针对机动目标的改进型交互多模型跟踪算法研究

为了提高对机动目标的跟踪精度,更准确地获得目标实时位置与速度信息,提出了一种改进型交互多模型跟踪算法.采用目标特征数据为初始数据提供限定域,然后在滤波器中加入调节参数,从而利用目标状态增益矩阵与协方差矩阵的迭代完成对跟踪精度的优化.实验仿真分析了机动目标的3种常见状态,并与传统交互多模型跟踪算法进行了对比.实验结果显示...

An improved interactive multi-model tracking algorithm for maneuvering targets

In order to improve the tracking accuracy of maneuvering targets and obtain more accurate real-time position and velocity information of the targets, an improved interactive multi-model tracking algorithm is proposed. Based on the traditional interactive multi-model, this algorithm introduces adjustment parameters associated with target features. The target feature data is used to provide a limited domain for the initial data, and then the adjustment parameters are added to the filter, so as to complete the optimization of the tracking accuracy by the iteration of the target state gain matrix and the covariance matrix. Experimental simulation analyzes three common states of maneuvering targets and compares them with traditional interactive multi-model tracking algorithms. The experimental results show that, when the deflection angles of the adjustment parameters of the algorithm are 4°, 2° and 1°, the mean root mean square errors are 15.91 m, 11.79 m and 11.39 m respectively, which are significantly better than the traditional algorithms mean value of 21.39 m. At the same time, with the improvement of parameter setting accuracy, it has a certain inhibitory effect on the error fluctuation caused by the maneuvering target state.