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Focusing inverse synthetic aperture radar images with higher-order motion error using the adaptive joint-time–frequency algorithm optimised with the genetic algorithm and the particle swarm optimisation algorithm – comparison and results

Focusing inverse synthetic aperture radar images with higher-order motion error using the adaptive joint-time–frequency algorithm optimised with the genetic algorithm and the particle swarm optimisation algorithm – comparison and results

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Algorithms based on the genetic algorithm (GA) and the particle swarm optimisation (PSO) algorithm were designed for focusing inverse synthetic aperture radar (ISAR) images that suffered from degradation because of Doppler smearing. These algorithms optimised the adaptive joint-time–frequency (AJTF) algorithm by replacing the exhaustive search as the primary search tool used to determine focusing parameters. The use of the PSO for ISAR image focusing is a unique application of this evolutionary search. Performance of the GA and the PSO were compared with the PSO producing the optimal results of being able to focus a 211 pulse ISAR image with second-order motion error in 9 s or 24% of the cost function calculations required for an exhaustive search. The PSO algorithm was then applied to a 211 pulse ISAR image with fourth-order motion error. The PSO algorithm was able to focus this image in 20 s with 33% of the cost function calculations required by the exhaustive search. This study also introduces a new method of determining basis function suitability using the fast Fourier transform.

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