Taxiway Line Vision Navigation for GNSS-Denied Aircraft Positioning
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Solution Overview
Problem
Conventional navigation systems, such as GNSS and INS, may not provide sufficient accuracy for aircraft to avoid collisions with airport infrastructure and other vehicles, especially in GNSS-denied environments.
Innovation Solution
A vision-based navigation system using an imager to measure angular orientation and position relative to line markings on a taxiway, combined with inertial data and additional aiding devices, to estimate kinematic states like position, velocity, and attitude, enabling more accurate collision avoidance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional navigation systems (GNSS and INS) are used to estimate aircraft kinematic states, then the system is simple and easy to operate, but the navigation accuracy is insufficient to enable collision avoidance
Solution Approach 1:
The patent combines multiple navigation systems (GNSS receiver, INS, and vision-based system) into an integrated navigation system. The vision-based system uses an imager to capture images of line markings on the taxiway and processes these images to determine aircraft position and orientation. This merged system fuses data from all sources to achieve high navigation accuracy for collision avoidance while maintaining operational simplicity through automated processing.
Solution Approach 2:
The patent introduces an intermediary processing system that acts as a mediator between the imager and the navigation output. This intermediary component processes images of line markings, extracts geometric features, and transforms them into navigation data (position, orientation). This intermediary layer enables the complex vision processing to be transparent to the user, maintaining ease of operation while achieving high measurement precision.
2Measurement precision
If vision-based navigation system with imager is used to measure angular orientation and position relative to line markings, then navigation accuracy is enhanced, but device complexity increases
Solution Approach 1:
The patent replaces complex mechanical measurement systems with an optical/vision-based system. Instead of using mechanical sensors to directly measure position and orientation, the system uses an imager to capture images of line markings and computationally derives navigation data. This substitution achieves high measurement precision while the complexity is managed through software-based image processing rather than complex mechanical mechanisms.
Solution Approach 2:
The patent creates a visual copy of the physical environment by capturing images of line markings on the taxiway. This optical copy is then processed to extract geometric information about the aircraft's position and orientation. By working with this visual copy rather than directly measuring physical quantities, the system achieves high precision while the complexity is contained within the image processing algorithms.
3Adaptability or versatility
If GNSS-denied environments are considered for navigation, then adaptability of the navigation system is improved, but reliability of conventional navigation systems deteriorates
Solution Approach 1:
The patent applies local quality by using vision-based navigation specifically in GNSS-denied environments (such as during taxiing on the ground near airport infrastructure) while potentially relying on GNSS/INS for other phases of flight. The vision system processes images of local line markings on the taxiway to provide reliable navigation locally where GNSS is unavailable, thus improving overall system adaptability without compromising reliability in its designated operating domain.
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AI summary
System and methods are described that illustrate how to more accurately determine at least one state variable of a vehicle using imaging of a travel way line. Imaging can be used to determine an angle between a longitudinal axis of the travel way line and a longitudinal axis of the vehicle, a shortest distance between the center axis and a reference point on or in the vehicle, and corresponding errors. The determined angle, the determined distance, and the corresponding errors can be used to more accurately determine the at least one state variable.