Stereo Cloud Height Measurement With Direction Error Correction
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Solution Overview
Problem
Existing cloud height measurement systems, such as ceilometers and stereo camera systems, lack accuracy and coverage in measuring cloud heights across the entire sky due to limited horizontal range and inadequate correction for directional deviations in camera positioning.
Innovation Solution
A cloud measuring system utilizing a stereo camera with adjustable cameras for capturing stereo images, combined with a correction process that accounts for directional deviations through feature point matching and correction processing, enabling precise cloud height estimation across the entire sky.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a ceilometer using a laser is used to measure cloud height, then the measurement of cloud height immediately above is achieved, but the measurable range in the horizontal direction is narrow
Solution Approach 1:
The sky is divided into multiple regions that are sequentially imaged by moving the camera platform. Each camera captures a specific angular range, and by segmenting the full 360-degree sky into multiple fields of view, the system achieves comprehensive coverage while maintaining measurement precision in each segment.
Solution Approach 2:
The camera platform is made movable to dynamically adjust the imaging direction and cover different parts of the sky. The system transitions from a static single-point measurement to a dynamic multi-point measurement by changing the camera's angular position in both pan and tilt directions.
2Area of stationary object
If a stereo camera system is used to measure cloud heights in a wide range, then the horizontal coverage is improved, but directional deviation and camera lens distortion correction is inadequate
Solution Approach 1:
Camera calibration is performed in advance to pre-calculate correction values for lens distortion and directional deviation. By performing preliminary calibration and storing correction data, the system compensates for optical imperfections before actual cloud height measurement, ensuring high precision across the entire sky coverage.
Solution Approach 2:
The system uses feature point matching between left and right camera images to detect directional deviations in real-time. By comparing the positions of identical features in stereo images and calculating the deviation, the system provides feedback to correct camera positioning errors and maintain measurement accuracy.
3Measurement precision
If camera calibration is carried out on the basis of stars during clear nighttime, then lens distortion correction is achieved, but correction can be made only during clear nighttime
Solution Approach 1:
The calibration method is extended to work under multiple conditions (daytime and nighttime) by using different reference objects (celestial bodies at night, ground features or clouds during day). This universal calibration approach allows the system to perform lens distortion correction regardless of time of day or weather conditions.
Solution Approach 2:
The calibration reference changes based on operational conditions: celestial bodies are used for nighttime calibration, while alternative reference objects are used during daytime. By changing the calibration parameter (reference object) according to environmental conditions, the system maintains calibration capability across all operating scenarios.
4Ease of operation
If the camera is fixed in a direction toward the zenith, then simple positioning is achieved, but directional deviation and aging effects cannot be corrected
Solution Approach 1:
The system continuously monitors camera directional deviation by matching feature points in stereo images and calculates correction amounts. This feedback mechanism detects aging-induced deviations and positioning errors, automatically compensating for them to maintain high measurement precision without requiring manual repositioning.
Solution Approach 2:
The camera system performs self-correction of directional deviations through automated feature point matching and correction amount calculation. The system detects its own positioning errors and applies corrections without external intervention, maintaining accuracy despite aging or environmental changes.
Data Source
AI summary
A cloud measuring system includes: a stereo camera capturing stereo images by cameras each changing pan and tilt angles; a camera control section controlling the pan and tilt angles to control imaging; a reception section receiving the stereo images; a matching coordinate acquisition section acquiring a feature point of an object in the stereo images, and acquiring, as matching coordinates, a combination of reference coordinates where the feature point is to be located in the images, and coordinates of the acquired feature point; a difference detection section acquiring a displacement amount of the feature point from the matching coordinates, acquiring direction difference amounts in pan and tilt directions from the displacement amount, and generating correction information; a correction processing section correcting the stereo images on the basis of the correction information; and a height estimation section estimating a cloud height on the basis of the corrected stereo images.