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TDOA Estimation With Compressive Sensing Measurements and Hadamard Matrix

机译:具有压缩传感测量和Hadamard矩阵的TDOA估计

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摘要

This paper employs a special property of the Hadamard matrix to develop a novel compressive sensing (CS) based framework that eliminates the complex reconstruction step required by standard CS methods. In particular, time-difference-of-arrivals (TDOAs) of a signal at different receivers involved in positioning of unknown sources are directly estimated from CS measurements, without any attempt to reconstruct the full signals. Although this approach is designed for TDOA estimation, it is also capable of accommodating other CS applications.
机译:本文利用Hadamard矩阵的特殊性质来开发一种新颖的基于压缩感知(CS)的框架,该框架消除了标准CS方法所需的复杂重建步骤。特别是,直接从CS测量中直接估计与未知信号源定位有关的不同接收器处的信号到达时间差(TDOA),而无需尝试重​​建完整信号。尽管此方法专为TDOA估计而设计,但它也能够适应其他CS应用。

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