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A cumulant-based parameter estimation algorithm for near-field sources

机译:基于累积量的近场源参数估计算法

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摘要

To efficiently use the array aperture and avoid the complicated parameter pairing computation, this paper proposes a new cumulant-based algorithm for localizing near-field narrowband sources. Firstly, this algorithm proposes a symmetric uniform lineararray (ULA), and constructs three cumulant matrices by using the fourth-order cumulants of some properly chosen sensor outputs; secondly, unlike the conventional parallel factor (PARAFAC) analysis models in data or subspace domain, it forms a three-wayarray (TWA) in the fourth-order cumulant domain using the three matrices, and analyzes the uniqueness of its low-rank decomposition; thirdly, it jointly estimates the frequency, the direction-of-arrival (DOA), and the range of each near-field source fromthe matrices via the low-rank decomposition of the TWA. The simulation results are presented to validate the performance of our proposed method.
机译:为了有效地利用阵列孔径并避免复杂的参数配对计算,本文提出了一种新的基于累积量的近场窄带源定位算法。首先,该算法提出了一种对称均匀线性阵列(ULA),并利用一些正确选择的传感器输出的四阶累积量构造了三个累积量矩阵。其次,与数据或子空间域中的常规并行因子(PARAFAC)分析模型不同,它使用这三个矩阵在四阶累积量域中形成三向阵列(TWA),并分析其低秩分解的唯一性。第三,通过TWA的低秩分解,从矩阵联合估计频率,到达方向(DOA)和每个近场源的范围。仿真结果表明了该方法的有效性。

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