ToF Sensor Integration Time Adaptation Across Multiple Time Windows
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Solution Overview
Problem
Existing time-of-flight (ToF) sensor technologies lack a robust and reliable method to automatically select the number of windows and assign integration times for optimal performance in varying scene conditions, particularly affecting depth quality and resilience to environmental factors.
Innovation Solution
An optoelectronic sensor with an iterative process that adapts integration times based on environmental factors like ambient light and scene conditions to minimize non-detection events and optimize signal-to-noise ratio (SNR), using a processing unit to adjust integration times dynamically across multiple time windows.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple time windows are used to cover the targeted range, then the range coverage is improved, but the complexity of selecting integration times for each window increases
Solution Approach 1:
The patent applies preliminary action by pre-defining multiple candidate integration time sets, each corresponding to different numbers of time windows (e.g., first set with 1 window, second set with 2 windows, etc.). This allows the system to have integration time configurations ready in advance, eliminating the need for complex real-time optimization and making the selection process simpler while maintaining adaptability to different range requirements.
Solution Approach 2:
The patent implements parameter changes by varying the number of time windows and their corresponding integration times across different candidate sets. Each candidate integration time set represents a different parameter configuration (number of windows, duration of each window), allowing the system to adapt to different scene conditions by selecting the appropriate parameter set without increasing operational complexity.
2Measurement precision
If integration time is extended to improve detection of dark objects or long ranges, then the signal-to-noise ratio is improved, but the time required for each measurement increases
Solution Approach 1:
The patent applies dynamics by making the integration time configuration adaptive rather than fixed. The system dynamically selects from multiple candidate integration time sets based on scene conditions (e.g., ambient light level, detected range). This allows the integration time to be extended only when necessary (for dark objects or long ranges) while using shorter integration times for brighter or closer objects, thereby optimizing the signal-to-noise ratio without unnecessarily increasing measurement time in all cases.
Solution Approach 2:
The patent implements parameter changes by providing multiple candidate integration time sets with different duration parameters. Each set is optimized for specific conditions (e.g., longer integration times for low-light scenarios, shorter times for bright conditions). The system changes the integration time parameter based on detected scene characteristics, achieving high measurement precision when needed while minimizing measurement time in other scenarios.
3Measurement precision
If the number of windows is limited to concentrate integration time budget, then the integration time per window is improved, but the total range covered by the sensor is reduced
Solution Approach 1:
The patent applies segmentation by dividing the total measurement time budget into multiple candidate integration time sets, where each set corresponds to a different segmentation of time windows. For example, the first candidate set may have 1 window occupying the full time budget, the second set may have 2 windows with divided budgets, and so on. This segmented approach allows flexible allocation of integration time to different range segments, improving precision for the targeted range while maintaining the option to cover extended ranges when needed.
Solution Approach 2:
The patent implements dynamics by making the number of time windows and their time budget allocation adaptive. The system dynamically selects the appropriate candidate integration time set based on scene conditions. When objects are concentrated in a specific range, the system can use fewer windows with longer integration times for that range. When objects are distributed across a wide range, the system can switch to more windows with shorter integration times, thus dynamically balancing precision and range coverage.
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
Improves depth quality and resilience to challenging conditions by automatically adapting integration times, enhancing the sensor's performance in diverse lighting scenarios and reducing non-detection events.
Implementation Method 1
a pixel is formed by a photodiode, for example a single-photon avalanche diode (SPAD)
Data Source
AI summary
An optoelectronic sensor for a time-of-flight (ToF) measurement includes a light projector, a light receiver, a receiver logic, and a processing unit. The light receiver includes a number of macro-pixels. The receiver logic is operable to generate light ToF data for the respective macro-pixels corresponding to a number of time windows. The processing unit selects an initial set of integration times that defines an integration time for each time window and macro-pixel and acquires an initial frame of ToF data by collecting ToF generated from the macro-pixels according to the time windows and integration times defined in the initial set of integration times. The processing unit also computes a metric from the initial frame of ToF data. The metric is indicative of a data quality generated by the respective macro-pixels.