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| Direction of Arrival Estimation Approach Based on Phase Angle Feature of Correlation Function Using RBF Neural Networks |
| Zhang Min①②; Li Peng-fei①② |
| ①Division 309, Hefei Electronic Engineering Institute, Hefei 230037, China; ②Anhui Electronic Restricting Technique Key Laboratory, Hefei 230037, China |
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Abstract Effective feature extraction is very important when building the smart DOA estimation model. Based on analyzing the correlation function of the array signal, this paper firstly presents using the angles of contiguous array signal’s correlation function for DOA estimation purpose instead of common used upper triangular half of the covariance matrix, which eliminates the irrelevant magnitude information and redundant direction characteristic. Therefore the feature dimension is largely reduced without losing any DOA information. Experimental results show that the performance of RBF neural network using proposed Phase-feature is superior to the common used upper triangular half of the covariance matrix in terms of neural network size, generalization, estimation precision and real-time performance, so it has a broad application value.
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Received: 10 December 2008
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2009, Vol. 31 
