基于CS-Jerk模型的改进机动目标跟踪算法

Modified Maneuvering Target Tracking Algorithm Based on CS-Jerk Model

文中通过对CS-Jerk模型中的参数以及卡尔曼滤波的分析,提出了一种改进的CS-Jerk模型目标跟踪算法。该算法根据量测新息及其变化率,通过模糊推理机制自适应的调整"当前"统计Jerk模型的机动频率,接着利用强跟踪滤波器对运动模型进行滤波来弥补卡尔曼滤波器的不足。仿真结果表明,提出的改进CS-Jerk模型目标跟踪算法显著提高了原CS-Jerk模型在不同机动模式下对高机动目标的跟踪精度,验证了算法的合理性和可行性。

In this paper,by analyzing the parameters in CS-Jerk model and Kalman filter,a modified CS-Jerk model for target tracking algorithm was proposed.According to the residuals and its change rate,the fuzzy inference mechanism was used to adjust motor frequency of CS-Jerk model,and then,strong tracking filter in the motor model was used to compensate shortcomings of the Kalman filter.The simulation results show that the modified CS-Jerk model remarkably improves the tracking accuracy of high maneuvering target in different motor model in contrast with the original model,validating that the improved algorithm is reasonable and feasible.