TOF Module Distance Estimation Using Multi-Algorithm Fusion
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Solution Overview
Problem
Time-of-flight (TOF) sensors face challenges in accurately measuring distance at close ranges due to optical cross-talk and the parallax effect, which overlap and reduce signal magnitude, leading to inaccurate proximity and distance calculations.
Innovation Solution
The implementation of a method using multiple algorithms to combine distance measurement outputs, each providing a confidence level, to improve estimation accuracy. This includes dual peak detection, peak edge detection, triangulation, and intensity-based methods, with compensation for ambient light and manufacturing tolerances, to enhance distance calculation robustness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single TOF measurement algorithm is used, then the device complexity is low, but the measurement precision deteriorates due to optical cross-talk and parallax effects at close distances
Solution Approach 1:
The patent combines multiple TOF measurement algorithms (first algorithm, second algorithm, and third algorithm) into a single processing system. Each algorithm handles different aspects or conditions of distance measurement, and their results are integrated to produce a final accurate distance value, thereby resolving the contradiction between measurement precision and device complexity.
Solution Approach 2:
The measurement process is segmented into multiple independent algorithms, each capable of handling specific measurement scenarios. The system processes distance measurements through separate algorithmic paths and then combines the results, allowing for specialized processing that improves overall precision without requiring a single overly complex algorithm.
2Measurement precision
If multiple algorithms are combined to improve measurement accuracy, then the measurement precision improves, but the processing time increases
Solution Approach 1:
The system applies multiple algorithms to the TOF measurement data, with the understanding that not all algorithms may be equally necessary for every measurement scenario. The combination of algorithms provides comprehensive coverage for different measurement conditions, ensuring high precision while managing processing time through selective application of algorithms based on measurement requirements.
3Measurement precision
If algorithms are used to distinguish object signals from cross-talk signals, then the measurement precision improves, but the difficulty of detecting and measuring increases
Solution Approach 1:
The signal processing is segmented into multiple algorithmic stages, where each algorithm handles specific aspects of signal distinction. The first, second, and third algorithms separately address different characteristics of object signals versus cross-talk signals, making the complex detection task more manageable and improving overall precision through specialized processing at each stage.
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 significantly improves the accuracy of distance measurements over a wide range of conditions by synergistically combining different algorithms, effectively distinguishing between object and cross-talk signals and compensating for environmental distortions, thereby enhancing the reliability of proximity and distance determinations.
Implementation Method 1
The TOF sensor can be used to resolve distance based on the known speed of light by measuring the time-of-flight of a light signal between the sensor and the object
Implementation Method 2
a single, very short pulse can be directed toward, and reflected by, an object
Data Source
AI summary
A method of using an optical TOF module to determine distance to an object. The method includes acquiring signals in the TOF module indicative of distance to the object, using a first algorithm to provide an output indicative of the distance to the object based on the acquired signals, using at least one second different algorithm to provide an output indicative of the distance to the object based on the acquired signals, and combining the outputs of the first and at least one second algorithms to obtain an improved estimate of the distance to the object. In some implementations, each of the first and at least one second algorithms further provides an output representing a respective confidence level indicative of how accurately distance to the object has been extracted by the particular algorithm.