Aircraft Docking Sensor Fusion for Curved and All-Weather Tracking
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Solution Overview
Problem
Current aircraft docking systems face challenges such as accuracy issues in curved approaches, limited range detection, difficulty in detecting dark-colored aircraft, and performance in adverse weather conditions, leading to failed dockings and increased turnaround times.
Innovation Solution
The proposed system combines camera image sensors and LIDAR/Radar sensors with data fusion processes to create a robust, 3D model-based aircraft detection and tracking system. This system provides long-range detection, accurate guidance, and operates effectively in all weather conditions, enabling precise aircraft positioning and orientation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional laser/LIDAR systems are used for aircraft detection and tracking, then long-range detection capability is provided, but accuracy deteriorates in curved approaches, dark colored aircraft detection, and adverse weather conditions
Solution Approach 1:
The patent combines multiple sensor types (cameras, LIDAR, radar) into a multi-sensor system that merges their respective strengths. Cameras provide good performance in curved approaches and adverse weather, LIDAR provides accurate distance measurements, and radar provides all-weather capability. The fusion of these sensor data streams resolves the contradiction by compensating for individual sensor weaknesses.
Solution Approach 2:
The system dynamically adjusts sensor parameters and fusion weights based on operating conditions. For example, in adverse weather conditions, the system increases reliance on radar and camera data while reducing dependence on LIDAR. This adaptive parameter adjustment maintains detection accuracy across varying environmental conditions.
2Ease of operation
If camera systems are used for aircraft tracking, then visual guidance is provided, but accuracy deteriorates in distance measurements and calibration becomes complex
Solution Approach 1:
The patent introduces LIDAR and radar sensors as intermediary measurement devices that provide accurate distance and position data. These intermediaries complement the camera system's visual guidance capability by supplying precise metric information that cameras alone cannot provide, thereby resolving the measurement accuracy limitation.
Solution Approach 2:
The system replaces complex manual calibration procedures with automated calibration algorithms that use data from multiple sensors. The fusion of data from cameras, LIDAR, and radar enables automatic determination of sensor parameters and geometric relationships, eliminating the need for precise manual calibration while maintaining measurement accuracy.
3Adaptability or versatility
If manual approaches are used for aircraft docking guidance, then flexibility is maintained, but error rate increases and consistency deteriorates
Solution Approach 1:
The automated docking guidance system performs self-calibration and self-adjustment based on real-time sensor data. The system automatically compensates for environmental conditions, sensor variations, and aircraft characteristics without requiring manual intervention, thereby maintaining operational flexibility while significantly improving reliability and consistency.
Solution Approach 2:
The system implements continuous feedback loops where sensor data from cameras, LIDAR, and radar are constantly monitored and used to adjust guidance commands. This real-time feedback mechanism enables the system to maintain high accuracy and consistency across different operations while adapting to changing conditions, resolving the contradiction between flexibility and reliability.
4Ease of operation
If early DGS with mirrors were used, then visual guidance was provided, but pilot distraction occurred and effectiveness deteriorated
Solution Approach 1:
The patent replaces mirror-based visual guidance systems with electronic display systems that present guidance information on screens within the pilot's field of view. This substitution eliminates the need for physical mirrors that caused distraction, while maintaining visual guidance functionality through digital overlays and augmented reality displays.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system achieves improved accuracy and reliability in aircraft docking, reduces turnaround times, and enhances safety by providing real-time guidance and obstacle detection, even in adverse weather conditions.
Implementation Method 1
receiving LIDAR/Radar sensor data of the aircraft
Implementation Method 2
laser to track an aircraft's movement on the ground
Implementation Method 3
receiving LIDAR/Radar sensor data of the aircraft
Implementation Method 4
receiving camera image data of the aircraft
Implementation Method 5
camera image sensors and LIDAR/Radar sensors
Data Source
AI summary
Tracking aircraft in and near a ramp area is described herein. One system for tracking an aircraft, comprising: a sensor array, positioned at or near a ramp area at an airport, having a camera image sensor device and a light detection and ranging (LIDAR) sensor device that are both located at a single sensor array location with respect to the ramp area; the camera image sensor device configured to capture camera image data illustrating the aircraft while the aircraft is approaching or in the ramp area; the LIDAR sensor device configured to capture LIDAR sensor device data illustrating the aircraft while the aircraft is approaching or in the ramp area.