Abstract
In the field of Radar Automatic Target Recognition (RATR), in order to ensure that the target recognition algorithm based on High-Resolution Range Profile (HRRP) still has excellent recognition performance when performing small-sample and multi-class target recognition, it is necessary to propose a recognition algorithm with excellent generalization performance and low computational complexity. Use the ratio to calculate a ratio distance between two vectors, and apply the ratio distance to a distance classifier, which is called D distance classifier. Then, the D distance classifier is compared with some other RATR statistical models using the measured data of eight ground targets, and its recognition accuracy in small samples and multi-class targets is analyzed respectively. The final result verifies that the D distance classifier still has excellent generalization performance and low computational complexity when recognition is performed with small-sample and multi-class target.
| Translated title of the contribution | D Distance Classifier for HRRP Multi-Class Recognition |
|---|---|
| Original language | Chinese (Traditional) |
| Pages (from-to) | 1144-1149 |
| Number of pages | 6 |
| Journal | Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology |
| Volume | 42 |
| Issue number | 11 |
| DOIs | |
| Publication status | Published - Nov 2022 |
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