A new recursive satellite selection method for multi-constellation GNSS. Issue 373 (3rd July 2020)

• Record Type: Journal Article
• Authors: Abedi, A. A.; Mosavi, M. R.; Mohammadi, K.
• Is Part Of: Survey review. Volume 52:Issue 373(2020)
• Page Start: 330
• Page End: 340
• Publication Date: 2020-07-03
• Subjects: GPS -- GLONASS -- Galileo -- Beidou -- Constellation -- GDOP -- Complexity; Surveying -- Periodicals; Great Britain -- Surveys -- Periodicals; 526.9
• DOI: 10.1080/00396265.2019.1574113
• Languages: English
• ISSNs: 0039-6265

Abstract

Abstract : Development of navigation satellites systems as GPS, GLONASS, Galileo and Beidou has increased the accuracy and reliability. On the other hand, by employing more satellites, the receivers' computational load increases, and their power consumption rises. Therefore, the selection of optimum satellites from the visible satellites can provide good accuracy. At the same time, the computational burden does not increase significantly. A new algorithm for optimal satellite selection is proposed in this paper. This algorithm is based on a down-top recursive that initial combination of satellites is obtained in a simple method, and then a satellite from the remaining satellites with a special GDOP-based metric is added to this subset. In the next step, a satellite is removed from this new combination with another specific criterion. The process of increasing and decreasing the number of satellites will continue for a certain number of repetitions, and eventually the optimal combination of satellites is achieved. The computational load of this method has been decreased by two factors. One is the reduction of the number of repetitive loops to achieve an optimal subset, and the other is the selection of initial combination with fewer satellites. This method in some cases improves accuracy compared to previous methods. This new approach is evaluated via collected data from four stations. The results indicate that this new algorithm can reduce the number of multiplication and addition operations more than Top-Down recursive method by 20% and 56%, respectively.