Time-of-Flight Distance Imaging With SNR-Adaptive Averaging
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Solution Overview
Problem
Time-of-flight sensors suffer from statistical fluctuations in distance accuracy, leading to inconsistent measurements in identical scenarios, and existing averaging methods using fixed thresholds compromise accuracy and introduce distortions, especially in fast-moving scenes or non-planar objects.
Innovation Solution
Adopting a method that uses dynamic, signal-to-noise ratio-dependent thresholds for temporal and spatial averaging of distance values, minimizing time delay and edge distortion by selecting data points based on standard deviation and echo intensity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a fixed distance difference threshold is used for averaging, then the method is simple to implement, but the distance accuracy deteriorates in scenes with varying signal-to-noise ratios
Solution Approach 1:
The patent applies dynamics by replacing the fixed averaging threshold with a dynamic threshold that adapts to the signal-to-noise ratio. The threshold is calculated based on the standard deviation of distance measurements and the echo intensity, allowing it to automatically adjust to different scene conditions. This resolves the contradiction by maintaining simplicity in the averaging concept while introducing adaptability in the threshold selection to preserve distance accuracy across varying SNR conditions.
Solution Approach 2:
The patent changes the parameter of the averaging threshold from a fixed value to a variable value that depends on the signal-to-noise ratio. Specifically, the threshold is set to a first value when the SNR is above a reference level and to a second, lower value when the SNR is below the reference level. This parameter change allows the system to maintain both simplicity and accuracy by adapting the threshold to current measurement conditions.
2Measurement precision
If temporal averaging is performed to improve distance accuracy, then statistical fluctuations are reduced, but time delay increases
Solution Approach 1:
The patent applies local quality by performing temporal averaging selectively only for data points where the signal-to-noise ratio is below the reference level. High-SNR measurements are processed without averaging to minimize time delay, while only low-SNR measurements undergo temporal averaging to reduce statistical fluctuations. This localized application of averaging resolves the contradiction by improving accuracy where needed without introducing unnecessary time delay throughout the entire dataset.
3Measurement precision
If spatial averaging is performed to reduce statistical errors, then distance accuracy improves, but edge distortion increases
Solution Approach 1:
The patent applies local quality by performing spatial averaging selectively based on the signal-to-noise ratio of individual data points. Only data points with low SNR undergo spatial averaging to reduce statistical errors, while high-SNR data points are processed without averaging to preserve edge clarity. This localized approach resolves the contradiction by improving accuracy in noisy regions without blurring edges in high-quality measurements.
Solution Approach 2:
The patent segments the data points into two groups based on their signal-to-noise ratio: high-SNR points that are processed without spatial averaging to maintain edge clarity, and low-SNR points that undergo spatial averaging to reduce statistical errors. This segmentation allows the system to apply different processing strategies to different parts of the data, resolving the contradiction between accuracy improvement and edge preservation.
4Reliability
If a large fixed threshold is used for averaging, then worst-case scenarios with large statistical variance are optimized, but data points are averaged inappropriately in high-SNR conditions
Solution Approach 1:
The patent changes the threshold parameter from a large fixed value to an adaptive value that depends on the signal-to-noise ratio. When SNR is high, the threshold is set to a lower value that prevents inappropriate averaging, while when SNR is low, the threshold is raised to capture statistical fluctuations. This dynamic parameter adjustment resolves the contradiction by maintaining robustness to statistical variance in worst-case scenarios while avoiding the penalties of over-averaging in high-SNR conditions.
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 distance accuracy by adapting averaging thresholds to scene conditions, reducing statistical errors and maintaining edge clarity, especially in scenes with varying signal-to-noise ratios.
Implementation Method 1
Both types of sensors determine the distance of an object in the environment of the sensor on the basis of the principle of time of flight measurement. For this purpose, such a sensor emits a pulsed transmission signal that is reflected at the object. The reflected pulses are detected in the form of an echo signal. Based on this echo signal, the sensor determines the time of flight of the pulses from the sensor to the object and back.
Implementation Method 2
such a sensor emits a pulsed transmission signal that is reflected at the object. The reflected pulses are detected in the form of an echo signal.
Data Source
AI summary
In one embodiment, a method for providing an output distance image of a time-of-flight sensor (10) has the following steps: supplying an individual image of a scene, wherein each data point of the individual image comprises a distance value, which is determined from at least one echo signal (S′) received by the time-of-flight sensor (10), an intensity and a noise floor strength; determining a first intermediate image by a temporal averaging of the at least one distance value of a plurality of data points, preferably of each data point, of the individual image or of a second intermediate image with a respective distance value of a corresponding data point of a settable number of preceding individual images using a first dynamic threshold that is at least dependent on the signal-to-noise ratio; and/or determining a second intermediate image by a spatial averaging of the at least one distance value of the plurality of data points, preferably of each data point, of the individual image or of at least one distance value of a plurality of data points, preferably of each data point, of the first intermediate image with at least one distance value of a settable number of neighboring data points of the individual image or of the first intermediate image using a second dynamic threshold that is at least dependent on the signal-to-noise ratio; and providing the first or the second intermediate image as the output distance image of the time-of-flight sensor.