Soutenance Ouzeau

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Soutenance Ouzeau

  1. 1. Laboratoire de Ecole Nationale Traitement du Signal et de l’Aviation civile des Télécommunications Degraded Modes Resulting from the Multi Constellation Use of GNSS Christophe OUZEAU Ph.D. Defense 1 /47
  2. 2. Ecole Nationale Laboratoire de Traitement du Signal et des Context de l’Aviation civile Télécommunications Context • Multiplication of satellite radio navigation systems (Global Navigation Satellite System: GNSS), the variety of radio navigation signals increases • Global Positioning System (GPS) provides an accurate positioning service but its standalone use cannot meet the civil aviation requirements • The GPS is modernized progressively with new signals transmitted by new satellites (GPS block II-R, II-F and III) • Galileo is the European positioning system and will be operational in the next years • Galileo E1, E5a/E5b and GPS L1 C/A, L1C, L5 signals in Aeronautical Radio Navigation Services (ARNS) frequency bands, interest for civil aviation 2 /47
  3. 3. Ecole Nationale Laboratoire de Traitement du Signal et des Context de l’Aviation civile Télécommunications Context • The EURopean Organization for Civil Aviation Equipment provides a European forum for resolving technical problems with electronic equipment for air transport • The EUROCAE deals with aviation standardization and organizes Working Groups , in particular, the WG 62 (Galileo) objectives are to*: – Make recommendations to the Galileo project on issues of concern to civil aviation airborne and ground equipment – Produce a list of working assumptions for the operational use of Global Navigation Satellite System – Produce a Minimum Operational Performance Standard for airborne GPS/Galileo/Satellite Based Augmentation System receiver equipment – Produce a MOPS for both ground and airborne equipment for precision approach – Address the need for standardisation associated with the introduction of dual frequency Satellite Based Augmentation System services *Terms Of Reference approved by EUROCAE council on July 8th, 2003 3 /47
  4. 4. Ecole Nationale Laboratoire de Traitement du Signal et des Introduction de l’Aviation civile Télécommunications Introduction • This thesis was conducted in coordination with the WG 62 and focuses on the multi-system and multiple frequency issues of satellite navigation in aviation applications • We propose a combined receiver architecture and we look for algorithms performances for civil aviation application, we have to consider standardized assumptions and comply with International Civil Aviation Organization (ICAO) requirements • We focus on the interferences detection and the particular case of ionospheric code delay estimation, when a frequency is lost because of a jammer 4 /47
  5. 5. Ecole Nationale Laboratoire de Traitement du Signal et des Outline de l’Aviation civile Télécommunications Outline 1. GNSS applied to civil aviation operations 2. Combined receiver architecture 3. Interference detection 4. Ionospheric code delay estimation 5. Conclusion and future works 1. GNSS applied to civil aviation operations 2. Combined receivers architecture 3. Interference detection 4. Ionospheric code delay estimation 5. Conclusion and future works 5 /47
  6. 6. Laboratoire de 1. GNSS applied to civil aviation Ecole Nationale Traitement du Signal et des de l’Aviation civile Télécommunications 1.1. SIS performance requirements Signal In Space performance requirements • Future combined receivers will have to comply with the following ICAO requirements: Accuracy Accuracy Time Vertical Typical Horizontal Horizonta Vertical Integrity To Alert Continuity Availability Operation Alert limit l 95% 95% risk Alert limit 3.7 km 1×10-4/h to 0.99 to En-route N/A 1-1× 10-7 /h 5 min 7.4 km N/A (2.0 NM) 1×10-8/h 0.99999 En-route, 0.74 km 1×10-4/h to 0.99 to N/A 1-1 ×10-7 /h 15 s 3.7 km N/A Terminal (0.4 NM) 1×10-8/h 0.99999 Initial approach 220 m 1×10-4/h to 0.99 to Intermediate, N/A 1-1× 10-7 /h 10 s 556 m N/A -8/h (720 ft) 1×10 0.99999 NPA, Departure 16 m 20 m 1-2× 10-7 in 1-8×10-8 /h 0.99 to APV I (52 ft) (66 ft) any 10 s 40 m 50 m per 15 s 0.99999 approach 8m 1-2× 10-7 in 16 m 1-8×10-8/h 0.99 to APV II (26 ft) any 6s 40 m 20 m (52 ft) per 15 s 0.99999 approach 6 m to 4m 1-2× 10-7 in Category I 16 m 15.0 m 1-8×10-8/h 0.99 to (20ft to any 6s 40 m Precision App (52 ft) to 10 m per 15 s 0.99999 13ft) approach ICAO SIS performance requirements Source: [ICAO, 2006] 6 /47
  7. 7. Ecole Nationale Laboratoire de Traitement du Signal et des 1. GNSS applied to civil aviation de l’Aviation civile Télécommunications 1.2. Modes of operation Modes of operation • Aircraft modes of operation are defined in [EUROCAE, 2007]: – Nominal mode of operation: the receiver achieves the required level of performance, using a pre-described, preferred combination of signals – Alternate mode: the receiver achieves the same level of performance than in the nominal mode, using alternative means or augmentations. The receiver enters into this mode when one or several signals of the nominal mode are not available – Degraded mode: the receiver is unable to achieve the level of performance of the nominal mode. In this case, an alert must be flagged 7 /47
