Title

Cooperative Navigation Using Pairwise Communication with Ranging and Magnetic Anomaly Measurements

Document Type

Article

Publication Date

2020

Abstract

The problem of cooperative localization for a small group of Unmanned Aerial Vehicles (UAVs) in a GNSS denied environment is addressed in this paper. The presented approach contains two sequential steps: first, an algorithm called cooperative ranging localization, formulated as an Extended Kalman Filter (EKF), estimates each UAV's relative pose inside the group using inter-vehicle ranging measurements; second, an algorithm named cooperative magnetic localization, formulated as a particle filter, estimates each UAV's global pose through matching the group's magnetic anomaly measurements to a given magnetic anomaly map. In this study, each UAV is assumed to only perform a ranging measurement and data exchange with one other UAV at any point in time. A simulator is developed to evaluate the algorithms with magnetic anomaly maps acquired from airborne geophysical survey. The simulation results show that the average estimated position error of a group of 16 UAVs is approximately 20 meters after flying about 180 kilometers in 1 hour. Sensitivity analysis shows that the algorithms can tolerate large variations of velocity, yaw rate, and magnetic anomaly measurement noises. Additionally, the UAV group shows improved position estimation robustness with both high and low resolution maps as more UAVs are added into the group.

Comments

The "Link to Full Text" on this page directs to the arXiv e-print hosted at the arXiv.org repository.

Copyright © 2020 by Chizhao Yang, Jared Strader, Yu Gu, Aaron Canciani, and Kevin Brink. Published by the American Institute of Aeronautics and Astronautics, Inc., with permission.

DOI

10.2514/1.I010785

Source Publication

Journal of Aerospace Information Systems

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