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| Content Provider | IET Digital Library |
|---|---|
| Author | Li, Long Jiang, Jie Liu, Zheng |
| Abstract | The radar high-resolution range profile (HRRP) is of great significance for target recognition in the ground compound environment. As two essential processes of HRRP target recognition, discrimination and classification performance improvement are studied in this study. A novel target recognition method is designed, denoted by multiple support vector (SV) method. In the training phase, a multiple correlate SV model is constructed, which separates the multi-target feature space into several central-coherence distributed regions. Each region has been described by the modified SV method, and the category determination is based on the description of multiple regions. This method can overcome the issues of both outlier discrimination and targets classification. Due to the hierarchical process in the testing phase, this method needs less memory and calculation to fit the practical radar target recognition task. Finally, the experiment based on the measured data verifies the excellent performance of this method. |
| Starting Page | 6327 |
| Ending Page | 6330 |
| Page Count | 4 |
| Volume Number | 2019 |
| e-ISSN | 20513305 |
| Issue Number | Issue 19, Oct (2019) |
| Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/joe/2019/19 |
| Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/10.1049/joe.2019.0138 |
| Journal | The Journal of Engineering |
| Publisher | The Institution of Engineering and Technology |
| Publisher Date | 2019-05-30 |
| Access Restriction | Open |
| Rights License | Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/) |
| Subject Keyword | Central-coherence Distributed Regions Classification Performance Improvement Computer Vision And Image Processing Technique Essential Processes Feature Extraction Ground Compound Environment HRRP Target Recognition Image Classification Image Recognition Knowledge Engineering Technique Multiple Correlate SV Model Multiple Region Multiple Support Vector Method Multitarget Feature Space Novel Target Recognition Method Optical, Image And Video Signal Processing Outlier Discrimination Practical Radar Target Recognition Task Radar Equipment Radar High-resolution Range Profile Recognition Radar Resolution Radar Target Recognition Signal Processing And Detection Statistics Support Vector Machine System And Application Targets Classification Training Phase |
| Content Type | Text |
| Resource Type | Article |
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