Satellite Selection with Multi-Objective Genetic Algorithm for Multi-GNSS Constellations

doi:10.16183/j.cnki.jsjtu.2017.12.016

Abstract

Abstract: With the development of multi-global navigation satellite system (GNSS) constellations, more and more satellites will be available. To ensure the accuracy of positioning, we have to select optimal satellites to improve the real-time performance of the receiver. In this paper, we firstly consider that satellite selection of multi-GNSS constellation can be used as a discrete multi-objective optimization problem with constraint conditions, and a new method based on non-dominated sorting genetic algorithm (NSGA)-II is proposed. This method can comprehensively optimize the geometric dilution of precision (GDOP) and the number of selected satellites at the same time. We can obtain good positioning accuracy while reducing the amount of computation of the receiver. The simulation results show that the proposed method is effective in both static and dynamic conditions with good real-time capabilities.

Key words: satellite selection, multi-objective optimization, non-dominated sorting genetic algorithm (NSGA)-II, geometric dilution of precision (GDOP), multi-global navigation satellite system (GNSS) constellation

CLC Number:

P 228.1

XU Xiaojun1,2，MA Lihua1，AI Guoxiang1. Satellite Selection with Multi-Objective Genetic Algorithm for Multi-GNSS Constellations[J]. Journal of Shanghai Jiaotong University, 2017, 51(12): 1520-1528.

References

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