基于卡尔曼滤波的高精度弹道滤波算法研究

在弹道轨迹估计中,卡尔曼滤波算法是一种普遍使用的算法,常规卡尔曼滤波算法适用于线性离散系统.对于非线性离散系统模型,为了提高滤波的精度,减小系统模型误差以及未知的量测噪声和过程噪声统计特性对滤波精度的影响,提出了一种带有噪声统计估计器的拟线性最优平滑滤波算法.将该算法应用到弹道系统模型中,对弹道轨迹进行滤波估计.通过计算机建模仿真改进的算法和传统的拟线性最优平滑滤波算法,得到的实验结果表明,改进后的算法可以减小由于系统模型不精确带来的误差,很大程度上提高了弹道轨迹滤波估计的精度.

High accuracy ballistic filtering algorithm based on the Kalman filter

Kalman filter is one of the most commonly used algorithms in the trajectory estimation of ballistic.The conventional Kalman filter is adapted to discrete linear system.But in the non-linear system,in order to improve the filtering precision and reduce the influence of modeling error and the character of unknown statistic in the process noise and measurement noise,this paper presents a method of noise statistics estimator based on the quasi linear optimal smooth filtering algorithm.The algorithm is applied to a model of the ballistic system and estimate the trajectory of the ballistic.The improved algorithm and the traditional quasi linear optimal smooth filtering algorithm are simulated in the computer.The simulation result shows that the error caused by the inaccuracy system model can be reduced and the filtering precision can be greatly improved.