Real-Time Passive Localization of TDOA via Neural Networks

Abstract

This letter proposes the use of neural networks to realize the passive localization by signal time difference of arrival (TDOA). In the face of multiple complex targets with radiation sources in a specific area, real-time localization is an urgent problem. In this letter, positions of the known targets from the prior data are obtained and their time difference is calculated, which will be connected as data pairs and input to the neural network trained to obtain a corresponding model. Subsequently, unknown targets can be localized by this network. It is verified that the localization accuracy of the algorithm is reliable and its robustness is higher than that of traditional algorithms. The proposed method also shows that great reduction of operation time depending on the previous network training can complete real-time goals.