Abstract
In monostatic Multi-Input Multi-Output (MIMO) radar system, Direction Of Arrival (DOA) estimation is important for target detection. However, conventional MIMO DOA estimation approaches suffers from the off-grid issue which refers that the real DOAs deviate from the predefined grid points. In this paper, a grid adaptive DOA estimation method is proposed to address the off-grid error and the improper initial grid problem for monostatic MIMO radar system. We construct a Bayesian learning framework with Laplacian prior to adjust grid and observation dictionary adaptively. Simulation results show the superior performance of the proposed method in terms of high angle resolution and robustness against the noise by comparing with the state-of-the-art DOA estimation methods in MIMO radar system.
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