Maximum a-posteriori probability direction finding and the dynamic-programming algorithm

In this paper, a dynamic programming (DP) algorithm is proposed to compute the maximum a posteriori probability (MAP) estimate of the random loction of multiple sources by passive sensor array. Based on the principle of optimality, the multivariate MAP decision problem can be transformed into a multistage one-dimensional maximization problem. By a recursive computation and backward optimum searching technique, the MAP solution can be obtained. The computational complexity is much less than that of the direct MAP searching method, especially when the number of sensors and/or the number of sources is large. In addition, the DP computation technique is equally applicable both in the case of correlated sources and the case of uncorrelated sources.