SIA OpenIR  > 智能检测与装备研究室
雷达信号处理系统的性能预测与优化方法研究
其他题名Research on Performance Prediction and Optimization Method of Radar Signal Processing System
李想1,2
导师杜劲松
分类号TN957.51
关键词雷达信号处理 软件化雷达 性能预测 性能优化
索取号TN957.51/L36/2018
页数105页
学位专业机械电子工程
学位名称博士
2018-05-16
学位授予单位中国科学院沈阳自动化研究所
学位授予地点沈阳
作者部门智能检测与装备研究室
摘要

本文的研究内容依托于XX单位的XX项目,在国内外相关研究成果的基础上,针对现代雷达系统中迫切需要解决的问题,具体从以下几方面开展研究工作:(1) “软件化雷达”技术研究。提出了“软件化雷达”的实现思路和方法。设计了开放式可扩展的模块库,并对系统软硬件进行解耦,实现了雷达信号处理系统的模块化、可视化、标准化的开发方式,通过自动代码生成技术来代替传统的人工编程,极大地提高开发效率。以软件定义方式开发雷达信号处理系统,可以使开发出的系统便于进行功能扩展和性能升级,从而快速响应实际需求。而且,模块化开发和分层解耦技术也为系统的性能预测与优化奠定了基础。(2) 雷达信号处理系统的性能预测算法研究。首先给出了雷达信号处理系统的性能评价指标。然后提出了一种将分析方法与仿真方法相结合的性能预测算法,对雷达信号处理流程图、硬件平台拓扑结构图和映射方案进行分析,提取出系统软硬件信息,进行时序仿真,根据仿真得到的系统时序图,计算出系统各项性能指标值。最后给出了系统性能指标实际值的测试方案,并将性能预测算法得到的预测值与实际值进行比较,验证了该性能预测算法的有效性与可行性。(3) 雷达信号处理系统的性能优化算法研究。首先提出了一种将人工免疫算法与多Agent系统相结合的多目标优化算法,通过邻域克隆选择行为、竞争行为、协作行为以及自学习行为,实现高效的局部与全局搜索,并引入了适应度共享策略,更好地保证种群多样性。通过将本文算法与NSGA2和SPEA2两种经典的多目标优化算法进行比较,证明了本文算法得到的解具有更好的收敛性和分布均匀性。然后将该多目标优化算法应用到雷达信号处理系统的性能优化中,自动生成使雷达系统的各项性能指标整体上达到最优的映射方案。实验结果表明,应用该多目标优化算法能够搜索出最优映射方案,对雷达信号处理系统的优化设计和性能提升具有重要指导意义。(4) 雷达信号处理系统的集成开发环境。设计开发了雷达信号处理系统的集成开发环境RadarLab。RadarLab实现了“软件化雷达”的核心技术理念,并基于本文提出的性能预测与性能优化算法,实现了雷达信号处理系统的性能预测与优化功能。RadarLab已经在中国电科38所和中船724所进行了实际测试和应用,取得了良好的效果。

其他摘要

This thesis relies on XX project of XX institution. On the basis of related research achievements at home and abroad, this thesis carries out research work in the following aspects to solve the pressing problems in the modern radar system. (1) Study of “software radar” technology. Realization idea and method of “Software radar” are proposed. An open-ended and extensible module library is designed, and software and hardware of the system are decoupled, to realize a modularized, visualized and standardized development mode of radar signal processing system. In this new mode, the traditional manual programming is replaced by automatic code generation. Development efficiency is significantly improved. With the software definition mode of developing radar signal processing system, the developed system is convenient for function extension and performance upgrade, so as to quickly respond to actual demands. Moreover, modularized development mode and decoupling technology lay the foundation to performance prediction and optimization of the system. (2) Study of performance prediction algorithm of radar signal processing system. Firstly, the performance index system of radar signal processing system is given. Then a performance prediction algorithm combining the analytical method with the simulation method is proposed. The algorithm analyzes the signal processing flowchart, the hardware topology structure chart and the mapping scheme, and extracts software and hardware information of the system to start timing simulation. According to the sequence chart of system, the algorithm calculates the performance indexes of the system. Finally, the test scheme of actual values of performance indexes is given. The comparison between the predicted values and the actual values shows that the performance prediction algorithm proposed is valid and feasible. (3) Study of performance optimization algorithm of radar signal processing system. Firstly, a multi-objective optimization algorithm combining artificial immune algorithm with multi-agent system is proposed. The proposed algorithm completes the local and global search efficiently through neighborhood clone selection operator, competition operator, collaboration operator and self-learning operator. Fitness sharing strategy is introduced to keep individual diversity. The proposed algorithm is compared with two classic multi-objective optimization algorithms: NSGA2 and SPEA2. Experimental results show that the optimal solutions of the proposed algorithm are better in terms of convergence and uniformity. Then the proposed algorithm is applied to performance optimization of radar signal processing system, automatically searching out the mapping schemes that make system performance reach optimum. Experimental results show that the proposed multi-objective optimization algorithm can search out the optimal mapping schemes. It is of great guiding significance for optimal design and performance improving of radar signal processing system. (4) Study of integrated development environment of radar signal processing system. Integrated development environment of radar signal processing system--RadarLab is designed and developed. RadarLab achieves the core technology concept of “software radar”, and also performance prediction and performance optimization of radar signal processing system based on the proposed performance prediction and performance optimization algorithms. RadarLab has already been tested and used in NO.38 Research Institute of China Electronic Technology Group Corporation and NO.724 Research Institute of China Shipbuilding Industry Corporation. RadarLab obtains good effect in the practice.

语种中文
产权排序1
文献类型学位论文
条目标识符http://ir.sia.cn/handle/173321/21785
专题智能检测与装备研究室
作者单位1.中国科学院沈阳自动化研究所
2.中国科学院大学
推荐引用方式
GB/T 7714
李想. 雷达信号处理系统的性能预测与优化方法研究[D]. 沈阳. 中国科学院沈阳自动化研究所,2018.
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