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Mathematical Problems in Engineering
Volume 2015, Article ID 231307, 8 pages
Research Article

Direction of Arrival Estimation Based on DDOA and Self-Organizing Map

School of Science, North University of China, Taiyuan, Shanxi 030051, China

Received 4 June 2015; Revised 23 July 2015; Accepted 5 August 2015

Academic Editor: Peter Liu

Copyright © 2015 Xiuhui Tan et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


An effective two-level self-organizing map (SOM) neural network for direction of arrival (DOA) of sound signals estimation is proposed. The approach is based on the distance difference of arrival (DDOA) and a uniform linear sensor array in a 2D plane; it performs a nonlinear mapping between the DDOA vectors and angles of arrival (AOA). We found that the topological order of DDOA vectors and AOAs of same signals is uniform; thus, the topological order preserving of SOM network makes it valid to estimate AOA through DDOA. From the results of simulations and lake experiments, it is shown that the network has the advantage of accuracy and robustness, can be trained in advance, and is easy to implement.