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| Adaptive Learning of Classifier Parameters for Radar High Range Resolution Profiles Recognition |
| Yuan Li; Liu Hong-wei; Bao Zheng |
| National Lab of Radar Signal Processing, Xidian University, Xi’an 710071, China |
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Abstract Radar High Range Resolution Profile (HRRP) is very sensitive to target aspect variation. To deal with this problem, usually, multiple statistical models are built for different target aspect sector when using HRRP for target recognition. Therefore, how to determine target aspect sector number and how to divide target aspect sector play an important role in classifier training. A data driven adaptive learning algorithm is proposed in this paper, which determines the target aspect sector boundary based on a multivariate Gaussian statistical data model and an iteration algorithm, and the target aspect sector number can be determined simultaneously. Comparing with the traditional equal interval target aspect partition approach, the proposed approach can achieve better recognition performance with lower computation complexity. Experimental results based on the measured data show the efficiency of the proposed method.
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Received: 19 June 2006
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2008, Vol. 30 
