量子粒子群算法的弹载SAR图像自聚焦方法

为了补偿弹载合成孔径雷达( SAR)回波数据中的相位误差,研究了一种新颖的SAR图像自聚焦算法.该方法以量子粒子群( QPSO)算法为基础,利用最小熵准则作为评判标准,通过多维搜索完成相位误差校正,改善聚焦质量以提高打击精度.同传统的相位梯度自聚焦算法(PGA)相比,该方法具有较好的鲁棒性和收敛速度快的特点,对低频高阶...

A Missile-borne SAR Autofocus Method Based on Quantum Particle Swarm Optimization Algorithm

A new autofocus method is presented to compensate the phase error in missile-borne SAR echo.This method utilizes the quantum particle swarm optimization(QPSO) algorithm and takes image entropy(IE) as the criterion to search for the optimum solution.It greatly improves the focusing quality of missile-borne SAR to increase the missile’s attack precision.It has better robustness and more rapid convergence compared with the traditional phase gradient autofocus algorithm(PGA).It can compensate the low-frequency high order phase error.Furthermore,this method can be used in many situations,especially for the images without any significant features.The simulation results show the validity of the proposed method.