Yuan, J., Zhang, G., Leung, H. and Ma, S. (2023) Off-Grid DOA Estimation for Noncircular Signals via Block Sparse Representation Using Extended Transformed Nested Array. IEEE Signal Processing Letters, 30, 130-134.
https://doi.org/10.1109/LSP.2023.3242808

has been cited by the following article:

• 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.