An Angular Parameter Estimation Method for Incoherently Distributed Sources Via Generalized Shift Invariance
Renzheng Cao, Feifei Gao, Xiaofei Zhang · IEEE Transactions on Signal Processing · 2016
This paper proposes a new algorithm to estimate the nominal direction-of-arrival (DOA) and the angular spread of multiple incoherently distributed (ID) sources. With the general array manifold (GAM) model, the nominal DOAs are first separated from the original array manifold. Then, a generalized shift invariance property inside the array manifold is identified, based on which the nominal DOAs are obtained when the rank of a trickily formulated matrix drops. Next, the angular spreads are estimated from the central moments of the angular distribution. We also derive a polynomial rooting based search-free method for nominal DOA estimation. This method can greatly reduce the computational complexity. As compared with the popular ESPRIT-ID algorithm, the proposed algorithm can achieve higher accuracy, can handle more sources, and applies to a more general array structure. Extensive simulations are provided to demonstrate the superior performance of the proposed algorithm over the existing works.