This paper presents a novel approach to enhance sensing capabilities in UAV-enabled MIMO-OFDM ISAC systems by leveraging UAV mobility as a mono-static radar. By integrating uniform planar arrays (UPAs) and modeling the UAV dynamics in SE(3), we address key challenges such as 3D space sensing and trajectory design. We propose a target tracking scheme using extended Kalman filtering (EKF) in SE(3), along with trajectory optimization based on the conditional Posterior Cramer-Rao bound (CPCRB). Numerical results demonstrate the effectiveness of the proposed trajectory design in enhancing performance of target tracking and physical parameter estimation in UAV-enabled MIMO-OFDM ISAC systems.
@article{arxiv.2501.11687,
title = {SE(3)-Based Trajectory Optimization and Target Tracking in UAV-Enabled ISAC Systems},
author = {Dongxiao Xu and Xinyang Li and Vlad C. Andrei and Moritz Wiese and Ullrich J. Moenich and Holger Boche},
journal= {arXiv preprint arXiv:2501.11687},
year = {2025}
}
Comments
Accepted by IEEE International Symposium on Information Theory 2025