Low complexity subspace approach for direction finding in bistatic MIMO radar

Joint estimation on direction of departure (DOD) and direction of arrival (DOA) is a key problem in bistatic multiple-input multiple-output (MIMO) radar. The conventional singular value decomposition (SVD) or eigenvalue decomposition (EVD) based subspace algorithms have heavy computational burden when the large transmit/receive array size and snapshots are required. In this paper, a low complexity subspace approach is proposed for joint DOD and DOA estimation. Firstly, the received data can be tr into a real-valued one by exploiting the centro-symmetric property of the virtual array. Then the subspace for direction finding is changed into real-valued by the Nystöm method, which avoids the estimation and decomposition of the covariance matrix. Combined with the classical subspace based Unitary ESPRIT algorithm, the proposed method provides the comparable angle estimation performance with lower computational complexity compared with the conventional SVD/EVD-based subspace algorithms. Some simulation results verify the performance of the proposed method.