  8. 8. Ecole Nationale Laboratoire de Traitement du Signal et des 1. GNSS applied to civil aviation de l’Aviation civile Télécommunications 1.2. Modes of operation Modes of operation and GNSS components (1/2) • The WG 62 identified promising GNSS components combinations as nominal, alternate and degraded means to provide navigation solution and integrity to the aircraft • We focused on the APV I phase of flight because: – It requires vertical guidance – It has more restrictive requirements than En-route down to NPA Typical Nominal Alternate Degraded Operation •GPS Single Frequency + SBAS En-route •Galileo Safety of Life •Galileo Single Frequency + down to •Galileo E1/ E5b + SBAS Safety of Life No integrity information NPA •GPS L1/L5 + SBAS •Combination of all available pseudo ranges + RAIM •Galileo Single Frequency + •Galileo Safety of Life •GPS Single Frequency + SBAS Safety of Life APV I •Galileo E1/E5b + SBAS •Galileo Single Frequency + •Combination of all available •GPS L1/L5 + SBAS SBAS pseudo ranges + RAIM Identified nominal, alternate and degraded modes GNSS combinations for En-Route to NPA and APV I phases of flight Source: ConOps [EUROCAE, 2008] 8 /47
  9. 9. Ecole Nationale Laboratoire de Traitement du Signal et des 1. GNSS applied to civil aviation de l’Aviation civile Télécommunications 1.2. Modes of operation Modes of operation and GNSS components (2/2) • The Galileo Safety of Life service (E1/E5b) satisfies needs for safety critical users and is compliant with civil aviation applications. Integrity provided in the I/NAV message (satellites clock and ephemeris deviation) [EUROCAE, 2007], computation of the integrity risk at the alert limit, no protection level computation • The Satellite Based Augmentation System is used to provide ephemeris + clock + ionospheric corrections + DON’T USE flags to calculate protection levels (GPS SBAS) • The Receiver Autonomous Integrity Monitoring algorithm is used to provide integrity when GPS SBAS and Galileo SoL are not available Typical Nominal Alternate Degraded Operation •GPS Single Frequency + SBAS En-route •Galileo Safety of Life •Galileo Single Frequency + down to •Galileo E1/ E5b + SBAS Safety of Life No integrity information NPA •GPS L1/L5 + SBAS •Combination of all available pseudo ranges + RAIM •Galileo Single Frequency + •Galileo Safety of Life •GPS Single Frequency + SBAS Safety of Life APV I •Galileo E1/E5b + SBAS •Galileo Single Frequency + •Combination of all available •GPS L1/L5 + SBAS SBAS pseudo ranges + RAIM Identified nominal, alternate and degraded modes GNSS combinations for En-Route to NPA and APV I phases of flight Source: [EUROCAE, 2008] 9 /47
  10. 10. Ecole Nationale Laboratoire de Traitement du Signal et des 2. Combined receiver architecture de l’Aviation civile Télécommunications Onboard combined receivers architecture (1/2) • We proposed the following receiver architecture to the WG 62, for each mode of operation: – Navigation function selects the GNSS components combinations and provides navigation solution and integrity • Protection levels calculation by augmentation systems: GBAS, SBAS, ABAS (RAIM) • Fault Detection and Exclusion : alerts • Integrity risk for Galileo SoL – Detection function monitors degradations at different levels within the receiver GNSS combination The detection function is selected not an integrity monitoring Navigation Detection function: function: function, it monitors performances degradation Selection of the Detection of GNSS appropriate signal signals and combination and integrity means integrity method Performance level reached, loss or recovery among all those loss or recovery of available component Operation mode navigation and detection functions 10 /47
  11. 11. Ecole Nationale Laboratoire de Traitement du Signal et des 2. Combined receiver architecture de l’Aviation civile Télécommunications Onboard combined receivers architecture (2/2) • We proposed this receiver architecture to the WG 62 based on the Begin operation: following switching strategy selection of the • Switches between modes of operation depends upon the availability performance level of the GNSS components combinations required • When the receiver enters a degraded mode, it flags an alert Alert Performance level No nominal Nominal modes available Nominal mode of Nominal Alternate mode of modes available Degraded mode of operation modes operation and alternate operation available mode available Navigation Navigation Navigation No nominal No nominal and Detection Detection Detection modes alternate modes available available Nominal modes available 11 /47
  12. 12. Laboratoire de 2. Combined receiver architecture Ecole Nationale Traitement du Signal et des de l’Aviation civile Télécommunications 2.1. Conclusion Conclusion about combined receivers • The proposed architecture, based on switching between GNSS components combinations, is driven by detection functions: – Detection algorithms must be implemented to flag a loss or recovery of component, more precisely, to monitor if the system is compliant with the performance needed to start or continue an operation: integrity, continuity, accuracy and availability matched or not – The receiver can decide to initiate a switch after a detection flag • In case of degraded mode, the receiver must flag an alert [EUROCAE, 2007], and: – We propose to try to maintain as long as possible some performances during the current operation (reconfiguration of the navigator) – Otherwise, other means must be used to continue the current phase of flight (INS etc.) • We look for algorithms performances for civil aviation application under standardized assumptions, regards to parameters linked to civil aviation requirements (False alarm rate, missed detection probability, protection levels…). In particular, we focused on interferences detection and ionospheric code delay estimation 12 /47
