基于张量代数表征的多维度合成孔径雷达干扰抑制技术

This project addresses the severe challenges caused by interference to the robustness of synthetic aperture radar systems in complex electromagnetic environments. Based on the development trend of SAR systems as well as the frontier technologies of signal processing theory, this project conducts the research on interference suppression techniques for multi-dimensional SAR data based on the tensor algebra representation. Emphasis is placed on echo signal modeling and interference characteristics analysis in multi-dimensional tensor representation space, adaptive interference detection and type identification, and interference suppression methods based on tensor learning strategies. By fully exploiting the coupling redundancy among multiple measurements, such as the time, frequency, and polarization, as well as the advantages of multi-dimensional joint processing, this project intends to explore new concepts and clarify the principles of information collaborative joint analysis in the multi-dimensional tensor representation space, and further proposes novel processing criterions and methods. The key scientific issues to be solved include the accurate description of scattering properties and statistical characteristics between the interference and useful signal, and multi-sources signal separation and precise echo reconstruction problem. This project seeks to produce innovative research outputs including the establishment of multi-dimensional coupling echo model, and the interference suppression techniques using multi-dimensional joint optimization. Therefore, the research results would lay a theoretical foundation for improving the anti-interference performance of SAR system, and provide key technology support for ensuring the information acquiring capability of China’s earth observing SAR system in complex electromagnetic environment.

本项目针对复杂电磁环境下干扰对合成孔径雷达系统的稳健性造成的严峻挑战，结合SAR系统发展趋势，聚焦信号处理理论发展前沿，开展基于张量代数表征的多维度SAR干扰抑制技术研究，重点开展维张量表征空间的回波信号建模和干扰特征分析、多维张量表征空间的干扰自适应检测和类型辨识、基于张量学习策略的多维度协同干扰抑制方法研究。通过充分挖掘时间-频率-极化等多维观测域联合处理的优势，探索多维域干扰抑制的新概念，阐明多维张量表征空间中信息协同联合分析的原理，提出有效的处理新准则、新方法。拟解决的关键科学问题包括多维张量表征空间中的干扰和目标回波特征差异精准描述问题、多维张量表征空间中的多源信号分离与精确重构问题。力求在回波多维耦合表征建模理论、多维域协同优化干扰抑制技术等方面取得创新性研究成果，为提升我国SAR系统抗干扰性能奠定理论基础，为保障复杂电磁环境中我国SAR系统的对地遥感观测能力提供关键技术支撑。

针对复杂电磁环境下合成孔径雷达系统面临的严峻干扰问题战，结合SAR系统发展趋势，聚焦信号处理理论发展前沿，依照“模型构建”-“机理分析”-“方法设计”-“验证评估”的思路，本项目开展了基于张量代数表征的多维度合成孔径雷达干扰抑制技术研究。通过挖掘时间-频率-极化等多维观测域联合处理的优势，探索了多维域干扰抑制的新概念，阐明了多维信息协同联合分析的原理，重点围绕干扰和目标回波特征差异精准描述、多源信号分离与精确重构等关键科学问题，提出了有效的干扰检测与抑制处理新方法，取得了一定的基础理论创新成果，为保障复杂电磁环境中我国SAR系统的对地遥感观测能力提供关键技术支撑。