摘要
在ＧＰＳ观测数据中经常出现野值以及幅值和相位作随机跃变的正弦扰动分量．对此，文中提出了剔除野值的改进的卡尔曼滤波、抑制观测噪声中周期干扰的推广卡尔曼滤波．此外，还引用了可跟踪噪声方差变化的ＱＲ自适应卡尔曼滤波器．对实测ＧＰＳ静态和动态定位数据进行上述卡尔曼滤波的结果表明，定位精度有了很大提高．
In the GPS observation data,it has been shown by an investigation that there exist outliers and sinusoidal disturbances with randomly and stepwisely changing magnitude and phase.Therefore,a modified Kalman filter for removing the outliers and an new extended Kalman filter for depressing the sinusoidal disturbaces are developed.Then,an adaptive Kalman filter for tracking the time varying dynamic and observation noises variances Q and R is also introduced.The effectiveness in improving the positioning accuracy is illustrated by two case studies of real data processing.
出处
《中央民族大学学报（自然科学版）》
1999年第1期32-39,共8页
Journal of Minzu University of China(Natural Sciences Edition)
