基于CT非线性模型的水下目标跟踪算法比较

针对水下目标跟踪非线性跟踪精度问题,假设目标机动模型为恒转速运动模型,贝叶斯框架下,因扩展卡尔曼滤波跟踪方法进行模型在估计点的泰勒展开,忽略一阶以上高阶项,存在模型误差,比较了扩展卡尔曼滤波、无迹卡尔曼滤波、容积卡尔曼滤波在高斯噪声干扰下滤波误差均方根,以及3种方法运行时间。仿真证明,非线性系统下状态维度为5,容积卡尔曼滤波跟踪的精度高于无迹卡尔曼滤波,无迹卡尔曼滤波高于扩展卡尔曼滤波。该研究为海上目标非线性测量系统提供仿真实例,为进一步滤波算法改进提供基础。

Comparison of Underwater Target Tracking Algorithms Based on CT Non-linear Model

Aiming at the problem of non-linear tracking accuracy of underwater target tracking,the target maneuver model is assumed to be a constant speed motion model, under the Bayesian framework,because the extended Kalman filter tracking method carries out Taylor expansion of the model at the estimated point,ignoring the second-order and higher-order terms,there are model errors.The root mean square of filtering errors of extended kalman,unscented Kalman and cubature Kalman under the interference of Gauss noise are compared,and the running time of the three methods are also given. The simulation results show that the tracking accuracy of the cubature Kalman filter is higher than that of the unscented Kalman filter and the unscented Kalman filter is higher than that of the extended Kalman filter in the nonlinear system of 5 state dimensions. A simulation example is provided for adaptive modeling and filtering of non-linear measurement systems such as sonar for offshore targets,it also provides a basis for next step of filter algorithm improvement.