机载雷达前视成像与雾霾天候下着陆指示方法研究

The research of airborne forward-looking radar imaging and autonomous landing instruction method is to realize airborne real beam radar forward-looking imaging and to accomplish the detection and recognition tasks of the foreign matter in landing area under fog and haze weather through signal processing techniques. This research provides the technology basement for autonomous landing of aerial vehicles. The research aims at studying the basic theory and realization method of forward-looking radar imaging, deconvolution, foreign matter detecting, landing area instruction. Based on these, the echo model and imaging method of forward-looking radar together with detection and recognition method is carried out. What’s more, the multi-source information fusion-based deconvolution and information entropy grads evolution-based dynamic monitoring method is proposed, which breaks through the corresponding key technologies. Along with the theoretical research, the system is improved and several field experiments are carried out. This project is at the frontier of international radar imaging processing and its research results are capable of enhancing the application level in this area domestically. Additionally, the research results obtain proprietary intellectual property rights and exhibit significant scientific value along with application value.

机载雷达前视成像与雾霾天候下自主着陆指示方法研究是通过信号处理方法，实现机载实波束雷达前视成像，并对备降区域及异物图像特征进行检测判别，完成备降区域指示，从而为航空飞行器在雾霾天候下自主着陆提供技术基础。本项目围绕雷达前视成像、卷积反演、异物检测、着陆区域指示的基础理论及方法问题，开展前视成像回波模型、成像方法、检测与识别方法研究，提出基于多源信息融合的卷积反演和基于信息熵梯度演化的动态监测方法，突破卷积反演、成像区域多源先验信息融合、时间序贯动态规划等关键技术，并进行系统改进，开展外场试验。本项目的研究成果能够提高国内在该领域的研究和应用水平，形成自主知识产权的技术体系，具有重要的科学意义。

本项目针对雾霾天候下航空飞行器空中救援、物质空投、迫降等重大应用需求，围绕开展雷达前视成像与备降区自主指示难题，突破了雷达前视成像回波建模、卷积反演前视成像方法、备降区与异物检测等关键技术，完成了实验系统改造及前视对地成像试验，形成了具有自主知识产权的技术体系，为推动“小雷达”技术在低空通用航空领域的应用提供理论基础和技术支撑。项目组围绕研究目标与应用需求，针对项目的多项研究内容开展研究工作，在项目组成员的相互配合下，项目进展顺利，现已完成了全部的研究目标与研究内容。