Fast and Effective Satellites Selection Algorithm for Multi-Constellation GNSS Receiver Based on Incremental Greedy Approach

The combined utilization of signals from multiple constellations has become a prevailing trend in the advancement of GNSS. This paper addresses the problem of accuracy and the computational complexity for Multi-Constellation GNSS receiver. This problem is rather crucial for applications just like most of real time and SOC GNSS receiver due to the limited recourses regarding the huge number of visible and available GNSS satellites for the navigation filter algorithms. Where the traditional existed receivers either use all the available observations to estimate the user position or set some simple rules regarding some metrics or elevation angle mask, many studies analyze the optimization process and suggest smart selection algorithms. However, these methods are still costly and were not tested on real data. The method proposed in this article can reduce computational time up to 4.2 times compared to state-of-the-art algorithms at a cost of additional 6% position estimation error, as the experimental results show.