Direction of Arrival Estimation by Using Artificial Neural Networks

Direction-of-arrival (DOA) evaluation involves the procedure by which multiple electromagnetic (EM) waves from the outputs of various receiving antennas that construct a sensor array retrieve the direction information. There are many algorithms for the direction of arrival estimation in the literature like MUSIC, ESPRIT, first-order forward prediction, Capon, etc. These algorithms have heavy calculation operations. This situation could cause lags in the algorithm's response time and may pose an essential disadvantage in real time applications. To overcome this problem, artificial neural network (ANN) can be used. The training stage of an ANN needs significant time and sources, but after training, the estimation of Direction of arrival using ANN is very fast. An ANN method for the direction of arrival estimation in uniform linear array antennas has been projected in this project. In training, the whole pseudo spectrum is scanned by 10-degree steps. A uniform linear array with 2,3,4, and 5 isotropic antenna elements and one source signal is considered in the simulations. Tests of the trained ANN have been done for various arrival angles, and satisfactory results have been obtained.