A novel passive location algorithm based on neural networks

A novel short-wave passive location algorithm based on radial basis function neural networks (RBFNN) is proposed. Using the RBFNN´s characteristic of approximating any continuous nonlinear function, the fusion of electromagnetic spectrum sensing data is realized by sample learning. And the mapping model of short-wave monitoring data, detecting data and targets´ position information is constructed. Moreover, the effect of error and ionosphere disturbance on the accuracy of location accuracy can be relieved by using the generalization and robustness of RBFNN. A large number of measured data verify the scientificity and the accuracy of the proposed algorithm.