdivided into 5 sub-frames with 300 bits. The control segment periodically updates the information transmitted by the navigation message. It is well known that the presence of dual-frequency measurements (L1 and L2) has good advantages to eliminate the effect of the ionosphere and enhance the ambiguity resolution, especially for the high precision measurements.
 <figure label>
 {{ :en:drones:platforms:gps_signal_spectrum.png?direct&400 | title}}
@@ Line 198: / Line 199: @@
 ==== BeiDou signals ====
-BeiDou transmits navigation signals in three frequency bands: B1, B2, and B3, which are in the same area of L-band as other GNSS signals. To benefit from the signal interoperability of BeiDou with Galileo and GPS China announced the migration of its civil B1 signal from 1561.098 MHz to a frequency centred at 1575.42 MHz — the same as the GPS L1 and Galileo E1 civil signals — and its transformation from a quadrature phase-shift keying (QPSK) modulation to a multiplexed binary offset carrier (MBOC) modulation similar to the future GPS L1C and Galileo’s E1.
+BeiDou transmits navigation signals in three frequency bands: B1, B2, and B3, which are in the same area of L-band as other GNSS signals. To benefit from the signal interoperability of BeiDou with Galileo and GPS China announced the migration of its civil B1 signal from 1561.098 MHz to a frequency centered at 1575.42 MHz — the same as the GPS L1 and Galileo E1 civil signals — and its transformation from a quadrature phase-shift keying (QPSK) modulation to a multiplexed binary offset carrier (MBOC) modulation similar to the future GPS L1C and Galileo’s E1.
 <figure label>
 {{ :en:drones:platforms:beidou_signal_spectrum.png?direct&400 | title}}
@@ Line 205: / Line 206: @@
 ==== GNSS signal processing ====
-The main function of the signal processor in the receiver is the reconstruction of the carriers and extraction of codes and navigation messages. After this stage, the receiver performs the Doppler shift measurement by comparing the received signal by a reference signal generated by the receiver. Due to the motion of the satellite, the received signal is Doppler shifted. The code ranges are determined in the delay lock loop (DLL) by using code correlation. The correlation technique provides all components of bi-modulated signals. The correlation technique is performed between the generated reference signal and the received one. The signals are shifted concerning time so that they are optimally matched based on mathematical correlation.
+The main function of the signal processor in the receiver is the reconstruction of the carriers and extraction of codes and navigation messages. After this stage, the receiver performs the Doppler shift measurement by comparing the received signal with a reference signal generated by the receiver. Due to the motion of the satellite, the received signal is Doppler shifted. The code ranges are determined in the delay lock loop (DLL) by using code correlation. The correlation technique provides all components of bi-modulated signals. The correlation technique is performed between the generated reference signal and the received one. The signals are shifted concerning time so that they are optimally matched based on mathematical correlation.
 The GNSS receiver could be designed to track the different GNSS signals and could be of many types:
-  * The first type could process all GNSS signals GPS L1, L2, L5 and Galileo OS, CS using L1, E5 and E6 and also Glonass L1 and L2.
+  * The first type could process all GNSS signals GPS L1, L2, L5, and Galileo OS, CS using L1, E5, and E6, and also Glonass L1 and L2.
   * The second type uses free signal and codes, GPS L1 and L2C and Galileo OS, on L1 and E5.
   * The third type uses L1 and E5.
@@ Line 219: / Line 220: @@
 ==== GNSS differential position ====
-There is an increased interest in differential positioning due to the numerous advantages of wireless communications and networks. Most of the errors that affect GNSS are common between the receivers, which observe the same set of satellites. Thus, by making differential measurement between two or more receivers, most of these errors could be cancelled.
+There is an increased interest in differential positioning due to the numerous advantages of wireless communications and networks. Most of the errors that affect GNSS are common between the receivers, which observe the same set of satellites. Thus, by making differential measurements between two or more receivers, most of these errors could be canceled.
 The basic concept of differential position is the calculation of position correction or range correction at the reference receiver and then sending this correction to the other receiver via radio link.
 <figure label>
@@ Line 236: / Line 237: @@
 Selection of the appropriate augmentation method or correction service depends on the performance required for vehicle or aircraft navigation software. There are essentially four levels of positioning: standalone uncorrected; positioning derived from publicly available correction services such as the WAAS network in North America or Europe’s EGNOS system; positioning solutions derived from globally available subscription-based L-band services; and regional/ local RTK network solutions.
-Standalone uncorrected and WAAS/EGNOS type solutions provide position accuracy ranging from 1-10 metres. On the other end of the scale, RTK correction networks provide the most accurate centimetre-level solutions. While L-band solutions deliver corrections directly to the GNSS receiver via satellite, RTK solutions require a base station and a radio to get the corrections needed, limiting operator flexibility and increasing total system cost and complexity.
+Standalone uncorrected and WAAS/EGNOS type solutions provide position accuracy ranging from 1-10 meters. On the other end of the scale, RTK correction networks provide the most accurate centimeter-level solutions. While L-band solutions deliver corrections directly to the GNSS receiver via satellite, RTK solutions require a base station and a radio to get the corrections needed, limiting operator flexibility and increasing total system cost and complexity.
 With subscription-based L-band correction services, users receive Precise Point Positioning (PPP) corrections to help mitigate and remove measurement errors and position jumps. PPP solutions utilize modeling and correction products including precise satellite clock and orbit data to enhance accuracy.
@@ Line 245: / Line 246: @@
 ==== GNSS EGNOS ====
-The European Geostationary Navigation Overlay Service (EGNOS) is being developed by the European Space Agency (ESA), for the Safety of Air Navigation (Eurocontrol). EGNOS will complement the GNSS systems. It consists of three transponders installed in geostationary satellites and a ground network of 34 positioning stations and four control centres, all interconnected. EGNOS as WAAS broadcast the differential corrections to the GNSS users through Geostationary satellites, in the European region and beyond.
+The European Geostationary Navigation Overlay Service (EGNOS) is being developed by the European Space Agency (ESA), for the Safety of Air Navigation (Eurocontrol). EGNOS will complement the GNSS systems. It consists of three transponders installed in geostationary satellites and a ground network of 34 positioning stations and four control centers, all interconnected. EGNOS as WAAS broadcast the differential corrections to the GNSS users through Geostationary satellites, in the European region and beyond.