  13. 13. Laboratoire de 3. Interference detection Ecole Nationale Traitement du Signal et des de l’Aviation civile Télécommunications 1. GNSS applied to civil aviation operations 2. Combined receivers architecture 3. Interference detection 4. Ionospheric code delay estimation 5. Conclusion and future works Interference detection • Aircraft embedded receiver interference environment: – Pulsed interferences (DME/TACAN on L5, E5a/E5b, Radars on E5b) can affect in particular GPS L5 and Galileo E5a, their mitigation is already studied in details for the WG 62 [Bastide, 2004], [Raimondi, 2008] – In band Continuous Waves (CW) and Narrow Band (NB) interferences can affect all GNSS signals (even simultaneously), for instance the GPS L1 C/A and Galileo E1 OS signals [Bastide, 2001], [Rollet, 2008] 13 /47
  14. 14. Laboratoire de 3. Interference detection Ecole Nationale Traitement du Signal et des de l’Aviation civile Télécommunications 3.1. Context Interference detection and combined receivers • Future civil aviation combined receivers will be composed of filters ([EUROCAE, 2007]), for resistance to jammers (RF and IF filters). The resulting interference threshold masks provide the characteristics of the interferences mitigation receiver capability • For civil aviation applications, interferences with power level below the interference masks defined in [EUROCAE, 2007], are expected to generate acceptable tracking errors • But, CW can stay a certain time near highest amplitudes code spectrum lines of the GNSS signals and generate larger tracking errors than expected by the WG 62, signal-jammer relative Doppler shift rate, [Rollet, 2008] determined this rate between 2.9 Hz/s and 3.1 Hz/s • We focus on CW detection, with the maximum interference power specified by the WG62: -155 dBW and a Doppler shift rate equal to 2 Hz/s 14 /47
  15. 15. Laboratoire de 3. Interference detection Ecole Nationale Traitement du Signal et des de l’Aviation civile Télécommunications 3.2. Simulation assumptions Impacted GNSS signals • Priority is given to L1 C/A (BPSK) and E1 L1 C/A OS/SoL (CBOC) signals, L5 and E5 major threats are pulsed interferences (same band than DME) already studied [EUROCAE, 2007] FC f -2Fc -Fc FR 2FC • The PRN codes correlated at the receiver level: E1 Normalized correlator outputs 1 BPSK(1) BOC(1,1) CBOC(6,1,1/11) f -2Fc -Fc FR FC 2FC Normalized Correlation Function 0.5 • PSD of the materialized PRN code (black) : • PSD of the materialization waveform (green) 0 • PSD of the PRN sequence (blue) Characteristics GNSS signal GPS L1 C/A Galileo E1 OS -0.5 -1 -0.8 -0.6 -0.4 -0.2 0 0.2 Code Delay (Chips) 0.4 0.6 0.8 1 Code line PRN 6 38 Code delay (chips) Freq w.r.t L1 227 kHz 673.5 kHz • Theoretical receiver correlation functions Power w.r.t total -21.29 dB -28.81 dB considering L1 C/A (BPSK) in blue, in the power following, E1 OS is assumed as a BOC signal Characteristics of highest amplitude code lines (red) instead of CBOC (black) for each signal, within the main lobes 15 /47
  16. 16. Laboratoire de 3. Interference detection Ecole Nationale Traitement du Signal et des de l’Aviation civile Télécommunications 3.3. Impact of CW on signals processing Impact of CW interference on signals processing • A CW hitting a code spectrum line, affects the receiver correlators outputs, code and carrier 39 dB Hz L1 C/A tracking outputs and code-carrier smoothing (100 s-Hatch filter) • We used a MATLAB Rx simulator to process the GPS L1 C/A, the PRN 6 worst code line is impacted by – 155 dBW CW, Doppler shift rate = 2 Hz per second. CW starts 200 seconds after the tracking loop C/N0 at the correlator output (dBHz) DLL: 1st order, PLL: 3rd order, BW: 1 Hz, dot BW: 10 Hz, product arctan discriminator discriminator Code tracking error (m) Phase tracking error (rad) 16 /47
  17. 17. Laboratoire de 3. Interference detection Ecole Nationale Traitement du Signal et des de l’Aviation civile Télécommunications 3.4. Detection algorithms Elaboration of detection techniques L1 C/A correlator output Normalized correlator outputs • Because of the CW, sine waves appear on top of the correlation peak when interference I prompt occurs (on the I channel for instance) correlator output • Their amplitudes are dependent of: – The jammer power, – The PRN code spectrum line amplitude, – The frequency offset between jammer and nearest PRN code line Correlator index • Detection is achieved through monitoring of multiple correlators outputs (68 for GPS L1 C/A and 72 for Galileo E1 OS, from the spectrum characteristics, code lines spacing) • Two proposed detection algorithms tested over 1.5 106 outputs for each correlator: – Monitoring instantaneous FFT of correlators outputs – Monitoring Auto Regressive model errors of all correlators time variations 17 /47
