Compressed Sensing Reconstruction Algorithms with Prior Information: Logit Weight Simultaneous Orthogonal Matching Pursuit

Prior information is easily obtained in many applications of compressed sensing. This paper considers the sparse signal recovery using certain types of prior information. Our major contribution is proposing two novel reconstruction algorithms with prior information named as logit weight simultaneous orthogonal matching pursuit (LW-SOMP) and logit weight simultaneous orthogonal matching pursuit with amplitude information (LW-SOMP-A) for joint sparsity model of distributed compressed sensing. Simulation results demonstrate improved performance of the proposed algorithms (with respect to the conventional algorithm).