← 研踪 PaperTrailarXiv:2611.02378 · v1
A Beam-Switched Sparse Circular Array for Passive Wi-Fi Sensing
首次提交 2026-11-02 09:46
版本更新 2026-11-02 09:46
雷达观测 2026-11-04 23:42
摘要
Wi-Fi sensing applications require unambiguous angle-of-arrival (AoA) estimation over the full azimuth plane. Uniform circular arrays (UCAs) are shown to remove this ambiguity, but deploying the four RF chains typically available on commercial Wi-Fi chipsets into a sparse layout suffers from spatial undersampling. Such undersampling produces strong grating lobes. To overcome this hardware bottleneck, we first establish a generalized array manifold incorporating element radiation patterns, revealing the suitability and degradation mechanisms of directional UCAs. Then we propose an angularly staggered beam-switched UCA architecture that leverages the spatial complementarity. Numerical evaluations demonstrate that the proposed scheme effectively mitigates grating-lobe ambiguities without increasing the number of RF chains, significantly reducing AoA estimation outliers and improving omnidirectional tracking performance.
作者备注：5 pages, 8 figures. Submitted to EuCAP 2027
观测到的版本
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v1 · 2026-11-02 09:46 · 最新观测版本
A Beam-Switched Sparse Circular Array for Passive Wi-Fi Sensing
Wi-Fi sensing applications require unambiguous angle-of-arrival (AoA) estimation over the full azimuth plane. Uniform circular arrays (UCAs) are shown to remove this ambiguity, but deploying the four RF chains typically available on commercial Wi-Fi chipsets into a sparse layout suffers from spatial undersampling. Such undersampling produces strong grating lobes. To overcome this hardware bottleneck, we first establish a generalized array manifold incorporating element radiation patterns, revealing the suitability and degradation mechanisms of directional UCAs. Then we propose an angularly staggered beam-switched UCA architecture that leverages the spatial complementarity. Numerical evaluations demonstrate that the proposed scheme effectively mitigates grating-lobe ambiguities without increasing the number of RF chains, significantly reducing AoA estimation outliers and improving omnidirectional tracking performance.
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