Airport Traffic Control False Target Detection From Sensor Inconsistency
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Solution Overview
Problem
Air traffic control systems at airports are compromised by false targets created by sensor errors, leading to safety issues and delays due to incorrect decision-making by controllers.
Innovation Solution
A system and method for false target detection using a computing device with a processor and memory to analyze sensor reports, determine false targets through inconsistency and machine learning models, and display them differently on a user interface to assist controllers in making informed decisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If tracking systems display all detected targets on airport maps, then complete target monitoring is achieved, but false targets created by sensor errors compromise safety and cause delays
Solution Approach 1:
The system segments targets into two distinct categories: valid targets and false targets. This is achieved by analyzing sensor reports and dividing them into consistent reports (from multiple sensors agreeing on target location) and inconsistent reports (from single sensors or conflicting sensor data). This segmentation allows the system to display only valid targets on airport maps, eliminating false targets while maintaining complete monitoring of actual targets.
Solution Approach 2:
The patent introduces an intermediary processing layer between sensor detection and target display. This intermediary consists of the computer-readable instructions that analyze sensor reports, determine consistency among multiple sensors, and filter targets before display. This intermediary processing layer acts as a mediator that prevents false targets from reaching the display while ensuring all valid targets are properly monitored and shown.
2Measurement precision
If multiple sensor reports are analyzed to determine target validity, then false target detection accuracy is improved, but processing time and computational complexity increase
Solution Approach 1:
The system performs preliminary grouping of sensor reports by target location before detailed analysis. Sensor reports are pre-organized and associated with specific target locations, and consistency is determined by comparing pre-grouped reports. This preliminary organization reduces the computational burden during actual false target detection, allowing rapid processing of multiple sensor reports without sacrificing detection accuracy.
Data Source
AI summary
Methods, devices, and systems for false target detection for airport traffic control are described herein. One device includes a user interface, a memory, and a processor configured to execute executable instructions stored in the memory to receive one or more sensor reports from one or more sensors, aggregate data that corresponds to a particular target from the one or more sensor reports, determine the particular target is a false target responsive to only one of the sensor reports including data that corresponds to the particular target, and display the particular target as a false target on the user interface responsive to determining the particular target is a false target.