10.07102501 - Progress In Electromagnetics Research B, Vol....

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Progress In Electromagnetics Research B, Vol. 1, 159–176, 2008 A SAR AUTOFOCUS ALGORITHM BASED ON PARTICLE SWARM OPTIMIZATION T. S. Lim, V. C. Koo, H. T. Ewe, and H. T. Chuah Faculty of Engineering & Technology Multimedia University Jalan Ayer Keroh Lama, Bukit Beruang, 75450 Melaka, Malaysia 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 ±sh schooling. PSO has been successfully applied in many di²erent 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 signi±cant improvement in SAR image focus quality after the distorted SAR signal was compensated by the proposed algorithm. 1. INTRODUCTION Synthetic Aperture Radar (SAR) system achieves ±ne azimuth resolution by taking the advantage of the forward motion of the radar platform to synthesize a very large antenna aperture and special processing of the backscattered echoes. A major challenge in SAR system development involves compensation for undesirable variations in the azimuth SAR phase history. Primary causes of these phase variations include oscillator and other subsystem phase instabilities, uncompensated sensor motion, and atmospheric propagation.
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160 Lim et al. The uncompensated along-track motions errors can cause a severe loss of geometry accuracy and degrade SAR image quality. In a typical airborne SAR system, an inertia navigation unit (INU) and a global positioning system (GPS) are employed to provide real- time data for motion error compensation. After conventional motion compensation, autofocus techniques are widely used to improve image focus. Autofocus refers to the computer-automated estimation and compensation of residual phase errors in SAR imagery. Basically phase errors may be categorized as low-frequency phase errors and high-frequency phase errors. The detail classiFcation of phase errors can be found in [4]. Depending on its nature and magnitude, phase errors can signiFcantly degrade the image quality in terms of geometry linearity, resolution, image contrast, and signal- tonoise ratio (SNR). Basically the low-frequency phase errors a±ect the mainlobe of the system impulse response while high-frequency phase errors a±ect the sidelobe region.
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10.07102501 - Progress In Electromagnetics Research B, Vol....

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