LWIR Sensor Thermal Pattern Analysis for Atmospheric Detection
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Solution Overview
Problem
Autonomous vehicles and vehicles with driver assist functions face challenges in accurately determining atmospheric conditions, such as precipitation, which can affect sensor performance and vehicle safety, as existing sensor systems may struggle in adverse weather conditions like rain, snow, or fog.
Innovation Solution
The implementation of a long-wave infrared (LWIR) sensor system that uses thermal image data to identify atmospheric conditions by comparing characteristics of thermal images from unknown conditions with known conditions, generating a confidence level for vehicle control systems, and combining this data with RGB camera information to enhance accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing sensor systems are used to detect atmospheric conditions, then the system structure is simple, but the detection accuracy deteriorates in adverse weather conditions like rain, snow, or fog
Solution Approach 1:
The patent combines multiple sensor types (LWIR sensor, RGB camera, barometer, humidity sensor, temperature sensor) into an integrated atmospheric condition detection system. The LWIR sensor detects thermal radiation patterns characteristic of precipitation, while RGB cameras capture visual information, and environmental sensors provide complementary data. This multi-sensor fusion approach resolves the contradiction by achieving high detection accuracy through combined sensor capabilities while managing system complexity through integrated processing.
Solution Approach 2:
The patent introduces thermal image data from LWIR sensors as an intermediary to detect atmospheric conditions indirectly through characteristic thermal patterns of precipitation particles. Rather than directly detecting rain or snow, the system identifies thermal radiation signatures that serve as intermediaries indicating atmospheric conditions, thereby improving detection accuracy without requiring direct contact with precipitation.
2Measurement precision
If thermal image data from LWIR sensor is used to detect atmospheric conditions, then the detection accuracy improves, but the use of energy increases
Solution Approach 1:
The patent implements selective sensor activation where the LWIR sensor and full RGB camera processing are activated only when atmospheric condition detection is required or when initial sensors detect potential precipitation conditions. During normal clear conditions, the system relies on less energy-intensive sensors, thereby reducing overall energy consumption while maintaining high detection accuracy when needed.
Solution Approach 2:
The LWIR sensor serves multiple functions: detecting precipitation, estimating intensity, and providing thermal context for other sensors. This multi-functionality reduces the need for additional dedicated sensors, thereby improving detection accuracy without proportionally increasing energy consumption.
3Measurement precision
If multiple sensor data are combined to improve detection accuracy, then the measurement precision improves, but the device complexity increases
Solution Approach 1:
The patent segments the atmospheric condition detection system into functional modules: LWIR thermal pattern recognition module, RGB visual analysis module, environmental sensor data collection module, and integrated processing module. Each module handles specific sensor data types and processing tasks independently, then combines results. This segmentation improves detection accuracy through comprehensive data analysis while managing complexity through modular architecture.
Solution Approach 2:
The system implements feedback loops where detection results and confidence levels inform subsequent sensing and processing actions. When atmospheric conditions are detected with high confidence, the system can reduce sensing intensity or frequency, thereby managing operational complexity while maintaining high detection accuracy through adaptive response.
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
This approach allows for more accurate detection of atmospheric conditions, enabling vehicles to adjust operations, such as speed or sensor cleaning, thereby improving safety and navigation in various environmental conditions.
Implementation Method 1
a long wave infrared (LWIR) sensor... receiving thermal image data from the LWIR sensor
Data Source
AI summary
Apparatus and methods for determining an atmospheric condition in an environment of a vehicle are described herein. A long wave infrared camera may be used to produce thermal image data from a field of view of the LWIR camera that includes an unknown atmospheric condition. The thermal image data may include a characteristic that may be compared to characteristic of thermal image data for a known atmospheric condition. A result of the comparison may be used to make a determination related to the unknown atmospheric condition which may be used in controlling the vehicle.