APPROACH FOR APPROXIMATION OF SIGNAL SUBSPACE VIA NEURAL NETWORKS
谱峰搜索的神经网络实现

A neural method to solve the orthogonality search problem arising in direction-of-arrival (DOA) estimation is proposed. The problem is mapped onto the snergy function of the neural network as a linear programming problem. The most important feature of this method hinges upon the fact that the number of neurons in the network is linearly dependent on the number of sensors in the sensor array, rather than the discretization levels of parameter space. Theoretical analysis and simulation results show that the performance of the neural method is exactly equivalent to that of the standard MUSIC method or the real domain DOA estimation method.