ARAIM DEMONSTRATOR. ITSNT th November, ENAC (Toulouse)

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1 ARAIM DEMONSTRATOR ITSNT th November, ENAC (Toulouse) D. Salos, M. Mabilleau, Egis Avia N. Dahman, Airbus Defence and Space S. Feng, Imperial College of London JP. Boyero, Commission Moses1978 copyright ITSNT /11/2017 1

2 CONTENT 1 INTRODUCTION 2 PROJECT OVERVIEW 3 FOCUS ON USER AND GROUND ALGORITHMS 4 SUMMARY AND NEXT STEPS ITSNT /11/2017 2

3 INTRODUCTION copyright Getty Images_Robert Churchill Project funded by Horizon 2020 Programme ITSNT /11/

4 CONTEXT GNSS capacity is growing fast with development and improvement of new core components resulting in a Dual-Frequency Multi-Constellation (DFMC) environment ICAO augmentations systems can benefit from those improvements SBAS evolution: SBAS Dual-Frequency Multi-Constellation GBAS evolution: GAST-F Concept ABAS evolution: Advanced Receiver Autonomous Integrity Monitoring (ARAIM) ARAIM is future modernized ABAS designed to operate in a DFMC environment Current ABAS/RAIM schemes cannot benefit from DFMC scenario because of design assumptions (single simultaneous satellite fault, constant Psat, negligible probability of wide fault, etc.) ARAIM airborne user algorithm deals with multiple constellations and multiple simultaneous faults Is dual-frequency capable (iono free) Requires inputs provided via Integrity Support Message (ISM) ISM updates parameters like Psat and Pconst, and fault-free SiS characterization (URA, Bnom) ARAIM performs a ground monitoring of SiS to generate ISM ITSNT /11/2017 4

5 ARAIM SCHEME ARAIM airborne user algorithm ARAIM ground monitoring ISM generation * Image based on [WGC,2016] The method for ISM transmission to users is under discussion, with two potential solutions: within core GNSS SiS within aircraft database The ISM update rate and its contents depend on targeted operation: Horizontal or Vertical navigation [WGC,2016] WGC, Milestone 3 Report, 25th February 2016 ITSNT /11/2017 5

6 ARAIM DEFINITION AND STANDARDIZATION STATUS ARAIM concept and system definition is on-going Three Milestone Reports produced by EU/US Working Group C (WGC) in 2012, 2015 and 2016 to define ARAIM concept ARAIM reference airborne user algorithm definition under discussion within WGC but in mature state ARAIM ground algorithms under discussion within WGC ARAIM standardization plans ICAO NSP, EUROCAE WG62 and RTCA SC 159 have included H-ARAIM in ir respective work plans as part of ir short term standard productions (between 2018 and 2020) Concept of Operations (CONOPS) document under development within WGC - presented as Working Paper in ICAO Navigation System Panel ITSNT /11/2017 6

7 PROJECT OVERVIEW copyright Getty Images_Robert Churchill Project funded by Horizon 2020 Programme ITSNT /11/

8 OBJECTIVES The ADAM (ARAIM Demonstrator and Experimentation) project has been launched by Commission under Horizon 2020 R&D Programme, with objective of: Develop an ARAIM Demonstrator End to end tool implementing both ground segment and user airborne algorithm To conduct experiments in a multi-constellation dual-frequency environment including tests with real Galileo Signal In Space Including data from real flights The project results are intended to serve as proof of concept for ARAIM and to provide recommendations on ARAIM operational implementation Contribute to ARAIM standardization (CONOPS) ITSNT /11/2017 8

9 ADAM PROJECT OVERVIEW ARAIM Demonstrator Design and Implementation Experimentations Fault-free syntic experimentations Data Processing Hardware & Software User Algorithm Ground algorithm Analysis module Fault-free real experimentations including data from flight tests Faulty syntic experimentations Faulty real experimentations (15 months) (9 months) Operational Recommendation and Awareness ARAIM implementation recommendations CONOPS ITSNT /11/2017 9

10 PROJECT PHASES Demonstrator design and implementation 15months Experimentations 9 months fault free syntic signals support assessment of ARAIM concept and identification of configurations of interest faulty syntic signals identification and analysis of GNSS threats (feared events) fault free real signals performance assessment based on real data Long duration experimentation results based on real DFMC networks 6 months Flight tests performed with aircraft of DSNA / DTI faulty real signals (replay faulty scenario) Faulty real signals Operational recommendation and awareness throughout project ITSNT /11/

