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Source Association, DOA, and Fading Coefficients Estimation for Multipath Signals

机译:多径信号的信号源关联,DOA和衰落系数估计

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This paper addresses the source association (SA), direction of arrival (DOA), and fading coefficients (FCs) estimation problem in multipath environment. First, we establish a rank reduction property for a multipath signal model with the existence of multiple groups of coherent signals. Subsequently, based on this property, effective algorithms for SA, DOA, and FCs estimation have been developed. The proposed DOA and FCs estimation methods exploit the multipath structure information to achieve improved accuracy. The new DOA estimation methods work well even in the case that the DOAs of the multipath signals associated with different sources are (nearly) overlapped. Meanwhile, the new methods are applicable to arbitrary array geometry while without decreasing the effective array aperture. Then, the stochastic Cramér-Rao bound on DOA and FCs estimation of multipath model (MCRB) exploiting the multipath structure information is derived in closed form. Numerical simulations have been provided to demonstrate the effectiveness of the proposed methods.
机译:本文解决了多径环境中的信源关联(SA),到达方向(DOA)和衰落系数(FCs)估计问题。首先,我们建立了具有多组相干信号的多径信号模型的秩降低特性。随后,基于此属性,开发了用于SA,DOA和FC估计的有效算法。提出的DOA和FC估计方法利用多径结构信息来提高准确性。即使在与不同源关联的多径信号的DOA(几乎)重叠的情况下,新的DOA估计方法也能很好地工作。同时,新方法适用于任意阵列几何形状,而不会减小有效阵列孔径。然后,以封闭形式导出DOA的随机Cramér-Rao边界和利用多径结构信息的多径模型(MCRB)的FC估计。提供了数值模拟,以证明所提出方法的有效性。

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