为改善现有机动目标跟踪方法存在的跟踪精度不高、滤波易发散的问题,提出了一种RA-Jerk-EKF算法,该算法将目标径向加速度信息引入量测向量,通过增加雷达量测向量维数提高机动目标的跟踪精度。在信号处理阶段利用分数阶傅里叶变换(FRFT)估计出目标的径向加速度, 并将其通过坐标转换引入量测向量中;在数据处理阶段采用Jerk模型和扩展卡尔曼滤波(EKF)算法解决滤波算法中非线性量测方程问题;最后将该方法与传统的不带径向加速度的Jerk-EKF方法进行了仿真比较。结果表明, 该方法在跟踪精度, 位置、加速度和速度估计精度方面均有所改善。

In order to improve the performance of maneuvering target tracking, a RA-Jerk-EKF method is proposed by integrating the target radial acceleration into the measurement matrix, thus to improve the tracking accuracy by increasing the dimensions of measurement matrix.In the proposed method, the radial acceleration is derived based on Fractional Fourier Transformation (FRFT) in signal processing phase, and is then brought into the measurement vector through coordinate transformation.In data processing phase, a method of Extended Kalman Filter (EKF) based on Jerk model is adopted to resolve the problem of the non-linearity of the measurement equation in filtering.Simulation is made to compare the proposed method with the traditional Jerk model based EKF without acceleration measurement.The results show that the proposed algorithm has better performance on tracking accuracy, and estimation accuracies of position, acceleration and velocity are improved at the same time.