11 ADAM DEMONSTRATOR ARCHITECTURE ITSNT /11/

12 USER AND GROUND ALGORITHMS copyright Getty Images_Robert Churchill Project funded by Horizon 2020 Programme ITSNT /11/

13 USER ALGORITHMS The ARAIM demonstrator will implement two user algorithms: The reference airborne user algorithm described in WGC Milestone 3 Report Latest evolution of above algorithm (presented in WGC in September 2017) User algorithms based on Multiple Hyposis Solution Separation (MHSS) Psat and Pconst, alpha_ura and Bnom provided via ISM Considers probability of independent individual satellite faults (narrow faults) and multiple satellite faults generated by a common cause (wide faults) Protects against any combination of simultaneous narrow and/or wide faults Provides HPL and VPL for Fault Detection (FD) and Fault Detection and Exclusion (FDE) The user algorithm definition developed within WGC is in a mature stage. However, it may evolve in future. ITSNT /11/

14 GROUND OFFLINE MONITORING The demonstrator will implement offline ground algorithms in line with WGC work The ARAIM ground offline monitoring algorithm: Monitors SiS (Detection of fault states, characterization of fault-free SiS distribution) Generates ISM contents Ground monitoring steps: 1) Obtain a truth reference for satellite orbit and clock Broadcast satellite orbit and clock «Truth» reference satellite orbit and clock 2) The orbit and clock error is obtained comparing broadcast values against truth reference 3) The error is projected to obtain SiS Instantaneous User Range Error (IURE) at Worst User Location & at a set of use locations in satellite s footprint 4) IURE are stored in datasets per satellite and processed for error analysis and characterization 5) Generation of ISM Observed satellite orbit and clock errors Error analysis and characterization Computation of ISM parameters ITSNT /11/

15 OFFLINE GROUND MONITORING : ORBIT AND CLOCK ERROR DETERMINATION (1/2) 1) Broadcast orbit and clock obtained from ephemeris Broadcast satellite orbit and clock «Truth» reference satellite orbit and clock Consolidated navigation RINEX 2) Truth orbit and clock determination (1/2): Method 1: precise orbit and clock from SP3 files Very precise offline orbit and clock information Observed satellite orbit and clock errors Error analysis and characterization Computation of ISM parameters Potential need to translate precise satellite orbits referred to satellite Centre of Mass (CoM) to Antenna Phase Centre (APC) via ANTEX files Potential clock inaccuracies due to time reference inaccuracy of SP3 files in multi constellation case Limitations: No commitment from SP3 providers on data accuracy and integrity The truth reference generation process is not under full control of ARAIM system ITSNT /11/

16 OFFLINE GROUND MONITORING : ORBIT AND CLOCK ERROR DETERMINATION (2/2) 2) Truth orbit and clock determination (2/2): Method 2 : orbit and clock estimated using measurements from a ground station network Allows full control of truth orbit and clock determination process Assures satellite orbit and clock are captured even during fault conditions Method based in algorithm relying in GPS ephemeris model [Joerger et al., 2015] The ephemeris model of each satellite is estimated from code and phase measurements made by a ground station network assumes ephemeris parameters remain constant for a given period of time (eg. 4 hours) 3) Observed satellite and clock errors are obtained by comparison between broadcast and truth reference values [Joerger et al., 2015] Mathieu Joerger, Yawei Zhai, and Boris Pervan, Online Monitor Against Clock and Orbit Ephemeris Faults in ARAIM, Proceedings of ION 2015 Pacific PNT Meeting Marriott Waikiki Beach Resort & Spa Honolulu, Hawaii ITSNT /11/

17 OFFLINE GROUND MONITORING: ORBIT AND CLOCK ERROR PROJECTION The Instantaneous User Range Error (IURE) is obtained projecting satellite error: Broadcast satellite orbit and clock «Truth» reference satellite orbit and clock into a set of user locations within satellite s footprint Suitable distribution to characterize fault-free SiS distribution (Bnom) into Worst User Location (WUL) Maximum Projection Error, useful for fault state detection IURE results from addition of two components: Observed satellite orbit and clock errors Error analysis and characterization Computation of ISM parameters orbit error projection, which depends on relative position between orbit error vector and user clock error, which is same for all users in footprint The WUL IURE can be computed analytically Taking into account that orbit and clock components may add or cancel depending on ir sign The WUL IURE projection is contained in plane containing orbit error and center of Earth ITSNT /11/

