Time-of-Flight Measurement Noise Suppression via Digital Filtering
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Solution Overview
Problem
Time-of-flight measurement systems face inaccuracies due to noise signals from ambient light or detector noise, which cannot be distinguished from echo signals, leading to incorrect distance calculations.
Innovation Solution
A method involving digital filtering of histogram data to identify the peak value corresponding to the echo signal, and coherent processing of timestamp sets to enhance the signal-to-background noise ratio (SBNR), thereby improving measurement accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Length of moving object
If SPAD is used to detect single photons for measuring distance to farther objects with limited laser power, then measurement range is improved, but measurement accuracy deteriorates due to noise signals from ambient light or detector noise being indistinguishable from echo signals
Solution Approach 1:
The patent segments the measurement process into multiple integration periods and divides histogram data into multiple groups for parallel processing. Each group processes a subset of timestamp sets, and the results are combined to produce the final time of flight measurement. This segmentation allows noise reduction through statistical processing while maintaining the ability to detect faint echo signals from distant objects.
Solution Approach 2:
The patent performs multiple integration periods and processes more timestamp sets than the minimum required. By accumulating photon events over multiple integration periods and processing multiple groups of timestamps, the system accumulates sufficient signal photons to distinguish the echo signal from noise, even when the echo signal is very weak from distant objects.
2Measurement precision
If digital filtering and coherent processing are applied to enhance signal-to-background noise ratio, then measurement accuracy is improved, but computational complexity increases
Solution Approach 1:
The patent divides the computational workload by segmenting timestamp sets into multiple groups that can be processed in parallel. Each group performs filtering and histogram analysis independently on a subset of data, reducing the computational burden on any single processing unit and enabling efficient implementation of complex filtering algorithms.
Solution Approach 2:
The system uses the statistical properties of the accumulated timestamp data itself to perform noise filtering. By constructing histograms from multiple integration periods and identifying peak positions, the system leverages the inherent statistical distribution of the data to distinguish signal from noise without requiring complex external filtering hardware or algorithms.
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 method effectively suppresses noise signals and enhances the SBNR, leading to more accurate time-of-flight measurements and improved distance detection.
Implementation Method 1
the SPAD receives an echo signal to perform photoelectric conversion and an avalanche effect to generate a pulse electrical signal
Implementation Method 2
the SPAD receives an echo signal to perform photoelectric conversion and an avalanche effect to generate a pulse electrical signal
Data Source
AI summary
This application discloses a time-of-flight measurement method, apparatus, and system. The method includes obtaining histogram data of a target object. The histogram data includes m counts, m is an integer greater than 1, and each of the m counts is associated with a time. The method also includes performing digital filtering on the m counts to obtain m filtered values respectively corresponding to the m counts, and determining a time of flight of the target object based on a time corresponding to a peak value in the m filtered values.