 <figure egnosconcept1>
-{{ :en:drones:platforms:egnos_concept.png?direct&500 | WAAS concept}}
+{{ :en:drones:platforms:egnos_concept.png?direct&500 | EGNOS concept}}
-<caption> WAAS concept</caption>
+<caption> EGNOS concept</caption>
 </figure>
 <figure egnosconcept2>
-{{ :en:drones:platforms:egnos_range.png?direct&500 | WAAS range}}
+{{ :en:drones:platforms:egnos_range.png?direct&500 | EGNOS range}}
-<caption> WAAS range</caption>
+<caption> EGNOS range</caption>
 </figure>
@@ Line 262: / Line 263: @@
   * 40 RIMS: the main function of the RIMS is to collect measurements from GPS satellites and transmit these raw data each second to the Central Processing Facilities (CPF) of each MCC. The configuration used for the initial EGNOS OS includes 40 RIMS sites located over a wide geographical area.
   * 2 MCC: receive the information from the RIMS and generate correction messages to improve satellite signal accuracy and information messages on the status of the satellites (integrity). The MCC acts as the EGNOS system’s 'brain'.
-  * 6 NLES: the NLESs (two for each GEO for redundancy purposes) transmit the EGNOS message received from the central processing facility to the GEO satellites for broadcasting to users and to ensure the synchronisation with the GPS signal.
+  * 6 NLES: the NLESs (two for each GEO for redundancy purposes) transmit the EGNOS message received from the central processing facility to the GEO satellites for broadcasting to users and to ensure the synchronization with the GPS signal.
 <figure label>
@@ Line 270: / Line 271: @@
 === Support segment ===
-In addition to the stations/centres, the system has other ground support installations that perform the activities of system operations planning and performance assessment, namely the Performance Assessment and Checkout Facility (PACF) and the Application Specific Qualification Facility (ASQF) which are operated by the EGNOS Service Provider (ESSP).
+In addition to the stations/centers, the system has other ground support installations that perform the activities of system operations planning and performance assessment, namely the Performance Assessment and Checkout Facility (PACF) and the Application Specific Qualification Facility (ASQF) which are operated by the EGNOS Service Provider (ESSP).
-  * PACF: provides support to EGNOS management in such area as performance analysis, troubleshooting and operational procedures, as well as upgrade of specification and validation, and support to maintenance.
+  * PACF: provides support to EGNOS management in such areas as performance analysis, troubleshooting, and operational procedures, as well as upgrade of specification and validation, and support to maintenance.
   * ASQF: provides civil aviation and aeronautical certification authorities with the tools to qualify, validate and certify the different EGNOS applications.
@@ Line 277: / Line 278: @@
 Composed of three geostationary satellites broadcasting corrections and integrity information for GPS satellites in the L1 frequency band (1575,42 MHz). This space segment configuration provides a high level of redundancy over the whole service area in case of a geostationary satellite link failure. EGNOS operations are handled in such a way that, at any point in time, at least two of the three GEOs broadcast an operational signal.
 <figure label>
-{{ :en:drones:platforms:sbas.gif?direct&536 | title}}
+{{ :en:drones:platforms:sbas_constellation.jpg?direct&400 | title}}
 <caption> SBAS Constellation in space</caption>
 </figure>
@@ Line 285: / Line 286: @@
 ==== GNSS RTK Network ====
-RTK network concept is similar to the WADGNSS, but the reference stations are generally distributed over a regional area, and the network control centre is responsible for transmitting the phase measurement correction to the GNSS user (rover receiver). Mobile wireless networks are generally used in this type of applications due to the need for duplex communication where the rover receiver should send the approximate position initially to the network processing centre. The network processing centre computes VRS observations and sends it to the user. The number of reference stations in the single RTK approach is 30 stations in 10,000 km2.
+RTK network concept is similar to the WADGNSS, but the reference stations are generally distributed over a regional area, and the network control center is responsible for transmitting the phase measurement correction to the GNSS user (rover receiver). Mobile wireless networks are generally used in this type of application due to the need for duplex communication where the rover receiver should send the approximate position initially to the network processing center. The network processing center computes VRS observations and sends them to the user. The number of reference stations in the single RTK approach is 30 stations in 10,000 km2.
 <figure label>
 {{ :en:drones:platforms:gnss_rtk_system.png?direct&500 | title}}
@@ Line 293: / Line 294: @@
 ==== GNSS Performance and Accuracy ====
 Four parameters are used to characterize GNSS performance which is based on the RNP specification:
-  * **Accuracy**: The accuracy of an estimated or measured position of a craft (vehicle, aircraft, or vessel) at a given time is the degree of conformance of that position with the true position, velocity and/or time of the craft. Since accuracy is a statistical measure of performance, a statement of navigation system accuracy is meaningless unless it includes a statement of the uncertainty in a position that applies.
+  * **Accuracy**: The accuracy of an estimated or measured position of a craft (vehicle, aircraft, or vessel) at a given time is the degree of conformance of that position with the true position, velocity, and/or time of the craft. Since accuracy is a statistical measure of performance, a statement of navigation system accuracy is meaningless unless it includes a statement of the uncertainty in a position that applies.
   * **Availability**: The availability of a navigation system is the percentage of time that the services of the system are usable by the navigator. Availability is an indication of the ability of the system to provide usable service within the specified coverage area. Signal availability is the percentage of time that navigation signals transmitted from external sources are available for use. It is a function of both the physical characteristics of the environment and the technical capabilities of the transmitter facilities.
   *
@@ Line 300: / Line 301: @@
   * **Integrity**: Integrity is the measure of the trust that can be placed in the correctness of the information supplied by a navigation system. Integrity includes the ability of the system to provide timely warnings to users when the system should not be used for navigation.
-The basic idea of GNSS systems is establishing a satellite network in which each satellite sends a signal at a defined time to receivers. The distance from the satellite to the receiver can be calculated by measuring the time difference from the transmitter to receiver. Using at least 4 satellites simultaneous the 3D Position of the receiver (vertical and horizontal) can be calculated if the position of each satellite is known. The accuracy of GNSS Systems is influenced by the realization of the needed infrastructure, causing the influences on the transmitted signals that make the position calculation possible. Satellites used for GNSS Systems are moving at approx. 4 km per seconds (to the earth) under varying conditions. Due to the movement of the receiver and the transmitter, there is the need to take a look at the factors that determine the accuracy of GNSS Systems.
+The basic idea of GNSS systems is establishing a satellite network in which each satellite sends a signal at a defined time to receivers. The distance from the satellite to the receiver can be calculated by measuring the time difference from the transmitter to the receiver. Using at least 4 satellites simultaneously the 3D Position of the receiver (vertical and horizontal) can be calculated if the position of each satellite is known. The accuracy of GNSS Systems is influenced by the realization of the needed infrastructure, causing the influences on the transmitted signals that make the position calculation possible. Satellites used for GNSS Systems are moving at approx. 4 km per second (to the earth) under varying conditions. Due to the movement of the receiver and the transmitter, there is the need to take a look at the factors that determine the accuracy of GNSS Systems.
