A SAR Autofocus Algorithm Based on Particle Swarm Optimization

Citation

Lim, Tien Sze and Koo, Voon Chet and Ewe, Hong Tat and Chuah, Hean Teik (2008) A SAR Autofocus Algorithm Based on Particle Swarm Optimization. Progress In Electromagnetics Research B, 1. pp. 159-176. ISSN 1937-6472

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Abstract

In synthetic aperture radar (SAR) processing, autofocus techniques are commonly used to improve SAR image quality by removing its residual phase errors after conventional motion compensation. This paper highlights a SAR autofocus algorithm based on particle swarm optimization (PSO). PSO is a population-based stochastic optimization technique based on the movement of swarms and inspired by social behavior of bird flocking or fish schooling. PSO has been successfully applied in many different application areas due to its robustness and simplicity [1–3]. This paper presents a novel approach to solve the low-frequency high-order polynomial and high-frequency sinusoidal phase errors. The power-to-spreading noise ratio (PSR) and image entropy (IE) are used as the focal quality indicator to search for optimum solution. The algorithm is tested on both simulated two-dimensional point target and real SAR raw data from RADARSAT-1. The results show significant improvement in SAR image focus quality after the distorted SAR signal was compensated by the proposed algorithm.

Item Type: Article
Subjects: Q Science > Q Science (General)
Divisions: Faculty of Engineering and Technology (FET)
Depositing User: Ms Rosnani Abd Wahab
Date Deposited: 29 Nov 2013 04:52
Last Modified: 29 Dec 2020 17:32
URII: http://shdl.mmu.edu.my/id/eprint/4510

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