基于UKF航迹滤波的干扰目标智能识别算法研究  

An Intelligent Recognition Method for Jamming Target Based on UKF Track Filtering

作　　者：王铮[1] 韩宝玲[1] Wang Zheng;Han Baoling(Beijing Institute of Technology, Beijing 100081, China)

机构地区：[1]北京理工大学,北京100081

出　　处：《航空兵器》2019年第1期83-88,共6页Aero Weaponry

摘　　要：针对雷达导引头末制导阶段抗干扰技术,建立了典型的距离-速度拖引干扰模型,采用无迹卡尔曼滤波(UKF),研究了基于速度、加速度、过载等指标的干扰目标智能识别技术。首先建立距离-速度拖引干扰模型,通过引入弹目相对距离、径向速度、高低角与方位角建立了系统跟踪模型。其次,给出了基于UKF实现目标跟踪与识别的滤波框架。在此基础上,以径向速度、径向加速度、角加速度与过载为评价指标,建立了目标智能识别指标体系。最后,通过典型的目标运动模型(目标跃升),对目标施加的四次距离-速度拖引干扰(两次前拖、两次后拖)进行目标识别。仿真结果表明,利用UKF滤波信息能够有效实现对距离-速度拖引干扰下的干扰和目标智能识别,仿真结果验证了该识别方法的可行性与有效性。Aiming at the anti-jamming technology in radar seeker terminal guidance phase, with the typical range-velocity pull-off(RVPO) jamming model, an intelligent method for target and jamming intelligent recognition technology based on UKF filtering is studied. Firstly, RVPO model is established, by introducing missile-target relative distance, radial velocity, high-low angle and azimuth angle, the tracking system model is established. Secondly, the filtering framework for target tracking and recognition based on UKF is given, and target recognition index system is established based on radial velocity, radial, acceleration, angular acceleration and overload. Finally, a simulation experiment is performed based on a typical target motion (zooming) model. In this experiment, a target that launched four RVPO jamming attacks is identified. The simulation results show that the UKF filtering information could help achieve effective target recognition under RVPO jamming attacks. In addition, the simulation results also validate the feasibility and effectiveness of the recognition method developed in this study.

关 键 词：航迹滤波 目标智能识别 抗干扰 距离-速度拖引 无迹卡尔曼滤波 

分 类 号：TJ760[兵器科学与技术—武器系统与运用工程] TJ765.3