 The positioning accuracy depends on many factors. Position and time error given by GPS receivers are influenced by:
   * Ionospheric delay - disturbances in the speed of propagation of signals from satellites in the ionosphere (error about 7 m),
-  * Tropospheric delay - an analogous phenomenon in the troposphere caused by changes in humidity, temperature and air pressure (± 0.5 m),
+  * Tropospheric delay - an analogous phenomenon in the troposphere caused by changes in humidity, temperature, and air pressure (± 0.5 m),
   * Ephemeris error - differences between the theoretical and actual position of the satellites (± 2.5 m),
   * satellite clock inaccuracy (± 2 m),
@@ Line 337: / Line 338: @@
 === EDCN Introduction ===
-EGNOS Data Collection Network (EDCN) was created in 2001, to acquire experience but also develop procedures on how to assess and validate the performance provided by augmentation systems like EGNOS. This data collection network is composed of multiple stations hosted often at Universities. It is complemented by the contributions from Air Navigation Service Providers interested on certifying and providing SBAS services in their national air space (among others AENA Spain, DTI/DSNA France, NATS UK, ENAV Italy, NAV Portugal, Skyguide Switzerland, PANSA Poland). All collected data is managed by EUROCONTROL in France, in charge not only of developing all the software used to process the data defined in the avionics standards, but also the definition of procedures and accumulation of results to present them coherently to the Regulator body in charge of the ESSP certification as EGNOS Operator.
+EGNOS Data Collection Network (EDCN) was created in 2001, to acquire experience but also develop procedures on how to assess and validate the performance provided by augmentation systems like EGNOS. This data collection network is composed of multiple stations hosted often at Universities. It is complemented by the contributions from Air Navigation Service Providers interested in certifying and providing SBAS services in their national air space (among others AENA Spain, DTI/DSNA France, NATS UK, ENAV Italy, NAV Portugal, Skyguide Switzerland, PANSA Poland). All collected data is managed by EUROCONTROL in France, in charge not only of developing all the software used to process the data defined in the avionics standards, but also the definition of procedures and accumulation of results to present them coherently to the Regulator body in charge of the ESSP certification as EGNOS Operator.
 == EDCN Components ==
@@ Line 353: / Line 354: @@
 <figure egnosmonitoringsystem1>
-{{ :en:drones:platforms:egnos_monitoring_system.png?direct&500 | EGNOS monitoring system}}
+{{ :en:drones:platforms:egnos_monitoring_system.png?direct&500 | EGNOS architecture diagram}}
-<caption> EGNOS monitoring system</caption>
+<caption> EGNOS architecture diagram</caption>
 </figure>
@@ Line 369: / Line 370: @@
 == EGNOS Signal Continuity ==
-Availability EGNOS SIS signal for PRN120 sattelite.
+Availability EGNOS SIS signal for PRN120 satellite.
 <figure label>
 {{ :en:drones:platforms:egnos_prn120_sis1.png?direct&500 | title}}
@@ Line 382: / Line 383: @@
 ==== GNSS Receiver hardware chips ====
-Autonomous UAV usually rely on a GPS position signal which, combined with inertial measurement unit (IMU) data, provides highly precise information that can be implemented for control purposes. To avoid accidents in an area heavily populated by other UAV or manned vehicles, it is necessary to know exactly where the UAV is located at all times. Equipped with GPS, a UAV can not only provide location and altitude information but necessary vertical and horizontal protection levels.
+Autonomous UAVs usually rely on a GPS position signal which, combined with inertial measurement unit (IMU) data, provides highly precise information that can be implemented for control purposes. To avoid accidents in an area heavily populated by other UAVs or manned vehicles, it is necessary to know exactly where the UAV is located at all times. Equipped with GPS, a UAV can not only provide location and altitude information but necessary vertical and horizontal protection levels.
 Typical GNSS receivers which can be easily used in the UAV platforms are listed below.
 === Multi-GNSS Receiver Module Model GN-87 ====
-GN-8720is a stand-alone, complete GNSS receiver module that can provide accurate GNSS PVT (Position, Velocity & Time) information through the serial communication channel. The key device inside is eRideOPUS 7, the latest monolithic GNSS receiver chip that contains ARM9 processor for signal tracking and processing, high performance integrated LNA, PLL Synthesizer, Down-converter, ADC and DSP. GN-8720 also contains Flash ROM for firmware and data storage, TCXO for reference clock, 32kHz crystal for RTC (Real-time clock), L1 band SAW filter and power-on reset circuit. Main features are as follows:
+GN-8720is a stand-alone, complete GNSS receiver module that can provide accurate GNSS PVT (Position, Velocity & Time) information through the serial communication channel. The key device inside is eRideOPUS 7, the latest monolithic GNSS receiver chip that contains an ARM9 processor for signal tracking and processing, high-performance integrated LNA, PLL Synthesizer, Down-converter, ADC, and DSP. GN-8720 also contains Flash ROM for firmware and data storage, TCXO for reference clock, 32kHz crystal for RTC (Real-time clock), L1 band SAW filter, and power-on reset circuit. The main features are as follows:
   * Supports GPS, GLONASS, SBAS, QZSSand Galileo,
   * Outputs a time pulse (1PPS) synchronized to UTC time,
@@ Line 412: / Line 413: @@
 === BCM47755 ===
-The BCM47755 supports two frequencies (L1+L5), achieves lane-level accuracy outdoors and much higher resistance to multipath and reflected signals in urban scenarios, as well as higher interference and jamming immunity. The BCM47755 incorporates numerous technologies that enable ultralow power consumption in both the location function and the sensor hub function. The device features a low-power RF path, a Big/Little CPU configuration composed of an ARM-based 32-bit Cortex-M4F (CM4), an ARM-based Cortex-M0 (CM0), and is built in a 28 nm process. The BCM47755 can simultaneously receive the following signals:
+The BCM47755 supports two frequencies (L1+L5), achieves lane-level accuracy outdoors, and much higher resistance to multipath and reflected signals in urban scenarios, as well as higher interference and jamming immunity. The BCM47755 incorporates numerous technologies that enable ultralow power consumption in both the location function and the sensor hub function. The device features a low-power RF path, a Big/Little CPU configuration composed of an ARM-based 32-bit Cortex-M4F (CM4), an ARM-based Cortex-M0 (CM0), and is built in a 28 nm process. The BCM47755 can simultaneously receive the following signals:
   * GPS L1 C/A
   * GLONASS L1
@@ Line 428: / Line 429: @@
 === UBLOX NEO-M9N module ===
-The NEO-M9N module is built on the robust u-Blox M9 GNSS chip, which provides exceptional sensitivity and acquisition times for all L1 GNSS systems. The u-Blox M9 standard precision GNSS platform, which delivers meter-level accuracy, succeeds the well-known u-Blox M8 product range. NEO-M9N supports concurrent reception of four GNSS. The high number of visible satellites enables the receiver to select the best signals. This maximizes the position accuracy, in particular under challenging conditions such as in deep urban canyons.
