Abstract
ABSTRACTExisting direction of arrival (DOA) estimation methods in multiple-input multiple-out (MIMO) radar systems will encounter the performance degradation in the cases of few snapshots, low signal-to-noise ratio (SNR), closely spaced targets, or strongly correlated sources. To improve it, this paper develops a new sparse representation-based DOA estimation method. The main contributions are as follows: i) we construct a new real-valued double weighted -norm minimisation model; ii) we derive an improved reduced-dimension technique to enhance estimation accuracy; and iii) we design optimal and sparse weights carefully to improve the corresponding estimation accuracy. Finally, the effectiveness and theoretical analysis of the presented approach are verified by extensive numerical simulations, which proves that the new algorithm performs well at low SNR and with a small number of snapshots as well as at the coherent source case.
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