A Novel Unitary ESPRIT Algorithm for Monostatic FDAMIMO Radar A novel unitary estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithm, for the joint direction of arrival (DOA) and range estimation in a monostatic multipleinput multipleoutput (MIMO) radar with a frequency diverse array (FDA), is proposed. Firstly, by utilizing the property of CentroHermitian of the received data, the extended realvalued data is constructed to improve estimation accuracy and reduce computational complexity via unitary transformation. Then, to avoid the coupling between the angle and range in the transmitting array steering vector, the DOA is estimated by using the rotation invariance of the receiving subarrays. Thereafter, an automatic pairing method is applied to estimate the range of the target. Since phase ambiguity is caused by the phase periodicity of the transmitting array steering vector, a removal method of phase ambiguity is proposed. Finally, the expression of Cramerxe2x80x93Rao Bound (CRB) is derived and the computational complexity of the proposed algorithm is compared with the ESPRIT algorithm. The effectiveness of the proposed algorithm is verified by simulation results.

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 directionofdeparture (DOD) and directionof arrival (DOA) estimation for bistatic multipleinput 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 semidefinite 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 shiftinvariance parameter estimation. It overcomes the gridmismatch effect of gridpartition of the conventional CS methods, and outperforms the traditional subspacebased methods. Numerical simulations are presented to demonstrate the estimation performance of the proposed algorithm.