  18. 18. Laboratoire de 3. Interference detection Ecole Nationale Traitement du Signal et des de l’Aviation civile Télécommunications 3.4. Detection algorithms: performance evaluation Detection algorithms performance evaluation process • The performance evaluation process can be described in a few steps: 1. A detection criterion is defined from correlators outputs characteristics 2. Detection criterion parameters are set during a training stage without interference under APV I phase of flight conditions (dynamics, multipath, Doppler) 3. The detection threshold is set such that PFA < 1.6 10-5 /sample (for APV I continuity, [ICAO, 2006]) 4. Then the PMD value is determined, generating interferences, PMD = (number of tests where the detection criterion is lower than the pre-defined threshold) / (total number of tests) 5. The impact of non-detected interferences on tracking error at any time is then discussed 18 /47
  19. 19. Laboratoire de 3. Interference detection Ecole Nationale Traitement du Signal et des de l’Aviation civile Télécommunications 3.4. Detection: simulation assumptions Simulation assumptions • We considered the following simulation assumptions for a receiver onboard an aircraft: • Normal aircraft maneuvers generated according to maximum dynamics specifications ([RTCA, 2006]): Typical maximum values for normal Dynamics parameters aircraft manoeuvres ([EUROCAE, 2007]) Ground speed 800 Kt Horizontal acceleration 0.58 g Vertical acceleration 0.5 g Total jerk 0.25 g/s • Multipath generated each time a tracking procedure is initiated thanks to the Aeronautical Channel model (DLR), considering a 10 degree elevation satellite in view (Galileo satellites mask angle, [EUROCAE, 2008]) • Doppler shift between the jammer and the signal, with a Doppler shift rate of 2 Hz/s • Received signals carrier to noise ratio at the correlator output level, according to the received power level specified in [EUROCAE, 2008]: GNSS signal GPS L1 C/A Galileo E1 OS C/N0 39 dBHz 34 dBHz 19 /47
  20. 20. Laboratoire de 3. Interference detection Ecole Nationale Traitement du Signal et des de l’Aviation civile Télécommunications 3.4. Detection algorithms: FFT model Algorithm 1: FFT of the correlators outputs Normalized correlator outputs • Detection algorithm monitors the Fast Fourier Transform of correlation outputs (snapshot), Correlators outputs [Bastide, 2001] for the L1 C/A, PRN • Criterion is defined as: 6, impacted by a - max_ fourier − mean(max_ fourier) inst 155 dBW CW std (max_ fourier) • Parameters inside criterion determined through a training simulation without interferences and under APV I conditions Chip spacing Number of correlator outputs • Instantaneous maximum of the correlation Threshold peak FFT determined at each instant during the for APV I performance test simulation Test distribution 20 /47
  21. 21. Laboratoire de 3. Interference detection Ecole Nationale Traitement du Signal et des de l’Aviation civile Télécommunications 3.4. Detection algorithms: FFT model Performances of the algorithm 1 (1/2) • For GPS L1 C/A PRN 6 worst line, with: • Maximum normal aircraft dynamics, • Multipath (DLR model, elevation= 10°), • Signal to jammer Doppler shift rate of 2 Hz/s, • C/N0 = 39 dBHz at correlator output, • PFA = 1.6 10-5 /sample (APV I) PMD = 6.67 10-5 Missed detection probability • Tracking error when CW not detected • DLL: 1st order, BW: 1 Hz, dot product discriminator, • PLL: 3rd order, BW: 10 Hz, arctan discriminator • PMD as a function of raw tracking error. PMD * (number of times tracking error = N meters mod 1 meter)/number of tracking errors N =Raw tracking error in meters 21 /47
  22. 22. Laboratoire de 3. Interference detection Ecole Nationale Traitement du Signal et des de l’Aviation civile Télécommunications 3.4. Detection algorithms: FFT model Performances of the algorithm 1 (2/2) • Results for other L1 C/A PRN strong code lines within main lobe, exemple of PRN 10 worst line, low tracking errors but same PMD, considering: • Maximum normal aircraft dynamics, • Multipath (DLR model, elevation= 10°), • Signal to jammer Doppler shift rate of 2 Hz/s, • C/N0 = 39 dBHz at correlator output • PFA = 1.6 10-5 /sample (APV I) • For E1 OS, non detected raw tracking errors never exceed 9 meters (1.2 m after smoothing) obtained for PRN 38 worst line (Power of lines lower than L1 C/A lines), • Same assumptions except C/N0 = 34 dBHz 22 /47
  23. 23. Laboratoire de 3. Interference detection Ecole Nationale Traitement du Signal et des de l’Aviation civile Télécommunications 3.4. Detection algorithms: AR model Algorithm 2: Multichannel AR model (1/2) • Interference implies abnormal Normalized correlator outputs correlators outputs time variations • A 3 rd-order multichannel Auto Regressive model used to monitor simultaneously all correlators outputs, at t [Marple, 1987]: 3 x [t] = ∑ai [k]xi [t − k] ˆ i k =1 (xi: ith correlator, a: AR coefficient) Normalized correlator outputs Chip spacing Correlators outputs for the L1 C/A, PRN 6, impacted by a -155 dBW CW 23 /47
  24. 24. Laboratoire de 3. Interference detection Ecole Nationale Traitement du Signal et des de l’Aviation civile Télécommunications 3.4. Detection algorithms: AR model Algorithm 2: Multichannel AR model (2/2) • AR model error is determined, first • When impacting the L1 C/A PRN 6 worst during a training stage: code line, considering: 3 e [t] = x [t] − x [t] = x [t] + ∑a0[k]x0[t − k] i 0 i 0 ˆ i 0 ii 0 i • Maximum normal aircraft dynamics, k =1 • Multipath (DLR model, elevation= 10°), • And then during simulation tests, on studied samples: • Signal to jammer Doppler shift rate of 3 2 Hz/s, e [t] = x [t] − x [t] = x [t] + ∑ai [k]xi [t − k] i i ˆ i i k =1 • C/N0 = 39 dBHz at correlator output • Detection criterion is calculated • PFA = 1.6 10-5 /sample (norm of the E vector containing the correlators outputs AR errors):  E[t]  PMD = 10-5 log  E [t]    0  24 /47
