Fast Algorithm for Joint Azimuth and Elevation Angles, and Frequency Estimation via Hierarchical Space-Time Decomposition

This paper presents a fast algorithm for joint estimation of the azimuth and elevation angles, and frequencies of the incoming signals 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 techniques (ESPRIT) algorithms to estimate these parameters alternatively in a hierarchical tree structure. Also, in between every other 1-D unitary ESPRIT, a temporal filtering process or a spatial beamforming process is invoked to partition the signals into finer groups to enhance the estimation accuracy and to alleviate the contaminated noise. Furthermore, the pairing of these parameters is automatically determined. Simulation results show that the new algorithm provides satisfactory performance but with drastically reduced computations compared with previous works. Simulation results show that the new algorithm provides satisfactory performance but with drastically reduced computations compared with previous works.