Low complexity DOA estimation approach through multitask Bayesian compressive sensing strategies
Based on the Multitask Bayesian Compressive Sensing (MT-BCS) framework, a novel DOA estimation approach for planar array is proposed in this paper. Different from the traditional CS-based DOA model, where the spatial observation is characterized in one large scale matrix, to reduce the complexity, a separable observation structure is proposed, which separates the joint spatial observation into two individual parts, and thus, the large scale matrix can be split into two small scale matrices. In addition, the Multitask Bayesian Compressive Sensing framework is engaged to build a MT-BCS-based DOA estimation scheme (MT-BCS-DOA). The simulation results show the superior capability of the proposed approach.