+The NEO-M9N module is built on the robust u-Blox M9 GNSS chip, which provides exceptional sensitivity and acquisition times for all L1 GNSS systems. The u-Blox M9 standard precision GNSS platform, which delivers meter-level accuracy, succeeds the well-known u-Blox M8 product range. NEO-M9N supports the concurrent reception of four GNSS. The high number of visible satellites enables the receiver to select the best signals. This maximizes the position accuracy, in particular under challenging conditions such as in deep urban canyons.
-NEO-M9N detects jamming and spoofing events and reports them to the host so that the system can react to such events. Advanced filtering algorithms mitigate the impact of RF interference and jamming, thus enabling the product to operate as intended. A SAW filter combined with an LNA in the RF path is integrated into the NEO-M9N module. This setup allows normal operation even under strong RF interferences, for example, when a cellular modem is co-located with NEO-M9N. NEO-M9N offers backwards pin-to-pin compatibility with previous u-Blox generations, which saves designers time and cost when upgrading their design. Software migration requires little effort thanks to the continuous support of UBX messages across product generations.
+NEO-M9N detects jamming and spoofing events and reports them to the host so that the system can react to such events. Advanced filtering algorithms mitigate the impact of RF interference and jamming, thus enabling the product to operate as intended. A SAW filter combined with an LNA in the RF path is integrated into the NEO-M9N module. This setup allows normal operation even under strong RF interferences, for example, when a cellular modem is co-located with NEO-M9N. NEO-M9N offers backward pin-to-pin compatibility with previous u-Blox generations, which saves designers time and cost when upgrading their design. Software migration requires little effort thanks to the continuous support of UBX messages across product generations.
 <figure label>
@@ Line 437: / Line 438: @@
 ==== UAV designed GNSS Receiver modules ====
-The UAV industry requires lightweight heavy-duty fully IP69K or IP67 waterproof and low power GNSS receiver modules.  The sample list of useful UAV GNSS receiver modules which uses different popular GNSS receiver hardware chips are listed below:
+The UAV industry requires lightweight heavy-duty fully IP69K or IP67 waterproof and low-power GNSS receiver modules.  The sample list of useful UAV GNSS receiver modules which uses different popular GNSS receiver hardware chips are listed below:
 === Radiolink TS100 Mini GPS Module for Mini PIX Flight Controller ===
-The Radiolink TS100 Mini GPS Module for Mini PIX Flight Controller can measure with a 50-centimetre precision of accuracy when working with concurrent GNSS. The prc-lNA low loss circuit design has enhanced ability to capture extremely weak signals. The TS100 can seize very weak signals and effective suppression of input interference at the same time.
+The Radiolink TS100 Mini GPS Module for Mini PIX Flight Controller can measure with a 50-centimeter precision of accuracy when working with concurrent GNSS. The prc-lNA low loss circuit design has enhanced the ability to capture extremely weak signals. The TS100 can seize very weak signals and effective suppression of input interference at the same time.
 **Description**
@@ Line 474: / Line 475: @@
   * Geomagnetic: QMC5883L which with the same technology as HMC5983 form
   * Antenna: 2.5dbI high gain and selectivity ceramic antenna
-  * Double filter: SAWF(Surface acoustic wave filter) form Murata
+  * Double filter: SAWF(Surface acoustic wave filter) from Murata
 **Dimensions**
@@ Line 497: / Line 498: @@
   * Compass Gyro Accelerometer: ICM20948
   * Barometer: MS5611
-  * Receive type: 72-channel u-blox M8N engine GPS/QZSS L1C/A, GLONASSL10F BeiDou B11, Galileo E1B/C SBAS L1 C/A: WAAS, EGNOS, MSAS, GAGAN
+  * Receive type: 72-channel u-Blox M8N engine GPS/QZSS L1C/A, GLONASSL10F BeiDou B11, Galileo E1B/C SBAS L1 C/A: WAAS, EGNOS, MSAS, GAGAN
   * Navigation update rate: Max 10Hz
   * Positioning Accuracy: 3D FIX
@@ Line 504: / Line 505: @@
   * Assisted GNSS: Assist Now GNSS Online, AssistNow GNSS Offline (up to 35 days), AssistNow Autonomous (up to 6 days) OMA SUPL& 3GPP compliant
   * Oscillator: TCXO(NEO-M8N/Q)
-  * RTC Crystal: Built in
+  * RTC Crystal: Built-in
   * ROM: Flash(NEO-M8N)
   * Available Antennas: Active antenna and passive antenna
@@ Line 605: / Line 606: @@
 === BN-345AJ GNSS antenna ===
-BN-345AJ is a multi-star multi-frequency satellite navigation antenna with high gain, miniaturization, high sensitivity, multi-system compatibility. The bottom of the antenna is magnetized for easy attachment. The antenna is made of UV-resistant PC material and ultrasonic technology. It can be sun-proof, high-temperature resistant and IP67 waterproof.
+BN-345AJ is a multi-star multi-frequency satellite navigation antenna with high gain, miniaturization, high sensitivity, multi-system compatibility. The bottom of the antenna is magnetized for easy attachment. The antenna is made of UV-resistant PC material and ultrasonic technology. It can be sun-proof, high-temperature resistant, and IP67 waterproof.
 **Specification**
   * Frequency Range: BDS B1/B2/B3 MHz
-  * GNSS Constelations: GPS L1/L2/L5 GLONASS G1/G2 GALILEO E1/E2/E5a/E5b/E6
+  * GNSS Constellations: GPS L1/L2/L5 GLONASS G1/G2 GALILEO E1/E2/E5a/E5b/E6
   * Gain: <5.5 dBi
   * Antenna AR: ≤3.0 dB
@@ Line 625: / Line 626: @@
 === BN-244 spiral GNSS antenna ===
-The antenna has the characteristics of small volume, high positioning precision and lightweight. The total weight of the antenna is less than 30g, which is especially suitable for equipment such as an unmanned aerial vehicle (UAV).
+The antenna has the characteristics of small volume, high positioning precision, and lightweight. The total weight of the antenna is less than 30g, which is especially suitable for equipment such as an unmanned aerial vehicle (UAV).
