An Enhanced Multi-GNSS Navigation Algorithm by Utilising a Priori Inter-System Biases

Abstract

The integration of multi-constellation Global Navigation Satellite System (GNSS) measurements can effectively improve the accuracy and reliability of navigation and positioning solutions, while the Inter-System Bias (ISB) is a key issue for compatibility. The ISB is traditionally estimated as an unknown parameter along with three-dimensional position coordinates and a receiver clock offset with respect to Global Positioning System (GPS) time. ISB estimation of this sort will sacrifice a satellite observation for each integrated GNSS system. These sacrificed observations could be vital in situations of limited satellite visibility. In this study, an enhanced multi-GNSS navigation algorithm is developed to avoid sacrificing observations under poor visibility conditions. The main idea of this algorithm is to employ a moving average filter to smooth the ISBs estimated at previous epochs. The filtered value is utilised as a priori information at the current epoch. Experimental tests were conducted to evaluate the enhanced algorithm under open and blocked sky conditions. The results show that the enhanced algorithm effectively improves the accuracy and availability of navigation solutions under the blocked sky condition, with performance being comparable to traditional ISB estimation algorithms in open sky conditions. The improvement rates of the three-dimensional position accuracy and availability reach up to 63% and 21% in the blocked sky environment. Even in the case of only four different GNSS satellites, a position solution can still be obtained using the enhanced algorithm.