Dynamic Sample Point Arrangement for Distance Measurement
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Solution Overview
Problem
Existing distance measuring devices using the direct time-of-flight method face challenges in arranging sample points within a pixel array to obtain comprehensive distance information due to the large circuit requirements for time measurement, histogram generation, and peak detection units, limiting the number of histograms that can be generated and thus the number of sample points.
Innovation Solution
A distance measuring device and system that includes a pixel array with a determination unit and storage units for sample point state and movement rules, allowing for the dynamic arrangement and updating of sample points based on a sample point state table and movement rule table to optimize the position of sample points for improved distance information acquisition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the number of sample points is increased to obtain more distance information, then the measurement precision is improved, but the device complexity increases due to the large circuit scale required for time measurement, histogram generation, and peak detection units
Solution Approach 1:
The pixel array is divided into multiple regions, with different numbers of sample points allocated to different regions based on their specific requirements. This segmentation allows the system to concentrate computational resources where they are most needed while reducing complexity in other areas, thereby improving overall distance measurement precision without uniformly increasing device complexity across the entire array.
Solution Approach 2:
Different regions of the pixel array are assigned different sampling densities according to their local characteristics. Regions requiring higher precision have more sample points with finer sampling intervals, while regions with lower requirements have fewer sample points. This local optimization approach ensures that measurement precision is improved where necessary without unnecessarily increasing device complexity throughout the entire system.
2Quantity of substance
If more pixels are used as sample points, then the quantity of distance information is improved, but the ease of operation deteriorates due to the difficulty in optimally arranging sample points across the pixel array
Solution Approach 1:
The sampling interval is made dynamic rather than fixed, allowing it to be adjusted based on distance information and regional requirements. The determination unit dynamically calculates optimal sampling intervals for different regions, enabling the system to effectively use more pixels as sample points while automatically optimizing their arrangement. This dynamic approach simplifies operation by eliminating the need for manual configuration of sample point positions.
Solution Approach 2:
The system uses feedback from distance information to automatically adjust sample point arrangement. The determination unit receives distance information from the light receiving unit and uses it to optimize the sampling interval and sample point distribution in subsequent measurements. This feedback mechanism enables the system to handle a larger number of sample points effectively while automatically maintaining optimal arrangement, thereby improving quantity of distance information without compromising ease of operation.
3Measurement precision
If the sampling interval is decreased to increase sample point density, then the measurement precision is improved, but the productivity decreases due to the increased processing load and time required for histogram generation
Solution Approach 1:
The pixel array is segmented into multiple regions with different sampling intervals optimized for their specific requirements. Regions requiring high spatial resolution have smaller sampling intervals, while other regions use larger intervals. This segmentation allows the system to maintain high measurement precision in critical areas without applying fine sampling across the entire array, thereby preserving processing speed and productivity.
Solution Approach 2:
Different regions are assigned different sampling intervals based on their local quality requirements. Areas requiring high spatial resolution receive smaller sampling intervals, while regions with lower requirements use larger intervals to reduce processing load. This local optimization approach ensures that measurement precision is improved where necessary without unnecessarily decreasing productivity across the entire system.
4Adaptability or versatility
If sample points are arranged to cover the entire pixel array, then the adaptability is improved, but the measurement precision deteriorates in specific regions due to the limited number of histograms that can be generated
Solution Approach 1:
The pixel array is divided into multiple regions, each with its own optimized sampling strategy. This segmentation allows the system to maintain wide adaptability and coverage across the entire array while concentrating sample points in specific regions where high measurement precision is required. Different regions can be adapted to their specific needs without compromising the overall coverage capability.
Solution Approach 2:
Different regions of the pixel array are assigned different sampling densities according to their local requirements. Regions requiring high precision have denser sample point arrangements, while other regions use sparser arrangements. This local quality approach ensures that measurement precision is improved in specific regions without sacrificing the overall adaptability and coverage of the system.
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
This approach enables the generation of more detailed distance information by dynamically updating and rearranging sample points, enhancing spatial resolution and motion tolerance in distance measurement.
Implementation Method 1
a time of flight from a timing at which irradiation light is emitted to a timing at which reflected light is received is directly measured to calculate a distance from an object
Implementation Method 2
photodetectors called single photon avalanche diodes (SPADs) are arranged in light receiving pixels, respectively
Data Source
AI summary
The present technology relates to a distance measuring device, a control method thereof, and a distance measuring system capable of arranging sample points of a pixel array so as to obtain more distance information. A distance measuring device includes: a pixel array in which pixels that receive reflected light obtained by reflecting irradiation light from an object are arranged in a matrix; a determination unit that determines some of the pixels of the pixel array as a sample point for detecting distance information; and a storage unit that stores a sample point state table that stores distance information of the sample point and a sample point movement rule table that stores a movement rule of the sample point, in which the determination unit updates position information of the sample point on the basis of the sample point state table and the sample point movement rule table. The present technology can be applied to, for example, a distance measuring system or the like that detects a distance from a subject in a depth direction.