Gipson, Jonathon (United States Air Force Institute of Technology (AFIT)), Leishman, Robert (Air Force Institute of Technology), Schubert Kabban, Schubert Kabban (Air Force Institute of Technology)

Swarm Control for Autonomous Navigation Support

Scheduled for presentation during the Regular Session "Networked Swarms II" (WeC3), Wednesday, September 2, 2020, 18:00−18:20, Edessa

2020 International Conference on Unmanned Aircraft Systems (ICUAS), September 1-4, 2020 (Postponed from June 9-12, 2020), Athens, Greece

This information is tentative and subject to change. Compiled on May 10, 2024

Abstract

In a denied environment, vehicles equipped with all-source navigation capabilities (e.g. magnetic, visual, etc.) can maintain assured PNT solutions and serve as anchors for other vehicles in a surveillance network. Mission vehicles not equipped with these features are subject to integration drift and can benefit from relative navigation updates. In a surveillance network, vehicles can perform relative measurement updates using radio ranging. In a time-synchronized network, localization accuracy for vehicles equipped only with radio ranging is primarily dependent on multilateration geometry. The primary contribution of this paper is a real-time distributed swarm control scheme to autonomously optimize multilateration for offboard mission vehicles in a surveillance network. Swarm guidance is provided by Semi-Cooperative Self-Aligning Swarm (SCSAS), a distributed greedy algorithm which uses surveillance data to control navigation support vehicles to optimize multilateration for selected offboard mission vehicles. Using multiple 10K-trial Monte Carlo simulations, the proposed algorithm demonstrates distributed control which results in consensus-like optimization of 2-D position MSE for selected offboard mission vehicles broadcasting surveillance data.