Parallel implementation and performance analysis of beamspace ESPRIT

Most high-resolution algorithms for sensor array processing require an eigendecomposition which is difficult to implement in parallel and costs at least O(M³) multiplications for an M×M matrix, corresponding to M sensors. Recently, S.D. Silverstein et al, (1991) presented a subband parallel scheme, which reduced the computation time from O(M³) to O(L³ ), where L(<M) is the subband length or the beamspace dimension. However, the potential problem is that a uniform linear array commonly used in direction finding loses its displacement invariance structure after the beamspace transformation. Thus, the DOA estimation may be more computationally intensive since the computationally efficient ESPRIT algorithm cannot be applied directly. The authors show a way of restoring the lost structure, which results in a new beamspace ESPRIT algorithm. The asymptotic performance analysis and simulation results of the beamspace ESPRIT method are presented