Integration of Navigation and Remote Sensing in LEO Satellite Constellations

2025-11-15

AI Summary

To address the functional isolation and insufficient synergy between navigation and remote sensing in low Earth orbit (LEO) satellite constellations, this paper proposes a novel deeply integrated navigation–remote sensing constellation architecture. A multi-satellite cooperative beamforming design is developed to establish a unified signal model, and— for the first time—a joint performance metric combining the Cramér–Rao bound (CRB) and signal-to-ambiguous-interference-and-noise ratio (SAINR) is introduced to enable dual-function coupling optimization. Furthermore, a weighted position–velocity–time (PVT) error minimization framework for joint beamforming is proposed, achieving significant PVT error reduction while satisfying SAINR constraints for remote sensing. Simulation results demonstrate that the proposed scheme improves navigation accuracy by over 35% compared to conventional segregated designs, establishing a scalable, synergistic optimization paradigm for multifunctional LEO satellite networks.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Intelligent Robots: State Estimation
• Constraint Satisfaction and Optimization: Constraint Optimization

Application Category

• Semantics and Knowledge: Methods to enhance, augment, integrate or synergize semantic models such as knowledge graphs and LLMs
• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization
• Security and Privacy: Large-scale security measurements

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.

Problem

• Integrating navigation and remote sensing in LEO constellations
• Developing joint beamforming design for dual functions
• Minimizing positioning errors while ensuring sensing performance

Innovation

• Dual-function LEO satellite constellation frame structure
• Joint beamforming design minimizing PVT error
• Multi-satellite cooperative beamforming for integrated navigation