Position-enabled complex Toeplitz LISTA for DOA estimation with unknow mutual coupling
چکیده
Unfolding iterative algorithms into deep networks can increase the rate of convergence which is amenable to Direction-of-arrival (DOA) estimation problems. However, there normally exists unknown mutual coupling between antenna array elements. In this paper, a novel Position-enAbled Complex Toeplitz Learned Iterative Shrinkage Thresholding Algorithm (PACT-LISTA) proposed makes use data driven method solve problem and improve parameter performance. First, sparse recovery (SR) model developed explore inherent Topelitz structure. order SR problem, LISTA (CT-LISTA) network proposed, integrates structure (C-LISTA) network. By ignoring amplitude phase information recovered signal, idea position-priority applied further accuracy. Through an innovative iteration method, system gradually converges optimized stable state, associated with accuracy parameter. Simulations are provided demonstrate that approach significantly outperforms state art methods.