3D LIDAR Aircraft Docking Guidance for Curved Centerline Tracking
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Solution Overview
Problem
Conventional aircraft docking guidance systems face limitations due to fixed fields of view, weather interference, visibility issues, and difficulty in tracking aircraft around curved centerlines, leading to inaccurate positioning and potential delays.
Innovation Solution
A system combining three-dimensional LIDAR data with machine learning to simulate a complete aircraft model, providing navigation guidance through a two-dimensional image, capable of tracking aircraft in various weather conditions and curved paths.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional docking guidance systems use fixed field of view sensors, then the system structure is simple, but the system cannot track aircraft around curved centerlines and has limited adaptability
Solution Approach 1:
The system transitions from fixed field of view sensors to dynamic 360-degree LIDAR sensors that can rotate and scan the entire docking area. This allows the system to adapt to aircraft moving along curved centerlines and provides comprehensive spatial coverage, resolving the contradiction between tracking capability and system complexity.
Solution Approach 2:
The system employs 360-degree horizontal scanning and vertical angle scanning capabilities, adding rotational and angular dimensions to the sensing system. This multi-dimensional approach enables complete coverage of the docking area and accurate tracking of aircraft on curved paths, overcoming the limitations of fixed field of view sensors.
2Measurement precision
If conventional systems rely on visual guidance methods, then the system is simple to implement, but the accuracy of aircraft position is insufficient
Solution Approach 1:
The system replaces manual visual guidance methods with automated LIDAR-based detection and tracking systems. The LIDAR sensors provide precise measurement of aircraft position, dimensions, and orientation, while the computer system automatically calculates docking parameters and provides guidance, significantly improving measurement precision over manual methods.
Solution Approach 2:
The system creates a digital 3D model of the aircraft by synthesizing LIDAR data from multiple angles and processing it through computer algorithms. This virtual copy of the aircraft contains precise dimensional and positional information, enabling accurate docking guidance without requiring direct physical measurement.
3Measurement precision
If the system uses LIDAR data synthesis and 3D modeling, then the aircraft position accuracy is improved, but the data processing complexity increases
Solution Approach 1:
The system performs preliminary synthesis of LIDAR data from multiple sensors and angles before final processing. By pre-integrating the raw data and creating a consolidated 3D model in advance, the system reduces the computational burden during real-time tracking and docking guidance, managing data processing complexity while maintaining high precision.
Solution Approach 2:
The system introduces an intermediary computational layer that processes raw LIDAR data and transforms it into a simplified 3D aircraft model. This intermediary representation serves as a bridge between complex sensor data and the final docking guidance output, making the data more manageable and reducing processing complexity.
4Reliability
If manual docking guidance is used, then the system is easy to operate, but consistency and accuracy are problematic
Solution Approach 1:
The system implements self-service automation where the LIDAR-based detection and tracking system automatically provides docking guidance without requiring manual intervention. The computer system independently processes sensor data, calculates aircraft position and orientation, and generates guidance commands, ensuring consistent and reliable performance free from human error.
Solution Approach 2:
The system incorporates continuous feedback loops where LIDAR sensors constantly monitor aircraft position, the computer system compares actual position with target position, and adjusts guidance commands in real-time. This closed-loop feedback mechanism ensures high reliability and consistency in docking guidance, automatically compensating for deviations.
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
Enhances aircraft positioning accuracy and safety by generating a comprehensive aircraft model for pilots, ensuring precise docking regardless of weather or visibility, and accommodating aircraft of varying sizes and shapes.
Implementation Method 1
capturing, by a light detection and ranging (LIDAR) sensor, LIDAR sensor data of an aircraft
Implementation Method 2
capturing, by a light detection and ranging (LIDAR) sensor, LIDAR sensor data of an aircraft
Data Source
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AI summary
Devices, methods, and systems for aircraft detection, tracking, and docking using three dimensional sensor data are described herein. One method includes capturing, by a light detection and ranging (LIDAR) sensor, LIDAR sensor data of an aircraft while the aircraft is approaching a docking area of an airport, receiving, from the LIDAR sensor, the sensor data of the aircraft while the aircraft is approaching a docking area, retrieving, by a computing device, a simulated two dimensional image of the aircraft generated based on simulated data of the aircraft, tracking, by the computing device, a position of the aircraft while the aircraft is approaching the docking area using the LIDAR sensor data and the simulated two dimensional image, and displaying an image including the position of the aircraft while the aircraft is approaching the docking area to provide navigation guidance to a pilot.