基于空气动力学模型含雷达散射截面观测的联合目标跟踪识别

发布时间：2018-04-10 17:30

本文选题：雷达工程 + 空气动力学模型　；参考：《兵工学报》2014年03期

【摘要】：以地基被动警戒雷达为应用背景,主要监视低空突防来袭目标,利用地面上多个商业广播发射的无线电调频(FM)信号,提出基于空气动力学模型含雷达散射截面(RCS)观测的联合目标跟踪识别技术。该技术使用空气动力学模型来描述目标的平动和转动,并将分类器输出的具体参数传递给跟踪器,实现基于动力学模型的跟踪;同时将RCS包括在观测中,它既可提供主要的分类特征,又可根据跟踪器的输出来预测RCS值。跟踪与分类被紧密结合,充分发挥联合跟踪识别的优势,有效提高目标的跟踪性能和识别概率。运用FEKO电磁仿真软件,实时获得目标的RCS观测值,通过粒子滤波实现联合跟踪识别,搭建了基于FM信号的被动雷达目标跟踪识别仿真平台。仿真结果表明,交互式多模型正则化粒子滤波的跟踪精度和识别概率都要优于交互式多模型粒子滤波。
[Abstract]:Taking the ground passive warning radar as the application background, it mainly monitors the low altitude penetration target and uses FM FM signals transmitted by several commercial broadcasts on the ground.A joint target tracking and identification technique based on aerodynamics model with radar cross section (RCS) observation is proposed.The aerodynamics model is used to describe the translation and rotation of the target, and the specific parameters of the classifier output are transferred to the tracker to realize the tracking based on the dynamic model, and the RCS is included in the observation.It can not only provide the main classification features, but also predict the RCS value based on the output of the tracker.Tracking and classification are closely combined to give full play to the advantages of joint tracking and recognition, and effectively improve the tracking performance and recognition probability.The FEKO electromagnetic simulation software is used to obtain the RCS observation value of the target in real time, and the joint tracking recognition is realized by particle filter. A passive radar target tracking and recognition simulation platform based on FM signal is built.Simulation results show that the tracking accuracy and recognition probability of interactive multi-model regularized particle filter are better than interactive multi-model particle filter.
【作者单位】：北京航空航天大学飞行器控制一体化技术重点实验室;洛阳电光设备研究所火力控制技术国防科技重点实验室;
【基金】：航空科学基金项目(20125151028)
【分类号】：TN957

【参考文献】