Machine learning ensemble models predict GNSS signal quality scores from indicators; activation functions convert scores to weights for WLS positioning, yielding error reductions and geographical transferability on Hong Kong and Tokyo urban datasets.
Reliable Urban Canyon Navigation Solution in GPS and GLONASS Integrated Receiver Using Improved Fuzzy Weighted Least-Square Method
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A Machine Learning Framework for Weighted Least Squares GNSS Positioning based on Activation Functions
Machine learning ensemble models predict GNSS signal quality scores from indicators; activation functions convert scores to weights for WLS positioning, yielding error reductions and geographical transferability on Hong Kong and Tokyo urban datasets.