预警雷达辅助知识库建模与仿真

发布时间：2018-06-18 15:49

本文选题：辅助知识库 + 知识辅助　；参考：《电子科技大学》2016年硕士论文

【摘要】：雷达在地/海/城市等强杂波背景中对目标进行探测时,弱小目标往往被强杂波掩盖,而飞行器隐身性能和机动性能的提高进一步增加了雷达探测的难度。与传统的微弱目标探测技术仅利用雷达回波数据不同,基于辅助知识库的微弱目标探测技术通过对地形、高程及气象等先验环境信息进行分析处理来构建辅助知识库,从而对传统的检测跟踪算法进行知识辅助,有效提高了传统检测跟踪算法在复杂环境下的探测性能,成为微弱目标探测领域的研究热点。然而,辅助知识库作为一种新兴技术,仍有大量技术问题有待解决,如辅助知识的获取、动态更新和工程化应用等。本文围绕以上问题,研究了辅助知识的获取和动态更新算法,以及雷达辅助知识库的建模和工程化应用方案,具体如下:1.研究了地形覆盖信息、高程信息、杂波幅度分布模型信息、强弱杂波分区等多种辅助知识的获取方法;提出了一种结构化、参数化的雷达辅助知识库建模方法。2.提出了基于双AD检验的动态更新算法和基于指数平滑的动态更新算法,两种算法可对相应的辅助知识进行有效的动态更新,大幅提高辅助知识与探测环境的匹配程度。3.提出了基于强弱杂波分区的知识辅助恒虚警检测算法,该算法利用强弱杂波分区知识将复杂探测环境划分为局部的均匀探测环境,从而有效的提升了背景杂波功率水平的估计精度,提高了非均匀探测环境下雷达的目标检测能力及虚警点控制能力。4.在分析了辅助知识库建模过程中资源需求的基础上,提出了雷达辅助知识库的工程应用方案。5.设计并实现了雷达辅助知识库软件,能够实现辅助知识库快速建模、动态更新、知识提取及知识辅助检测跟踪等功能。以上所提出的算法均通过仿真实验及雷达实测数据验证,结果证明了雷达辅助知识库的有效性。
[Abstract]:When radar detects a target in a ground / sea / city background, the weak target is often masked by a strong clutter, and the stealth and maneuverability of the aircraft further increase the difficulty of radar detection. Unlike the traditional weak target detection technology, which only uses radar echo data, the weak target detection technology based on auxiliary knowledge base constructs the auxiliary knowledge base by analyzing and processing the prior environmental information, such as terrain, elevation and meteorology, etc. Thus, the traditional detection and tracking algorithm is supported by knowledge, which effectively improves the detection performance of the traditional detection and tracking algorithm in complex environment, and becomes a research hotspot in the field of weak target detection. However, as a new technology, there are still a lot of technical problems to be solved, such as the acquisition of auxiliary knowledge, dynamic updating and engineering application. In this paper, the acquisition and dynamic updating algorithm of auxiliary knowledge and the modeling and engineering application scheme of radar aided knowledge base are studied, which are as follows: 1. In this paper, the acquisition methods of terrain coverage information, elevation information, clutter amplitude distribution model information, strong and weak clutter partition and so on are studied, and a structured and parameterized method of radar aided knowledge base modeling is proposed. A dynamic updating algorithm based on double AD test and a dynamic updating algorithm based on exponential smoothing are proposed. The two algorithms can effectively update the corresponding auxiliary knowledge and greatly improve the matching degree between the auxiliary knowledge and the detection environment. A Knowledge-Aided CFAR detection algorithm based on strong and weak clutter partition is proposed. The algorithm divides the complex detection environment into local uniform detection environment by using the strong and weak clutter partition knowledge. Therefore, the estimation accuracy of background clutter power level is improved effectively, and the target detection ability and false alarm control ability of radar under non-uniform detection environment are improved. Based on the analysis of the resource requirements in the modeling process of the auxiliary knowledge base, the engineering application scheme of the radar aided knowledge base is proposed. The software of radar aided knowledge base is designed and implemented, which can realize the functions of fast modeling, dynamic updating, knowledge extraction and knowledge aided detection and tracking. The proposed algorithms are verified by simulation experiments and radar measured data, and the results show the effectiveness of the radar auxiliary knowledge base.
【学位授予单位】：电子科技大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TN959;TP391.9

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