ToF Distance Sensing with Region-Specific Depth Coefficients
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Solution Overview
Problem
Conventional Time of Flight (ToF) sensors use the same computation coefficients for distance measurement regardless of object distance, leading to reduced accuracy for both short and long distance measurements.
Innovation Solution
A distance measuring device with an array of light-receiving elements and computing units that generate depth information using computation coefficients tailored to specific regions within the array, optimizing coefficients for noise filtering and threshold settings based on expected object distances.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the same computation coefficients are used for all regions in the array, then the device complexity is reduced, but the distance measurement precision deteriorates
Solution Approach 1:
The light-receiving element array is divided into multiple regions, and each region is assigned dedicated computing units with region-specific computation coefficients. This segmentation allows each region to be optimized for its typical distance range (near, mid, or far), resolving the contradiction by improving measurement precision through region-specific coefficients while managing complexity through systematic division of the array into manageable segments.
Solution Approach 2:
Different computation coefficients are applied to different regions of the array based on their specific characteristics and typical measurement distances. Each region has tailored coefficients that optimize performance for its local conditions, thereby improving overall measurement precision without requiring a single complex universal coefficient set.
2Measurement precision
If region-specific computation coefficients are used, then the distance measurement precision is improved, but the device complexity increases
Solution Approach 1:
The array is segmented into multiple regions with dedicated computing units, allowing region-specific coefficients to be applied. This segmentation manages the complexity by organizing the system into modular regions rather than requiring a single complex processing unit, thus improving precision while keeping the overall architecture manageable.
Solution Approach 2:
Each computing unit is designed to handle its specific region with optimized coefficients, but the overall system maintains universality by using the same basic computing unit architecture across all regions. This multi-functionality approach allows the system to achieve region-specific optimization without proportionally increasing overall device complexity.
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 enhances distance measurement accuracy by using region-specific computation coefficients, reducing noise interference and improving resolution for both short and long distance measurements.
Implementation Method 1
an array in which a plurality of light-receiving elements are arranged, each of the light-receiving elements being configured to detect incidence of a photon
Implementation Method 2
the time (hereinafter referred to as the time of flight) taken from light emission from a light source to incidence of reflected light (hereinafter referred to as echo) on the SPADs is measured
Data Source
AI summary
Reduction in distance measurement accuracy is decreased. A distance measuring device according to embodiments includes an array (142) in which a plurality of light-receiving elements each configured to detect incidence of a photon are arranged, a read circuit (22) configured to read a detection signal from each of the light-receiving elements, and a plurality of computing units (15-1 to 15-4) configured to generate depth information on a distance to an object present in an angle of view in different regions in the array, based on the detection signals read from the light-receiving elements belonging to the different regions. The computing units generate the depth information using computation coefficients (16-1 to 16-4) at least partially different from each other.