认知雷达目标检测跟踪方法研究

发布时间：2018-02-13 03:41

本文关键词： 认知雷达目标检测目标跟踪闭环反馈波形自适应　出处：《大连海事大学》2017年硕士论文　论文类型：学位论文

【摘要】：认知雷达通过引入接收机到发射机的闭环反馈使雷达具有感知环境与判断决策的能力,从而在当今复杂多变的电磁环境下更加游刃有余的完成相应任务。认知雷达中有两项关键技术:波形最优化技术与自适应机制。本文着重探讨这两项关键技术在检测与跟踪两大典型雷达任务中的应用。论文主要工作如下:(1)论述了认知雷达目标检测识别的波形最优化方法,在统计假设检验理论基础上建立目标响应模型与杂波环境下的收发模型,并基于奈曼皮尔逊准则构建最优波形的目标函数以求解最优波形。研究了单目标跟踪的最优发射波形选择算法,阐述发射波形参数同卡尔曼滤波中测量噪声协方差的联系,并分别利用最小均方误差准则和最大互信息准则进行波形参数选择。(2)综合采用了雷达发射机-接收机闭环反馈和接收机内部检测器-跟踪器闭环反馈两种自适应机制,建立了杂波环境下单目标认知的PDA跟踪算法。在发射机-接收机的闭环反馈中,将波形选择模块引入传统概率数据关联算法,提高了目标的跟踪精度;在接收机内部检测器-跟踪器闭环反馈中,进行检测与跟踪的综合处理,并引入目标的幅值和位置联合信息对关联概率进行修正,与传统算法相比提高了目标检测性能和跟踪精度。(3)在单发射波束下将波形选择模块引入传统联合概率数据关联算法中,建立了杂波环境下多目标认知的JPDA跟踪算法。仿真表明,对存在航迹交叉的运动目标,与传统算法相比跟踪精度得到提高。建立了多目标跟踪的多发射波束有限功率资源的智能化分配算法,提高了最差目标的跟踪精度。(4)提出一种自适应机动目标认知跟踪算法,在变结构交互多模型算法基础上采用一种波门自适应调节方法以处理因目标机动导致的跟丢率骤增情况,同时引入波形选择模块,使跟踪误差逼近估计量的克拉美罗下界,并仿真验证了波形选择算法的鲁棒性。
[Abstract]:By introducing closed-loop feedback from receiver to transmitter, cognitive radar has the ability to perceive environment and judge decision. There are two key technologies in cognitive radar: waveform optimization technology and adaptive mechanism. This paper focuses on these two key technologies in the field of cognitive radar. Application of two typical radar tasks: detection and tracking. The main work of this paper is as follows: 1) the waveform optimization method for target detection and recognition of cognitive radar is discussed. Based on the statistical hypothesis test theory, the target response model and the transceiver model in clutter environment are established. The objective function of the optimal waveform is constructed based on the Nyman Pearson criterion to solve the optimal waveform. The optimal waveform selection algorithm for single target tracking is studied. The relationship between the parameters of the transmitting waveform and the measurement noise covariance in Kalman filter is discussed. The minimum mean square error criterion and the maximum mutual information criterion are used to select the waveform parameters respectively. The two adaptive mechanisms of radar transmitter receiver closed-loop feedback and receiver internal detector tracker closed-loop feedback are adopted respectively. The PDA tracking algorithm for target recognition in clutter environment is established. In the closed-loop feedback between transmitter and receiver, the waveform selection module is introduced into the traditional probabilistic data association algorithm to improve the tracking accuracy of the target. In the closed-loop feedback of the receiver's internal detector and tracker, the detection and tracking are integrated, and the associated probability is corrected by introducing the joint information of the target amplitude and position. Compared with the traditional algorithm, the target detection performance and tracking accuracy are improved. (3) the waveform selection module is introduced into the traditional joint probabilistic data association algorithm under single transmit beam, and a multi-target cognitive JPDA tracking algorithm in clutter environment is established. Compared with the traditional algorithm, the tracking accuracy of moving targets with track crossing is improved. An intelligent allocation algorithm for multi-beam finite power resources with multi-target tracking is established. An adaptive maneuvering target cognitive tracking algorithm is proposed. Based on the variable structure interactive multi-model algorithm, a wave gate adaptive adjustment method is adopted to deal with the sudden increase in the loss rate caused by target maneuvering. At the same time, the waveform selection module is introduced to make the tracking error approach the lower bound of the estimator, and the robustness of the waveform selection algorithm is verified by simulation.
【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】：TN958

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