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Using Outage History to Exclude High-Risk Satellites from GBAS Corrections

Using Outage History to Exclude High-Risk Satellites from GBAS Corrections. Sam Pullen and Per Enge Stanford University spullen@stanford.edu. ION GNSS 2011 Portland, Oregon Session C5-8 23 September 2011. A Look Backward….

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Using Outage History to Exclude High-Risk Satellites from GBAS Corrections

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  1. Using Outage History to Exclude High-Risk Satellites from GBAS Corrections Sam Pullen and Per Enge Stanford University spullen@stanford.edu ION GNSS 2011 Portland, Oregon Session C5-8 23 September 2011

  2. A Look Backward… • Satellite selection in GPS user receivers first became an issue in the early 1990’s • GPS satellite constellation quickly expanded to the 24-satellite standard. • 4- and 6-channel receivers could not track all satellites in view and needed to select the optimal subset for positioning. • Use of almanac and minimum(PDOP) algorithms became standard techniques. • Research on computationally-efficient methods continues. • Availability of 12-channel (or more) receivers has made this “problem” a memory. Excluding High-Risk Satellites from GBAS

  3. A Look Forward… • The combined use of multiple GNSS constellations (GPS, GLONASS, Galileo, Compass, and augmenta-tions) for positioning provides many more satellites. • Are all of these satellites useful for positioning? • Beyond a certain point, don’t additional satellites add more integrity risk than they are worth? • Channel-limited scenario: as in the past, hardware limitations prevent all satellites from being used. • Even though modern receivers can track plenty of satellites, GBAS VDB can only broadcast so many SV corrections. • Channel-unlimited scenario: • No receiver or correction limits, but performance improvement is desired (or needed) Excluding High-Risk Satellites from GBAS

  4. GPS Satellite Fault Probabilities • From GPS SPS Signal Standard (4th Ed, Sept. 2008): • No more than three (3) GPS service failures per year (across GPS constellation) for a max. constellation of 32 satellites. • Service failure: SV failure leading to SPS user range error > 4.42 URA without timely OCS warning or alert • Assuming 3 failures/year over 32-SV constellation: • GBAS assumes 10-4 events/SV/hour per fault class. • Is it sufficient to treat all satellites as having the same failure probability? • “GPS Satellites are operated to failure.” • Col. Gaylord Green, USAF (Ret.), former GPS JPO director Excluding High-Risk Satellites from GBAS

  5. Today’s GPS Satellite Constellation (as of 20 September 2011) “Reborn” satellites – decomm., recomm., and still healthy 22 20 18 16 Linear fit Fairly uniform age distribution at present, but not always true in past 14 Sorted in order of launch 12 SV age (years) 10 SV ages 8 6 4 2 Sources: GPS NANU’s and Status Messages. 0 0 5 10 15 20 25 30 SV index (rank from newest to oldest) Excluding High-Risk Satellites from GBAS

  6. Unscheduled GPS Satellite Outages Since 1999 A textbook example of a “bathtub” failure curve! 20 25 “What happened to Social Security?” Increasing trend due to increasing age of older SV’s 178 total unscheduled outages 18 22 22 16 20 20 53 above “expected life” 14 15 14 14 12 15 “50 is not the new 30” “Infant mortality” SV Age (years) “Old Age Champs” No. of Occurrences 10 10 9 8 10 8 “Prime of life” 7 7 6 6 OCS software switchover 4 4 4 4 5 3 3 2 2 2 2 0 0 2000 2002 2004 2006 2008 2010 2012 0 2 4 6 8 10 12 14 16 18 20 Outage Date Range of expected SV lifetimes SV Age (years) Excluding High-Risk Satellites from GBAS

  7. Simplified Histogram of Unscheduled Outages 60 Beyond expected lifetime, outage rate is further elevated. • 178 outages over 156 mo, or 113,958 hrs • Total outage probability  1.16 × 10-3 per hour • Dividing over 24 satellites gives  6.51 × 10-5/SV/hr (below GBAS integrity fault allocation per cause) • Fraction of these that represent “service failures” or potential GBAS threats is unknown but likely small 50 Outages of SV above expected lifetime grouped together 40 From 10 to 13 years, outage rate is significantly elevated. No. of Occurrences 30 20 Within the first 10 years of life, outage rates are low enough  no need to differentiate. 10 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14+ SV Age (years) Excluding High-Risk Satellites from GBAS

