Abstract：An original Generalized Maximum Likelihood(GML) algorithm for dircction-of-arrival estimation is proposed in this paper. A new data model is established based on generalized steering vectors and generalized array manifold matrix. For the novel GML algorithm, the incident sources may be a mixture of multi-clusters of coherent sources, the array’s geometry is unrestricted and more importantly, the number of sources resolved can be larger than the number of sensors. The comparison between the GML algorithm and conventional DML algorithm is presented based on their respective geometrical interpretation. Subsequently the estimation consistency of GML is proved and the estimation variance of GML is derived. Theoretical analysis shows that the performance of GML algorithm is consistant with DML’s in incoherent sources case, and it improves greatly in coherent source case. Using the genetic algorithm, the GML algorithm is realized in the paper, and its efficacy is proved by means of the Monte-Carlo Simulations.
2004, Vol. 26 
