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Passive Localization of Mixed Far-Field and Near-Field Sources without Estimating the Number of Sources

机译:混合远场和近场源的被动定位,而无需估计源数量

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This paper presents a novel algorithm for the localization of mixed far-field sources (FFSs) and near-field sources (NFSs) without estimating the source number. Firstly, the algorithm decouples the direction-of-arrival (DOA) estimation from the range estimation by exploiting fourth-order spatial-temporal cumulants of the observed data. Based on the joint diagonalization structure of multiple spatial-temporal cumulant matrices, a new one-dimensional (1-D) spatial spectrum function is derived to generate the DOA estimates of both FFSs and NFSs. Then, the FFSs and NFSs are identified and the range parameters of NFSs are determined via beamforming technique. Compared with traditional mixed sources localization algorithms, the proposed algorithm avoids the performance deterioration induced by erroneous source number estimation. Furthermore, it has a higher resolution capability and improves the estimation accuracy. Computer simulations are implemented to verify the effectiveness of the proposed algorithm.
机译:本文提出了一种新的混合远场源(FFSs)和近场源(NFSs)定位算法,无需估计源数。首先,该算法通过利用观测数据的四阶时空累积量,将到达方向(DOA)估计与距离估计分离。基于多个时空累积量矩阵的联合对角化结构,导出了新的一维(1-D)空间谱函数,以生成FFS和NFS的DOA估计。然后,识别FFS和NFS,并通过波束成形技术确定NFS的范围参数。与传统的混合源定位算法相比,该算法避免了错误的源数估计所导致的性能下降。此外,它具有更高的解析能力并提高了估计精度。进行计算机仿真以验证所提出算法的有效性。

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