An autonomous celestial navigation method for LEO satellite based on unscented Kalman filter and information fusion

被引：67

作者：

Ning, Xiaolin ^{[1
]}

Fang, Jiancheng ^{[1
]}

机构：

[1] Beijing Univ Aeronaut & Astronaut, Sch Instrumentat Sci & Optoelect Engn, Beijing 100083, Peoples R China

来源：

AEROSPACE SCIENCE AND TECHNOLOGY | 2007年 / 11卷 / 2-3期

关键词：

autonomous navigation; celestial navigation; satellite; information fusion;

D O I：

10.1016/j.ast.2006.12.003

中图分类号：

V [航空、航天];

学科分类号：

08 ; 0825 ;

摘要：

A reliable and secure navigation system and assured autonomous capability of satellite are in high demand in case of emergencies in space. Celestial navigation is a fully autonomous navigation method for satellite. To near earth satellite, the earth direction is the most important measurement and the horizon sensing accuracy is the most important factor which effects celestial navigation accuracy. According to the mode of acquiring horizon measurement, satellite celestial navigation methods can be broadly classified into two approaches: directly sensing horizon using earth sensor and indirectly sensing horizon by observation of starlight atmospheric refraction. For these two methods are complementary to each other, a new Unscented Kalman Filter (UKF) based information fusion method is proposed here for hybriding them. Compared to the traditional celestial navigation method, this method can provide better navigation performance and higher reliability. The hardware-in-loop test results demonstrate the feasibility and effectiveness of this method, in most cases the accuracy is sufficient for near earth civilian satellite and moreover it can be used as a backup system to provide redundancy. (c) 2007 Elsevier Masson SAS. All rights reserved.

引用

页码：222 / 228

页数：7

共 50 条

[41] GPS/DR navigation data fusion method based on Kalman filter
School of Transportation, Jilin University, Changchun 130025, Jilin, China
J. Traffic Transp. Eng., 2006, 2 (65-69):
[42] Federated Filter Based on Dynamic Information Allocation with Unscented Kalman Filter
Jue, Huang
Bin, Yan
PROCEEDINGS OF THE 2015 2ND INTERNATIONAL CONFERENCE ON ELECTRICAL, COMPUTER ENGINEERING AND ELECTRONICS (ICECEE 2015), 2015, 24 : 911 - 916
[43] An Improved Unscented Kalman Filter for Satellite Tracking
Zhu, Zhenyu
Wu, Qiong
Gao, Kun
Zhuang, Youwen
Wang, Jing
Wang, Guangping
OPTICAL SENSING AND IMAGING TECHNOLOGIES AND APPLICATIONS, 2018, 10846
[44] Robust Unscented Kalman Filter-Based Decentralized Multisensor Information Fusion for INS/GNSS/CNS Integration in Hypersonic Vehicle Navigation
Hu, Gaoge
Xu, Linyan
Gao, Bingbing
Chang, Lubin
Zhong, Yongmin
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2023, 72
[45] Unscented Kalman filter-based method for spacecraft navigation using resident space objects
Driedger M.
Rososhansky M.
Ferguson P.
Aerospace Systems, 2020, 3 (3) : 197 - 205
[46] The fault-detection method of a navigation system based on a strong tracking unscented kalman filter
Cui N.
Han P.
Mu R.
Harbin Gongcheng Daxue Xuebao/Journal of Harbin Engineering University, 2011, 32 (10): : 1295 - 1299
[47] GPS/SINS navigation data fusion using quaternion model and unscented Kalman filter
Gul, Farid
Fang Jiancheng
Gaho, Anwar Ali
IEEE ICMA 2006: PROCEEDING OF THE 2006 IEEE INTERNATIONAL CONFERENCE ON MECHATRONICS AND AUTOMATION, VOLS 1-3, PROCEEDINGS, 2006, : 1854 - +
[48] Information Fusion for State Estimation of Power Battery in Electric Vehicle Based on Unscented Kalman Filter
Zheng, Hongyu
Zong, Changfu
SENSORS, MEASUREMENT AND INTELLIGENT MATERIALS, PTS 1-4, 2013, 303-306 : 975 - 978
[49] Attitude information fusion method based on extended kalman filter
Lu Y.
Chen Y.
Zhang X.
Zhang T.
Yi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument, 2020, 41 (09): : 281 - 288
[50] Adaptive unscented Kalman filter based on sequential state difference for spacecraft autonomous navigation during the approach phase
Zhang, Wenjia
Ma, Xin
Wang, Shuting
Cui, Peiling
Ning, Xiaolin
MEASUREMENT, 2025, 243

← 1 2 3 4 5 →