Aircraft Flight Information Display for Uncertain Hazard Intersections
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Solution Overview
Problem
Current Detect and Avoid (DAA) systems for aircraft struggle with real-time processing of position and velocity uncertainties, leading to inaccurate and delayed situational awareness, particularly in dynamic airspace conditions, resulting in higher false alarm rates and unnecessary aircraft maneuvering.
Innovation Solution
The aircraft flight information system determines a set of bounding relative position vectors and velocity vectors to generate Apollonius circles or spheres, which define candidate intersection points and speed ratios, allowing for efficient identification of regions of interest and timely situational awareness displays, even with uncertainties in aircraft and navigation hazard positions and velocities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional DAA systems process position and velocity data in real-time, then situational awareness is provided to pilots, but processing delays and inaccuracies occur due to uncertainty calculations
Solution Approach 1:
The system pre-calculates and stores bounding relative position vectors and speed ratios in lookup tables before flight operations. During real-time operation, the processor simply retrieves pre-computed values based on current position and velocity measurements, eliminating complex uncertainty calculations from the critical path and reducing processing delays while maintaining accuracy
Solution Approach 2:
The patent divides the uncertainty analysis into separate pre-processing and real-time phases. The computationally intensive bounding vector calculations are segmented from the time-critical situational awareness display generation, allowing each to be optimized independently for accuracy and speed respectively
2Reliability
If DAA systems evaluate all possible flight paths to detect navigation hazards, then detection accuracy improves, but false alarm rates increase due to dynamic airspace changes
Solution Approach 1:
The system focuses computational resources on calculating bounding relative position vectors and speed ratios only for the specific region of interest between the aircraft and detected navigation hazards, rather than evaluating all possible flight paths globally. This localized approach maintains detection accuracy for relevant hazards while reducing false alarms from irrelevant airspace evaluations
Solution Approach 2:
The patent transforms the hazard detection problem by changing parameters from evaluating complete flight paths to using bounding relative position vectors and speed ratios. This parameter transformation simplifies the detection criterion, improving reliability by focusing on critical geometric relationships that truly indicate potential hazards while reducing false alarms from minor trajectory variations
3Measurement precision
If comprehensive uncertainty analysis is performed for aircraft and hazard positions, then situational awareness accuracy improves, but computational resources are excessively consumed
Solution Approach 1:
Bounding relative position vectors and speed ratios are pre-calculated and stored in lookup tables based on uncertainty analysis, eliminating the need for complex real-time uncertainty computations. The processor only performs simple table lookups during flight operations, maintaining measurement precision while dramatically reducing processing complexity
Solution Approach 2:
The patent creates simplified copies of the uncertainty analysis results in the form of pre-computed bounding vectors and speed ratios. These copies capture the essential uncertainty information without requiring the full computational complexity of the original uncertainty models, enabling accurate situational awareness with minimal processing resources
Data Source
AI summary
A method includes determining data indicating velocity uncertainty, relative position uncertainty, or both, associated with an aircraft and a navigation hazard. The method also includes determining a set of bounding vectors based on the data and determining a plurality of candidate intersection points that together correspond to circular or spherical regions defined by the set of bounding vectors. The method also includes identifying a region of interest based on a projected intersection of the aircraft or the navigation hazard with a candidate intersection point and generating a situational awareness display based on the region of interest.