A novel neural network based approach for direction of arrival estimation

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2007
Çaylar, Selçuk
In this study, a neural network(NN) based algorithm is proposed for real time multiple source tracking problem based on a previously reported work. The proposed algorithm namely modified neural network based multiple source tracking algorithm (MN-MUST) performs direction of arrival(DoA) estimation in three stages which are the detection, filtering and DoA estimation stages. The main contributions of this proposed system are: reducing the input size for the uncorrelated source case (reducing the training time) of NN system without degradation of accuracy and insertion of a nonlinear spatial filter to isolate each one of the sectors where sources are present, from the others. MN-MUST algorithm finds the targets correctly no matter whether the targets are located within the same angular sector or not. In addition as the number of targets exceeds the number of antenna elements the algorithm can still perform sufficiently well. Mutual coupling in array does not influence MN-MUST algorithm performance. iv MN-MUST algorithm is further improved for a cylindrical microstrip patch antenna array by using the advantages of directive antenna pattern properties. The new algorithm is called cylindrical patch array MN-MUST(CMN-MUST). CMN-MUST algorithm consists of three stages as MN-MUST does. Detection stage is exactly the same as in MN-MUST. However spatial filtering and DoA estimation stage are reduced order by using the advantages of directive antenna pattern of cylindirical microstrip patch array. The performance of the algorithm is investigated via computer simulations, for uniform linear arrays, a six element uniform dipole array and a twelve element uniform cylindrical microstrip patch array. The simulation results are compared to the previously reported works and the literature. It is observed that the proposed algorithm improves the previously reported works. The algorithm accuracy does not degrade in the presence of the mutual coupling. A uniform cylindrical patch array is successfully implemented to the MN-MUST algorithm. The implementation does not only cover full azimuth, but also improv the accuracy and speed. It is observed that the MN-MUST algorithm provides an accurate and efficient solution to the targettracking problem in real time.

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Citation Formats
S. Çaylar, “A novel neural network based approach for direction of arrival estimation,” Ph.D. - Doctoral Program, Middle East Technical University, 2007.