 **Specification**
@@ Line 658: / Line 659: @@
 ==== Introduction to the indoor positioning ====
-In the previous chapter [[en:drones:platforms:navigation]], there is a presentation of the navigation methods for drones that are flying outdoors and can receive satellite signals. To some extent, satellite-based navigation works indoors but usually with much-lowered accuracy and not in the deep shade from the surrounding walls and ceiling. Moreover, outdoor positioning inaccuracy, i.e. 1m, does not impact mission to the extent as may indoors.\\
+In the previous chapter [[en:drones:platforms: navigation]], there is a presentation of the navigation methods for drones that are flying outdoors and can receive satellite signals. To some extent, satellite-based navigation works indoors but usually with much-lowered accuracy and not in the deep shade from the surrounding walls and ceiling. Moreover, outdoor positioning inaccuracy, i.e. 1m, does not impact the mission to the extent as may indoors.\\
-Indoor positioning requires then different techniques, where some of them need additional infrastructure while others base on the on-board of the drone hardware and algorithms. Usually, it applies to the smaller drones and requires precision positioning in 3D space, even some 1cm accuracy. There are several techniques available to solve this problem that we present below.
+Indoor positioning requires then different techniques, where some of them need additional infrastructure while others base on the on-board of the drone hardware and algorithms. Usually, it applies to smaller drones and requires precision positioning in 3D space, even some 1cm accuracy. There are several techniques available to solve this problem that we present below.
 === Positioning methods ===
 Among the algorithms used for localization, we can distinguish methods based on the measurement of signal propagation time or measurement of signal strength. Using the signal temporal propagation model, we can use techniques such as:
   *AOA (Angle of Arrival) – this method uses the measurement of the angle of the incoming signal from the broadcasting station to approximate the location ((R. Peng and M. L. Sichitiu, "Angle of Arrival Localization for Wireless Sensor Networks," 2006 3rd Annual IEEE Communications Society on Sensor and Ad Hoc Communications and Networks, Reston, VA, 2006, pp. 374-382.)).
-  *ADOA (Angle Difference of Arrival) – like the AOA method, it is based on calculating the differences of angles of the signal received from the transmitter ((B. Zhu, J. Cheng, Y. Wang, J. Yan and J. Wang, "Three-Dimensional VLC Positioning Based on Angle Difference of Arrival With Arbitrary Tilting Angle of Receiver," in IEEE Journal on Selected Areas in Communications, vol. 36, no. 1, pp. 8-22, Jan. 2018.)).
+  *ADOA (Angle Difference of Arrival) – like the AOA method, it is based on calculating the differences of angles of the signal received from the transmitter ((B. Zhu, J. Cheng, Y. Wang, J. Yan, and J. Wang, "Three-Dimensional VLC Positioning Based on Angle Difference of Arrival With Arbitrary Tilting Angle of Receiver," in IEEE Journal on Selected Areas in Communications, vol. 36, no. 1, pp. 8-22, Jan. 2018.)).
 Methods that measure the angles can be performed if the receiver is equipped with directional antennas or with a matrix of antennas.
-  *TOA (Time of Arrival) – with this method the time of arrival of the signal transmitted from the mobile client to the base stations is measured. The distance from each station is calculated by determining the time of arrival of the signal, depending on the speed of wave propagation ((M. Kanaan and  K. Pahlavan Algorithm for TOA-based indoor geolocation, IET Electronics letters. Volume 40, Issue 22, 28 October 2004, p. 1421 – 1422, )). The precise synchronization is required in this method.
+  *TOA (Time of Arrival) – with this method the time of arrival of the signal transmitted from the mobile client to the base stations is measured. The distance from each station is calculated by determining the time of arrival of the signal, depending on the speed of wave propagation ((M. Kanaan and  K. Pahlavan Algorithm for TOA-based indoor geolocation, IET Electronics letters. Volume 40, Issue 22, 28 October 2004, p. 1421 – 1422, )). Precise synchronization is required in this method.
-  *TDOA (Time Difference of Arrival) – It is similar to the previous method with one difference; transmitting base stations and receiver do not have to be synchronized with each other. The geometry of this technique is also used in multirateriation ((R. Hach and A. Rommel, "Wireless synchronization in a time difference of arrival based real-time locating systems," 2012 9th Workshop on Positioning, Navigation and Communication, Dresden, 2012, pp. 193-195.)).
+  *TDOA (Time Difference of Arrival) – It is similar to the previous method with one difference; transmitting base stations and receivers do not have to be synchronized with each other. The geometry of this technique is also used in Multirateriation ((R. Hach and A. Rommel, "Wireless synchronization in a time difference of arrival based real-time locating systems," 2012 9th Workshop on Positioning, Navigation and Communication, Dresden, 2012, pp. 193-195.)).
-  *TOF (Time of Flight) – it is a technique used to measure distances between several devices. In a one-way TOF receiver must be precisely synchronized with the transmitter. In TW TOF (Two Way TOF, also known as RTT – Round Trip Transmission) each device has a transmitter and receiver, and the flight time measurement process includes signal exchange and measurement of results between two cooperating units ((David Bartlett Essentials of Positioning and Location Technology. Cambridge, 2013, p. 63)). One of the devices initiates the internal time measurement and sends the message to the responding unit. The answering device sends its measurements - delay from receipt to response. Using both time measurements internal and external, the initiator calculates the distance.
+  *TOF (Time of Flight) – it is a technique used to measure distances between several devices. A one-way TOF receiver must be precisely synchronized with the transmitter. In TW TOF (Two Way TOF, also known as RTT – Round Trip Transmission) each device has a transmitter and receiver, and the flight time measurement process includes signal exchange and measurement of results between two cooperating units ((David Bartlett Essentials of Positioning and Location Technology. Cambridge, 2013, p. 63)). One of the devices initiates the internal time measurement and sends the message to the responding unit. The answering device sends its measurements - delay from receipt to response. Using both time measurements internal and external, the initiator calculates the distance.
 Among the techniques that use signal propagation, we find techniques that use geometric transformations. These are:
   *Triangulation – positioning by angle measurement ((David Bartlett Essentials of Positioning and Location Technology. Cambridge, 2013, p. 63)). Using the knowledge of geometry, we can calculate the receiver's location relative to known transmitter positions. Knowing the angles of incoming signals from at least three transmitters, it is possible to determine the position of the receiver.
-  *Multilateration – also known as hyperbolic navigation, positioning by measuring the distance difference (or time difference of flight)  between the receiver and stations placed at known positions. It is also possible to measure the difference of distance from one sending station to two receivers. As a result of measurements, we obtain a hyperbolic curve with a large number of possible positions. To determine the exact position, a second measurement is made, using different sending stations, in which we get another curve intersecting the first in the place that will be the designated position ((L. Asmaa, K. A. Hatim and M. Abdelaaziz, "Localization algorithms research in wireless sensor network based on Multilateration and Trilateration techniques," 2014 Third IEEE International Colloquium in Information Science and Technology (CIST), Tetouan, 2014, pp. 415-419.)).
