A slope-based fast satellite selection algorithm for multi-constellation RAIM

The gradual improvement of global navigation satellite systems in recent decades and their combination greatly increase the visible satellite number for positioning and integrity monitoring process. This enhances the positioning accuracy and availability of the navigation system but at the cost of the large growth in computation load and function failure rate. Satellite selection is a useful way to relieve the side effect of superabundant measurements in use and has been developed for geometric dilution of precision (GDOP) optimization, but it has scarcely been studied in the integrity monitoring field. This paper proposes a slope-based fast satellite selection algorithm with the motivation to optimize the horizontal protection level (HPL) of subset while maintaining an acceptable positioning accuracy. The basis of this algorithm is a cost function which illustrates the relationship between satellite geometry and the slope effect. While the principle is to find the max slope satellite in the subset and introduce a new satellite which can significantly reduce the max slope by the cost function so the HPL decreases. Comparison simulations show the effectiveness of the proposed algorithm in HPL reduction, positioning accuracy maintenance and computation load mitigation, which means it is more suitable for real-time multi-constellation navigation applications.