In array signal processing, source-sensor amplitude responses are in general assumed to be in equality and signal parameters are estimated by exploiting spatial phase difference caused by propagation delay. This is unrealistic when sources are located in the near-field of the array. In near field, array sensors’ amplitude responses are inversely proportional to the radial distance from the sources. This spatial amplitude ratio is exploited for near-field parameter estimation in this letter. We derive an angle, range and polarization parameters estimation algorithm for multiple polarized sources using a linear cocentered orthogonal loop and dipole (COLD) array. We define the algorithm’s name as SPatial Amplitude Ratio based Estimator (SPARE). Compared with previous phase-based algorithms, SPARE has the following advantages: (1) it is closed-form, non-iterative, and search-free, (2) it is applicable to irregular array geometry, and has no restrict on minimum sensor-spacing, since array sensors’ amplitude responses are necessarily unambiguous, and (3) it can be applied to the arrays with phase uncertainties.

中文翻译：

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使用空间幅度比的偏振源近场参数估计

在阵列信号处理中，通常假设源-传感器幅度响应是相等的，并且通过利用传播延迟引起的空间相位差来估计信号参数。当源位于阵列的近场时，这是不现实的。在近场中，阵列传感器的幅度响应与距源的径向距离成反比。在这封信中，该空间幅度比被用于近场参数估计。我们使用线性同心正交环和偶极子 (COLD) 阵列推导出用于多个偏振源的角度、距离和偏振参数估计算法。我们将算法的名称定义为基于空间幅度比的估计器 (SPARE)。与之前的基于相位的算法相比，SPARE 具有以下优点：（1）它是封闭形式的，