Improved autofocusing of 110 2500

ostepped-frequency ISAR images using new form of particle swarm optimisation S.H. Park, H.T. Kim and K.T. Kim An autofocusing method is proposed to compensate for the inter-pulse phase errors in stepped-frequency ISAR imaging. A genetic algorithm, particle swarm optimisation (PSO), and a combination of PSOs (CPSO) model were applied and compared with the existing subarray averaging and entropy minimisation method. In simulations using measured data, CPSO gave the most accurate and stable results. Introduction: In stepped-frequency ISAR imaging, the motion of the target between pulses in a burst can blur the range profile seriously. We propose a stepped-frequency motion compensation procedure using particle swarm optimisation (PSO) [1]. For this purpose, a genetic algorithm (GA) [2] and PSO using the entropy cost functio