Time-of-Flight Sensor Glare Correction via Masking
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Solution Overview
Problem
Time-of-flight sensors are unreliable in environments with highly reflective objects due to glare, leading to inaccurate intensity and distance measurements, which can hinder the identification and characterization of objects, particularly in autonomous vehicles, reducing safety.
Innovation Solution
The implementation of glare correction techniques that quantify and remove the effects of glare from sensor data by identifying a glare region, determining glare depth and intensity, and generating a glare mask to correct pixel values, resulting in improved intensity and depth data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If time-of-flight sensors are used to measure intensity and distance, then measurement capability is provided, but measurement precision deteriorates in environments with highly reflective objects due to glare
Solution Approach 1:
The patent identifies glare regions by detecting areas where reflected light creates abnormal intensity patterns, then uses these identified glare regions to calculate correction factors. The harmful glare effect is converted into useful information about where and how much correction is needed, improving measurement accuracy in reflective environments.
Solution Approach 2:
The patent introduces an intermediary processing step that calculates glare correction factors based on identified glare regions. These correction factors act as intermediaries between the raw sensor data and the final corrected measurements, allowing the system to compensate for glare effects without requiring hardware modifications.
2Measurement precision
If glare correction processing is applied to sensor data, then measurement precision improves, but device complexity increases due to additional processing steps
Solution Approach 1:
The patent segments the sensor data processing into distinct stages: identifying glare regions, calculating glare correction factors for each region, and applying corrections to affected pixels. This segmentation allows the complex correction process to be broken down into manageable, modular operations that can be implemented efficiently.
Solution Approach 2:
The patent applies glare correction locally to specific glare regions rather than uniformly to the entire image. By identifying and correcting only the affected areas using region-specific correction factors, the system reduces unnecessary processing overhead while maintaining accuracy where it matters most.
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 enhances the accuracy of sensor data, providing safer navigation and more confident vehicle control by eliminating glare-induced errors, thereby improving object detection and characterization.
Implementation Method 1
Sensors, such as time-of-flight sensors, may be unreliable in certain environments
Implementation Method 2
highly reflective objects can cause glare, and glare can result in inaccurate measurements
Data Source
AI summary
Sensors, including time-of-flight sensors, may be used to detect objects in an environment. In an example, a vehicle may include a time-of-flight sensor that images objects around the vehicle, e.g., so the vehicle can navigate relative to the objects. Sensor data generated by the time-of-flight sensor can be impacted by glare. In some examples, corrected data is generated by quantifying glare. A glare region including pixels that are not associated with an object in a range of the time-of-flight sensor may provide glare intensity and glare depth values used to quantify the glare. The glare intensity and glare depth may be used to correct measured data.