Vehicle Navigation Weighting for Multi-Sensor Uncertainty
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Solution Overview
Problem
Current vehicle navigation systems face challenges in accurately determining navigational parameters due to measurement errors and uncertainties, which can lead to inaccuracies in flight paths and fuel management, especially when relying on multiple data sources like sensors, GPS, and inertial reference systems.
Innovation Solution
A method that collects navigation parameters from sensors, GPS, and inertial reference systems, applies a Kalman filter to determine preliminary solutions, calculates statistical uncertainties, associates statistical weights based on these uncertainties, and blends solutions to form a navigational solution that minimizes overall uncertainty, thereby improving navigation accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If multiple data sources (sensors, GPS, inertial reference systems) are used for navigation, then the quantity of navigational data increases, but measurement errors and uncertainties increase
Solution Approach 1:
The patent combines multiple independent navigational data sources (GPS, inertial reference system, sensors) into a single integrated navigation solution. By merging these data sources and applying statistical blending based on their respective uncertainties, the system achieves a unified navigational fix that is more accurate than any individual source alone, resolving the contradiction between data quantity and measurement precision
Solution Approach 2:
The patent changes the parameter of data weighting by assigning statistical weights to each navigational parameter based on its uncertainty. This dynamic parameter adjustment allows the system to optimize the contribution of each data source according to its reliability, thereby improving overall measurement precision while utilizing multiple data sources
2Measurement precision
If statistical blending is applied to multiple navigational parameters, then navigation accuracy improves, but computational complexity increases
Solution Approach 1:
The patent implements feedback by using the calculated uncertainties to dynamically adjust the statistical weights of different navigational parameters. This feedback mechanism allows the system to automatically optimize its computational approach based on the quality of incoming data, improving navigational accuracy while managing computational complexity through adaptive rather than static processing
3Reliability
If statistical uncertainties are calculated and weights are assigned to navigation parameters, then reliability of navigational solution improves, but processing time increases
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing the statistical uncertainties associated with each navigational parameter from different sources. These pre-computed uncertainty values are then used to determine statistical weights without requiring complex real-time calculations during navigation updates, thereby improving reliability while minimizing additional processing time
Data Source
AI summary
A method of operating a vehicle includes navigating the vehicle along a path, collecting a set of navigation parameters of the vehicle from at least one of a sensor, a global positioning system, or an inertial reference system, determining a set of statistical uncertainties related to at least some navigation parameters in the set of navigation parameters, and associating a set of statistical weights to the at least some navigation parameters.