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

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。

Joint Target Tracking and Classification Based on Aerodynamic Model and RCS Observation

An effective joint target tracking and classification technology, which uses the radio frequency modulation (FM) signals transmitted by the commercial broadcast stations on ground, based on the aerodynamic model and RCS observation is proposed for the ground-based passive warning radars for monitoring the low altitude penetration incoming targets. The aerodynamic model is used to describe the translation and rotation of target, and the specific parameters of a particular type of aircraft are transferred to the tracker to realize the aerodynamic model-based tracking; at the same time, the radar cross section (RCS) is included in the observation to provide the main classification featuers, and the outputs of the tracker are used to predict the RCS value. Therefore, tracking and classification are coupled tightly to give full play to the advantage of joint tracking and classification, effectively improving the tracking performance and classification probability. In the implementation of this technology, the electromagnetic simulation software FEKO is applied to obtain the target’s real-time RCS observation; this joint tracking and classification is realized by particle filtering. A simulation platform for the FM signal-based target tracking and classification by passive radar is built. The simulation results show that the interacting multiple model regularized particle filter works better than the interacting multiple model particle filter in tracking accuracy and classification probability.