粗差拟准检定法在星载GPS低轨卫星定轨中的应用
|
摘要
利用自适应卡尔曼滤波进行星载GPS低轨卫星定轨时,必须解决量测方程中经常存在的粗差问题.在分析以往方法的优缺点后,用拟准检定法来探测和修正量测方程中存在的粗差.该法的优点是辨识粗差准确率高,能同时定位多个粗差.另外,为了克服星载GPS低轨卫星定轨的滤波器可能出现的数值不稳定性及发散现象,还采用了UD分解算法及Sage自适应滤波器.最后用一个CHAMP卫星的模拟算例验证本方法的可行性和有效性.
Kalman filtering technique can be used as optimal estimation of motion state of a LEO (Low-Earth-Orbiter); it can be applied directly to real time Orbit Determination (OD), or to Precise Orbit Determination (POD) with post-processing mode. The OD accuracy using Kalman filters depends on a priori knowledge of system models, noise statistics, especially quality of observations from onboard GPS receiver on LEO. When using Kalman filtering technique for GPS-based OD of LEOs, the gross errors in observation equation must be well dealt with firstly. Having analyzed the characteristics of solving gross errors in pervious methods, QUasi-Accurate Detection (QUAD) of gross errors method has been employed to detect and correct gross errors in observations. The advantages of this method are: accuracy rate of detecting gross errors is high; multiple gross errors can be detected at the same time. In addition, UD decomposition technique and Sage adaptive filter are employed to overcome the instability of numerical value computation and divergence of filter that properly occurred. At last, a simulation example of CHAMP satellite is used to demonstrate the feasibility and validity of new method presented in this paper.
Kalman filtering technique can be used as optimal estimation of motion state of a LEO (Low-Earth-Orbiter); it can be applied directly to real time Orbit Determination (OD), or to Precise Orbit Determination (POD) with post-processing mode. The OD accuracy using Kalman filters depends on a priori knowledge of system models, noise statistics, especially quality of observations from onboard GPS receiver on LEO. When using Kalman filtering technique for GPS-based OD of LEOs, the gross errors in observation equation must be well dealt with firstly. Having analyzed the characteristics of solving gross errors in pervious methods, QUasi-Accurate Detection (QUAD) of gross errors method has been employed to detect and correct gross errors in observations. The advantages of this method are: accuracy rate of detecting gross errors is high; multiple gross errors can be detected at the same time. In addition, UD decomposition technique and Sage adaptive filter are employed to overcome the instability of numerical value computation and divergence of filter that properly occurred. At last, a simulation example of CHAMP satellite is used to demonstrate the feasibility and validity of new method presented in this paper.
引文
Busse Franz D, Simpson James. Demonstration of adaptive extended Kalman filter for low earth orbit formation estimation using CDGPS. Institute of Navigation GPS Meeting, Portland OR, 2002
韩保民.基于星载GPS的低轨卫星几何法定轨理论研究.博士论文,中国科学院测量与地球物理研究所, 2003
[1] Xu Tianhe et al. The Improved Method of Sage Adaptive Filtering. Sci. Survey Map., 2000, 25(3): 22-24. in Chinese(徐天河等.改进的Sage自适应滤波方法.测绘 科学,2000,25(3):22-24)
[2] Yang Yuanxi. The Theory and applications of Robust Estimation. Beijing: Bayi Press, 1993. in Chinese(杨元 喜.抗差估计理论及其应用.北京:八一出版社, 1993)
[3] Yang Y, He H, Xu G. A new adaptively robust filtering for kinematic geodetic positioning. IUGG/IAG Birmingham, 1999
[4] Grewal M S, Andrews A P. Kalman Filtering: Theory and Practice Using MALTAB (2nd Edition). New York: John Wiley & Sons, 2001
[5] Lichten S M. Estimation and filtering for high precision GPS positioning applications. Man. Geod., 1990, 15:159-177
[6] Tao Benzao. The identification of Kalman filtering model errors. J. Crustal Deform. Earthq., 1999, 19(4):15-20.in Chinese(陶本藻.卡尔曼滤波模型误差 的识别.地壳形变与地震, 1999,19(4):15-20)
[7] Koch K R, Yang Y. Robust Kalman filter for rank deficient observation models. J. Geod., 1998, 72(8):436-441
[8] Chai Hongzhou, Cui Y. Robust Kalman Filter for GPS Kinematic Positioning. J. Inst. Surv. Mapp., 2001, 18(1):12-15.in Chinese(柴洪洲等.抗差卡尔曼滤波在 GPS动态定位中的应用.测绘学院学报,2001,18(1):12- 15)
[9] Ou J K. A design of triple-step resistance to gross errors. Acta Geod. Cart. Sinica, 1996, 25(3):173-179, in Chinese(欧吉坤.一种三步抗差方案的设计.测绘学报, 1996,25(3):173-179)
[10] Ou J K. A new method of identifying and locating gross errors-Quasi-Accurate Detection. Sci. Bull, 1999, 44(16):1777-1781. in Chinese
[11] Schwarz K P et al. A comparison of GPS kinematic models for the determination of position and velocity along a trajectory. Man. Geod., 1989, 14:345-353
韩保民.基于星载GPS的低轨卫星几何法定轨理论研究.博士论文,中国科学院测量与地球物理研究所, 2003
[1] Xu Tianhe et al. The Improved Method of Sage Adaptive Filtering. Sci. Survey Map., 2000, 25(3): 22-24. in Chinese(徐天河等.改进的Sage自适应滤波方法.测绘 科学,2000,25(3):22-24)
[2] Yang Yuanxi. The Theory and applications of Robust Estimation. Beijing: Bayi Press, 1993. in Chinese(杨元 喜.抗差估计理论及其应用.北京:八一出版社, 1993)
[3] Yang Y, He H, Xu G. A new adaptively robust filtering for kinematic geodetic positioning. IUGG/IAG Birmingham, 1999
[4] Grewal M S, Andrews A P. Kalman Filtering: Theory and Practice Using MALTAB (2nd Edition). New York: John Wiley & Sons, 2001
[5] Lichten S M. Estimation and filtering for high precision GPS positioning applications. Man. Geod., 1990, 15:159-177
[6] Tao Benzao. The identification of Kalman filtering model errors. J. Crustal Deform. Earthq., 1999, 19(4):15-20.in Chinese(陶本藻.卡尔曼滤波模型误差 的识别.地壳形变与地震, 1999,19(4):15-20)
[7] Koch K R, Yang Y. Robust Kalman filter for rank deficient observation models. J. Geod., 1998, 72(8):436-441
[8] Chai Hongzhou, Cui Y. Robust Kalman Filter for GPS Kinematic Positioning. J. Inst. Surv. Mapp., 2001, 18(1):12-15.in Chinese(柴洪洲等.抗差卡尔曼滤波在 GPS动态定位中的应用.测绘学院学报,2001,18(1):12- 15)
[9] Ou J K. A design of triple-step resistance to gross errors. Acta Geod. Cart. Sinica, 1996, 25(3):173-179, in Chinese(欧吉坤.一种三步抗差方案的设计.测绘学报, 1996,25(3):173-179)
[10] Ou J K. A new method of identifying and locating gross errors-Quasi-Accurate Detection. Sci. Bull, 1999, 44(16):1777-1781. in Chinese
[11] Schwarz K P et al. A comparison of GPS kinematic models for the determination of position and velocity along a trajectory. Man. Geod., 1989, 14:345-353
版权所有：© 2023 中国地质图书馆 中国地质调查局地学文献中心