Automated Go-Around Maneuver Detection System
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Solution Overview
Problem
Current methods for detecting a go-around maneuver in aircraft rely on human analysis of data from sources like ground-based radar and ADS-B, leading to delays and potential missed detections due to human error and distraction.
Innovation Solution
A computer system that analyzes in-flight surveillance information, such as speed and altitude data, to automatically detect go-around maneuvers by identifying specific patterns indicative of the maneuver, enabling immediate action by air traffic controllers and other stakeholders.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If human analysis is used to detect go-around maneuvers, then the system can interpret complex flight patterns, but detection speed decreases and errors increase
Solution Approach 1:
The patent replaces human manual analysis with an automated computer system that processes flight data automatically. The system uses algorithms to detect go-around maneuvers by analyzing patterns in speed, altitude, and other flight parameters, eliminating human reaction time and subjectivity while maintaining high detection accuracy.
Solution Approach 2:
The system monitors and detects maneuvers autonomously without requiring human intervention during the detection process. The computer system continuously analyzes flight data, identifies patterns indicative of go-around maneuvers, and triggers alerts automatically, allowing the system to serve itself in real-time.
2Productivity
If automated detection systems are implemented, then detection speed increases, but system complexity increases
Solution Approach 1:
The detection system is divided into separate functional modules: data collection module (gathering flight information from multiple sources), analysis module (processing data to identify maneuver patterns), and alert module (triggering notifications). This segmentation allows each component to be optimized independently while working together to achieve high-speed automated detection.
Solution Approach 2:
The system is designed to detect multiple types of flight maneuvers and anomalies using a unified approach. The same algorithmic framework can identify go-around maneuvers, abnormal descents, and other flight pattern deviations, making the system versatile without requiring separate specialized systems for each detection task.
3Reliability
If multiple data sources are integrated, then detection reliability improves, but information processing complexity increases
Solution Approach 1:
The system merges data from multiple sources including ground-based radar, ADS-B, and other surveillance systems into a unified data stream. By combining these data sources and processing them through a single analytical framework, the system achieves higher reliability through cross-validation while managing complexity through integrated processing rather than separate analysis pipelines.
Data Source
AI summary
Aspects of the present disclosure provide systems and methods for in-flight go-around maneuver detection. An example method includes monitoring information associated with a flight path of a first aircraft while the first aircraft is flying. The method further includes detecting a maneuver associated with the flight path in response to one or more criteria associated with the monitored information being satisfied. The method further includes performing one or more actions associated with the second aircraft in response to detecting the maneuver.