摘要
阐述了用于雷达测量的雷达散射截面(RCS)序列特征提取方法,再对这些特征进行置信度分析,然后根据置信区间是否重叠选择恰当的RCS特征值作为目标识别的特征向量。利用RCS仿真数据来验证以置信度分析为基础的雷达目标识别方法。数值实验结果表明,以置信区间不重叠的RCS特征作为目标识别依据的特征向量,能较准确地识别雷达跟踪目标。
In the paper,some radar cross section(RCS)feature extraction methods for radar target are introduced.Then these features are in confidence level analysis.The suitable features without confidence interval overlap are regarded as RCS feature vectors for target recognition.We use RCS simulation results to verify the availability of the radar target recognition method based on confidence level analysis.The simulation experiments show that the RCS features without confidence interval overlap can represent as basic feature vectors to improve the effectiveness of radar target recognition.
作者
占洪涛
郭亮
詹武平
郑永煌
ZHAN Hongtao;GUO Liang;ZHAN Wuping;ZHENG Yonghuang(School of Physics and Optoelectronic Engineering,Xidian University,Xi’an 710071,China)
出处
《微型电脑应用》
2022年第7期35-37,47,共4页
Microcomputer Applications
基金
装备预研领域基金(61404160104)
国防科技大学科研计划项目(ZK18-01-02)。
关键词
雷达
雷达散射截面特征
置信区间
目标识别
radar
radar cross section feature
confidence region
target recognition