+  *Multilateration – also known as hyperbolic navigation, positioning by measuring the distance difference (or time difference of flight)  between the receiver and stations placed at known positions. It is also possible to measure the difference of distance from one sending station to two receivers. As a result of measurements, we obtain a hyperbolic curve with a large number of possible positions. To determine the exact position, a second measurement is made, using different sending stations, in which we get another curve intersecting the first in the place that will be the designated position ((L. Asmaa, K. A. Hatim and M. Abdelaziz, "Localization algorithms research in wireless sensor network based on Multilateration and Trilateration techniques," 2014 Third IEEE International Colloquium in Information Science and Technology (CIST), Tetouan, 2014, pp. 415-419.)).
   *Trilateration - positioning by measuring the distance (or time of flight) from signals coming from many transmitters ((David Bartlett Essentials of Positioning and Location Technology. Cambridge, 2013, p. 63)). Knowledge of the angle of incidence of signals is not needed here. Two intersecting circles marked with a signal from transmitters will allow us to determine the position. Due to noise in measurements, at least three transmitters are used in typical applications. GPS system is a hyperbolic navigation system using the TDOF technique but also determines the TOF according to the receiver's clock.
-Using the signal strength model, we can use the RSSI (received signal strength indicator) signal in the receiver, which is a measurement of the power present in a received radio signal. It is provided in Bluetooth and WiFi devices. It can be used to determine the distance from the transmitter, but the transmission power fluctuates due to changes in environment, objects movement which results in inaccurate positioning. That’s why the fingerprinting method is the preferred method for positioning.
+Using the signal strength model, we can use the RSSI (received signal strength indicator) signal in the receiver, which is a measurement of the power present in a received radio signal. It is provided in Bluetooth and Wi-Fi devices. It can be used to determine the distance from the transmitter, but the transmission power fluctuates due to changes in environment, objects movement which results in inaccurate positioning. That’s why the fingerprinting method is the preferred method for positioning.
-  *Fingerprinting – It assumes measuring the signal strength in the tested room, at measuring points located at a fixed distance from each other (this distance determines the measurement precision), and based on this data, a map of the signal strength in the room is created. The receiving device then measures the signal strength and compares it with the map mentioned above ((Y. Wang, Q. Ye, J. Cheng and L. Wang,  "RSSI-Based Bluetooth Indoor Localization," in 2015 11th International Conference on Mobile Ad-hoc and Sensor Networks (MSN), Shenzhen, China, 2015 pp. 165-171.)).
+  *Fingerprinting – It assumes measuring the signal strength in the tested room, at measuring points located at a fixed distance from each other (this distance determines the measurement precision), and based on this data, a map of the signal strength in the room is created. The receiving device then measures the signal strength and compares it with the map mentioned above ((Y. Wang, Q. Ye, J. Cheng, and L. Wang,  "RSSI-Based Bluetooth Indoor Localization," in 2015 11th International Conference on Mobile Ad-hoc and Sensor Networks (MSN), Shenzhen, China, 2015 pp. 165-171.)).
-There are some technologies based on different principles that can be used in indoor positioning systems, including radio waves, image recognition, visible or infrared light, ultrasound, inertial and others. Here we shortly present some of the possible solutions.
+There are some technologies based on different principles that can be used in indoor positioning systems, including radio waves, image recognition, visible or infrared light, ultrasound, inertial, and others. Here we shortly present some of the possible solutions.
 == Inertial and Dead reckoning ==
@@ Line 687: / Line 688: @@
 == Magnetic field ==
-The Earth has its own natural magnetic field. The field intensity can be easily measured anywhere on its surface. Studies have shown that buildings cause changes in magnetic field values ((T. H. Riehle, S. M. Anderson, P. A. Lichter, J. P. Condon, S. I. Sheikh and D. S. Hedin, "Indoor waypoint navigation via magnetic anomalies," 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Boston, MA, 2011, pp. 5315-5318.)). These changes depend on the building materials used during the construction of the building. Due to the fact that these values do not change over time, it is possible to use them to create a map of the building with a specific magnetic field strength at individual points. This allows determining the position after measuring the magnetic field. This solution does not require any additional infrastructure in the building. The magnetometer is available on virtually every smartphone. This issue was addressed by the Finnish company IndoorAtlas ((IndoorAtlas positioning overview. https://indooratlas.freshdesk.com/support/solutions/articles/36000079590-indooratlas-positioning-overview)).
+The Earth has its own natural magnetic field. The field intensity can be easily measured anywhere on its surface. Studies have shown that buildings cause changes in magnetic field values ((T. H. Riehle, S. M. Anderson, P. A. Lichter, J. P. Condon, S. I. Sheikh, and D. S. Hedin, "Indoor waypoint navigation via magnetic anomalies," 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Boston, MA, 2011, pp. 5315-5318.)). These changes depend on the building materials used during the construction of the building. Due to the fact that these values do not change over time, it is possible to use them to create a map of the building with a specific magnetic field strength at individual points. This allows determining the position after measuring the magnetic field. This solution does not require any additional infrastructure in the building. The magnetometer is available on virtually every smartphone. This issue was addressed by the Finnish company IndoorAtlas ((IndoorAtlas positioning overview. https://indooratlas.freshdesk.com/support/solutions/articles/36000079590-indooratlas-positioning-overview)).
 == Light and vision systems ==
 Some systems utilize QR codes as markers placed on the ceiling or walls ((Suresh, Sujith & Anand, Rubesh & Lenin, D. (2015). A Novel Method for Indoor Navigation Using QR Codes. International Journal of Applied Engineering Research. 10. 451-454.)). A smartphone camera detects and decodes the markers to get the location inside a room. QR code detection and decoding are relatively simple and memory efficient. Each code contains an ID, which delivers enough information to deliver the information required to determine its reference location.
-An interesting approach has been proposed by Philips ((Indoor Positioning White Paper. Philips. https://www.lighting.philips.com/main/systems/themes/led-based-indoor-positioning.#form_white_paper)). Its indoor positioning system is based on two, well-known assumptions: every building has to have lights installed, and every LED light flickers with some frequency. This product uses lamps as well known and calibrated reference points. Each of the lamps has a unique (across given venue) ID. This ID is encoded in the form of the frequency of the LED and is invisible to a human eye. Cellular phone’s camera captures signals, and then the phone decodes the LED ID from its frequency and determines the lamp position on the captured frame.
