摘要
该文针对全球定位系统(GPS)和高精度气压高度表测高误差的不同特性,建立基于三阶全微分的气压高度表原理误差补偿模型,并提出一种基于"当前"统计模型自适应卡尔曼滤波(KF)的GPS与高精度气压高度表在线互标定方法,实现GPS与气压高度表的优势互补。通过加速度的均值和方差的自适应跟踪,完成驱动噪声方差阵和状态参数的自适应修正。同时,引入自适应遗忘因子,充分利用"现时"的测量数据,改善滤波器的动态性能。真实航路数据的半物理仿真验证了该文方法的有效性。
According to the different characteristic of the height error＇s measurement between Global Positioning System（GPS） and baro-altimeter, an error model of baro-altimeter based on third differential is established, and a method of intercalibration for GPS and high precision baro-altimeter on line is proposed. The adaptive Kalman filter based on the current statistical model is used in this method, which combined GPS and baro-altimeter efficaciously. This method can track the acceleration mean and covariance adaptively, and adjust the process noise covariance matrix and state parameters adaptively. At the same time, fading factor is used to make the best of current measurement data, and then improve the dynamics of filter. Based on the trajectory of real fairway, the semi-physical simulation results illustrate the validity of this method.
出处
《电子与信息学报》
EI
CSCD
北大核心
2009年第4期818-821,共4页
Journal of Electronics & Information Technology
基金
国家863计划项目(2006AA12A108)
国家自然科学基金(60602047)资助课题
关键词
全球定位系统
高度表
自适应滤波
标定
Global Positioning System（GPS）
Altimeter
Adaptive filtering
Calibration