  25. 25. Laboratoire de 3. Interference detection Ecole Nationale Traitement du Signal et des de l’Aviation civile Télécommunications 3.5. Estimation and repair algorithm Estimation and repair algorithm • When the CW detection is successful, we launch CW parameters estimation thanks to a third order Prony model • We repaired the correlators outputs (L1 C/A) • We observed the code tracking error (m), considering: • DLL: 1st order, BW: 1 Hz, dot product discriminator Code tracking error (m) as a function of time (sec) Statistics Before After • PLL: 3rd order, BW: 10 Hz, arctan correction correction discriminator Mean 19.9 m - 0.009 m • Red plot: when the L1 C/A PRN 6 Standard highest code spectrum line is Raw 10.5 m 1.9 m deviation impacted by a -155 dBW CW Maximum 45.2 m 8.6 m • Blue plot: tracking loop output, the Mean 13.7 m 0.03 m sine wave is removed from the Standard 5.3 m Smoothed 0.04 m correlator output deviation Maximum 18.4 m 0.16 m Raw and smoothed code tracking errors statistics before and after correction 25 /47
  26. 26. Laboratoire de 3. Interference detection Ecole Nationale Traitement du Signal et des de l’Aviation civile Télécommunications 3.6. Conclusions Conclusions on interference detection (1/2) • Simulation assumptions: • Worst cases considered in terms of: - Interference power under interference mask: maximum CW power -155 dBW, - Code spectrum lines impacted (on PRN 6 for L1 C/A, on PRN 38 for E1 OS), - Dynamics (maximum parameters as defined in [EUROCAE, 2007]), - Multipath (low elevation angle) - Minimum C/N0 • Algorithms proposed: • Two detection algorithms based on multi correlators outputs monitoring: - Computation of correlators FFT - Multi channel AR model of correlators outputs • Results obtained: • FFT: PMD = 6.67 10-5, AR: PMD = 10-5 , but interference probability of occurrence unknown, integrity risk = PMD * probability of occurrence? • Maximum smoothed tracking error resulting from non-detected CW: 15 m (raw: 52 m) for GPS L1 C/A and 1.2 m (raw < 9 m) for Galileo E1 with FFT algorithm • Capability of repair algorithm: std of the tracking error divided by 5 26 /47
  27. 27. Laboratoire de 3. Interference detection Ecole Nationale Traitement du Signal et des de l’Aviation civile Télécommunications 3.6. Conclusions Conclusions: contributions for CA receivers (2/2) • Detection algorithms reduce integrity risk due to interferences • When the CW was not detected we studied the impact on code tracking error • When the CW was detected, a repair algorithm tested with good performances • Possibility to switch to other GNSS components after detection, during APV I : Details of a detection function for the particular case of interference detection for APV I 27 /47
  28. 28. Laboratoire de 3. Interference detection Ecole Nationale Traitement du Signal et des de l’Aviation civile Télécommunications 3.6. Perspectives Perspectives • Need to determine minimum number of useful correlators without loss of performance for each signal • Make simulations to determine how far interference detection + repair + RAIM provide integrity and accuracy compliant with APV I requirements • But interference probability of occurrence unknown • Tracking loop behavior during abnormal aircraft manoeuvres, repair algorithm capability? • Tests over actual measurements must be performed • The major risk induced by the loss of frequency is due to the ionosphere if the SBAS is not available, during a degraded mode 1. GNSS applied to civil aviation operations 2. Combined receivers architecture 3. Interference detection 4. Ionospheric code delay estimation 5. Conclusion and future works 28 /47
  29. 29. Laboratoire de 4. Ionospheric code delay estimation Ecole Nationale Traitement du Signal et des de l’Aviation civile Télécommunications 4.1. Context Ionospheric code delay estimation: context Typical Nominal Alternate Degraded Operation •Galileo Safety of Life •GPS Single Frequency + SBAS •Galileo Single Frequency + •Galileo E1/E5b + SBAS •Galileo Single Frequency + Safety of Life APV I •GPS L1/L5 + SBAS SBAS •Combination of all available pseudo ranges + RAIM • In a dual frequency nominal mode of operation, smoothed ionospheric-free range measurements are used. The ionospheric error is estimated and corrected thanks to the use of dual frequency measurements • In an alternate mode of operation, the SBAS is used to provide the ionospheric corrections • In the case of loss of frequency leading to a degraded mode, an estimation of the ionospheric delay may be provided either by the Klobuchar model for GPS or the NeQuick one in case of Galileo. But, the models only estimate part of the error ([RTCA, 2006], [GSA, 2008]) • This implies large overbounded ionospheric std values, that does not allow to support flight operations that require vertical protection levels computation – In the following, we propose algorithms to keep the accuracy of the dual frequency ionospheric delay estimation compatible with APV I, in a degraded mode of operation 29 /47
