基于扩展目标的强杂波信息约减因子法研究
Research on information reduction factor method for strong clutter based on extended targets
薛琛衍 1汪玲 2莫修辞3
作者信息
- 1. 南京航空航天大学雷达成像与微波光子技术教育部重点实验室,南京 211106;中国航空工业集团公司雷华电子技术研究所,江苏无锡 214082
- 2. 南京航空航天大学雷达成像与微波光子技术教育部重点实验室,南京 211106
- 3. 中国航空工业集团公司雷华电子技术研究所,江苏无锡 214082
- 折叠
摘要
数智化时代下,日益复杂的电磁对抗态势不断促使着探测环境中杂波密度的上升,雷达分辨率的增强也己将目标量测的类型从点目标转变为扩展目标,二者在用于描述杂波的信息约减因子(IRF)法中均已成为重要的影响因素.针对这一现象,提出一种基于扩展目标的强杂波IRF法,并与传统的IRF法进行对比.实验结果表明:点目标量测类型下的强杂波信息约减因子(SCIRF)因量级过小而致使其包含的信息过少、性能欠佳;扩展目标量测类型下的SCIRF则拥有与点目标量测类型下理想或弱杂波环境IRF之相同的量级,具备同样的性能.最后,结合全局IRF等指标,从理论上分析了扩展目标量测类型能够改善点目标量测类型下SCIRF性能不佳的根本原因,并给予了其合理解释.
Abstract
In the current era of digital intelligence,the proliferation of sophisticated electromagnetic countermeasures has led to a rise in clutter density inside detection environments.The advancement in radar resolution has led to a shift in target measurement type,transitioning from point targets to extended targets.Both characteristics have emerged as significant contributors to the information reduction factor(IRF)utilised for characterising clutter.In order to address the challenge of detecting extended targets in a strong clutter environment,this study proposes an optimised IRF method and compares its performance with that of the classic IRF method.The experimental results show that the strong clutter information reduction factor(SCIRF)exhibits limited information and subpar performance in the context of point target measurement,which can be attributed to its relatively small magnitude.On the other hand,the SCIRF associated with extended target measurement demonstrates comparable magnitude and performance to the ideal or weak clutter environment's IRF under the point target measurement type.Finally,the present study undertakes a theoretical analysis of the underlying rationale for the enhanced performance of the SCIRF in the context of the point target measurement type by using the local IRF and other indicators,and a plausible explanation for this phenomenon is provided.
关键词
强杂波/点目标/扩展目标/信息约减因子Key words
strong clutter/point target/extended target/information reduction factor引用本文复制引用
出版年
2024
NETL
NSTL
万方数据