LiDAR Pixel Array Macro Block Segmentation for Laser Spot Detection
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Solution Overview
Problem
Existing LiDAR systems face inefficiencies in laser spot finding due to high data throughput, power consumption, and complex circuitry, particularly in time-of-flight measurements.
Innovation Solution
The method involves dividing a pixel array into macro blocks, initializing photon counters, and performing ambient and laser photon count measurements to selectively activate pixels for time-of-flight measurements, thereby reducing data throughput and power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If all pixels in the pixel array are used for time-of-flight measurements, then measurement coverage is improved, but data throughput and power consumption increase
Solution Approach 1:
The pixel array is divided into multiple macro blocks, with each macro block containing multiple pixels. This segmentation allows the system to process and evaluate pixels in manageable groups, enabling selective activation of only those pixels within macro blocks that are most likely to receive laser spots, thereby reducing overall data throughput while maintaining measurement accuracy.
Solution Approach 2:
Different macro blocks are selectively activated based on ambient photon count measurements. Instead of uniformly processing all pixels, the system applies different quality levels of processing to different regions - only activating macro blocks that show potential laser spot returns - which reduces data throughput while preserving necessary measurement coverage.
2Measurement precision
If all pixels are activated for time-of-flight measurements, then measurement coverage is improved, but power consumption increases
Solution Approach 1:
The pixel array is divided into multiple macro blocks, with each macro block containing multiple pixels. This segmentation allows the system to process and evaluate pixels in manageable groups, enabling selective activation of only those pixels within macro blocks that are most likely to receive laser spots, thereby reducing overall data throughput while maintaining measurement accuracy.
Solution Approach 2:
Different macro blocks are selectively activated based on ambient photon count measurements. Instead of uniformly processing all pixels, the system applies different quality levels of processing to different regions - only activating macro blocks that show potential laser spot returns - which reduces data throughput while preserving necessary measurement coverage.
3Measurement precision
If ambient photon count measurement is performed for all pixels, then laser spot finding accuracy is improved, but computational load increases
Solution Approach 1:
The pixel array is divided into multiple macro blocks, with each macro block containing multiple pixels. This segmentation allows the system to process and evaluate pixels in manageable groups, enabling selective activation of only those pixels within macro blocks that are most likely to receive laser spots, thereby reducing overall data throughput while maintaining measurement accuracy.
Solution Approach 2:
Instead of performing ambient photon count measurements and full time-of-flight processing on all pixels, the system performs partial action by only processing macro blocks that meet certain criteria. This reduces computational load while maintaining sufficient accuracy for laser spot identification.
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 system efficiency and memory bandwidth while decreasing computational load, data throughput, and system latency, thereby simplifying circuit complexity in LiDAR systems.
Implementation Method 1
LiDAR systems emit their own laser pulses
Implementation Method 2
The system measures the time it takes for the pulses to return, allowing it to create a detailed 3D map of the environment
Implementation Method 3
LiDAR works by aiming a laser at an object, measuring the speed and intensity of the reflected signal
Data Source
AI summary
Provided are systems, methods, and apparatuses for up and down counting for efficient laser spot finding in LiDAR. In one or more examples, the systems, devices, and methods include dividing a pixel array into multiple macro blocks, a first macro block including at least a first pixel and a second pixel of the pixel array and initializing a first photon counter of the first pixel and a second photon counter of the second pixel. The systems, devices, and methods include determining an ambient photon count of the first photon counter based on performing a set number of ambient cycles with a laser transmitter off, determining a laser photon count of the first photon counter with the laser transmitter on, and using the first pixel to perform a time-of-flight measurement based on the first pixel being selected according to the ambient photon count and the laser photon count.