DOA Estimation of Noncircular Signals With Nested Arrays: A Block Tensor Sparse Representation

This paper addresses the direction-of-arrival (DOA) estimation problem for non-circular signals in nested arrays through a block tensor sparse representation (TSR) framework. By establishing a 3D tensor dictionary that jointly discretizes the angular and non-circular phase domains, we formulate the multiparameter estimation as a constrained tensor recovery task. The proposed block TSR framework introduces a block diagonalized tensor decomposition scheme that enables parallel subproblem optimization while preserving parameter coupling, then the estimates of DOA are obtained by Lasso's algorithm. Simulation results show that the proposed method can still achieve higher angle estimation accuracy with lower signal-to-noise ratio compared with the classical sparse representation and state of the art block sparse representation methods.