Abstract
The presence of a space-invariant sinusoidal phase error in the azimuth SAR (synthetic aperture radar) signal history causes paired echoes to appear in the system impulse response [1]. These high peaksidelobes may be interpreted erroneously as separate targets by conventional autofocus algorithms. In this paper, a new approach to solve the high-frequency phase noise problems in SAR imaging is presented. The phase error is formulated as a nonlinear optimization problem for continuous variables. The optimum solution is obtained by minimizing the entropy of the signal. The proposed algorithm utilizes a real-coded genetic algorithm (GA) in the first stage to direct the search towards the global optimum region and a local search method in the second stage to do fine tuning. The algorithm is tested on simulated point targets and the results show significant improvement in the target response, as compared to the conventional autofocus and optimization algorithms. Thus the efficiency and the success rate of the algorithm are placed in sharper focus to minimize high frequency phase noise. Furthermore, the complexity of the problems solved clearly demonstrates the usefulness of this novel approach in solving such nonlinear systems.
Published Version
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