Time-of-Flight Sensor Power Control for Pixel Saturation
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Solution Overview
Problem
Time-of-flight sensors face reliability issues in environments with varied lighting and high reflectivity, leading to unreliable pixel data, which can hinder obstacle detection and safety in autonomous vehicles.
Innovation Solution
Active power control techniques are employed to adjust illumination power and integration time based on pixel data, distinguishing between saturation caused by active illumination and ambient light, to reduce saturated pixels and improve data fidelity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If the time-of-flight sensor operates in high-illumination environments or encounters highly reflective objects, then the sensor captures more light signal, but pixel saturation occurs making it impossible to infer any information about the scene
Solution Approach 1:
The patent implements dynamic adjustment of sensor parameters (integration time and illumination power) based on real-time analysis of pixel data characteristics. The system continuously monitors for saturation conditions and adjusts operating parameters accordingly, transforming the static sensor operation into a dynamic adaptive system that maintains optimal performance across varying environmental conditions.
Solution Approach 2:
The patent changes physical parameters of the sensor operation, specifically adjusting integration time and illumination power levels. By modifying these parameters based on detected saturation conditions, the system prevents pixel saturation while maintaining adequate signal capture, directly resolving the contradiction between capturing sufficient light and avoiding saturation.
2Measurement precision
If the sensor increases integration time to capture more signal in challenging environments, then signal strength improves, but saturation from active illumination and ambient light increases
Solution Approach 1:
The patent adjusts the integration time parameter dynamically based on detected saturation conditions. When saturation is detected in the pixel data, the system reduces integration time to prevent both active illumination and ambient light from causing saturation, while maintaining adequate signal capture through coordinated adjustment of illumination power.
Solution Approach 2:
The system implements feedback by analyzing pixel data for saturation indicators and using this information to adjust subsequent sensor operation. The feedback loop monitors the relationship between integration time, illumination power, and resulting pixel saturation, continuously optimizing parameters to maintain measurement precision while avoiding harmful saturation effects.
3Measurement precision
If the sensor uses higher illumination power to improve signal capture, then detection capability improves, but saturation and unreliable pixel data increase
Solution Approach 1:
The patent dynamically adjusts illumination power based on real-time analysis of pixel saturation conditions. When saturation is detected, the system reduces illumination power to prevent both active illumination saturation and ambient light saturation, thereby maintaining detection capability while ensuring pixel data reliability.
Solution Approach 2:
The system uses feedback from pixel data analysis to control illumination power levels. By monitoring for saturation indicators in the captured data and adjusting illumination power accordingly, the system maintains optimal detection capability while preventing the harmful effects of excessive illumination that would compromise data reliability.
4Adaptability or versatility
If the sensor operates in environments with varied lighting conditions, then environmental adaptability improves, but data reliability decreases due to different reflective and absorptive properties of objects
Solution Approach 1:
The patent implements dynamic parameter adjustment that adapts to varying environmental lighting conditions and object properties. By continuously monitoring pixel data for saturation and adjusting integration time and illumination power accordingly, the system maintains reliable data capture across diverse environments with different reflective and absorptive characteristics.
Solution Approach 2:
The system changes operational parameters (integration time, illumination power) based on detected environmental conditions and object properties. This parameter adaptation allows the sensor to maintain reliable pixel data across varied lighting conditions and objects with different reflective/absorptive properties, resolving the contradiction between environmental adaptability and data reliability.
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 reliability and accuracy of sensor data, enabling safer navigation and obstacle detection in autonomous vehicles by minimizing the impact of environmental factors on sensor performance.
Implementation Method 1
Time-of-flight sensors may be unreliable in certain environments
Implementation Method 2
reflections off objects that are extremely close to the sensor, reflections off objects that have high reflectivity
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 include saturated pixels, e.g., due to over-exposure, sensing highly-reflective objects, and/or excessive ambient light. In some examples, parameters associated with power of a time-of-flight sensor can be altered based on characteristics of the saturated pixels, as well as information about non-saturated pixels neighboring the saturated pixels. For example, the neighboring pixels may provide information about whether saturation is due to ambient light, e.g., sunlight, or due to emitted light from the sensor.