Array processing for passive localization of a source in the near field

C. Comsa
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Abstract

This publication presents a coherent processing method for RF (radio frequency) source localization in a plane by employing a passive sensor array, widely distributed over a given area. The context of the localization technique discussed involves placement of the source in the near field of the sensor array and unknown character of the source in the sense that the transmitted signal, its power spectral density, and its timing are unknown to the sensors. However, the sensors have ideal mutual time and phase synchronization, highly precise knowledge of their own location, and ideal communication link to a fusion center. The source location is centrally estimated by coherently processing the received signals. For this, an estimator is derived exploiting the source location information in the phase difference of the received signals at pairs of sensors. An analytical expression is developed for the Cramer Rao lower bound (CRLB) relating the mean square error (MSE) of the location estimates to the source signal parameters and sensors layout. Numerical examples and Monte Carlo analysis validate the close form expression developed and show the high accuracy capabilities of the source localization via the presented coherent processing method.
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近场源被动定位的阵列处理
本出版物提出了一种相干处理方法,射频(射频)源定位在一个平面上,采用无源传感器阵列,广泛分布在给定区域。所讨论的定位技术的背景涉及到源在传感器阵列近场的位置和源的未知特性,即发射信号、其功率谱密度和时间对传感器是未知的。然而,传感器具有理想的相互时间和相位同步,对自身位置的高度精确了解,以及与融合中心的理想通信链路。通过对接收到的信号进行相干处理,集中估计源位置。为此,推导了利用传感器对接收信号相位差中的源位置信息的估计器。给出了定位估计的均方误差(MSE)与源信号参数和传感器布局之间的Cramer - Rao下界的解析表达式。数值算例和蒙特卡罗分析验证了所建立的紧密形式表达式,并证明了该相干处理方法具有较高的源定位精度。
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