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Session B1: Collaborative Navigation Techniques

Resilience for Multi-Filter All-source Navigation Framework
Jonathon S. Gipson and Robert C. Leishman, ANT Center, Air Force Institute of Technology
Date/Time: Tuesday, Aug. 24, 2:50 p.m.

This effort augments the Autonomous and Resilient Management of All-source Sensors (ARMAS) framework and provides a convenient method to assure real-time navigation resilience and eliminate subfilter respawn downtime in the event of a sensor failure. This method presents a novel "observability" subfilter bank. The ARMAS framework was originally developed with linear 2D position and velocity sensors which provided fully overlapping position observability. Initial analysis of ARMAS with GNSS pseudorange data from a sUAS flight test at Camp Atterbury, IN show that ARMAS operations can become inconsistent if the FDE layer subfilters lose overlapping position estimation observability.
To maintain resilience to a single simultaneous sensor failure, we must assume that a single sensor may fail at any time. Since the ``observability'' bank contains a subset of subfilters which will form the new FDE layer after a sensor exclusion, the observable and stabilizable properties guaranteed by SOM are inherited by the newly formed FDE layer. Furthermore, SOM provides the user with a timely warning to augment with additional sensor data and provides a notification when the augmented sensor information is sufficient for resilience to a single simultaneous sensor failure. A Monte Carlo analysis of four example scenarios proves that a loss of overlapping position observability in the FDE layer can result in an inability to exclude a failed sensor and inadvertent validation of a corrupted sensor, resulting in undetected corruption of the main navigation solution. SOM is shown to guarantee ARMAS framework resilience to a single simultaneous sensor failure and is proven by the preservation of the ARMAS FDE and validation processes.



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