ASTARS empowered Satellite Positioning Approach for Urban Canyons and Indoor Environments
🤖 AI Summary
To address GNSS positioning failure caused by the absence of line-of-sight (LOS) signals in urban canyons and indoor environments, this paper proposes a novel non-line-of-sight (NLOS) high-precision positioning paradigm leveraging actively tunable, transmissive–reflective reconfigurable intelligent surfaces (ASTARS). We introduce the concept of extended line-of-sight (E-LoS) paths and establish a carrier-phase observation model that integrates ASTARS’s dynamically controllable transmission and reflection characteristics. Coupled with network time synchronization (≤10 ns timing error) and a dynamic path-distance correction algorithm, our approach significantly enhances the quality of NLOS measurements. Position estimation is performed via least-squares optimization. Simulation results demonstrate positioning errors ≤4 m in both indoor and urban-canyon scenarios—improving upon conventional NLOS methods by over 3 m—and confirm substantial gains in accuracy and continuity under challenging multipath and signal-obstruction conditions.
Application Category
📝 Abstract
To mitigate the loss of satellite navigation signals in urban canyons and indoor environments, we propose an active simultaneous transmitting and reflecting reconfigurable intelligent surface (ASTARS) empowered satellite positioning approach. Deployed on building structures, ASTARS reflects navigation signals to outdoor receivers in urban canyons and transmits signals indoors to bypass obstructions, providing high-precision positioning services to receivers in non-line-of-sight (NLoS) areas. The path between ASTARS and the receiver is defined as the extended line-of-sight (ELoS) path and an improved carrier phase observation equation is derived to accommodate that. The receiver compensates for its clock bias through network time synchronization, corrects the actual signal path distance to the satellite-to-receiver distance through a distance correction algorithm, and determines its position by using the least squares (LS) method. Mathematical modeling of the errors introduced by the proposed method is conducted, followed by simulation analysis to assess their impact. Simulation results show that: 1) in areas where GNSS signals are blocked, with time synchronization accuracy within a 10 ns error range, the proposed method provides positioning services with errors not exceeding 4 m for both indoor and outdoor receivers, outperforming conventional NLoS methods with positioning errors of more than 7 m; 2) the additional errors introduced by the proposed method do not exceed 3 m for time synchronization errors within 10 ns, which includes the phase shift, beamwidth error, time synchronization errors, and satellite distribution errors, outperforming traditional NLoS methods, which typically produce positioning errors greater than 5 m.
Problem
Research questions and friction points this paper is trying to address.
Mitigates signal loss in urban canyons and indoors
Enables high-precision NLoS positioning via ASTARS
Reduces errors below 4m vs traditional NLoS methods
Innovation
Methods, ideas, or system contributions that make the work stand out.
ASTARS reflects and transmits satellite signals
Improved carrier phase observation equation
Network time synchronization compensates clock bias
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