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2013 (Vol. 5, Issue: 06)
Article Information:

A Novel Approach For Known and Unknown Target Discrimination Using HRRP

Daiying Zhou
Corresponding Author:  Daiying Zhou 

Key words:  Known-target model, likelihood ratio score, target discrimination using HRRP, unknown-target model , , ,
Vol. 5 , (06): 1943-1949
Submitted Accepted Published
July 07, 2012 August 15, 2012 February 21, 2013
Abstract:

In this study, a novel discrimination method for known and unknown target using High-Resolution Range Profile (HRRP), namely log-likelihood ratio score method, is proposed. The aim of this method is to minimize the error probability of discrimination by constructing the unknown target model when the data of unknown target is lack. The Gaussian Mixture Model (GMM) is introduced to model the statistical characteristics of targetí HRRPs. The unknown-target model, which describes statistical distribution of unknown-targetí HRRPs, is proposed. The statistics of unknown target can be computed approximately via finite known-target models in training database. The experimental results for measured data show that the discrimination rate of proposed method is about 88%, which is higher than that of discrimination method without unknown-target model.
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  Cite this Reference:
Daiying Zhou, 2013. A Novel Approach For Known and Unknown Target Discrimination Using HRRP.  Research Journal of Applied Sciences, Engineering and Technology, 5(06): 1943-1949.
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ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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