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The Effects of Noise, Sparsity and Phase on Pseudo-Random Time-Space Modulation SAR Performance

SAR based on compressed sensing (CS) greatly reduces the amount of data. The pseudo-random space-time modulation technology could alleviate the constraint on the type of the observed scene. This paper provides a survey on the effects of noise, sparsity, and phase on the modulation technology performance. Selection of a suitable algorithm is necessary to achieve this goal. l1-norm algorithm performs the best of the three algorithms, including greedy algorithm, and Bayesian algorithm. The experiment results show that the performance of the pseudo-random space-time modulation SAR is improved. With the increase of the noise and the decrease of the sparsity, the performance improvement with modulation is more and more limited. With the decrease of phase density, the performance obtained by modulation decreases continuously. When the amplitude variation range exceeds [0,π], the improvements are similar.