Satellite Navigation: A Transmitting Intelligent Surface (TIS)-aided Indoor System

摘要

A transmitting intelligent surfaces (TISs) aided satellite indoor navigation system is investigated. By leveraging the unique features of TIS, we address the limitations of conventional global navigation satellite systems (GNSS) in providing reliable positioning services within indoor environments. To facilitate the extension of GNSS indoor signals, we establish an extended line-of-sight link using TIS which has the capability to change signal direction. A three-stage TIS-aided satellite indoor positioning algorithm (TSIPA), which utilizes the positions of TIS arrays and the angle of arrival, is proposed to locate indoor users. To evaluate the distribution of TIS arrays, we propose TIS position dilution of precision (TPDoP) to evaluate centroid deviation and utilize the root mean square error (RMSE) to represent compactness.

核心问题与主要方法

核心问题

Indoor GNSS positioning is unreliable because satellite signals lack direct LoS and decay too much indoors

场景：Satellite-to-indoor-user navigation with multiple window-mounted TIS arrays, pseudo-range measurements, and AoA-based localization

主要方法

TIS creates an extended LoS path by transmitting/reconfiguring incident satellite signals into the indoor space instead of relying on direct satellite-user visibility. Stage 1 treats the TIS-user distance as a systematic term and solves improved pseudo-range equations for TIS array coordinates using least squares. Stage 2 models transmit/receive array factors and estimates AoA from TIS to user with a maximum-likelihood estimator over a dictionary/codebook. Stage 3 converts estimated TIS positions and AoAs into rays and solves for the user location by minimizing total distance to non-intersecting rays under measurement error. TPDoP measures deviation of the TIS-array centroid relative to the estimated user location, while RMSE measures TIS distribution compactness.

关键贡献与后续阅读

关键贡献

Formulates a TIS-aided satellite indoor navigation system that uses transmitting intelligent surfaces to extend GNSS-style satellite signals into indoor environments through alternative LoS-like paths. Introduces TSIPA, a three-stage localization pipeline combining pseudo-range-based TIS localization, MLE AoA estimation, and geometric/optimization-based indoor user positioning. Unifies two pseudo-range modes for the same positioning framework: CEM using clock-error-derived range and CPM using carrier phase with integer ambiguity handled via LAMBDA. Defines TPDoP as a placement-quality metric for TIS array centroid deviation and pairs it with RMSE to characterize compactness of TIS deployments. Provides numerical comparisons showing CPM slightly outperforming CEM in the reported setting and LSM outperforming or matching other tested user-position solvers under angular ambiguity and distance sweeps.

研究启发

How sensitive is TSIPA to non-ideal synchronization, atmospheric delays, multipath, and TIS hardware phase/amplitude quantization, which are simplified or ignored in the excerpt? Does the first-stage TIS localization require prior approximate user-TIS distance or an initialization that may be hard to obtain in real indoor deployments? Are the Monte Carlo simulations based on realistic satellite geometry, indoor layouts, and TIS aperture/element constraints, or mainly controlled synthetic placements? How does time-slot activation of one TIS array at a time affect update rate, latency, and scalability for multiple users?

限制与不确定性

The evidence is primarily model- and simulation-based; no real hardware, field trial, or measured indoor GNSS/TIS experiment is present in the payload. Several assumptions are strong for deployment: window-mounted multiple TIS arrays, separable time slots, known satellite positions, resolvable CPM integer ambiguity, and simplified delay/error handling. Positioning accuracy is explicitly degraded by angular ambiguity and by larger TIS-user distances; the method depends on TIS aperture/beamwidth and AoA resolution. The extracted document has rendering gaps for equations, so exact derivations and optimization formulations cannot be fully audited from the payload alone. Relevance and value fields are null, so recommendation relies only on the document excerpts and structure extraction.

参考文献

13 条

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