Optimizing a Bank of Kalman Filters for Navigation Integrity using Efficient Software Design

Luis E. Sepulveda, Robert C. Leishman, Kyle Kauffman, Jonathon S. Gipson

Abstract: Alternative navigation is an area of research that employs a variety of sensor technologies to provide a navigation solution in Global Navigation Satellite System degraded or denied environments. The Autonomy and Navigation Technology Center at the Air Force Institute of Technology has recently developed the Autonomous and Resilient Management of All-source Sensors (ARMAS) navigation framework, which utilizes a bank of Kalman filters to provide a navigation solution resilient to sensor failures. The Kalman filter bank size increases exponentially as the number of system sensors and detectable faults are scaled up linearly, which in turn creates a stressful computational power requirement in a real-world large-scale ARMAS application. In an effort to engineer an operational real-time ARMAS system, this study presents a novel approach that utilizes multiple ARMAS subsystems cooperating as a single navigation system to generate a navigation solution with less computational demand. The new software design model allows batches of faulty sensors to be excluded from the final navigation solution under a multiple simultaneous sensor fault situation without the computational stress of identifying every individual faulty sensor. By segregating system sensors into unique groups that are susceptible to a failing under the same circumstances (i.e. satellites operating in the same frequency under a jamming scenario), an ARMAS subsystem can detect the first sensor failure in a group triggering the navigation system to remove the entire sensor group from the navigation solution while continuing recovery efforts within the ARMAS subsystem. Simulations results show that maintaining 37 simultaneous Kalman filters provided equivalent performance to the 2,533,987 simultaneous filters that would be required under the original formulation of ARMAS.
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: 2183 - 2200
Cite this article: Sepulveda, Luis E., Leishman, Robert C., Kauffman, Kyle, Gipson, Jonathon S., "Optimizing a Bank of Kalman Filters for Navigation Integrity using Efficient Software Design," 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. 2183-2200. https://doi.org/10.33012/2021.18069
Full Paper: ION Members/Non-Members: 1 Download Credit
Sign In