Stepwise fusion algorithm with dual correction for multi-sensor navigation. (8th June 2018)

• Record Type: Journal Article
• Authors: Wang, Rong; Xiong, Zhi; Liu, Jianye; Cao, Yuxuan
• Is Part Of: International journal of advanced robotic systems. Volume 15:Number 3(2018:May/Jun.)
• Publication Date: 2018-06-08
• Subjects: Multi-sensor navigation -- information fusion -- stepwise fusion -- dual correction -- celestial attitude determination system (CADS) -- high-altitude -- long-endurance unmanned aerial vehicle (HALE-UAV); Robotics -- Periodicals; Robotics; Periodicals; 629.892
• DOI: 10.1177/1729881418779931
• Languages: English
• ISSNs: 1729-8806

Abstract

In high-altitude, long-endurance unmanned aerial vehicles, a celestial attitude determination system is used to enhance the inertial navigation system (INS)/global positioning system (GPS) to achieve the required attitude performance. The traditional federal filter is not applicable for INS/GPS/celestial attitude determination system information fusion because it does not consider the mutually coupled relationship between the horizontal reference error in the celestial attitude determination system and the navigation error; this limitation results in reduced navigation accuracy. This article proposes a novel stepwise fusion algorithm with dual correction for multi-sensor navigation. Considering the horizontal reference error, the celestial attitude determination system measurement model is constructed and the issues involved in applying the federal filter are discussed. Then, preliminary error estimation and horizontal reference compensation are added to the navigation architecture. In addition, a sequential update strategy is derived to estimate the attitude error with the compensated celestial attitude determination system based on the preliminary estimation. A stepwise correction filtering algorithm with interactive preliminary and sequential updates that can effectively fuse celestial attitude determination system measurements with the INS/GPS is constructed. High-altitude, long-endurance unmanned aerial vehicle navigation in a remote sensing task is simulated to verify the performance of the proposed method. The simulation results demonstrate that the horizontal reference error is effectively compensated, and the attitude accuracy is significantly improved after stepwise error estimation and correction. The proposed method also provides a novel multi-sensor integrated navigation architecture with mutually coupled errors; this architecture is beneficial in unmanned aerial vehicle navigation applications.