Abstract
We consider the problem of target estimation in distributed MIMO radars that employ compressive sensing. The problem is formulated as a sparse signal recovery problem with magnitude constraints on the target reflection coefficients, where the signal to be recovered consist of equal size blocks that have the same sparsity profile. A solution is proposed based on the alternating direction method of multipliers (ADMM), which significantly lowers the computational complexity of sparse recovery and improves the estimation accuracy. Due to the block diagonal structure of the sensing matrix, the iterations of all ADMM subproblems are amenable to parallel implementation, which can reduce the running time. A semi-distributed implementation, which relaxes the need of a powerful fusion center is also discussed.
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