### An autonomous integrity monitoring method of integrated navigation based on multiple virtual observations #br# #br#

WU Kongyang, YE Xiaozhou, XIAO Wei, LIU Wenxiang, LIU Xiaohui*

1. National University of Defense Technology, Changsha 410073, China
• Received:2020-07-24 Revised:2020-08-27 Accepted:2020-09-12 Online:2021-06-25 Published:2021-06-25
• Contact: 刘小汇：lululiu@sina.com E-mail:lululiu@sina.com
• About author:吴孔阳（1995-），男，硕士，研究方向为卫星导航信息处理，nav_wky@163.com。 刘小汇（1976-），女，研究员，研究方向为卫星导航信号处理，lululiu@sina.com。
• Supported by:
国家自然科学基金（41604016）

Abstract: Integrity can provide timely warning in the event of a navigation system failure, which is an important performance indicator for users to consider life safety. This paper is based on the autonomous integrity monitoring algorithm of satellite navigation assisted by the inertial navigation system (INS). An autonomous integrity monitoring method for integrated navigation system was proposed. This method uses INS to construct three-virtual-satellite observations, and can realize fault detection under the condition of two visible satellites by constructing three satellites perpendicular to each other in the line-of-sight direction and using the navigation information of INS to the maximum extent. This improves the availability of detection algorithm compared with the traditional receiver autonomous integrity monitoring (RAIM). The fault detection probability of traditional weighted RAIM is 48.51% under the condition of GPS single constellation and INS positioning error variance σs=1m with the addition of 35m fault of single satellite. The detection probability of the algorithm proposed in this paper is 95.21%, and the detection performance is improved by 47%. This method also has a higher detection probability than the INS-aided Kalman filtering innovation method with the same INS accuracy. In addition, the influence of INS precision on the fault detection performance of this method was simulated and analyzed. The results show that the higher the INS precision is, the better the detection performance of the proposed method is.

CLC Number: