Integration of Navigation and Remote Sensing in LEO Satellite Constellations
Qi Wang, Xiaoming Chen, Qiao Qi, Zhaolin Wang, Yuanwei Liu
TL;DR
The paper addresses integrated navigation and remote sensing in global LEO constellations by proposing a unified dual-function frame and cooperative multi-satellite beamforming. It derives a $CRB$-based bound on PVT performance and a closed-form $SAINR$ for sensing, and then develops a SDR/$BCD$/$SCA$-based suboptimal beamforming algorithm with a rank-one penalty. The approach enables shared hardware and spectrum to deliver high-precision PVT to UEs while achieving high-quality remote sensing over a ground area, validated by simulations on a Walker-Delta-like constellation. The results show convergence within a few tens of iterations and outperformance over baseline designs, illustrating practical viability for future 6G-era satellite networks with global coverage.
Abstract
Low earth orbit (LEO) satellite constellations are becoming a cornerstone of next-generation satellite networks, enabling worldwide high-precision navigation and high-quality remote sensing. This paper proposes a novel dual-function LEO satellite constellation frame structure that effectively integrating navigation and remote sensing. Then, the Cramer-Rao bound (CRB)-based positioning, velocity measurement, and timing (PVT) error and the signal-to-ambiguity-interference-noise ratio (SAINR) are derived as performance metrics for navigation and remote sensing, respectively. Based on it, a joint beamforming design is proposed by minimizing the average weighted PVT error for navigation user equipments (UEs) while ensuring SAINR requirement for remote sensing. Simulation results validate the proposed multi-satellite cooperative beamforming design, demonstrating its effectiveness as an integrated solution for next-generation multi-function LEO satellite constellations.