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Optimal waveform selection for radar target classification

机译:雷达目标分类的最佳波形选择

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We apply a sequential experiment design procedure to the problem of signal selection for radar target classification. Radar waveforms are designed to discriminate between targets possessing a doubly-spread reflectivity function that are observed in clutter. The waveforms minimize decision time by maximizing the discrimination information in the echo signal. Each waveform selected maximizes the Kullback-Leibler (1951) information number that measures the dissimilarity between the observed target and alternative targets. We discuss two scenarios. In the first scenario, the target environment is assumed fixed during illumination. In this case the optimal waveform selection strategy leads to a fixed library of waveforms. During actual classification, the sequence in which the waveforms are selected from the library is determined from the noise to clutter power in the range-Doppler support of the targets. In the second scenario, the target environment changes between pulse transmissions. In this case, the maximum discrimination information is obtained by a repeated transmission of a single waveform designed from the reflectivity function of the targets. We show that our choice of signals can produce significant gains in detection performance.
机译:我们将顺序实验设计程序应用于雷达目标分类的信号选择问题。雷达波形旨在区分在杂波中观察到的具有双重扩展反射率功能的目标。波形通过最大化回波信号中的判别信息来最小化决策时间。所选的每个波形都会最大化Kullback-Leibler(1951)信息数量,该信息数量可衡量观察到的目标与替代目标之间的差异。我们讨论两种情况。在第一种情况下,假定目标环境在照明过程中是固定的。在这种情况下,最佳的波形选择策略将导致固定的波形库。在实际分类期间,从库中选择波形的顺序是根据目标的距离多普勒支持中的噪声到杂波功率来确定的。在第二种情况下,目标环境在脉冲传输之间改变。在这种情况下,最大的辨别信息是通过重复传输根据目标的反射率函数设计的单个波形获得的。我们证明了我们对信号的选择可以显着提高检测性能。

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