Navigation Error Correction via Residual Threshold Counting
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Solution Overview
Problem
Existing navigation systems face inaccuracies due to sensor uncertainties and processing errors, with current error correction methods either being computationally intensive or limited by the need for specific knowledge about error types, and often discard measurements based solely on error count rather than residual significance.
Innovation Solution
A method that computes error thresholds based on measurement uncertainties, analyzes redundancy, determines residuals, and increments an error count for discrepancies exceeding thresholds, allowing for the selection of measurements for fusion filter correction values, considering both error count and summed residuals to improve measurement selection for error correction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If stochastic measurement error detection methods are used to improve measurement accuracy, then measurement precision is improved, but computational effort becomes too high and long observation times are necessary
Solution Approach 1:
The patent changes the parameters of error detection by using a simplified statistical approach that counts the number of times a measurement exceeds error thresholds rather than performing complex stochastic analysis. This transforms the problem from high-computational stochastic methods to a simpler counting mechanism that achieves similar error detection goals with much lower computational effort.
Solution Approach 2:
Instead of performing complete stochastic analysis on all measurements, the patent applies partial action by only identifying and counting measurements that exceed predefined error thresholds. This selective approach focuses computational resources only on potentially erroneous measurements rather than analyzing all measurement data comprehensively.
2Productivity
If physical-model-based error detection methods are used to reduce computational effort, then processing speed is improved, but the methods require specific knowledge about error types and have limited versatility
Solution Approach 1:
The patent creates a universal error detection mechanism that works across different measurement types and error conditions. By using generic error thresholds and counting mechanisms that can be applied to any measurement, the system achieves versatility without requiring specific physical models for each error type, thus maintaining both processing speed and adaptability.
Solution Approach 2:
The patent segments the error detection process into distinct steps: defining error thresholds, comparing measurements against thresholds, counting exceedances, and evaluating accumulated counts. This segmentation allows the same framework to handle different measurement types and error conditions without requiring complete redesign, enhancing versatility while maintaining efficiency.
3Reliability
If measurements are discarded based solely on error count to improve reliability, then error correction quality is improved, but helpful measurements may be incorrectly discarded
Solution Approach 1:
The patent implements feedback by continuously monitoring the accumulated error counts and using this information to dynamically adjust which measurements are used for correction. The system feeds back the error count information to the measurement selection process, allowing it to reliably identify and discard erroneous measurements while preserving useful ones based on their error history.
Solution Approach 2:
The patent performs preliminary error threshold definition and measurement comparison before final correction decisions are made. By预先 establishing error thresholds and accumulating error counts in advance, the system can make informed decisions about which measurements to discard, reducing the risk of incorrectly discarding helpful measurements while maintaining correction reliability.
4Measurement precision
If reference measurements are used to correct base system errors to improve navigation accuracy, then position and velocity accuracy is improved, but the system becomes more complex and reference measurements may not always be available
Solution Approach 1:
The patent extracts the essential error correction function from the complex reference measurement system and implements a simplified correction mechanism. By separating the error detection and correction logic from the full reference measurement processing, the system achieves navigation accuracy improvement without proportionally increasing system complexity.
Solution Approach 2:
The patent implements dynamic measurement selection where the system adaptively chooses which reference measurements to use based on their error counts and quality. This dynamic approach allows the system to maintain high navigation accuracy when good reference measurements are available while gracefully degrading to use only base system measurements when reference measurements are unavailable or erroneous, without requiring complex system architecture changes.
Data Source
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AI summary
The invention regards a navigation system and a method for error correction. The navigation system comprises a base navigation system and a correction system. Measurement uncertainties are assigned to each measurement and an error threshold is computed on the basis of these uncertainties. Redundant measurements are determined and residuals for at least a pair of redundant measurements as a discrepancy measure are calculated. In case that the residual exceeds a respective threshold an error count for each measurement involved in the determination of the residual is increased. All residuals for each measurement are summed up for a particular measurement and for carrying out the correction in a fusion filter measurements are selected on the basis of their respective error count and summed up residuals.