Please wait a minute...
Frontiers of Information Technology & Electronic Engineering

ISSN 2095-9184

Front. Inform. Technol. Electron. Eng    2019, Vol. 20 Issue (6) : 829-841    https://doi.org/10.1631/FITEE.1800308
Orginal Article
An online error calibration method for spaceflight TT&C systems based on LEO-ground DDGPS
Qiao WANG(), Xiao-jun JIN(), Wei ZHANG, Shi-ming MO, Zhao-bin XU, Zhong-he JIN
Micro-Satellite Research Center, Zhejiang University, Hangzhou 310027, China
 Download: PDF(648 KB)  
 Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks
Abstract

To overcome the shortcomings of the traditional measurement error calibration methods for spaceflight telemetry, tracking and command (TT&C) systems, an online error calibration method based on low Earth orbit satellite-to-ground doubledifferential GPS (LEO-ground DDGPS) is proposed in this study. A fixed-interval smoother combined with a pair of forward and backward adaptive robust Kalman filters (ARKFs) is adopted to solve the LEO-ground baseline, and the ant colony optimization (ACO) algorithm is used to deal with the ambiguity resolution problem. The precise baseline solution of DDGPS is then used as a comparative reference to calibrate the systematic errors in the TT&C measurements, in which the parameters of the range error model are solved by a batch least squares algorithm. To validate the performance of the new online error calibration method, a hardware-in-the-loop simulation platform is constructed with independently developed spaceborne dual-frequency GPS receivers and a Spirent GPS signal generator. The simulation results show that with the fixed-interval smoother, a baseline estimation accuracy (RMS, single axis) of better than 10 cm is achieved. Using this DDGPS solution as the reference, the systematic error of the TT&C ranging system is effectively calibrated, and the residual systematic error is less than 5 cm.

Keywords Spaceflight      low Earth orbit (LEO)      Filter      Optimization      Calibration     
Corresponding Author(s): Qiao WANG,Xiao-jun JIN   
Issue Date: 01 August 2019
 Cite this article:   
Qiao WANG,Xiao-jun JIN,Wei ZHANG, et al. An online error calibration method for spaceflight TT&C systems based on LEO-ground DDGPS[J]. Front. Inform. Technol. Electron. Eng, 2019, 20(6): 829-841.
 URL:  
https://academic.hep.com.cn/fitee/EN/10.1631/FITEE.1800308
https://academic.hep.com.cn/fitee/EN/Y2019/V20/I6/829
[1] FITEE-0829-19007-QW_suppl_1 Download
[2] FITEE-0829-19007-QW_suppl_2 Download
[1] Weihua WU, Yichao CAI, Hongbin JIN, Mao ZHENG, Xun FENG, Zewen GUAN. Derivation of the multi-model generalized labeled multi-Bernoulli filter: a solution to multi-target hybrid systems[J]. Front. Inform. Technol. Electron. Eng, 2021, 22(1): 79-87.
[2] Rui WANG, Yahui LI, Hui SUN, Youmin ZHANG. Freshness constraints of an age of information based event-triggered Kalman consensus filter algorithm over a wireless sensor network[J]. Front. Inform. Technol. Electron. Eng, 2021, 22(1): 51-67.
[3] Feisheng YANG, Xuhui LIANG, Xiaohong GUAN. Resilient distributed economic dispatch of a cyber-power system underDoS attack[J]. Front. Inform. Technol. Electron. Eng, 2021, 22(1): 40-50.
[4] Guanghui WEN, Xinghuo YU, Zhiwei LIU. Recent progress on the study of distributed economic dispatch in smart grid: an overview[J]. Front. Inform. Technol. Electron. Eng, 2021, 22(1): 25-39.
[5] Wei-jiang HONG, Yi-jun LIU, Zhen-bang CHEN, Wei DONG, Ji WANG. Modified condition/decision coverage (MC/DC) oriented compiler optimization for symbolic execution[J]. Front. Inform. Technol. Electron. Eng, 2020, 21(9): 1267-1284.
[6] Ming-gang DONG, Bao LIU, Chao JING. A many-objective evolutionary algorithm based on decomposition with dynamic resource allocation for irregular optimization[J]. Front. Inform. Technol. Electron. Eng, 2020, 21(8): 1171-1190.
[7] Gang CHEN, Jun WANG. Robust mismatched filtering algorithm for passive bistatic radar using worst-case performance optimization[J]. Front. Inform. Technol. Electron. Eng, 2020, 21(7): 1074-1084.
[8] Yi-fei PU, Jian WANG. Fractional-order global optimal backpropagation machine trained by an improved fractional-order steepest descent method[J]. Front. Inform. Technol. Electron. Eng, 2020, 21(6): 809-833.
[9] Huan HU, Qing-ling WANG. Proximal policy optimization with an integral compensator for quadrotor control[J]. Front. Inform. Technol. Electron. Eng, 2020, 21(5): 777-795.
[10] Wan-ying RUAN, Hai-bin DUAN. Multi-UAV obstacle avoidance control via multi-objective social learning pigeon-inspired optimization[J]. Front. Inform. Technol. Electron. Eng, 2020, 21(5): 740-748.
[11] Ming-xin KANG, Jin-wu GAO. Design of an eco-gearshift control strategy under a logic system framework[J]. Front. Inform. Technol. Electron. Eng, 2020, 21(2): 340-350.
[12] Dai LIU, Yong-bo ZHAO, Zi-qiao YUAN, Jie-tao LI, Guo-ji CHEN. Target tracking methods based on a signal-to-noise ratio model[J]. Front. Inform. Technol. Electron. Eng, 2020, 21(12): 1804-1814.
[13] Hao ZHANG, Bin XIN, Li-hua DOU, Jie CHEN, Kaoru HIROTA. Areview of cooperative path planning of an unmanned aerial vehicle group[J]. Front. Inform. Technol. Electron. Eng, 2020, 21(12): 1671-1694.
[14] Cong-ying CAI, Xiao-lan YAO. Trajectory optimization with constraints for alpine skiers based on multi-phase nonlinear optimal control[J]. Front. Inform. Technol. Electron. Eng, 2020, 21(10): 1521-1534.
[15] Rui ZHOU, Yu FENG, Bin DI, Jiang ZHAO, Yan HU. Multi-UAVcooperative target tracking with bounded noise for connectivity preservation[J]. Front. Inform. Technol. Electron. Eng, 2020, 21(10): 1494-1503.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed