Sharif Digital Repository

In this paper we present a new algorithm based on Smoothed ℓ0 (SL0), called Block SL0 (BSL0), for Under-determined Systems of Linear Equations (USLE) in which the nonzero elements of the unknown vector occur in clusters. Contrary to the previous algorithms such as Block Orthogonal Matching Pursuit (BOMP) and mixed ℓ2/ℓ1 norm, our approach provides a fast algorithm, while providing the same (or better) accuracy. Moreover, we will see experimentally that BSL0 has better performance than SL0, BOMP and mixed ℓ2/ℓ1 norm when the number of nonzero elements of the source vector approaches the upper bound of uniqueness theorem  

Multiple-input multiple-output (MIMO) radars offer higher resolution, better target detection, and more accurate target parameter estimation. Due to the sparsity of the targets in space-velocity domain, we can exploit Compressive Sensing (CS) to improve the performance of MIMO radars when the sampling rate is much less than the Nyquist rate. In distributed MIMO radars, block CS methods can be used instead of classical CS ones for more performance improvement, because the received signal in this group of MIMO radars is a block sparse signal in a basis. In this paper, two new methods are proposed to improve the performance of the block CS-based distributed MIMO radars. The first one is a new...