自校正滤波器在卫星定位中的应用

Application of Self-Tuning Filter In Satellite Position

设计了一种新的基于ARMA模型的自校正卡尔曼滤波器,对卫星定位误差模型参数进行分段在线估计,根据误差模型估计参数直接求取滤波增益阵.并提出了一种直接计算滤波误差方差阵的方法,对两个不同的定位系统进行信息融合.仿真结果表明,在未知噪声统计特性的情况下,自校正卡尔曼滤波器能有效过滤观测噪声,基于它的信息融合规则能够有效提高定位精度.计算过程简单,并可以在线建模.

A new self-tuning Kalman filter based on ARMA model has been designed to estimate segmentally parameters of the error model of the satellite navigation on line, which can get the gain matrices from the estimated parameters directly. A method which can compute filtering error variance matrices directly is presented to fuse the position information from different satellite navigation system. The simulation results suggest that in the case of the characteristics of the noises are unknown , the self-tuning kalman filter performs effectively on filtering observation noises. The rule of the information fusion based on this filter is able to enhance the accuracy of navigation. It is very easy to be computed, so it can be modeled on line.