Position-grid based machine learning for GNSS warm-start position accuracy improvement
Abstract:
Aspects presented herein may improve the performance and accuracy of GNSS-based positioning, where a position-grid based ML may be implemented by a UE or a location server to improve the accuracy of identifying a warm-start position of the UE. In one aspect, a UE or a location server determines, for each grid point within a range of an initial position of a UE, a set of PR residuals based on PRs for each SV of a set of SVs. The UE or the location server determines an estimated position of the UE based on the sets of determined PR residuals.
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