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An intelligent optimization-based satellite selection algorithm for fast precise point positioning
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DOI：10.1088/2631-8695/ae1bfc.png)
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Abstract
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To address the computational redundancy in precise point positioning (PPP) caused by the growing number of observable satellites, as well as the high computational complexity of existing satellite selection algorithms in continuous positioning scenarios, this paper proposes an intelligent optimization-based satellite selection algorithm designed for fast PPP processing to enhance receiver computational efficiency. Specifically, the joint minimization of the geometric dilution of accuracy (GDOP) and the number of selected satellites is formulated as a discrete multi-objective optimization problem and solved by using a multi-objective genetic algorithm. Furthermore, by leveraging the temporal continuity inherent in epoch-by-epoch PPP processing, a cross-epoch elite retention strategy is introduced to improve computational efficiency. Thus, the receiver processing load can be reduced, as well as the consistency in satellite observations can be ensured. Experimental results demonstrate that the proposed algorithm can significantly reduce the computational complexity and accelerate convergence while maintaining positioning accuracy in PPP.
Keywords:
satellite selection
PPP
intelligent optimization algorithm
prediction
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