+An interesting approach has been proposed by Philips ((Indoor Positioning White Paper. Philips. https://www.lighting.philips.com/main/systems/themes/led-based-indoor-positioning.#form_white_paper)). Its indoor positioning system is based on two, well-known assumptions: every building has to have lights installed, and every LED light flickers with some frequency. This product uses lamps as well-known and calibrated reference points. Each of the lamps has a unique (across given venue) ID. This ID is encoded in the form of the frequency of the LED and is invisible to a human eye. The cellular phone’s camera captures signals, and then the phone decodes the LED ID from its frequency and determines the lamp position on the captured frame.
 Both systems require that the cellular phone’s camera is pointed to the ceiling what is rather an unnatural position while using the phone.
-Positioning systems can also use infrared light. There can be found systems with mobile IR transmitter (beacon) and stationary receivers ((Sakai, N.; Zempo, K.; Mizutani, K.; Wakatsuki, N. Linear Positioning System based on IR Beacon and Angular Detection Photodiode Array. In Proceedings of the International Conference on Indoor Positioning and Indoor Navigation (IPIN), Alcalá de Henares, Spain, 4–7 October 2016.)) or stationary light source and mobile IR receiver ((R. Salomon, M. Schneider and D. Wehden, "Low-Cost Optical Indoor Localization System for Mobile Objects without Image Processing," 2006 IEEE Conference on Emerging Technologies and Factory Automation, Prague, 2006, pp. 629-632.)).
+Positioning systems can also use infrared light. There can be found systems with mobile IR transmitters (beacons) and stationary receivers ((Sakai, N.; Zempo, K.; Mizutani, K.; Wakatsuki, N. Linear Positioning System based on IR Beacon and Angular Detection Photodiode Array. In Proceedings of the International Conference on Indoor Positioning and Indoor Navigation (IPIN), Alcalá de Henares, Spain, 4–7 October 2016.)) or stationary light source and mobile IR receiver ((R. Salomon, M. Schneider, and D. Wehden, "Low-Cost Optical Indoor Localization System for Mobile Objects without Image Processing," 2006 IEEE Conference on Emerging Technologies and Factory Automation, Prague, 2006, pp. 629-632.)).
 The image processing technology is also used to position the user. The challenge to implement such a system is the complexity and resource-intensiveness of the employed algorithms. Running these algorithms on a mobile device is usually not possible and thus has to be offloaded to a server. Another challenge is to recognize structures that are visually very similar such as plain walls which often repeat within buildings ((C. Marouane, M. Maier, S. Feld and M. Werner, "Visual positioning systems — An extension to MoVIPS," 2014 International Conference on Indoor Positioning and Indoor Navigation (IPIN), Busan, 2014, pp. 95-104.)). Although there are some examples of image processing implementations this technique seems to be too demanding to be widely used at this moment, however, early solutions that are implemented, i.e. using Intel Movidius processors used in DJI Tello home drones seems to be very promising [[https://www.intel.com/content/www/us/en/internet-of-things/computer-vision/overview.html]].
 //**Optical flow**// \\
-One of the oldest and most widely spread techniques for 2D flat positioning using vision systems is an Optical Flow. Optical flow positioning uses a similar technique that is present in the optical computer mouse. There is a camera observing surface under the drone, so optical flow technique is most suitable for 2D surface positioning, whereas altitude is controlled with a digital barometer. The principals of this technique are pretty simple: a camera facing downwards is observing any movements of the surface; thus deducing, the drone moves then the opposite way. There are many, ready modules to simplify this operation so nowadays, drone implementors not necessarily implement optical flow algorithm themselves, rather you use ready module that returns horizontal and vertical movement. Of course, integrated solutions (i.e. DJI drones using Movidius processor as a flight controller, i.e. DJI Tello) implement this feature natively, supporting not only the 2D surface but even 3D space, using downwards and forward camera.
+One of the oldest and most widely spread techniques for 2D flat positioning using vision systems is Optical Flow. Optical flow positioning uses a similar technique that is present in the optical computer mouse. There is a camera observing the surface under the drone, so the optical flow technique is most suitable for 2D surface positioning, whereas altitude is controlled with a digital barometer. The principles of this technique are pretty simple: a camera facing downwards is observing any movements of the surface; thus deducing, the drone moves then the opposite way. There are many, ready modules to simplify this operation so nowadays, drone implementors not necessarily implement optical flow algorithm themselves, rather you use ready module that returns horizontal and vertical movement. Of course, integrated solutions (i.e. DJI drones using Movidius processor as a flight controller, i.e. DJI Tello) implement this feature natively, supporting not only the 2D surface but even 3D space, using downwards and forward camera.
-Sample module (same used in many computer mouses) is ADNS3080:
+Sample module (same used in many computer mouse's) is ADNS3080:
 <figure OpticalFlowSensorADNS30801>
 {{ :en:drones:platforms:br-0016-01-2t.jpg?300 |}}
@@ Line 713: / Line 714: @@
 Optical flow is easy to integrate, and many flight controllers provide almost "plug and play" support for it. Anyway, they have many serious disadvantages as well:
-  * Limited range: works best on some centimetres to a couple of meters range. One limitation is fixed optics camera unable to get the sharp image below some distance on the one hand (also drone shadow won't help when hovering close to the surface), and camera's limited resolution when considering high altitude: small changes will remain unnoticeable because of the fixed FOW (Field of View).
+  * Limited range: works best on some centimeters to a couple of meters range. One limitation is fixed optics camera unable to get the sharp image below some distance on the one hand (also drone shadow won't help when hovering close to the surface), and camera's limited resolution when considering high altitude: small changes will remain unnoticeable because of the fixed FOW (Field of View).
   * Works best in good light conditions only: as it is a visible range camera used, it works more-less as human eyes do. It won't work correctly in darkness or low ambient light.
-  * Works only above irregular surfaces. As the camera needs to be able to identify some characteristic points, it won't work over the flat surface as, i.e. glass plane, the same way many PC mouses won't work.
+  * Works only above irregular surfaces. As the camera needs to be able to identify some characteristic points, it won't work over the flat surface as, i.e. glass plane, the same way many PC mice won't work.
-  * When surface moves, the drone will follow it!
+  * When the surface moves, the drone will follow it!
-<note important>It is a pretty common observation, that flying the drone with optical flow enabled over, i.e. grass field covered with leaves during autumn causes the drone to drift with the wind directions as leaves ar moving over the grass. Moreover, flying on low altitude generates propeller's airflow stream down hitting the ground, causing the aforementioned leaves to move, thus moving also the drone itself. Be careful and use it as supplementary, not primary technique!</note>
+<note important>It is a pretty common observation, that flying the drone with optical flow enabled over, i.e. grass field covered with leaves during autumn causes the drone to drift with the wind directions as leaves are moving over the grass. Moreover, flying at low altitude generates the propeller's airflow stream down hitting the ground, causing the aforementioned leaves to move, thus moving also the drone itself. Be careful and use it as supplementary, not primary technique!</note>
 == Radio ==
-Among radio technologies used for localization, the most popular ones are RFID, Bluetooth, and WiFi. New UWB technology has built-in functionality to help to implement the positioning systems.
