基于Jerk模型的一种改进多传感器数据融合算法

简要介绍了目前存在的一些机动模型和基于状态估计的滤波算法。将Jerk模型与强跟踪滤波算法有机地结合起来,并提出了一种通过时空综合分析的测量方差自适应估计方法以优化强跟踪滤波算法中次优渐消因子和滤波增益的在线选择,同时结合多传感器数据融合具有改善滤波精度的性质,最终给出了一种基于Jerk模型的改进多传感器数据融合算法。最后,通过蒙特卡罗仿真验证了该算法的有效性。

An improved multi-sensor data fusion algorithm based on Jerk model

Some maneuver model and filtering algorithm based on state estimation is briefly introduced.An improved multi-sensor data fusion algorithm based on Jerk model is presented.This algorithm firstly effectively combines Jerk model with strong tracking filter,and presents a method of the variance of the measured error adaptive through spatial-temporal analysis for on-line optimization of hypo-optimal fading factor and filter gain on the strong tracking filter.And the method utilizes the characteristic that multi-sensor data fusion can improve the precision of state estimation.Finally,Monte-Carlo simulation shows that this algorithm can obviously improve the efficiency of maneuvering target tracking.