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Monopulse Radar Detection and Localization of Multiple Unresolved Targets via Joint Bin Processing

机译:通过联合bin处理对多个未解决目标进行单脉冲雷达检测和定位

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摘要

If several closely spaced targets fall within the same radar beam and between two adjacent matched filter, samples in range, monopulse information from both of these samples can and should be used for estimation, both of angle and of range (i.e., estimation of the range to sub-bin accuracy). Similarly, if several closely spaced targets fall within the same radar beam and among three matched filter samples in range, monopulse information from all of these samples should be used for the estimation of the angles and ranges of these targets. Here, a model is established, and a maximum likelihood (ML) extractor is developed. The limits of the number of targets that can be estimated are given for both case A, where the targets are in a beam and in a range "slot" between the centers of two adjacent resolution cells (that is, from detections in two adjacent matched filter samples), and case B, where the targets are in two or more adjacent slots (among three or more adjacent samples). A minimum description length (MDL) criterion is used to detect the number of targets between the matched filter samples, and simulations support the theory.
机译:如果几个间隔很近的目标落在同一雷达波束内以及两个相邻的匹配滤波器之间,则在范围内的样本,来自这两个样本的单脉冲信息可以并且应该用于角度和范围的估计(即,范围的估计)以子箱精度)。同样,如果几个间隔很小的目标落在同一雷达波束内,并且在范围内的三个匹配滤波器样本之间,则应使用所有这些样本的单脉冲信息来估算这些目标的角度和范围。在此,建立模型,并开发最大似然(ML)提取器。对于两种情况A,都给出了可以估计的目标数量的限制,在这种情况下,目标位于光束中,并且位于两个相邻分辨率单元的中心之间的“狭槽”内(即,根据对两个相邻匹配单元的检测)过滤器样本)和情况B,其中目标位于两个或多个相邻的时隙中(三个或多个相邻的样本之中)。最小描述长度(MDL)准则用于检测匹配的滤波器样本之间的目标数量,并且仿真支持该理论。

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