Direct Time-of-Flight Depth Sensor with Segmented Coincidence Detection
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Solution Overview
Problem
Conventional direct time-of-flight (DTOF) imaging sensors face challenges in achieving high-quality LiDAR measurements, particularly in wide dynamic range scenarios due to issues with ambient light suppression and background noise interference, which affects the accuracy and detection speed of depth sensing across varying target reflectivities.
Innovation Solution
The proposed DTOF depth imaging sensor employs an array of photodetectors organized into subgroups with independent timestamping capabilities, allowing for non-blocking photon detection and enhanced depth information processing. This includes a coincidence tree for event propagation, photon rank units for signal quality assessment, and adaptive coincidence thresholds to manage background noise, enabling simultaneous detection across a wide dynamic range without discarding lower reflectivity signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If conventional coincidence detection is used to suppress ambient light, then background noise filtering is improved, but detection speed and accuracy deteriorate in wide dynamic range scenarios
Solution Approach 1:
The photodetector array is divided into multiple subgroups, each with independent timestamping capability. This segmentation allows parallel processing of depth information for different spatial regions, improving detection speed while maintaining accuracy through localized coincidence detection.
Solution Approach 2:
The system dynamically adjusts coincidence detection thresholds based on ambient light conditions and target reflectivity. This adaptive approach maintains optimal background noise filtering while preserving detection accuracy across wide dynamic range scenarios.
2Device complexity
If fixed coincidence thresholds are used, then processing simplicity is maintained, but robustness to varying target reflectivities deteriorates
Solution Approach 1:
The coincidence detection threshold is made dynamic and adaptive, automatically adjusting based on detected photon rates and ambient light conditions. This enables robust performance across targets with varying reflectivities while adding minimal complexity through automated threshold adjustment.
Solution Approach 2:
The system incorporates feedback mechanisms where detected photon rates and coincidence events are used to adaptively adjust detection thresholds. This feedback loop maintains optimal detection performance across wide dynamic range scenarios without requiring complex manual configuration.
3Device complexity
If resource sharing architecture is used, then device complexity is reduced, but pixel count and speed tradeoffs worsen
Solution Approach 1:
The system segments the photodetector array into independent subgroups with dedicated timestamping units. This segmentation eliminates resource sharing bottlenecks, allowing parallel depth calculation for all pixels simultaneously, thus improving detection speed without proportionally increasing overall complexity.
Solution Approach 2:
The architecture transitions from shared resource processing to distributed parallel processing by adding the temporal dimension through independent timestamping. This enables simultaneous depth calculation for multiple pixels without resource contention, improving productivity while maintaining manageable complexity through modular design.
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
The solution provides improved depth information resolution and robust noise filtering, enabling accurate depth sensing across a wide dynamic range with enhanced detection speed and reduced interference, allowing for precise imaging of targets with varying reflectivities.
Implementation Method 1
detecting the time of arrival of the reflected photons by a high-performance photo detector
Implementation Method 2
avalanche photodiodes, single-photon avalanche diodes (SPADs)
Implementation Method 3
an electronic circuitry is used to measure the time-of-flight, e.g. by means of a time-to-digital converter (TDC)
Implementation Method 4
coincidence detection which provides a technique utilizing spatial and temporal closeness of photons within a laser pulse to filter out background noise photons
Data Source
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AI summary
The present invention relates to a direct time-of-flight depth imaging sensor comprising: an array of photodetectors (43) arranged in one or more subgroups (41), wherein each subgroup (41) is divided into a plurality of minigroups (42) of photodetectors (43); digital processing and communication units (63) each associated to one of the minigroups (42), each comprising: a minigroup pixel address register (69) to store an address of the photodetector (43) in the respective minigroup (42) which has detected the last photon detection event within a coincidence window, wherein the coincidence window corresponds to detection window of a fixed duration starting with the first photon detection event within the respective subgroup (41); and a minigroup timestamp unit (68) configured to store minigroup timestamp data of the last photon detection event received in the coincidence window; a time to digital converter (61) configured to generate a subgroup timestamp data about the first photon detection event in the subgroup (41) during the coincidence window.