Ground Monitoring to Support ARAIM for Military Users: Alternatives for Rapid and Rare Update Rates

Sam Pullen, Sherman Lo, Alec Katz, Juan Blanch, Todd Walter, Andrew Katronick, Mark Crews, Robert Jackson

Abstract: Advanced Receiver Autonomous Integrity Monitoring, or ARAIM, is a methodology for using redundant satellite range measurements to detect and exclude faults in one or multiple satellites or GNSS constellations while calculating position-domain bounds (“protection levels”) on the unknown errors generated by the remaining measurements. In [1], the authors of this paper demonstrated the ability of ARAIM, to support high-integrity applications of military users such as aircraft approaches to LPV minima (i.e., decision heights as low as 250 ft). This was done by modifying the civil approach to ARAIM described in [2, 3] to support military use of GPS M-code on the L1 and L2 frequencies along with the optional use of Galileo Open Service (OS) signals as a cross-check. Paper [1] examined military ARAIM performance for assumed levels of the key Integrity Status Message (ISM) parameters URA (bound on signal-in-space user range error), P_sat and P_const (per-satellite and per-constellation fault probabilities), and MFD (mean fault duration before a system alert is received) as a function of ground monitoring response time, defined as follows: 1) Online: updates ISM parameters (if needed) from once per hour to once per day. 2) Offline: updates ISM parameters (if needed) from once per week to once per quarter (three months). 3) Frozen: updates ISM parameters very infrequently, if ever (e.g., if URA or Psat becomes unexpectedly large). This paper examines several algorithms for ground monitoring in support of military ARAIM and generates achievable values of URA for these ISM update alternatives and a range of potential choices of P_sat and P_const. As with ARAIM itself, all of these algorithms are evaluated using the WAAS version of the Matlab Algorithm Availability Simulation Tool (MAAST) software toolset [4]. A hypothetical global network of 32 ground monitor reference stations has been created, starting with the existing 6 U.S. Air Force and 10 U.S. National Geospatial Agency (NGA) GPS monitor stations [5]. Ground monitoring simulations are conducted for this network and subsets of 24 and 16 stations from this network. The baseline ground monitor algorithm generates estimation and monitoring of satellite clock and ephemeris errors in a manner similar to that used by future multi-frequency SBAS to generate Dual Frequency Range Error (DFRE) bounds (analogous to User Differential Range Error, or UDRE, for single-frequency SBAS) [6]. This process is “snapshot”, meaning that satellite error estimates and DFRE bounds are generated independently at each ground monitor epoch. The minimum detectable range-domain errors that determine DFRE can be lowered (at the expense of timely responsiveness) by estimating the satellite errors over time as suggested in [7]. To apply this concept to the SBAS approach, a batch filter of varying duration (based on the desired ISM update rate) is implemented for comparison. Since the most rapid possible ISM update interval is assumed to be 15 minutes, even the snapshot approach takes credit for simple estimate error averaging within that interval, as ground monitor estimate updates (“epochs”) can be generated once per minute. Nominal results for these methods are presented in terms of achievable ARAIM URAs as a function on response time (after filtering, if applied) as a function of the values of P_sat and P_const to which the URA bound must apply. In these results, slower update rates correspond to lower URAs because of the additional averaging time (or greater number of separate monitoring epochs) that is allowed. However, the penalty is sluggish or perhaps no response to variations in satellite error behavior. To address this, Monte Carlo simulations of abnormal satellite error behavior are generated in which errors on one or multiple GPS satellites begin to grow unexpectedly. Online ground monitoring is able to rapidly update the ISM in response to these changes, but frozen ground monitoring cannot do so. This means that the URAs provided by a frozen (or offline) ISM must include substantial margin to allow for this possibility. As in [1], the URAs and corresponding P_sat and P_const values will be included in military ARAIM simulations of LPV aircraft approaches using the ARAIM (user) version of MAAST. The results will be used to recommend a specific ground monitor architecture to future military ARAIM designers as a function of the achievable ISM update rate.
Published in: Proceedings of the 34th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2021)
September 20 - 24, 2021
Union Station Hotel
St. Louis, Missouri
Pages: 1481 - 1507
Cite this article: Pullen, Sam, Lo, Sherman, Katz, Alec, Blanch, Juan, Walter, Todd, Katronick, Andrew, Crews, Mark, Jackson, Robert, "Ground Monitoring to Support ARAIM for Military Users: Alternatives for Rapid and Rare Update Rates," Proceedings of the 34th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2021), St. Louis, Missouri, September 2021, pp. 1481-1507.
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