CAJ | 학술논문

传统雷达测角系统副瓣跟踪识别方法主要根据副瓣信号幅度较主瓣明显偏低这一特性提出，该文通过对副瓣跟踪原理的理论分析、仿真分析与实测验证，得出了关于副瓣跟踪特性的新结论：副瓣跟踪时和差相位正交、差和幅度比相对主瓣跟踪明显增大。在此基础上提出一种基于信号幅相特性的副瓣跟踪识别方法：构造以差和幅度比、和差相位差为描述子的幅相特征向量，采用支持向量机(SVM)对特征向量进行分类完成识别过程。实验结果表明，该文方法识别准确率高，鲁棒性、实时性、通用性强。
전통뢰체측각계통부판근종식별방법주요근거부판신호폭도교주판명현편저저일특성제출，해문통과대부판근종원리적이론분석、방진분석여실측험증，득출료관우부판근종특성적신결론：부판근종시화차상위정교、차화폭도비상대주판근종명현증대。재차기출상제출일충기우신호폭상특성적부판근종식별방법：구조이차화폭도비、화차상위차위묘술자적폭상특정향량，채용지지향량궤(SVM)대특정향량진행분류완성식별과정。실험결과표명，해문방법식별준학솔고，로봉성、실시성、통용성강。
The traditional methods for automatic recognition of sidelobe tracking of angle measurement system in radar techniques are presented based on the different magnitude between the signals of sum channel and difference channel. By researching the principal of sidelobe tracking, analyzing it through the computer simulations or the experimental results, a new conclusion about the features of sidelobe tracking is presented as the phases of the signals of sum channel and difference channel are orthogonal and the signal of difference channel is with high magnitude at the sidelobe tracking position. According to the above conclusion, a method based on the magnitude-phase characteristics is proposed: The eigenvector revealing magnitude-phase characteristics for recognizing sidelobe tracking is constructed and the Support Vector Machine (SVM) is employed for later classification process. It demonstrates in experiments that the recognition accuracy is significantly improved by using the new approach which is with strong robustness and high real-time performance.