A Neural Network Method for Direction of Arrival Estimation with Uniform Circular Dipole Array in The Presence of Mutual Coupling

In recent years application of Neural Network (NN) algorithms in both target tracking problem and DoA estimation have become popular because of the increased computational efficiency This paper presents the implementation of modified neural network algorithm(MN-MUST) to the uniform circular dipole array in the presence of mutual coupling. In smart antenna systems, mutual coupling between elements can significantly degrade the processing algorithms. In this paper mutual coupling affects on MN-MUST has been investigated. MN-MUST algorithm applied to the Uniform Circular Array (UCA) geometry for first time. The validity of MN-MUST algorithm in the presence of mutual coupling has been proved for UCA. Simulation results of MN-MUST algorithm are provided for UCA. The presence of mutual coupling degraded the MN-MUST algorithm performed in the absence of mutual coupling, as expected.