Abstract:

Aiming at the problem of two dimensional angles estimation for multiple-input multiple-output (MIMO) radar with L-shaped array, a new reduceddimensional direction of arrival (DOA) estimation method based on sparse reconstruction is proposed. Giving the steering vector of MIMO radar with Lshaped array, a reduced-dimensional matrix is employed, and data redundancy of high dimensional received data at the greatest degree can be removed via the reduced-dimensional transformation. Through the joint construction of the two-dimensional sparse linear model with covariance matrix, the dimension of the dictionary is reduced to one-dimension from twodimensional space, and the length of the redundant dictionary and computation complexity is largely reduced. Furthermore, the method, without costing the aperture of array, can realize two dimensional spatial angles estimation with automatic pairing. Compared with reduced-dimensional (RD) MUSIC, the proposed method can reduce the dimension of received data at the greatest degree and enhance sensors efficiency. Compared with the traditional subspace algorithms, the proposed method, which is based on the joint sparse linear model of the covariance matrix, makes the best of all apertures of array and can achieve better estimation performance under lower signal-noise-ratio(SNR) and a few snapshots without pre-estimation for the number of targets. Finally, simulation results verify the correctness of the theoretical analysis and the effect of the proposed algorithm.