  8. Number of Outages by Individual SV 14 12 10 8 Number of Outages 6 4 2 0 15 20 25 30 35 40 45 50 55 60 SVN Index Excluding High-Risk Satellites from GBAS

  9. Individual Satellite Outages:Age and Duration 20 18 16 SV age at end of outage 14 Outage duration SV age at start of outage 12 SV Age and Duration (years) 10 8 6 Record begins in 1999 4 2 0 15 20 25 30 35 40 45 50 55 60 SVN Number Excluding High-Risk Satellites from GBAS

  10. Zoom in on History of SVN 25 18 12 unsched. outages from 6/11/99 to 12/17/09 ( 9.22 × 104 hrs) 10/10/09 (~ 250 hrs) 6/26/09 (~ 130 hrs) 8/26/08 (~ 482 hrs) 16 4/22/07 (~ 85 hrs) 5/18/06 (~ 1000 hrs) 3/22/06 (~ 144 hrs) 12/23/05 (~ 8.5 hrs); then 12/25/05 (~ 721 hrs) 14 2/24/05 (~ 1 hr) Beyond expected lifetime 8/10/04 (< 1 hr) SV Age (years) 12 5 outages within 6 months! 10 10/02/00 (~ 35 hrs) 8 6/11/99 (< 1 hr) 6 25 SVN Number Excluding High-Risk Satellites from GBAS

  11. Example SV-Exclusion Heuristics • Examine GPS VDOP as multiple SVs are removed based on example heuristics (exclusion rules) • Assume heuristics are “hard” rules • “Channel-unlimited” scenario: SVs that fail tests are not used even if spare channels remain • Option 1: remove all satellites > 13 years old • Currently, don’t use SVNs 26 – 40 & 43 (PRNs 3, 4, 6, 8, 9, 10, 13, 26, 30) • 5 of these 9 SVs are in primary orbit slots • Option 2: remove all satellites > 10 years old & with one or more unscheduled outages in past 2 years • Currently, don’t use SVNs 26, 35, 38, 40, 51 (PRNs 8, 10, 20, 26, 30)  2 of these 5 SVs in primary orbit slots Excluding High-Risk Satellites from GBAS

  12. Satellite Geometry Sensitivity (1): Number of Usable Satellites in View Palo Alto, CA (37.4o N latitude) 5o mask angle Fairbanks, AK (64.8o N latitude) 5o mask angle Use All SVs 14 14 12 12 10 10 8 8 Number of Usable Satellites in View 6 6 4 4 Elim. SVs > 13 yrs old Elim. SVs > 10 yo w/outages 2 2 0 0 0 5 10 15 20 0 5 10 15 20 Time from midnight local time (hours) Time from midnight local time (hours) on 9/20/11 on 9/20/11 Excluding High-Risk Satellites from GBAS

  13. Satellite Geometry Sensitivity (2): Vertical DOP (VDOP) Palo Alto, CA (37.4o N latitude) 5o mask angle Fairbanks, AK (64.8o N latitude) 5o mask angle 10 10 Peak  37 Peak  16 Peak  45 9 9 8 8 Elim. SVs > 10 yo w/outages Elim. SVs > 13 yrs old 7 7 6 6 VDOP 5 5 4 4 3 3 2 2 1 1 Use All SVs 0 0 0 5 10 15 20 0 5 10 15 20 Time from midnight local time (hrs) Time from midnight local time (hours) on 9/20/11 on 9/20/11 Excluding High-Risk Satellites from GBAS

