GNSS Tracker Positioning from Intermittent Movement Measurements
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Solution Overview
Problem
Existing low-energy consumption GNSS trackers face challenges in achieving precise location determination, especially when moving, as current post-processing methods assume static positions and do not account for varying movement patterns.
Innovation Solution
A method and device that partition GNSS measurements into subsequences based on statistical data analysis, using geometric medians or means, to determine starting and ending positions of the tracker, while maintaining low energy consumption by intermittent measurement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If GNSS measurements are taken intermittently to save energy, then energy consumption is reduced, but location precision deteriorates
Solution Approach 1:
The patent applies preliminary action by performing statistical preprocessing on GNSS measurements before final position determination. The server computes statistical data (mean, covariance) from multiple intermittent measurements in advance, creating a processed dataset that maintains precision while enabling energy-efficient intermittent sampling. This preprocessing step allows the system to achieve accurate location determination without requiring continuous high-power measurements.
Solution Approach 2:
The patent introduces statistical data (mean and covariance matrices) as intermediaries between raw GNSS measurements and final position determination. These statistical parameters serve as mediators that capture the essential spatial information from intermittent measurements, allowing the system to reconstruct accurate position estimates without processing every individual measurement at full power. The statistical intermediaries enable precise location determination from limited intermittent data.
2Device complexity
If post-processing methods assume static tracker position, then computational complexity is reduced, but location precision deteriorates when tracker moves
Solution Approach 1:
The patent applies dynamics by transitioning from static position assumptions to dynamic position estimation. The method uses statistical data from multiple measurements to compute position and velocity estimates that adapt to tracker movement. By modeling the tracker as a dynamic object with changing position over time, the system maintains computational efficiency while accurately tracking moving targets, resolving the contradiction between simple static models and complex dynamic reality.
Data Source
AI summary
A method for a sequence of geographic location measurements of a tracer. The method includes: obtaining the sequence, ordered as a function of time of measurement; for an indexed measurement of the sequence, partitioning all the measurements in two ordered sets, the indexed measurement being either the last measurement of the first set or the first measurement of the second set; calculating statistical data for the first and second sets; calculating a distance between the sets as a function of a distance between the statistical data of the sets; determining a maximum distance among the distances for the set; the statistical datum of the first set defined for the indexed measurement associated with the maximum difference corresponding to a first position of the tracer and the statistical datum of the second set defined for the indexed measurement associated with the maximum distance corresponding to a second position of the tracer.