高超声速平台载雷达信号处理系统仿真

发布时间：2018-03-06 13:43

本文选题：高超声速飞行器　切入点：信号处理　出处：《西安电子科技大学》2014年硕士论文　论文类型：学位论文

【摘要】：高超声速技术是航空航天领域的一个重要研究方向,具有极其诱人的应用前景。高超声速平台的特性使得搭载的雷达在进行目标探测时面临重大挑战,现有的雷达目标探测技术会出现性能下降,甚至失效的可能。因此,开展高超声速平台载雷达目标探测技术研究具有重大意义。目前,高超声速飞行器(HyperSonic Vehicle,HSV)还处于论证试验阶段,难以在高超声速平台上直接验证雷达的信号处理性能,为了进行雷达信号处理方法的仿真演示和验证工作,开发一套高超声速平台载雷达(HyperSonic Vehicle-borne Radar,HSV-R)信号处理仿真系统具有现实意义。1.介绍了高超声速平台载雷达信号处理仿真系统的总体方案设计。该仿真系统的任务主要包括对HSV-R信号环境的模拟、HSV-R信号处理过程的模拟、提供良好的人机交互环境和提供简洁的系统维护与扩展途径四方面。依据仿真系统的任务制定系统设计思想。该仿真系统的功能模块分为演示导引、雷达回波信号仿真、雷达信号处理三部分,并对每一部分进行了更细致的功能划分。最后,介绍了仿真系统中各功能模块在公用参数、结果数据流动和软件功能操作上的联系。2.对高超声速平台载雷达信号处理仿真系统并行处理方法进行了研究。针对系统因运算量大而出现的执行速度问题,在对高超声速平台载雷达杂波模型分析的基础上,开展了并行处理方法研究,包括基于CPU的多核并行计算和基于GPU的众核并行计算,文中给出了并行计算效果并进行了分析。在基于CPU的多核并行计算中,介绍了基于parfor的并行计算方法和基于MDCS的并行计算方法。在基于GPU的众核并行计算中,对现有GPU技术和产品进行了介绍,将GPU和CPU进行了对比,并着重讲述了基于GPU的HSV-R杂波仿真方法。3.详细介绍了高超声速平台载雷达信号处理仿真系统的开发环境和开发过程中的关键技术,其中主要包括动态链接库的设计、数据可视化技术、公共数据类的设计、数据传递方式的设计和系统路径的索引方法。最后,展示了系统登录、主界面、飞行轨道演示、回波生成、杂波特性分析、空中高速目标检测与跟踪、地面动目标检测与定位、地面高分辨场景成像和用户设置共九个功能模块的实现情况。
[Abstract]:Hypersonic technology is an important research direction in the field of aeronautics and spaceflight, and has a very attractive application prospect. The characteristics of hypersonic platform make the radar on board face great challenge in target detection. The existing radar target detection technology will have the possibility of performance degradation or even failure. Therefore, it is of great significance to study the technology of radar target detection on hypersonic platform. The hypersonic vehicle HyperSonic vehicle HSV is still in the stage of demonstration and test, so it is difficult to directly verify the signal processing performance of radar on the hypersonic platform. It is of practical significance to develop a signal processing simulation system for hypersonic platform, HyperSonic Vehicle-borne Radarn HSV-R.The paper introduces the overall scheme design of the signal processing simulation system for hypersonic platform. The main tasks of the simulation system are as follows: 1. Including the simulation of the HSV-R signal environment and the simulation of the HSV-R signal processing process, According to the task of the simulation system, the system design idea is formulated. The function module of the simulation system is divided into demonstration guidance, radar echo signal simulation, and the simulation of radar echo signal, the function module of the simulation system is divided into four aspects: demonstration guidance, radar echo signal simulation, and so on. Radar signal processing is divided into three parts. Finally, the common parameters of each function module in the simulation system are introduced. Results the relationship between data flow and software function operation. 2. The parallel processing method of radar signal processing simulation system on hypersonic platform is studied. Based on the analysis of radar clutter model on hypersonic platform, parallel processing methods are studied, including multi-core parallel computing based on CPU and multi-core parallel computing based on GPU. In this paper, the parallel computing effect is given and analyzed. In the multi-core parallel computing based on CPU, the parallel computing method based on parfor and the parallel computing method based on MDCS are introduced. The existing GPU technology and products are introduced, and GPU and CPU are compared. The simulation method of HSV-R clutter based on GPU is described in detail. The development environment and key technologies of the radar signal processing simulation system based on hypersonic platform are introduced in detail, including the design of dynamic link library (DLL). Data visualization technology, design of common data class, design of data transfer mode and index method of system path. Finally, show system login, main interface, flight orbit demonstration, echo generation, clutter characteristic analysis. The realization of nine function modules such as high-speed air target detection and tracking, ground moving target detection and location, ground high resolution scene imaging and user setting.
【学位授予单位】：西安电子科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN957.51

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