  14. Heuristic Implementation in GBAS • Proposed SV exclusion rules are simple but require knowledge of SV age and outage history. • This information can be obtained from GPS NANUs but is not included in the broadcast satellite signals. • For GBAS ground stations that can only observe broadcast signals, less-informative means to update age and outage information would have to be used. • Can update satellite ages, PRN assignments, and outage statistics when new or re-commissioned satellites are manually added to the list of “usable” SVs. • Otherwise, sub-optimal tracking of outages observable to each ground station would be needed. Excluding High-Risk Satellites from GBAS

  15. Satellite-Geometry-based Heuristics • In principle, a real-time model that trades risk of using SV against geometry benefit gained from that SV would be superior to fixed (use/don’t use) rules. • The multiple-hypothesis (MH) protection level approach used by ARAIM makes this possible. • Resulting protection levels incorporate both positioning geometry and risk from each hypothesized fault • However, like existing protection levels, MH is only as good as the failure assumptions and probabilities that go into it. • Fixed heuristics are less sensitive to modeling errors but are likely to sacrifice performance to gain conservatism. • Experimentation with MH approach to follow… Excluding High-Risk Satellites from GBAS

  16. Summary • GPS outage data since 1999 shows that satellite failure probabilities are not evenly distributed. • Older satellites fail much more often than younger ones. • Satellites that begin experiencing outages are much more likely to continue having outages. • At present, the satellite integrity failure rate assumed by GBAS appears to cover all GPS satellites. • To provide more margin, or if circumstances change, heuristics derived from observed outage rates can be used to remove satellites with excessive risk. • Future GBAS using multiple constellations should allow marginal satellites to be excluded with negligible performance penalty. Excluding High-Risk Satellites from GBAS

  17. Backup Slides • Backup slides follow… Excluding High-Risk Satellites from GBAS

  18. A Preliminary Analysis Approach • “Back to the Future…” • Model GPS-only scenario with today’s constellation of several satellite “blocks” (IIA, IIR, IIR-M, IIF). • Consider the “channel-limited” case with 6- and 8-channel receivers (as in mid-1990’s). • Examine satellite failure probabilities and effects as a function of satellite age and recent failure history. • Explore simplified heuristics for inclusion or exclusion of individual satellites. • Examine potential system impacts. • Integrity could be threatened by including satellites with unacceptably high prior failure probabilities. • Availability and continuity potentially affected by exclusion of too many “marginal” satellites. Excluding High-Risk Satellites from GBAS

  19. Distribution of Current SV Ages 22 20 18 16 Linear fit 14 12 SV age (years) 10 SV ages 8 6 4 2 0 0 5 10 15 20 25 30 SV index (rank from newest to oldest) Satellite Selection for Modernized GNSS/GBAS

  20. Failure Probability Estimates from Outage Data • 178 unscheduled outages recorded from Jan. 1999 – Aug. 2011 (156 months, or 113,958 hours) • Relatively few of these represent “service failures” or potential GBAS threats, but actual fraction is unknown. • Total outage probability  1.16 × 10-3 per hour • Dividing over 24 satellites gives  6.51 × 10-5 per SV per hour (GBAS integrity failure assumption per cause exceeds this). • Satellites > 10 years old cause 117 of these outages (~ 66% of total) and are greatly over-represented. • SVs between 10 + d and 13 years old cause 46 outages (~ 36% of total). • If SV ages were evenly distributed between 0 and 20 years, this would imply 2.36 × average failure rate. • 53 outages (~ 30% of total) from SVs beyond 13 years old Excluding High-Risk Satellites from GBAS

  21. Significance of SV Outage History • Unscheduled satellite outages are rare, but they are not “memoryless” (assumed by Poisson approx.) • SVs with recent unscheduled outages are more likely to have future unscheduled outages. • This factor is correlated with SV age but has independent value in estimating future SV failure risk and should also be used in SV selection heuristics. • “Trackable” by reviewing NANUs, but NANUs represent external information not broadcast by satellites. • For GBAS, easier to track observed SV outages (“unhealthy” flags), but not all can be observed from one location, and observed flags would include scheduled outages. • Manual updates needed (e.g., when new SVs are approved) if NANUs are not used. Excluding High-Risk Satellites from GBAS

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