雷达资源管理及目标跟踪算法研究

发布时间：2018-04-28 13:37

本文选题：雷达资源管理 + 目标跟踪算法　；参考：《电子科技大学》2014年硕士论文

【摘要】：雷达是现代军事信息化战场中必不可少的高科技装备,随着隐身技术的发展和电磁环境的日益恶劣,雷达正在向自适应、多功能的方向发展。雷达资源管理就是提高雷达性能的手段之一,其实质是对雷达任务参数进行有效的配置,达到节约系统资源、充分发挥系统性能的目的。雷达资源管理可分为搜索任务管理、跟踪任务管理和波束驻留调度三个方面。在跟踪模块下进行资源管理主要是指通过对采样周期的控制来管理时间资源,对发射波形相关参数的控制来管理能量资源,最终在保证跟踪精度的前提下使系统参数得到最优化配置。本文围绕雷达资源管理下的跟踪模块进行研究,首先,从目标跟踪算法出发,介绍了卡尔曼滤波、???滤波和?????滤波三种基本目标跟踪算法以及“当前”统计模型(Current Statistical Model,CSM)滤波、自适应???滤波、交互多模型(Interacting Multiple Model,IMM)滤波三种机动目标跟踪算法。从跟踪性能和时间消耗两方面对三种机动目标跟踪算法进行了评估,通过仿真验证了IMM滤波具有更高的跟踪精度,CSM滤波的实时性更好。其次,针对相控阵雷达研究了三种基于自适应目标跟踪的资源管理算法。三种算法都是在CSM算法的基础上实现的。前两种算法分别利用预测协方差门限控制球坐标系下的预测协方差实现采样周期的自适应变化,利用期望跟踪精度控制球坐标系下的预测的估计误差协方差实现脉冲重复个数的自适应变化,他们分别对时间资源和能量资源进行了管理。第三种算法是前两种算法的结合,同时实现了采样周期和脉冲重复个数的自适应变化。仿真验证了三种方法的有效性以及全自适应参数情况下的优势。最后,结合雷达的射频隐身技术,对具有MIMO(Multiple Input Multiple Output)模式的新体制雷达进行了跟踪时的资源管理。在建立该问题的优化模型时,根据传统雷达截获因子的概念,推导了MIMO雷达截获因子的表达式,将其作为使雷达射频隐身性能优化的目标函数,模型的约束条件则是与预测协方差和回波信噪比相关的。模型中的优化参数为子阵划分个数、平均发射功率、波束驻留时间和采样周期,通过遗传算法对该模型的求解验证了该目标跟踪算法能提升MIMO雷达的射频隐身性能和跟踪精度。
[Abstract]:Radar is an indispensable high-tech equipment in the modern military information battlefield. With the development of stealth technology and the increasingly bad electromagnetic environment, radar is developing in the direction of self-adaptation and multi-function. Radar resource management is one of the methods to improve radar performance. Its essence is to effectively configure radar mission parameters to save system resources and give full play to system performance. Radar resource management can be divided into three aspects: search task management, tracking task management and beam resident scheduling. Resource management under the tracking module mainly refers to the control of the sampling period to manage the time resources and the control of the parameters related to the transmitting waveform to manage the energy resources. Finally, the system parameters are optimized under the premise of ensuring tracking accuracy. In this paper, the tracking module under radar resource management is studied. Firstly, the Kalman filter is introduced from the target tracking algorithm. Filtering and filtering? Filter three basic target tracking algorithms and "current Statistical Model CSM" filtering, adaptive? There are three maneuvering target tracking algorithms: filtering, interactive Multiple model filtering. Three maneuvering target tracking algorithms are evaluated in terms of tracking performance and time consumption. Simulation results show that IMM filter has higher tracking accuracy and better real-time performance. Secondly, three resource management algorithms based on adaptive target tracking are studied for phased array radar. All three algorithms are implemented on the basis of CSM algorithm. The first two algorithms use predictive covariance threshold to control the predictive covariance in spherical coordinate system to realize the adaptive change of sampling period. The covariance of prediction error in spherical coordinate system is controlled by the expected tracking precision to realize the adaptive variation of the number of pulse repeats. They manage the time resources and the energy resources respectively. The third algorithm combines the first two algorithms and adaptively changes the sampling period and the number of pulse repeats at the same time. Simulation results show the effectiveness of the three methods and the advantages of fully adaptive parameters. Finally, combined with the radio frequency stealth technology of radar, the resource management of the new system radar with MIMO(Multiple Input Multiple output mode is carried out. Based on the concept of the traditional radar interception factor, the expression of the MIMO radar interception factor is derived, which is regarded as the objective function to optimize the radar radio frequency stealthy performance. The constraints of the model are related to the prediction covariance and echo signal-to-noise ratio (SNR). The optimized parameters in the model are subarray number, average transmit power, beam-dwell time and sampling period. It is proved by genetic algorithm that the target tracking algorithm can improve the radio-frequency stealth performance and tracking accuracy of MIMO radar.
【学位授予单位】：电子科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN953

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