一种激光跟踪测量中的滤波算法

Filter Algorithm for Laser Tracking System

在跟踪问题的处理中 ,以往所经常采用的是白噪声观察模型。但是实际上测量噪声却经常是有色噪声 ,有色观测噪声会使跟踪算法的性能减退。为了提高跟踪精度 ,必须有效地消除有色噪声 ,因此有效地消除有色噪声是处理跟踪问题的关键所在。本文把观测噪声的成形滤波器假设为AR模型 ,提出了一种在线估计色噪声参数的方法。通过在线估计色噪声参数 ,即AR模型的参数 ,对测量噪声去相关来提高Kalman滤波精度 ,并且最终将这种方法应用于激光跟踪。仿真结果表明这种方法具有较好的去相关能力 ,大大提高了激光跟踪过程中角速度的跟踪性能 。

Color noise may degrade the performance of a tracking algorithm, and color noise must be eliminated to improve the tracking precision. Estimating online estimation of colored noise and decorrelation of noise is an important means to improve the precision of Kalman filter.The model of colored noise is supposed to be an autoregressive(AR)process and a new method is used to estimate colored noise on line. The results of simulation show that this method has a better decorrelation performance, and improves the performance of angle tracking.