LP-DSPE Algorithm for Angular Parameter Estimation of Coherently Distributed Sources

Abstract

The distributed source parameter estimator (DSPE) is one of the well-known angular parameter estimation techniques for coherently distributed sources. However, the computational cost of DSPE is not attractive due to the two-dimensional spectrum peak search. To overcome this problem, this letter proposes a novel DSPE algorithm based on compressive sensing theory, named as LP-DSPE algorithm. In the proposed method, at first, the nominal direction of arrival (DOA) estimation can be transformed into a linear programming problem through sparse recovery theory, whose feasible solution set is further expanded to improve the estimation accuracy. Then the angular spread can be obtained via a one-dimensional peak search utilizing the estimated nominal DOA. Compared with the previous works, the proposed algorithm can offer more accurate parameter estimation performance with lower computational complexity, even if in large angular spread scenarios. Theoretical analysis and simulation results demonstrate the performance of the proposed approach.