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Session F3: Navigating in Challenged Environments (e.g., Urban, Indoor and Subsurface Navigation)

Combining Navigation Resiliency and Optimal Guidance for Thrusted PGMs
Caleb Peck, Manan Gandhi, Connor Brashar, Sandia National Laboratories
Location: Room 6-8
Alternate Number 2

As the sensor suite supporting position, navigation, and timing (PNT) solutions of precision guided munitions (PGMs) continues to evolve and advance, the threats facing these systems also continue to grow [1,2,3]. Complex sensing can lead to complex vulnerabilities that must be considered when fielding these systems. The objective of this work is to ensure mission success by automating PNT threat considerations into the PGM mission planning process. This goal is accomplished by integrating threat-aware PNT constraints into a modern trajectory optimization system.
A key PNT threat to modern PGMs is the denial of GNSS through intentional interference, or jamming [4]. Jamming attempts to deny access to GNSS by raising the apparent noise floor to the point that navigation signals are obscured, thereby denying high-precision positioning information to the PGM. Modern navigation systems employ a variety of hardware and signal processing solutions to mitigate the effects of these attacks [5,6,7], but a poorly planned mission can still place a PGM into regions of total denial and put mission success at risk [8]. This work proposes an automated approach to guarantee safe mission planning by forming a tractable optimal control problem incorporating PNT requirements and solving it to guide a PGM safely to its target.
The vehicle considered in this work is a thrusted PGM with a GPS-INS sensor suite onboard. A simple 3 degree of freedom dynamics model is employed which balances model accuracy to computational expenditure. The objective is for the vehicle to reach the target state with maximum velocity subject to dynamic, control, and navigation constraints. This work considers mission-relevant vehicle dynamics and introduces a novel PNT threat modeling framework. An estimate of the navigation performance of the vehicle is computed by tracking the GPS state and position covariance of the vehicle throughout the mission. The GPS state is directly influenced by the GNSS threat environment which in turn affects the navigation performance of the vehicle’s PNT system. Constraints are placed in the optimal control problem to ensure PNT efficacy in the presence of threats. If no feasible solution exists, recommendations for next steps are proposed.
REFERENCES:
[1] A. Walsh, “Sweden accuses russia of gps jamming over baltic sea,” BBC, 4 Sept. 2025. URL: https://bbc.com/news/articles/clyx3ly54veo.
[2] S. McNeil and V. Petrova, “Russia is suspected of jamming navigation on eu leader’s plane above bulgaria, official says,” AP, 1 Sept. 2025. URL: https://apnews.com/article/europe-leyen-plane-radar-russia-
jammed-51fa78294c2d0464dce5fd24dd4f273b.
[3] https://gpsjam.org/.
[4] E. D. Kaplan and C. Hegarty, Understanding GPS/GNSS: principles and applications. Artech house, 2017.
[5] P. D. Groves and D. C. Long, “Combating gnss interference with advanced inertial integration,” The Journal of Navigation, vol. 58, no. 3, pp. 419–432, 2005.
[6] E. McMilin, D. S. De Lorenzo, T. Lee, P. Enge, D. Akos, S. Caizzone, and A. Konovaltsev, “Gps anti-jam: A simple method of single antenna null-steering for aerial applications,” in Proceedings of the ION 2015 Pacific PNT Meeting, pp. 470–483, 2015.
[7] F. Leveau, S. Boucher, E. Goron, and H. Lattard, “Anti-jam protection by antenna: Conception, realization, evaluation of a seven-element gnss crpa,” GPS world, vol. 24, no. 2, pp. 30–34, 2013.
[8] C. Peck, T. Bernard, C. Brashar, and J. Parish, “Navigation informed trajectory optimization,” in Proceedings of the ION Joint Navigation Conference, 2024

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