基于IMMUKF的目标定位跟踪算法研究

Research on Target Location and Tracking Algorithm Based on IMMUKF

目标定位跟踪的关键在于得到精确的定位数据,而要获取精确的定位数据取决于高效的滤波算法。无迹卡尔曼滤波由于具有定位精度高、算法复杂度低等特点,被广泛应用于非线性系统中。针对无迹卡尔曼滤波在目标运动状态突变时容易出现跟踪精度下降、目标丢失等问题,对传统无迹卡尔曼滤波算法进行优化和改进,通过将无迹卡尔曼滤波与IMM卡尔曼滤波算法相结合,利用IMM算法的鲁棒性有效提高了无迹卡尔曼滤波在目标机动运动时的跟踪精度,避免了目标丢失。实验仿真结果表明,IMMUKF算法具有很好的稳定性,可实现复杂的目标跟踪。

The key of locating and tracking is how to get accurate positioning data,and the acquisition of precise location data depends on effective filtering algorithm.The unscented Calman filter is widely used in nonlinear systems because of its high location accuracy and low algorithm complexity.In this paper,the traditional algorithm is optimized and improved in view of the error of the untracked Calman filter in tracking maneuvering target,such as the error of precision and the loss of the target.Combining the untracked Calman filter with the IMM Calman filter,the tracking precision of the untracked Calman filter in the maneuvering target is improved with the robustness of the IMM algorithm,and the loss of the target is avoided.Finally,experimental simulation is carried out to verify the effectiveness of the IMMUKF algorithm.