Time-of-Flight Sensor Pixel Filtering via Multi-Exposure Saturation Detection
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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 the identification and characterization of objects, especially in autonomous vehicles, potentially reducing safety.
Innovation Solution
The implementation of a method that involves generating multiple exposures, including a primary and secondary exposure, to determine saturation levels and adjust illumination and sensing parameters, allowing for pixel filtering based on intensity thresholds to improve data quality and reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If time-of-flight sensor is used in high reflectivity environments, then object detection capability is improved, but data reliability deteriorates due to saturation and unreliable pixel data
Solution Approach 1:
The system performs preliminary action by capturing a secondary exposure at reduced illumination intensity before the primary exposure. This preliminary capture allows determination of saturation levels in advance, enabling proactive adjustment of sensing parameters to prevent saturation in the primary exposure, thus resolving the contradiction between detecting high reflectivity objects and avoiding saturation artifacts
Solution Approach 2:
The system implements feedback by using the secondary exposure data to determine saturation levels and automatically adjusting the sensing parameters for the primary exposure. This closed-loop feedback mechanism ensures that when high reflectivity objects are detected in the secondary exposure, the system adapts by reducing illumination or adjusting integration time, thereby maintaining pixel data reliability while preserving the ability to detect these objects
2Reliability
If multiple exposures are generated to determine saturation levels, then pixel data reliability is improved, but processing time increases
Solution Approach 1:
The system extracts only the essential information from the secondary exposure - specifically the saturation levels of pixels - rather than processing the complete secondary exposure data. By extracting only the saturation metadata needed for parameter adjustment, the system minimizes additional processing time while maintaining data reliability benefits
Solution Approach 2:
The system applies partial action by performing saturation analysis only on a subset of pixels or regions where high reflectivity is suspected, rather than processing all pixels in the secondary exposure. This selective approach reduces processing overhead while still capturing the reliability improvements needed for critical high-reflectivity object detection
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 return pixels subject to over-exposure or saturation, which may be from stray light. In some examples, multiple exposures captured at different exposure times can be used to determine a saturation value for sensor data. The saturation value may be used to determine a threshold intensity against which intensity values of a primary exposure are compared. A filtered data set can be obtained based on the comparison.