基于奇异值分解的互耦DOA估计方法

Y. Qu, Jian Zhang
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引用次数: 1

摘要

提出了一种相互耦合情况下的测向方法。该方法利用奇异值分解(SVD)从初始估计的到达方向(DOA)计算耦合系数。利用这些计算得到的耦合系数,利用多信号分类(MUSIC)算法可以精确地估计出DOA。在此基础上,通过耦合系数与DOA之间的多次迭代实现盲定标。针对迭代过程中出现的局部最优问题,分别针对单源和多源提出了两种改进方法。仿真结果验证了所提方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SVD-based method for DOA estimation in the presence of mutual coupling
A method for direction finding in the presence of mutual coupling is proposed. The method uses the singular value decomposition (SVD) to calculate coupling coefficients from the initial estimates of the direction-of-arrival (DOA). Exploiting these calculated coupling coefficients, the DOA can be estimated precisely by the multiple signal classification (MUSIC) algorithm. Based on this, Blind calibration is realized by several iterations between coupling coefficients and DOA. To deal with the local optimum problem occurring in these iterations, two improved methods for single and multiple sources respectively are presented. Simulation results demonstrate the effectiveness of the proposed methods.
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