Integrity-Based Estimators for Precise Point Positioning and Other Applications

Juan Blanch, Yu-Fang Lai, and Todd Walter

Peer Reviewed

Abstract: In standard FDE algorithms, fault detection and exclusion are two discrete steps. In our previous work we have developed a new class of estimators where these two steps are merged into one. These estimators were shown to improve integrity performance in ARAIM scenarios. The key to the design of these estimators is to base them on the integrity and continuity requirements (rather than the accuracy). The purpose of this paper is to continue the development of these estimators and demonstrate their potential. We first refine the lower bound on achievable error bounds under error model uncertainty developed in [6], therefore tightening the distance between the performance of the integrity-based estimators and the achievable performance. We then provide explicit and practical formulas to implement the proposed estimators to any application where, under nominal conditions, a Kalman filter may be used to estimate the states – which covers a large variety of applications, including sensor fusion. Finally, we apply these estimators to multi-constellation Precise Point Positioning algorithms and evaluate their performance under several fault scenarios.
Published in: Proceedings of the ION 2024 Pacific PNT Meeting
April 15 - 18, 2024
Hilton Waikiki Beach
Honolulu, Hawaii
Pages: 477 - 490
Cite this article: Blanch, Juan, Lai, Yu-Fang, Walter, Todd, "Integrity-Based Estimators for Precise Point Positioning and Other Applications," Proceedings of the ION 2024 Pacific PNT Meeting, Honolulu, Hawaii, April 2024, pp. 477-490.
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