+Among radio technologies used for localization, the most popular ones are RFID, Bluetooth, and Wi-Fi. New UWB technology has built-in functionality to help to implement the positioning systems.
   *RFID - using an RFID system, tags are arranged in a fixed pattern on the floor. Absolute coordinates of the location are stored in each tag to provide the position data to the mobile receiver. An RFID reader reads the data from tags that are under the effective area of RFID antenna ((Lim, H.S., Choi, B.S. & Lee, J.M., An Efficient Localization Algorithm for Mobile Robots Based on RFID System, SICE-ICASE International Joint Conference, Busan, Korea, pp. 5945-5950, 2006.)).
-  *Bluetooth - there are some systems based on Bluetooth technology. Bluetooth Low Energy beacons are small devices that emit a signal which provides mobile applications with the context that they are running in. Using this information mobile phone can calculate the location of the user knowing where the given beacon is located. Such a system that uses information from one beacon only has rather low precision (10-50m) and can be used for applications where only information about presence in a given place is needed. The system based on this technology has been created by Apple, transmitters in this system are called IBeacon ((What is iBeacon, Apple, http://www.ibeacon.com/what-is-ibeacon-a-guide-to-beacons/)). It is also possible to calculate position using signals from more than one beacon ((A. De Blas and D. López-de-Ipiña, "Improving trilateration for indoor localization using BLE beacons," 2017 2nd International Multidisciplinary Conference on Computer and Energy Science (SpliTech), Split, 2017, pp. 1-6.)). The mobile device scans for beacons around it and using trilateration determine a more accurate location based on the signal strength (RSSI) from different beacons. Such a solution works pretty well in theory. Still, in the real environment, there are many difficulties like the noise and signal variation what makes it really hard to calculate the position properly.
+  *Bluetooth - there are some systems based on Bluetooth technology. Bluetooth Low Energy beacons are small devices that emit a signal which provides mobile applications with the context that they are running in. Using this information mobile phone can calculate the location of the user knowing where the given beacon is located. Such a system that uses information from one beacon only has rather low precision (10-50m) and can be used for applications where only information about presence in a given place is needed. The system based on this technology has been created by Apple, transmitters in this system are called IBeacon ((What is iBeacon, Apple, http://www.ibeacon.com/what-is-ibeacon-a-guide-to-beacons/)). It is also possible to calculate position using signals from more than one beacon ((A. De Blas and D. López-de-Ipiña, "Improving trilateration for indoor localization using BLE beacons," 2017 2nd International Multidisciplinary Conference on Computer and Energy Science (SpliTech), Split, 2017, pp. 1-6.)). The mobile device scans for beacons around it and using trilateration determines a more accurate location based on the signal strength (RSSI) from different beacons. Such a solution works pretty well in theory. Still, in the real environment, there are many difficulties like noise and signal variation what makes it really hard to calculate the position properly.
-  *WiFi - wireless networks can also be used to locate users ((R. Joseph and S. B. Sasi, "Indoor Positioning Using WiFi Fingerprint," 2018 International Conference on Circuits and Systems in Digital Enterprise Technology (ICCSDET), Kottayam, India, 2018, pp. 1-3.)). Access points are usually present in buildings with a wireless network. It is possible to use them for localization purposes. Their arrangement is adjusted so that the signal reaches all places in the building where system users can be found. The user's device has the ability to measure the signal strength of all access points within its range. Each of them has its own individual MAC address. In one place, the signal strength from specific access points remains at a similar level. This allows creating a map that specifies the signal strength from specific access points in different locations (fingerprinting). In this way, it is possible to determine the position after measuring the signal strength of the network access points.
+  *WiFi - wireless networks can also be used to locate users ((R. Joseph and S. B. Sasi, "Indoor Positioning Using Wi-Fi Fingerprint," 2018 International Conference on Circuits and Systems in Digital Enterprise Technology (ICCSDET), Kottayam, India, 2018, pp. 1-3.)). Access points are usually present in buildings with a wireless network. It is possible to use them for localization purposes. Their arrangement is adjusted so that the signal reaches all places in the building where system users can be found. The user's device has the ability to measure the signal strength of all access points within its range. Each of them has its own individual MAC address. In one place, the signal strength from specific access points remains at a similar level. This allows creating a map that specifies the signal strength from specific access points in different locations (fingerprinting). In this way, it is possible to determine the position after measuring the signal strength of the network access points.
-  *UWB ((Y. Cheng and T. Zhou, "UWB Indoor Positioning Algorithm Based on TDOA Technology," 2019 10th International Conference on Information Technology in Medicine and Education (ITME), Qingdao, China, 2019, pp. 777-782.)) (Ultra Wideband) is a technology intended for wireless digital data transmission over short distances at low power density. The technology occupies a large (greater than 500MHz) bandwidth of the radio frequency spectrum. Wide bandwidth is obtained with the usage of very short radio pulses. It works with limited power, not causing interferences with other radio systems like WiFi and Bluetooth. This technology can be used for high precision indoor positioning. Transmitters are equipped with hardware support to the RTT (Round Trip Transmission) time measurement. This allows measuring the TOF with good precision and using trilateration to calculate the position with centimetre accuracy. UWB seems to be the most promising technology for in-door positioning due to good accuracy, ease of implementation, inexpensive modules, small power consumption and no interferences with other systems.
+  *UWB ((Y. Cheng and T. Zhou, "UWB Indoor Positioning Algorithm Based on TDOA Technology," 2019 10th International Conference on Information Technology in Medicine and Education (ITME), Qingdao, China, 2019, pp. 777-782.)) (Ultra Wideband) is a technology intended for wireless digital data transmission over short distances at low power density. The technology occupies a large (greater than 500MHz) bandwidth of the radio frequency spectrum. Wide bandwidth is obtained with the usage of very short radio pulses. It works with limited power, not causing interferences with other radio systems like Wi-Fi and Bluetooth. This technology can be used for high-precision indoor positioning. Transmitters are equipped with hardware support to the RTT (Round Trip Transmission) time measurement. This allows measuring the TOF with good precision and using trilateration to calculate the position with centimeter accuracy. UWB seems to be the most promising technology for in-door positioning due to good accuracy, ease of implementation, inexpensive modules, small power consumption, and no interferences with other systems.

en/drones/platforms/navigation.1611223232.txt.gz · Last modified: 2021/01/21 10:00 (external edit)