Cooperative Navigation within UAV Swarms via Centralized-Unscented Kalman Filtering to Reduce C-SWAP Requirements

Eryn Jaramillo, Xander Jones, Daniel Kimball-Garrett Mills, David L. Olson, Stephen Bruder, and Aly El-Osery

Abstract:	Recent advancements in autonomous systems have spurred research in cooperative navigation. Inspired by the maneuvering abilities of a marching band, the unmanned aerial vehicles (UAVs) are equipped with a sensor array system comprising of an INS, GPS, and ranging device, ensuring comprehensive observability in both absolute and relative positioning. This paper adopts an error-space centralized-unscented Kalman filter architecture for swarm communication to estimate positions, velocities, and attitudes (PVAs), in order to enhance the overall positioning of a swarm of UAVs. The proposed algorithm is evaluated through Monte Carlo simulations, demonstrating improved swarm performance whilst traveling along a figure-eight trajectory while maintaining a pyramidal configuration. The study assesses individual and collaborative performance, revealing potential benefits from cooperative aiding that may reduce the cost, size, weight, and power (C-SWAP) requirements of the overall swarm by utilizing a leader to enhance the relative distancing and absolute positioning of its followers. The presented algorithm shows promise for reducing the C-SWAP requirements for real-world applications in swarm navigation.
Published in:	Proceedings of the ION 2024 Pacific PNT Meeting April 15 - 18, 2024 Hilton Waikiki Beach Honolulu, Hawaii
Pages:	636 - 648
Cite this article:	Jaramillo, Eryn, Jones, Xander, Mills, Daniel Kimball-Garrett, Olson, David L., Bruder, Stephen, El-Osery, Aly, "Cooperative Navigation within UAV Swarms via Centralized-Unscented Kalman Filtering to Reduce C-SWAP Requirements," Proceedings of the ION 2024 Pacific PNT Meeting, Honolulu, Hawaii, April 2024, pp. 636-648. https://doi.org/10.33012/2024.19622
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