A fast algorithm for joint two-dimensional direction of arrival and frequency estimation via hierarchical space–time decomposition

In this paper, we present a fast algorithm for joint estimation of the two-dimensional (2-D) directions of arrival (DOAs) and frequencies of the incoming signals in wireless communications using a hierarchical space–time decomposition (HSTD) technique. Based on the HSTD, the proposed algorithm makes use of a sequence of one-dimensional (1-D) Unitary estimation of signal parameters via rotational invariance technique (ESPRIT) algorithms to estimate these parameters alternatively in a hierarchical tree structure. Also, in between every other 1-D Unitary ESPRIT algorithm, a temporal filtering process or a spatial beamforming process is invoked to partition the incoming signals into finer groups stage by stage to enhance the estimation accuracy as well as to alleviate the contaminated noise. Furthermore, with such a tree-structured estimation scheme, the pairing of these parameters is automatically determined without extra computational overhead. Simulation results show that the new algorithm provides satisfactory performance but with drastically reduced computations compared with previous works.