Aircraft Heading Estimation with Incremental ALS Feature Updates
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Solution Overview
Problem
Aircraft struggle to accurately estimate heading in low visibility conditions due to insufficient detection of approach lighting system (ALS) lights or known objects, leading to increased risk of heading errors during landing.
Innovation Solution
An aircraft heading estimation system using sensors to detect features, compare with expected patterns, and incrementally update heading estimates as resolution improves, combining long-range sensors with image processing to enhance accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Length of stationary object
If long-range sensors are used to detect features in low visibility conditions, then the detection range is improved, but the measurement precision of heading estimation deteriorates
Solution Approach 1:
The system initiates heading estimation early in the approach using long-range sensor data, even when visibility is poor and features are distant. By starting the estimation process beforehand and continuously refining it as the aircraft approaches, the system overcomes the limitation of low precision at long ranges.
Solution Approach 2:
The system incrementally updates the heading estimation by comparing newly detected features with expected features and refining the estimate based on the difference. This feedback loop allows continuous improvement of heading accuracy as more features are detected and as the aircraft gets closer to the airport.
2Measurement precision
If high resolution sensors are used to detect features, then the measurement precision is improved, but the detection range deteriorates
Solution Approach 1:
The system uses long-range sensors to initiate heading estimation early in the approach, accepting lower resolution at long distances. As the aircraft approaches and resolution improves, the system refines the heading estimate, combining the benefits of early detection with later precision.
Solution Approach 2:
The system dynamically adapts its operation based on the aircraft's distance from the airport and current visibility conditions. It transitions from using long-range detection capabilities to relying more on high-resolution feature detection as the aircraft approaches, optimizing the balance between range and precision throughout the approach.
3Reliability
If multiple verification procedures are implemented to improve heading accuracy, then the reliability is improved, but the device complexity increases
Solution Approach 1:
The system employs a feedback mechanism where detected features are compared with expected features, and the heading estimation is incrementally updated based on the comparison results. This continuous refinement process provides multiple verifications of the heading estimate without requiring complex additional hardware or procedures.
Data Source
Figure 1~2
AI summary
An aircraft heading estimation system comprising: one or more sensors arranged on the aircraft to detect features in a viewing region and provide feature signals indicative of the detected features; an image processor storing predetermined image information of one or more expected features, being features that might be expected to be present in the viewing region, the image processor configured to compare the features indicated by the feature signals with the one or more expected features to generate an estimated observed image and to derive an estimated heading for the aircraft based on the estimate observed image; wherein the image processor is further configured to incrementally update the estimated observed image with new feature signals generated by the sensors as their distance to the viewing region changes, and to incrementally updated the estimated heading based on the updated estimate observed image.