自适应Kalman滤波器在红外夜视跟踪系统中的研究

Research of adaptive Kalman filter applied in infrared night vision tracking system

针对红外夜视系统背景较复杂,直角坐标系下的卡尔曼滤波容易发散,且影响滤波精度的特点,在分析自适应卡尔曼滤波算法优缺点的基础上,提出了一种针对红外夜视系统目标跟踪的自适应卡尔曼滤波算法,此算法利用投影分析法获得目标位置坐标.还对虚拟噪声进行估计,补偿系统的线性误差,消减系统观测误差,并对算法进行了仿真.仿真结果表明,该算法提高了滤波的稳定性和精确度,具有很好的优越性.

The background of infrared night vision tracking system is more complicated.Concerning the problem of instability in rectangular coordinate system and low accuracy of the passive Kalman filter,and on the basis of analyzing the advantages and disadvantages of the adaptive Kalman filter algorithm,a new Kalman filter for infrared night vision tracking system is presented.This algorithm obtains the coordinate of the target location by projection analysis method.Owing to estimating the statistics of the state virtual noise on-line,it overcomes the bad affect caused by linearization of the nonlinear state model.Simulation result shows that the algorithm improves the filtering convergence rate and accuracy.