Maximum likelihood estimation of multiple sources using a local optimization method

An effective method for solving a nonlinear optimizing problem is proposed here. This method is based on the maximum likelihood estimation of multiple sources by passive sensor array. The method employs the local optimization using the gradient of nonlinear function. Also described is how to determine the effective initial values leading to the global minimum but not to the local minimum. The proposed method in this paper easily obtained the optimized estimate of the maximum likelihood in multiple sources. This estimation usually requires great processing time using conventional methods because of a heavy computing load. Some simulations show that the proposed method has the properties of both better accuracy and lower computing time than a conventional method.