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Radar Signature Analysis Using a Joint Time-Frequency Distribution Based on Compressed Sensing

机译:基于压缩感知的联合时频分布的雷达签名分析

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摘要

A previously proposed time-frequency distribution based on compressed sensing (CS) is applied to radar backscattered signals for signature analysis. The CS joint time-frequency (CSJTF) distribution is based on the Wigner-Ville distribution, but employs CS to remove undesirable cross terms. To adapt the algorithm for radar signals, we develop a search procedure to find the optimal region in the ambiguity plane for achieving the best CSJTF distribution. The algorithm is then applied to backscattering data from several structures of interest, including a pipe, rotating turbine blades, and a moving human. The performance of the CSJTF is compared to that of the short-time Fourier transform and the reassigned spectrogram, and its limitations in time-frequency localization and resolution are discussed.
机译:先前提出的基于压缩感知(CS)的时频分布被应用于雷达反向散射信号以进行特征分析。 CS联合时频(CSJTF)分布基于Wigner-Ville分布,但采用CS消除了不希望的交叉项。为了使该算法适合雷达信号,我们开发了一种搜索程序,以在歧义平面中找到最佳区域以获得最佳CSJTF分布。然后将该算法应用于从多个感兴趣的结构(包括管道,旋转的涡轮叶片和移动的人)中反向散射数据。将CSJTF的性能与短时傅立叶变换和重新分配的频谱图进行了比较,并讨论了其在时频定位和分辨率方面的局限性。

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