Research on Generalized Orthogonal Matching Pursuit Algorithm Based on Backtracking Atom Support Set
To address the issue of the generalized orthogonal matching pursuit algorithm(gOMP)being unable to eliminate erroneously matched atoms during its iterative process,a novel algorithm was proposed,that is the generalized orthogonal matching pursuit based on backtracking atom support set(BgOMP).Before selecting atoms in each iteration,the BgOMP algorithm initially examined whether the support set contained atoms incorrectly chosen in previous iterations and updated the atom support set accordingly.This enhanced strategy allowed the algorithm to backtrack and correct previous errors during each iteration.Simula-tion experiments were conducted to verify the performance of the BgOMP algorithm,utilizing the successful reconstruction proba-bility of one-dimensional signals and the peak signal-to-noise ratio(PSNR)of two-dimensional signals as evaluation metrics.The results demonstrate that the BgOMP algorithm significantly improves signal reconstruction performance compared to the original gOMP algorithm.
compressed sensingreconstruction algorithmbacktracking ideaprobability of successful reconstructionpeak signal-to-noise ratio
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