In inverse synthetic aperture radar (ISAR) imaging, micro-Doppler (m-D) has always been a hot research topic. m-D will interfere with the imaging of the main body of the target, which will affect the image quality. However, m-D also contains micromotion information. In order to obtain a clearer image of the main body of the target and more micromotion information, some methods can be considered to separate the rigid body component and the micromotion component in the radar echo. To solve this problem, we propose a short-time chirplet decomposition algorithm to separate radar echo. This algorithm combines the window sliding mechanism with the adaptive chirplet decomposition algorithm. Compared with the adaptive chirplet decomposition algorithm and complex-valued empirical mode decomposition, it has a better separation effect and higher computational efficiency. The signal simulations, ISAR imaging simulations, and measured data experiments verify the effectiveness and superiority of the proposed algorithm.

中文翻译：

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基于短时chirplet分解的ISAR成像微多普勒分离方法

在逆合成孔径雷达（ISAR）成像中，微多普勒（mD）一直是研究的热点。mD 会干扰目标主体的成像，从而影响图像质量。但是，mD 也包含微动信息。为了获得更清晰的目标主体图像和更多的微动信息，可以考虑采用一些方法将雷达回波中的刚体分量和微动分量分离。为了解决这个问题，我们提出了一种短时chirplet分解算法来分离雷达回波。该算法结合了窗口滑动机制和自适应chirplet分解算法。与自适应chirplet分解算法和复值经验模态分解相比，它具有更好的分离效果和更高的计算效率。信号仿真、ISAR成像仿真和实测数据实验验证了所提算法的有效性和优越性。