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Mixed Near-Field and Far-Field Source Localization Based on Uniform Linear Array Partition

机译:基于均匀线性阵列划分的混合近场和远场源定位

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摘要

Based on the polynomial decomposing method and high-order cumulant technique, a novel localization algorithm for the mixed near-field (NF) and far-field (FF) sources is proposed by using a uniform linear array (ULA). First, the ULA is divided into two sub-arrays, with different phase reference points. Three special fourth-order cumulant matrices are designed to eliminate the range parameters of the NF sources in the steering vectors, which only contain the direction of arrival (DOA) information. Second, based on the ESPRIT algorithm, the DOA of each source at the phase reference point is estimated. Third, with the DOA estimation, the type of the sources is classified by computing its coefficient matrix. Finally, the range parameters of NF sources and the DOAs of FF sources are captured. The proposed algorithm does not require any spectral search, which leads to low computational complexity. Moreover, this algorithm avoids the parameter matching procedure. Numerical experiments are conducted to verify the effectiveness of the proposed algorithm.
机译:基于多项式分解方法和高阶累积量技术,提出了一种使用均匀线性阵列(ULA)的混合近场(NF)和远场(FF)源定位算法。首先,ULA分为两个子阵列,具有不同的相位参考点。设计了三个特殊的四阶累积量矩阵,以消除导引向量中NF源的范围参数,这些参数仅包含到达方向(DOA)信息。其次,基于ESPRIT算法,估计相位参考点处每个源的DOA。第三,利用DOA估计,通过计算其系数矩阵对源的类型进行分类。最后,捕获了NF源的范围参数和FF源的DOA。所提出的算法不需要任何频谱搜索,从而降低了计算复杂度。此外,该算法避免了参数匹配过程。进行了数值实验,验证了所提算法的有效性。

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