Flash LiDAR Binning Processing for Memory Reduction
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Solution Overview
Problem
Existing flash LiDAR technologies face challenges in reducing memory capacity while maintaining ranging accuracy and resolution, as simple binning processing decreases resolution and previous methods either require significant memory or fail to improve essential distance resolution.
Innovation Solution
A ranging device and method that incorporates a light receiving unit, binning processing unit, data accumulation unit, reflected light determination unit, and distance calculation unit to convert signals from multiple pixels into pixel blocks, accumulating time and frequency information to determine reflected light and calculate distances, thereby reducing memory requirements while maintaining accuracy and resolution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If simple binning processing is performed to reduce memory capacity, then memory capacity is reduced, but resolution decreases
Solution Approach 1:
The light receiving unit is divided into multiple unit regions, each processed independently through binning to create pixel blocks. This segmentation allows selective application of processing techniques to different regions, enabling memory reduction while preserving resolution in critical areas.
Solution Approach 2:
Different processing strategies are applied to different unit regions based on their characteristics. Some regions undergo binning for memory reduction, while others maintain full resolution through alternative processing, achieving local optimization of both memory usage and resolution.
2Measurement precision
If histogram information is generated for all pixels to improve ranging accuracy, then ranging accuracy is improved, but memory capacity increases
Solution Approach 1:
Multiple unit regions are merged into pixel blocks through binning processing, reducing the total number of histogram data structures needed. This merging maintains ranging accuracy by preserving distance information while reducing memory requirements through consolidated data representation.
Solution Approach 2:
Instead of applying full-resolution histogram processing to all pixels, the system applies binning processing to reduce memory usage while maintaining sufficient ranging accuracy through selective processing of unit regions and pixel blocks.
3Quantity of substance
If binning processing is applied to multiple pixels as one pixel to reduce memory capacity, then memory capacity is reduced, but resolution decreases
Solution Approach 1:
The image is segmented into multiple unit regions that are processed through binning to form pixel blocks. This segmentation allows the system to manage the trade-off between memory reduction and information preservation by organizing pixels into structured blocks rather than uniform binning.
Solution Approach 2:
The binning process transforms spatial information into a block-based structure, adding a hierarchical dimension to the data organization. This allows memory reduction through consolidation while preserving spatial relationships through the block structure and subsequent processing stages.
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 effectively reduces memory capacity while preserving ranging accuracy and resolution by processing signals from multiple pixels into pixel blocks, enhancing the ability to detect reflected light and calculate distances with improved efficiency.
Implementation Method 1
detecting reflected light from the ranging target object
Implementation Method 2
a light receiving unit including a plurality of pixels configured to detect a pulsed light
Implementation Method 3
a binning processing unit configured to convert a plurality of signals output from a plurality of unit regions each including at least one pixel into a plurality of signals corresponding to a plurality of pixel blocks
Implementation Method 4
measuring a distance to the target object from a relationship between a light emission timing of the surface light source and a detection timing of the reflected light from the target object
Implementation Method 5
The integration of the reflected light is performed by generating histogram information representing the relationship between the distance and the frequency
Data Source
AI summary
A ranging device includes a light receiving unit including pixels for detecting pulsed light reflected by an object, a binning processing unit for converting signals output from unit regions each including at least one pixel into signals corresponding to pixel blocks each including at least two unit regions, a data accumulation unit for accumulating, for each pixel block, information indicating a relationship between a class determined according to a time period from emission to detection of the pulsed light and a frequency, based on the signals output from the binning processing unit, a reflected light determination unit for extracting, for each of the unit regions, a candidate of a class including a signal based on a reflected light from the object from the information, and a distance calculation unit configured to calculate a distance to the object corresponding to each of the unit regions based on the candidate.