修正的截断正态概率密度模型自适应滤波算法

An adaptive filtering algorithm based on truncation gauss probability model modified

针对机动目标跟踪问题,在截断正态概率密度模型的基础上,通过目标机动状况与相邻采样时刻间位置估计量变化之间的函数关系实现噪声方差自适应调整,提出了一种新的自适应滤波算法——基于截断正态概率密度模型修正的自适应滤波算法。计算机仿真结果表明,该算法在跟踪机动目标时,具有良好的跟踪性能,并极大地改善了跟踪非机动目标的能力。

Based on truncation gauss probability model for target tracking, it utilizes the functional rela- tion between the maneuvering status of the target and the estimation of the neighboring inter - sample position information to carry out the self - adaption of the process noise variance. This algorithm avoids the adverse influence of the limit acceleration presupposed in the aspect of target tracking. A number of simulation results indicate that the algorithm not only makes good performances on tracking maneuvering target, but also greatly improves the capacity for tracking non - maneuvering target.