  30. 30. Laboratoire de 4. Ionospheric code delay estimation Ecole Nationale Traitement du Signal et des de l’Aviation civile Télécommunications 4.2. Introduction Ionospheric code delay estimation: introduction • In order to keep the accuracy of the dual frequency nominal mode for APV I, a potential solution is the ionospheric delay estimation through the Code Minus Carrier Divergence [NATS, 2003], indeed, the receiver outputs code and carrier phase measurements • But the carrier phase measurements can be affected by cycle slips, the integrity of the CMC technique has to be evaluated • First, we focus investigations on the integrity of the CMC technique by adding a cycle slip detection algorithm and assessing its performance – Availability of the detection method within Europe, for GPS and Galileo constellations, considering maximum normal maneuvers [EUROCAE, 2007] • Then, a Kalman filtering technique is proposed to estimate the CMC parameters and to maintain the accuracy of dual frequency measurements 30 /47
  31. 31. Laboratoire de 4. Ionospheric code delay estimation Ecole Nationale Traitement du Signal et des de l’Aviation civile Télécommunications 4.3. Cycle slip detection Candidate methods for cycle slip detection • We identified different cycle slip detection algorithms: – Monitoring derivatives of carrier phase measurements – Comparing smoothed and raw code pseudo ranges – Making a phase prediction using Doppler measurements: robust against high aircraft manoeuvres, needs Doppler measurements • Algorithm tested (Doppler-predicted phase): – Compute predicted phase: • Fd: Doppler frequency • : time delay between the previous and the current measurement – Cycle slip is detected if: 31 /47
  32. 32. Laboratoire de 4. Ionospheric code delay estimation Ecole Nationale Traitement du Signal et des de l’Aviation civile Télécommunications 4.3. Cycle slip detection Cycle slip probability of occurrence calculation during APV I TI PROBABILITY OF OCCURRENCE • Pr[occurrence of cycle slip] = OVER 150 SECONDS SIGNAL NORMAL ABNORMAL MANOEUVRES MANOEUVRES Where: GPS L1 4 ms 1.0 10-3 9.2 10-2 C/A, 10 ms 7.5 10-4 6.1 10-2 Galileo E1 20 ms 4.7 10-4 3.8 10-2 is determined from classical carrier tracking GPS L5, 4 ms 9.1 10-4 9.0 10-2 theory [Holmes, 1990], taking into account: Galileo 10 ms 6.8 10-4 6.0 10-3 E5a 20 ms 2.4 10-4 3.4 10-2 - The tracking loop std: 4 ms 9.1 10-4 9.0 10-2 - The integration time TI Galileo E5b 10 ms 6.9 10-4 6.0 10-3 - The C/N0 = 30 dBHz 20 ms 2.4 10-4 3.4 10-2 • ∆t =150 seconds corresponds to an aircraft - The loop bandwidth WL = 10Hz total approach duration, it includes APV I - The receiver dynamics ( ) - Jmax = 0.25 g/s (normal manoeuvers) or 0.74 g/s (abnormal manoeuvers) - is the signal wavelength 32 /47
  33. 33. Laboratoire de 4. Ionospheric code delay estimation Ecole Nationale Traitement du Signal et des de l’Aviation civile Télécommunications 4.3. Cycle slip detection: requirements Cycle slip detection and CA requirements • The integrity risk due to cycle slip is expressed as the product of the algorithm missed detection probability by the cycle slip probability of occurrence – Integrity risk due to undetected cycle slips is taken as 10-8/approach: • SIS integrity risk: 2. 10-7/approach or to manufacturer: 10-7 /approach [RTCA, 2006] • But risk not only allocated to cycle slips, and probability to have abnormal dynamics – Probability of occurrence of cycle slips for all signals and all integration times is assumed as 10-3 over 150 s for normal manoeuvres and up to 10-1 for critical abnormal ones Missed detection probability is taken as PMD_theory =10-5 for normal manoeuvres and 10-6 for abnormal manoeuvres • False alarm rate is taken as PFA = 1.6 10-5/sample from the APV I continuity requirements ([ICAO, 2006]) 33 /47
  34. 34. Laboratoire de 4. Ionospheric code delay estimation Ecole Nationale Traitement du Signal et des de l’Aviation civile Télécommunications 4.3. Cycle slip detection: performance evaluation Cycle slip detector performance evaluation • The methodology used to determine the smallest detectable bias with the proposed detection algorithm can be summarized in a few steps: 1. Pseudo ranges measurements are generated without cycle slips. The detection criterion is compared to varying thresholds 2. When PFA < 1.6 10-5/sample, the corresponding threshold is kept in memory 3. Then, pseudo ranges measurements are generated again with varying cycle slip amplitudes. The missed detection probability is estimated for each amplitude 4. The experienced missed detection probabilities are compared to the theoretically derived ones for normal (PMD_theory = 10-5) and abnormal manoeuvres (PMD_theory = 10-6) 5. When PMD < PMD_theory, the corresponding cycle slip amplitude is recorded as the minimum detectable error 34 /47
  35. 35. Laboratoire de 4. Ionospheric code delay estimation Ecole Nationale Traitement du Signal et des de l’Aviation civile Télécommunications 4.3. Cycle slip detection: assumptions Simulation assumptions • Assumptions on pseudo ranges, worst conditions: – Maximum dynamics defined in MOPS [EUROCAE, 2007] for normal and abnormal aircraft manoeuvres – Multipath: at low elevation angles (10 degrees) – Noise: standard deviation of PLL and DLL outputs, assuming C/N0 = 30 dB Hz – Ionosphere and troposphere by drawing successive independent random Gaussian values multiplied by classical std models ([RTCA, 2006]) 35 /47
