FMCW LiDAR Aircraft Positioning With Radial Velocity Segmentation
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Solution Overview
Problem
Existing aircraft positioning systems at airports face challenges due to limitations in accuracy and computational effort, particularly with incoherent laser scanners and camera systems, which are affected by ambient light and require high computational effort for image processing, leading to unsatisfactory detection of aircraft features like engine position or nose shape.
Innovation Solution
A device using a frequency-modulated continuous wave (FMCW) LiDAR sensor scans a monitoring area, segments measurement points into aircraft segments using digital image processing and machine learning, and determines radial velocities to improve segmentation and feature extraction, enabling precise aircraft type identification and positioning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If incoherent laser scanners or camera systems are used for aircraft detection, then the system can operate in ambient light conditions, but the measurement precision and detection accuracy of aircraft features deteriorate due to ambient light interference
Solution Approach 1:
The patent changes the fundamental measurement parameter from incoherent light intensity detection to coherent light phase detection. By using FMCW LiDAR with coherent light sources and measuring phase differences of reflected light waves, the system achieves immunity to ambient light interference while maintaining high measurement precision for aircraft features.
Solution Approach 2:
The patent replaces traditional optical-mechanical camera systems and incoherent laser scanners with a coherent light-based FMCW LiDAR system. This substitution enables the use of phase modulation and frequency sweeping techniques, fundamentally changing how distance and velocity measurements are obtained and eliminating susceptibility to ambient light conditions.
2Reliability
If traditional image processing methods are used to process aircraft detection data, then the system can identify aircraft features, but the computational effort and processing time increase significantly
Solution Approach 1:
The patent extracts and utilizes radial velocity information directly from the coherent light measurement data. By incorporating velocity data into the segmentation process, the system simplifies aircraft feature detection and reduces the computational complexity of image processing while improving reliability in distinguishing aircraft from background objects.
Solution Approach 2:
The patent applies segmentation to divide the measurement data into distinct aircraft components and background elements. By using both spatial position and radial velocity information for segmentation, the system efficiently identifies aircraft features with reduced computational effort compared to traditional full-image processing methods.
3Measurement precision
If FMCW LiDAR sensor with radial velocity measurement is used, then the segmentation accuracy of measurement points is improved, but the device complexity and sensor requirements increase
Solution Approach 1:
The FMCW LiDAR sensor performs multiple functions simultaneously: it measures distance, determines radial velocity, and provides segmentation information all through a single coherent light measurement process. This multi-functionality achieves high segmentation accuracy without proportionally increasing device complexity, as the velocity and position data are obtained from the same measurement mechanism.
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 FMCW LiDAR sensor provides enhanced accuracy and reduced computational effort by distinguishing static and moving objects, allowing efficient detection of aircraft features and reliable positioning, even in challenging ambient conditions, with reduced computational load.
Implementation Method 1
the optoelectronic sensor is designed as a frequency-modulated continuous wave (FMCW) LiDAR sensor that transmits modulated light waves into a monitoring area and detects reflected light from measurement points in the monitoring area
Implementation Method 2
The measurement data includes radial velocities of the measurement points
Implementation Method 3
The control and evaluation unit is configured to segment the measurement points using the radial velocities
Data Source
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AI summary
A device for positioning an aircraft within a monitoring area of an airport apron comprises at least one optoelectronic sensor for emitting light beams into the monitoring area, scanning a plurality of measurement points, and generating measurement data from the transmitted or reflected light emitted by the measurement points. A control and evaluation unit is configured to segment the measurement points, at least partially combine them into segments of the aircraft, extract features from the segments, assign the segments to an aircraft type from a plurality of aircraft types based on the extracted features, and output positioning information for the aircraft based on the assigned aircraft type. The at least one optoelectronic sensor is designed as an FMCW LiDAR sensor, and the measurement data includes radial velocities of the measurement points.