||Kirtland Air Force Base, NM 871175776
|Khanh Dai Pham
GPS is critically important to DoD because it offers ubiquitous positioning, navigation, and timing (PNT) services to the warfighter, particularly for military advantage. This capability becomes the foundation for the logistics and support functions behind the front lines and is also subject to a variety of interference and spoofing threats. Future joint all-domain engagements may necessitate operations in GPS-denied environments. As such, future missions may utilize Multi-Global Navigation Satellite Systems (MGNSS) to provide alternative PNT solutions by employing other satellite navigation sources from foreign GNSS, Regional Navigation Satellite Systems, and commercial signals.
In fact, each external satellite navigation signal carries with it the risk of expanding the surface of vulnerabilities and compromises into protected user equipment. It also introduces the risk of interfering with the quality of existing PNT services already built into the user equipment and thus, reducing their effectiveness. In seeking potential approaches to quantifying, objectively, and empirically assessments of trustworthiness of an actual MGNSS fusion for position, velocity, and time (PVT) solutions, it is important to considering onboard intelligent autonomous agents capable of taking the necessary response and recovery actions, with low-latency response times for confident decision making, robust data fusion techniques, and enhanced MGNSS signal monitoring for MGNSS receivers. The development of trusted use of satellite navigation sources for particular applications and DoD needs will require overcoming the following technical challenges: (i) trust algorithms making confident decisions on appropriate inclusions of satellite navigation sources given the connection of multiple resilience considerations associated with threat absorption, recovery, and adaptation of the user equipment in response to GNSS threats and outages; (ii) fused PVT solutions adaptively selecting meaningful signals based on the strength of association, consistency, and specificity with respect to DoD applications; and (iii) artificially intelligent agents residing onboard user equipment to estimate resilience measures for a given mission and/or application.
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3. Molina-Markham, Andres, and Joseph J. Rushanan. "Positioning, Navigation, and Timing Trust Inference Engine." Proceedings of the 2020 International Technical Meeting of The Institute of Navigation. 2020.
Satellite Navigation Sources; Multi-GNSS; Trust Algorithms; Robust Data Fusion; GNSS Signal Monitoring; Assured PNT solutions