用于 HRRP 多类目标识别的 D 距离分类器

Translated title of the contribution: D Distance Classifier for HRRP Multi-Class Recognition

Lu Yao, Lei Han*, Lei Yang, Xiaofei Chai

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

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 contributionD Distance Classifier for HRRP Multi-Class Recognition
Original languageChinese (Traditional)
Pages (from-to)1144-1149
Number of pages6
JournalBeijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology
Volume42
Issue number11
DOIs
Publication statusPublished - Nov 2022

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