TITLE:
Combining Self-Organizing Map and Lipschitz Condition for Estimation in Direction of Arrival
AUTHORS:
Xiuhui Tan, Peng Wang, Hongping Hu, Rong Cheng, Yanping Bai
KEYWORDS:
DOA Estimation, Kohonen SOM, Distance Difference of Arrival, Topological Order, Lipschitz Condition
JOURNAL NAME:
Open Journal of Applied Sciences,
Vol.13 No.7,
July
21,
2023
ABSTRACT: There are many DOA estimation methods based on different signal features, and
these methods are often evaluated by experimental results, but lack the
necessary theoretical basis. Therefore, a direction of arrival (DOA) estimation
system based on self-organizing map (SOM) and designed for arbitrarily
distributed sensor array is proposed. The essential principle of this method is
that the map from distance difference of arrival (DDOA) to DOA is Lipschitz
continuity, it indicates the similar topology between them, and thus Kohonen
SOM is a suitable network to classify DOA through DDOA. The simulation results
show that the DOA estimation errors are less than 1° for most signals between 0° to 180°. Compared to MUSIC, Root-MUSIC, ESPRIT, and RBF,
the errors of signals under signal-to-noise ratios (SNR) declines from 20 dB to
2 dB are robust, SOM is better than RBF and almost close to MUSIC. Further, the
network can be trained in advance, which makes it possible to be implemented in
real-time.