A direction finding method for spatial optical beam-forming network based on sparse Bayesian learning. Issue 2 (February 2017) - Wu, Liu-li; Liu, Zhang-meng; Jiang, Wen-li
Abstract This paper addresses the problem of direction-of-arrival (DOA) estimation of multiple sources for spatial optical beam forming network (SOBFN). A method which utilizes sparse Bayesian learning techniques to reconstruct the spatial power spectrum of the signals is proposed. The reconstruction procedure takes advantage of the amplitude distribution of the fiber-array output and the spatial sparsity of the incident signals. The reconstructed spectrum contains some evident peaks that indicate the coarse directions of the radiation sources. Then, a linear interpolation procedure is applied to make the DOA estimation results more precise. Sufficient numerical simulations are carried out to verify the performance of the proposed algorithm. Simulation results show that the proposed method fits well with the signal model of SOBFN and has favorable DOA estimation performance.