Dynamic Kalman Filter Error Adjustment for GPS Positioning
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Solution Overview
Problem
Existing GPS positioning systems using Kalman filters face accuracy issues due to incorrect measurement errors, leading to position jumps or delays, as they typically set measurement errors to fixed values, deviating from true values.
Innovation Solution
A method that dynamically adjusts measurement errors in Kalman filter processing based on signal strength and suitability determination conditions for each satellite signal, setting errors to larger values when observed values are unsuitable, improving positioning accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If measurement error is set to a fixed value in Kalman filter processing, then the positioning device can perform correction processing, but the measurement error deviates from the true value causing position jump or position delay
Solution Approach 1:
The patent applies dynamics by transitioning from a fixed measurement error value to a dynamically adjustable measurement error value that changes based on satellite signal conditions. The measurement error is adjusted according to signal strength and suitability determination conditions for each satellite, allowing the system to adapt to varying environmental conditions and maintain positioning accuracy.
Solution Approach 2:
The patent implements parameter changes by modifying the measurement error parameter based on satellite signal characteristics. The system changes the measurement error value according to signal strength metrics and suitability conditions, transforming a static parameter into a dynamic one that reflects actual signal quality and improves positioning precision.
2Measurement precision
If measurement error is set to a larger value for unsuitable satellites, then positioning accuracy improves, but the calculation complexity increases
Solution Approach 1:
The patent applies local quality by setting different measurement error values for different satellites based on their individual signal conditions. Each satellite's measurement error is determined locally according to its specific signal strength and suitability characteristics, rather than using a uniform value for all satellites. This allows precise error correction for each satellite while maintaining overall system efficiency.
Solution Approach 2:
The patent implements segmentation by dividing the satellite constellation into groups based on signal suitability conditions. Satellites are evaluated individually or in groups, and measurement errors are set separately for each satellite or group based on their specific conditions. This segmented approach simplifies the complexity by processing satellites in manageable units rather than requiring complex simultaneous processing of all satellites.
Data Source
AI summary
A positioning method includes: determining a receiving environment of a satellite signal from a positioning satellite; predicting a state vector including a position of a positioning device and a velocity of the positioning device based on the satellite signal; predicting a first distance-equivalent value indicating a distance between the positioning satellite and the positioning device; measuring a second distance-equivalent value indicating a distance between the positioning satellite and the positioning device; calculating an observed value indicating a difference between the first distance-equivalent value and the second distance-equivalent value; setting a first measurement error for the positioning satellite based on a signal strength of the satellite signal; setting a suitability condition of the observed value based on the receiving environment; setting a second measurement error larger than the first measurement error when the observed value is not suitable by the suitability condition; and correcting the state vector using the observed value and the second measurement error.