Admm for Gridless Dod and Doa Estimation in Bistatic Mimo Radar Based on Decoupled Atomic Norm Minimization with One Snapshot

In this paper, the issue of gridless compressed sensing (CS)-based direction-of-departure (DOD) and direction-of- arrival (DOA) estimation for bistatic multiple-input multiple- output (MIMO) radar is investigated with one snapshot, and an alternating direction method of multipliers (ADMM) for 2D parameter estimation using decoupled atomic norm minimization (DANM) is proposed. In the proposed algorithm, the decoupled atom set and atomic norm for DOD and DOA estimation are defined, then the atomic norm is transformed into a semi-definite programming (SDP) minimization problem. To decrease the computational complexity of solving SDP using interior point method based SDPT3 solver in CVX toolbox, the DANM with ADMM is deduced, which can greatly decrease the running time, especially in the presence of large scale arrays. Finally, the DOD and DOA are obtained via shift-invariance parameter estimation. It overcomes the grid-mismatch effect of grid-partition of the conventional CS methods, and outperforms the traditional subspace-based methods. Numerical simulations are presented to demonstrate the estimation performance of the proposed algorithm.