自适应Chirplet信号分解用于ISAR目标三维转动检测

当ISAR目标作复杂的三维转动时,目标上各散射点的相位误差将与它们在目标上所处的位置有关,传统的相位聚焦方法难以采用统一的相位校正函数来进行补偿。为解决此问题,论文提出了一种基于自适应Chirplet信号分解的ISAR目标三维转动检测方法,该方法使用自适应Chirplet信号分解的快速算法来估计散射点子回波的相位信息,并根据两个散射点相位之间的非线性度来判断目标是否存在三维转动,从而只选择那些仅具有二维转动的数据段进行成像。仿真实验结果表明了它的有效性。

Detecting the Three-dimensional Rotation of ISAR Target Using Adaptive Chirplet Signal Decomposition

In Inverse Synthetic Aperture Radar (ISAR) imaging, phase error caused by three-dimensional rotation is relevant to the position of the scatterer, so it is difficult to use traditional phase autofocus algorithms to complete phase compensation, in which the uniform phase correction function is applied. In order to resolve this problem, a three-dimensional rotation detection method is put forward to complete the selection of imaging times, in which the motion state of target is two-dimensional rotation. In this method, the phases of two arbitrary scatterers are estimated by adaptive Gaussian chirplet decomposition (AGCD) fast algorithm, and the target rotation state is obtained by measuring the non-linearity of the two phases, which means those intervals that the target just has two-dimensional rotation are selected to obtain the ISAR images. Numerical simulation results prove its good efficiency.