18 Broadcast satellite orbit and clock «Truth» reference satellite orbit and clock Observed satellite orbit and clock errors ISM GENERATION: α URA AND b nom Error analysis and characterization Computation of ISM parameters The ISM contains two parameters to characterize fault-free SIS distribution of a satellite α URA,i,j : multiplies broadcast σ URA,i,j (α URA,i,j 1) b nom,i,j : upper bound of nominal bias magnitude Steps to obtain α URA,i,j and b nom,i,j 1) Compute and store IURE for each satellite and its normalization by broadcast URA IURE obtained at a set of user locations distributed over satellite footprint 2) Create data sets of 1 month of IURE data for each SV 3) Process each data set 3.1) Obtain nominal bias as IURE mean of b nom,i,j ; 3.2) Obtain normalised nominal bias obtained as mean of normalised IURE 3.3) Compute normalised, zero-mean IURE data set by subtracting normalized nominal bias to normalised IURE 3.4) Obtain α URA,i,j by computing CDF overbounding of tails of distribution of normalised IURE (paired overbounding could be a potential alternative) ITSNT /11/

19 ISM GENERATION: P sat AND P const (1/2) The ISM contains two parameters to characterize probability of satellite faults P sat : probability of an independent individual satellite fault P const : probability of wide fault in a constellation Steps to obtain P sat,i,j and P const,i,j : 1) Compute and store SIS WUL IURE for each satellite 2) Determine if an SIS fault state exists on each satellite at each epoch A fault is detected if IURE > 4.42* σ URA GPS fault state definition applied to or constellations as well Only SIS fault states in healthy satellites are considered. 3) Two options for computing P sat,i,j : Option A) Rate between number of epochs in fault state and total number of epochs observed ITSNT /11/

20 ISM GENERATION: P sat AND P const (2/2) 3) Two options for computing P sat,i,j and P const,i,j : Option B: B.1: Estimate fault rate (R) and Mean Time To Notification (MTTN) from observed SIS fault states. B.2: Update P sat,i,j and P const,i,j as product of R and MTTN j. Multiple simultaneous faults are considered automatically constellation faults In final ARAIM implementation, an ISM Provider would need to assess case by case that simultaneous satellite faults have been originated by a common cause before accounting m in constellation fault probability Potential need of coordination with core constellation providers The resulting P sat,i,j and P const,i,j depend on observed length of data. Periods of 6, 12, 18, 24, 30 and 36 months analysed, taking maximum value ITSNT /11/

21 ONLINE ISM GENERATION Online ISM is defined to support navigation operations with vertical guidance Requires a higher update rate than Offline ISM Provides same ISM parameters as Offline message plus orbital corrections For demonstration purposes Online ISM will be generated based on truth orbit and clock references used for Offline mode ITSNT /11/

22 SUMMARY AND NEXT STEPS copyright Getty Images_Robert Churchill Project funded by Horizon 2020 Programme ITSNT /11/

23 SUMMARY ARAIM is future modernized ABAS designed to operate in a DFMC environment Design and standardization activities are ongoing The ADAM project develops an end to end ARAIM demonstrator Including user and ground monitoring algorithms Allowing to conduct experiments in a DFMC environment (with syntic and real signals) Intended to serve as proof of concept for ARAIM The methods that will be implemented to compute offline ISM parameters have been presented ITSNT /11/

24 NEXT STEPS The design of demonstrator architecture, user and ground algorithms are complete The demonstrator implementation has begun A first version of ARAIM Concept of Operations (Conops) has been provided for furr elaboration within WGC Next steps are to complete demonstrator implementation and start experimentation phase The opinions expressed in this paper reflect authors view only. Commission and or referenced bodies are not liable for use of any of information included herein. ITSNT /11/

25 CONTACT D a n i e l S a l o s Navigation Services daniel.salos@egis.fr ITSNT /11/