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 target’ HRRPs. The unknown-target model, which describes statistical distribution of unknown-target’ 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.

Keywords:

Known-target model, likelihood ratio score, target discrimination using HRRP, unknown-target model,

References

Competing interests

The authors have no competing interests.

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Copyright

The authors have no competing interests.