  36. 36. Laboratoire de 4. Ionospheric code delay estimation Ecole Nationale Traitement du Signal et des de l’Aviation civile Télécommunications 4.3. Cycle slip detection: performances Cycle slip detector performances Continuity requirements Integrity requirements PMD_theory Missed detection probability obtained as False alarm rate obtained as a function of a function the minimum detectable cycle the detection threshold used slip amplitude • These smallest detectable cycle slips imply an error on position which depends on the geometry. The availability of protection against cycle slip compatible with APV I depends on geometry and must be computed at every second 36 /47
  37. 37. Laboratoire de 4. Ionospheric code delay estimation Ecole Nationale Traitement du Signal et des de l’Aviation civile Télécommunications 4.3. Cycle slip detection: performances Cycle slip detector performance: availability • Determination of smallest detectable cycle slips for required PMD and PFA through simulations • Those cycle slips amplitudes were projected on the horizontal plane and the vertical axis. When the position errors were lower than the alert limits, the detection algorithm is declared available • The availabilities were computed over Europe for GPS and Galileo constellations in standalone modes 37 /47
  38. 38. Laboratoire de 4. Ionospheric code delay estimation Ecole Nationale Traitement du Signal et des de l’Aviation civile Télécommunications 4.3. Cycle slip detection: performances Availability of cycle slip detection over Europe Availability of cycle slip detection over Europe, APV I, 100 % degraded mode • Availability estimated over 70° N Europe, for both GPS and Galileo constellations, during APV I, maximum normal dynamics Latitude • GPS (first map), elevation mask angle: 5 degrees, period of revolution: 24 hours 100 % 97,5 % • Galileo (second map): elevation mask angle: 10 degrees 70° N 31° N elevation, period of revolution: 10 days • Low availability mostly due to vertical requirements: Latitude GPS: min=97%, Galileo: min=98% • HAL = 40 m, VAL = 50 m 98 % 31° N -9° E Longitude 50° E 38 /47
  39. 39. Laboratoire de 4. Ionospheric code delay estimation Ecole Nationale Traitement du Signal et des de l’Aviation civile Télécommunications 4.3. Cycle slip detection: conclusion Conclusions on cycle slip detection • The results obtained are promising (min availability = 97% for GPS, 98% for Galileo), since: – The availability must take into account the probability of falling into degraded single frequency mode – The performance test algorithm relies on worst case assumptions (simulated pseudo ranges: low elevations, low C/N0) • Continuity, integrity and availability of cycle slip detection plus Code Minus Carrier divergence technique is evaluated • In the following, the accuracy of ionospheric code delay estimation is studied using a Kalman filter to estimate the CMC parameters 39 /47
  40. 40. Re Laboratoire de 4. Ionospheric code delay estimation Ecole Nationale Traitement du Signal et des de l’Aviation civile Télécommunications 4.4. CMC Kalman filtering Code Minus Carrier Divergence and Kalman filtering • Code ( P ) minus carrier phase( φ ) allows to estimate ionospheric code delay : x x Pxk − φ xk = 2 I xk − N xk λ xk + w xk + v xk • Where: - N is the carrier phase ambiguity from one satellite and at a given frequency (x) - w and v are noise and multipath coming from code (w) and carrier phase (v) • A Kalman filter is used to estimate ionospheric delay and Receiver ambiguities: zenith X = ( I0 N1 N2 ... N Nb _ sat ) •Where: IPP • is the mean vertical ionospheric code Receiver E delay at the Ionosphere Pierce Point, h Ionosphere thin • is the obliquity factor Re shell model depending on the satellite elevation angle [RTCA, 2006] [RTCA, 2006] • The ionospheric delay at the receiver zenith can be expressed thanks to I0 plus South-North (A) and West- WGS 84 East (B) gradients: , in the following we assume A=B=0 40 /47
  41. 41. Laboratoire de 4. Ionospheric code delay estimation Ecole Nationale Traitement du Signal et des de l’Aviation civile Télécommunications 4.4. CMC Kalman filtering: measurements Choice of actual aircraft measurements • To comply with actual aircraft conditions, the Kalman filter performance is evaluated thanks to measurements made by L1/L2 dual frequency receiver onboard a flying Airbus aircraft around the Blagnac airport (Toulouse, France) Blagnac • 8 laps recorded, minimum number of 7 satellites in view Toulouse • Loss of L2 frequency, leading to GPS L1 C/A only simulated • Comparison between single L1 C/A Kalman estimations and classical nominal dual (L1 C/A + L2) estimations Aircraft path around the Blagnac airport 41 /47
  42. 42. Laboratoire de 4. Ionospheric code delay estimation Ecole Nationale Traitement du Signal et des de l’Aviation civile Télécommunications 4.4. CMC Kalman filtering: results Kalman filter estimations • The zenith ionospheric code delay is Number of Mean vertical ionospheric delay samples over all tracked satellites estimated thanks to the Kalman filter measurements (in red) and compared to mean dual Method Mean Standard frequency estimation (in green) over deviation all satellites in view Dual 3 104 11.1 m 3.3 m • The filter is initialized in dual frequency frequency mode and runs after a loss Single 3 104 10.9 m 1.5 m of L2 frequency frequency 24 m Code delay amplitude (m) Peaks observed due to losses of satellites, results obtained for one particular set of 6m measurements Time elapsed since the beginning of the simulation (sec) 42 /47
