The iterative algorithm for multiple incoherently distributed sources
Huigang Wang, Qi Chen · 2010
Most algorithms for multiple incoherently distributed sources are based on multimensional search of the objective function to find the central angle and angular spread, and the satisfactory performance is obtained only under high SNR or for spaced separately sources. A new iterative algorithm - the EM algorithm is proposed to obtain the accurate estimation for multiple incoherently distributed sources with Gaussian angular power density function. The optimization of the likelihood function for multiple distributed sources is simplified into multiple optimizations for single source and the performance of the EM algorithm is very close to the CRLB even for low SNR. Another advantage of the EM algorithm is that it is insensitive to overestimate the number of sources compared with other methods. Computer simulations verify that the EM algorithm is more effective than most existing algorithms.