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Direction-of-arrival estimation of multipath signals using independent component analysis and compressive sensing

机译:使用独立分量分析和压缩感测的多径信号到达方向估计

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摘要

Multipath signal is often considered an interference that must be removed. The coherence between multipath and direct component makes it difficult to use conventional direction-of-arrival (DOA) estimation methods in a smart antenna system. This study demonstrates a new multipath signal DOA estimation technique. Unlike the common methods, without decoherence preprocessing, the proposed algorithm first apply a complex fast independent component analysis (cFastICA) algorithm to obtain the steering vectors with multipath information that corresponds to each source signal. Then, according to the special structure of the obtained steering vectors and spatial sparsity of the multipath signal components, the algorithm uses the solution of the sparse signal reconstruction problem in the compressive sensing (CS) theory, and the DOA estimation of the multipath signal is translated into an l1 norm minimization problem. Finally, we search the space spectrums to acquire the DOAs for each direct component and multipath component. Comparative simulation tests and analysis prove the effectiveness of the proposed algorithm in estimation accuracy in underdetermined conditions.
机译:多径信号通常被认为是必须消除的干扰。多径和直接分量之间的相干性使得在智能天线系统中难以使用常规的到达方向(DOA)估计方法。这项研究演示了一种新的多径信号DOA估计技术。与常规方法不同,该算法无需进行去相干预处理,而是首先应用复杂的快速独立分量分析(cFastICA)算法来获得具有对应于每个源信号的多径信息的导引向量。然后,根据所获得的导引向量的特殊结构和多径信号分量的空间稀疏性,该算法使用了压缩感知(CS)理论中稀疏信号重构问题的解,并且多径信号的DOA估计为转化为l1范数最小化问题。最后,我们搜索空间光谱以获取每个直接分量和多径分量的DOA。对比仿真测试和分析证明了该算法在不确定条件下估计精度的有效性。

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