  43. 43. Laboratoire de 4. Ionospheric code delay estimation Ecole Nationale Traitement du Signal et des de l’Aviation civile Télécommunications 4.4. CMC Kalman filtering: conclusion Conclusions and future works on Kalman estimations • The performance of ionospheric delay estimation has been estimated in single frequency mode for civil aviation application • The method used is the Kalman filtering of Code Minus Carrier measurements SF : 10.9 m, DF : 11.9 m, and the std divided by 2 • The Kalman filter must be initialized in dual frequency mode, which implies to record dual ionospheric code delay estimations to start the filter • Trade-off between filter observation and state confidence. In our model, the ionosphere state noise variance larger than observation noise variance (smooth outputs), in case of scintillation, the filter innovation would increase (under-estimated perturbation) and the filter would take time to converge (TTA during APV I?) 1. GNSS applied to civil aviation operations 2. Combined receivers architecture 3. Interference detection 4. Ionospheric code delay estimation 5. Conclusion and future works 43 /47
  44. 44. Laboratoire de 5. Conclusions Ecole Nationale Traitement du Signal et des de l’Aviation civile Télécommunications 5.1. Combined receivers architecture Conclusions: combined receivers architecture (1/3) • Original contribution: future combined receivers architecture is proposed and discussed. A switching-based strategy between nominal, alternate and degraded modes of operation is described • The switching strategy depends upon the targeted operation (with or not vertical guidance). In particular, this thesis focuses on the APV I phase of flight • To initiate the switches between modes of operation, detection algorithms are implemented. The performances of such detection algorithms are assessed through simulations • The results obtained allow to determine whether or not the algorithms can be applied to civil aviation operations • Another important point assessed is how to maintain as long as possible the levels of performance required during degraded modes 44 /47
  45. 45. Laboratoire de 5. Conclusions Ecole Nationale Traitement du Signal et des de l’Aviation civile Télécommunications 5.2. Inteferences detection Conclusions: interference threat during APV I (2/3) • Focus on CW interference detection: can stay a long time near high power code spectrum lines, maximum power in compliance with the interference masks defined in [EUROCAE, 2007] • Focus on the GPS L1 C/A and Galileo E1 OS signals: highest power code spectrum lines • Multi correlators-based algorithms, continuity-compliant, provide low PMD, under worst conditions (multipath, C/N0, dynamics), alleviate integrity monitoring • Integrity risk not discussed because of the lack of information about interference probability of occurrence • When a CW is detected: – We propose the receiver can switch to another available GNSS combination to continue the current operation – Another solution can consist in estimating the CW characteristics and removing the interference effects from the correlators outputs, promising results • When the CW is not detected: – The impact on tracking loops outputs is studied 45 /47
  46. 46. Laboratoire de 5. Conclusions Ecole Nationale Traitement du Signal et des de l’Aviation civile Télécommunications 5.3. Ionospheric delay estimation Conclusions: ionospheric code delay estimation (3/3) • Method proposed: Code Minus Carrier divergence technique + Kalman + cycle slip detector under APV I degraded mode of operation • Original contribution: cycle slip detector integrity and continuity compliant • The availability of this technique has been studied for GPS and Galileo constellations • Worst cases considered: dynamics, C/N0, multipath, atmosphere • Expected low probability to fall into single frequency mode, to be determined • Availability expected to be compliant with APV I requirement • Original contribution for accuracy: CMC parameters estimated thanks to a Kalman filter initialized in dual frequency mode, accuracy maintained • Kalman algorithm tested over a set of actual measurements • Need to detect ionosphere scintillations 46 /47
  47. 47. Laboratoire de 5. Future works Ecole Nationale Traitement du Signal et des de l’Aviation civile Télécommunications Future works • The objective of this study (and future investigations) is to converge towards a final architecture of receiver for each operation in all identified configurations of operation modes • The detection algorithms proposed in this thesis focus on interferences (CW) and cycle slips detection. It is of interest to combine those algorithms with RAIM-type algorithms in future investigations to know precisely the performance of those combined algorithms for civil aviation use • This thesis focuses on the detection function and not on the navigation function. However, future works may include a complete simulator of protection levels computation, taking into account all the components described 47 /47

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