基于多频带无线电信道测量的多分辨率到达时间估计
Multiresolution time-of-arrival estimation from multiband radio channel measurements
摘要：
由于多径信道脉冲响应（CIR）不受带宽限制，因此在多径传播场景下利用通信信号的带限观测值实现高分辨率的到达时间（TOA）估计具有挑战性。将CIR建模为稀疏Dirac序列，TOA估计成为从观测到的带限信号进行参数谱推断的问题。为了提高分辨率而不达到不切实际的采样率，我们考虑多带采样方法，并提出了一个实用的多分支接收机的收购。由此产生的数据模型具有多个平移不变性结构，我们提出了相应的多分辨率TOA估计算法的基础上的ESPRIT算法。该算法的性能进行了比较，对派生的克拉美罗下界，使用模拟与标准化的超宽带（UWB）信道模型。我们表明，所提出的方法提供了高分辨率的估计，同时减少频谱占用和采样成本相比，传统的UWB方法。
英文摘要：
Achieving high resolution time-of-arrival (TOA) estimation in multipath propagation scenarios from bandlimited observations of communication signals is challenging because the multipath channel impulse response (CIR) is not bandlimited. Modeling the CIR as a sparse sequence of Diracs, TOA estimation becomes a problem of parametric spectral inference from observed bandlimited signals. To increase resolution without arriving at unrealistic sampling rates, we consider multiband sampling approach, and propose a practical multibranch receiver for the acquisition. The resulting data model exhibits multiple shift invariance structures, and we propose a corresponding multiresolution TOA estimation algorithm based on the ESPRIT algorithm. The performance of the algorithm is compared against the derived Cramér Rao Lower Bound, using simulations with standardized ultra-wideband (UWB) channel models. We show that the proposed approach provides high-resolution estimates while reducing spectral occupancy and sampling costs compared to traditional UWB approaches.
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