海防雷达仿真系统杂波抑制算法的研究

发布时间：2018-11-28 15:37

【摘要】：海防雷达系统在我国国防安全中扮演重要角色,雷达兵日常训练会影响雷达寿命,海防雷达仿真系统应运而生。通常雷达在接收目标回波的同时,不可避免的还有来自周围环境的海浪回波,雨雪云雾回波以及雷达内部噪声干扰等。因此高效的杂波抑制算法对目标检测和追踪有着重大意义。本文以杂波抑制算法为研究核心,首先对海杂波的产生机理进行分析研究,根据海杂波的产生机理综合分析现有的海杂波分布模型的适应范围、影响因素,其中包括Rayleigh分布,Lognormal分布,Weibull分布以及复合K分布,同时研究海杂波的时间相关性和空间相关性,分析证明海杂波具有混沌特性;然后分析粒子群算法(PSO)的轨迹收敛性和速度收敛性,发现由于粒子有可能出现"惰性",使进化过早收敛到局部最优点,因此通过加入混沌扰动优化粒子群算法,利用优化的混沌粒子群算法(CPSO)寻找支持向量机(SVM)的最优参数,结合相空间重构理论对海杂波时间序列进行回归预测,利用原始数据和回归预测数据的差值,完成海杂波的初步抑制;最后介绍海防雷达仿真系统中杂波抑制模块的设计思想及实现方法,利用奇异值分解法和中值滤波算法分别对海浪杂波和雨雪杂波展开进一步抑制,并展示抑制效果图。抑制效果证明,本文海防雷达仿真系统中的杂波抑制算法对各种海杂波产生较好的抑制效果,通过调节海浪抑制参数和雨雪抑制参数,可以不同程度的消除海浪杂波和雨雪杂波。为海防雷达仿真系统中目标检测与追踪提供有力帮助。
[Abstract]:The coastal defense radar system plays an important role in the national defense security of our country. The daily training of radar soldiers will affect the radar life, and the coastal defense radar simulation system emerges as the times require. At the same time of receiving the target echo, the radar inevitably also has the wave echo from the surrounding environment, rain, snow, cloud and fog echo, as well as the radar internal noise interference and so on. Therefore, efficient clutter suppression algorithm has great significance for target detection and tracking. In this paper, the clutter suppression algorithm is taken as the core of the research. Firstly, the mechanism of sea clutter generation is analyzed. According to the mechanism of sea clutter generation, the adaptive range of existing sea clutter distribution models and the influencing factors, including Rayleigh distribution, are analyzed synthetically. Lognormal distribution, Weibull distribution and compound K distribution. The temporal and spatial correlation of sea clutter is studied. The analysis shows that sea clutter has chaotic characteristics. Then, by analyzing the trajectory convergence and velocity convergence of particle swarm optimization (PSO) algorithm, it is found that the particle swarm optimization algorithm is optimized by adding chaos disturbance because of the possibility of "inertia" in particle evolution and premature convergence to local optimum. The optimized chaotic particle swarm optimization (CPSO) algorithm is used to find the optimal parameters of the support vector machine (SVM), and the phase space reconstruction theory is used to predict the sea clutter time series. The difference between the original data and the regression prediction data is used. The primary suppression of sea clutter is completed; Finally, the design idea and implementation method of clutter suppression module in sea defense radar simulation system are introduced. The singular value decomposition method and median filtering algorithm are used to further suppress wave clutter and rain and snow clutter, respectively, and display the suppression effect diagram. The suppression effect proves that the clutter suppression algorithm in the sea defense radar simulation system has good suppression effect on all kinds of sea clutter by adjusting the wave suppression parameters and the rain and snow suppression parameters. Can eliminate wave clutter and rain and snow clutter in varying degrees. It can provide powerful help for target detection and tracking in coastal defense radar simulation system.
【学位授予单位】：大连海事大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN959;TP391.9

【相似文献】