This letter presents a tensor-based joint AoA and ToF estimation method using the channel state information for Wi-Fi systems. Our method can mitigate the estimation error caused by the signal phase offset and noise interference using linear regression and discrete wavelet transform, respectively. Moreover, the Cramér-Rao lower bound for joint AoA and ToF estimation is derived for performance evaluation. Finally, Wi-Fi measurements are taken in indoor scenarios, and the numerical results show that the proposed method can reduce the estimation errors by more than 20% in comparison with existing algorithms.

中文翻译：

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一种基于张量的 Wi-Fi 系统联合 AoA 和 ToF 估计方法


这封信提出了一种使用 Wi-Fi 系统信道状态信息的基于张量的联合 AoA 和 ToF 估计方法。我们的方法可以分别使用线性回归和离散小波变换来减轻由信号相位偏移和噪声干扰引起的估计误差。此外，还导出了联合 AoA 和 ToF 估计的 Cramér-Rao 下界以进行性能评估。最后，在室内场景下进行Wi-Fi测量，数值结果表明，与现有算法相比，该方法可以减少估计误差20%以上。