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以空间目标为研究对象,针对双基地逆合成孔径雷达(BISAR)成像中双基角变化及同步误差导致的二维ISAR像散焦问题,提出了基于粒子群优化(PSO)的非参数自聚焦算法。算法首先将回波中平动和转动及同步误差等因素导致的相位变化项统一建模,其次将二维图像对比度最大作为优化目标,利用PSO算法对所有高次项相位进行整体优化估计,然后对高阶相位项进行补偿,最后基于补偿后剩余的一阶线性相位项进行方位压缩得到目标的二维ISAR像。算法可解决参数相位误差估计法中因模型误差导致的聚焦精度下降问题,同时也降低了BISAR自聚焦算法的复杂度。通过与参数法自聚焦算法的性能进行对比仿真实验,验证了算法的有效性。
Aiming at the problem of two-dimensional ISAR image defocus caused by bistatic angle variation and synchronization error in bistatic Inverse Synthetic Aperture Radar (BISAR) imaging with space object as the research object, a non-parametric self-focusing based on Particle Swarm Optimization (PSO) algorithm. Firstly, the phase changes due to translational and rotational errors and synchronization errors in the echo are modeled first. Secondly, the contrast of the two-dimensional image is maximized as the optimization objective. The PSO algorithm is used to optimize the phase estimation of all high order terms. The high order phase term is compensated. Finally, the target two dimensional ISAR image is obtained by performing azimuth compression based on the first order linear phase term remaining after compensation. The algorithm can solve the problem of the decrease of the focus accuracy caused by the model error in the parameter phase error estimation method and reduce the complexity of the BISAR self-focusing algorithm. By comparing with the performance of the parameter method self-focusing algorithm, the effectiveness of the algorithm is verified.