LiDAR Sunlight Noise Suppression via 3D Invalid Region
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Solution Overview
Problem
Existing monitoring systems using LiDAR devices face erroneous detection issues due to noise caused by the sun, as they lack effective countermeasures for sunlight interference, leading to inaccurate shape determination of targets in outdoor facilities.
Innovation Solution
A monitoring system that calculates a straight line connecting the light source and the LiDAR device, defines a three-dimensional invalid region affected by noise, and processes point cloud data to exclude this region, thereby preventing erroneous detection by identifying and removing noise-affected data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If LiDAR performs scanning in the direction of the sun to acquire point cloud data, then the monitoring coverage is improved, but sunlight enters the receiver causing noise and measurement errors
Solution Approach 1:
The system performs preliminary actions by calculating the straight line connecting the light source and LiDAR, and defining the invalid region before processing point cloud data. This preventive approach identifies noise-affected areas in advance, allowing the system to exclude them during monitoring without affecting the overall measurement process
Solution Approach 2:
The invention extracts and removes the harmful component (sunlight noise) from the measurement system by defining a three-dimensional invalid region around the straight line connecting the light source and LiDAR. This separation allows the system to process only valid point cloud data, eliminating the negative impact of sunlight interference on measurement precision
2Measurement precision
If the system defines an invalid region to exclude noise-affected data, then measurement precision is improved, but the device complexity increases due to additional calculation and region definition processes
Solution Approach 1:
The system changes parameters by introducing coordinate-based spatial parameters (straight line equation, invalid region boundaries) to define the noise-affected area. This mathematical parameterization allows the system to automatically determine valid and invalid regions based on geometric relationships, improving precision without requiring complex hardware modifications
Solution Approach 2:
The invention introduces an intermediary computational layer that calculates the invalid region based on the straight line connecting the light source and LiDAR. This intermediary process acts as a filter between the raw point cloud data and the final monitoring results, managing system complexity by providing a clear mathematical criterion for data validation
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 system effectively suppresses erroneous detection by isolating and removing noise-affected data, ensuring accurate monitoring results even in conditions where sunlight interferes with LiDAR measurements.
Implementation Method 1
LiDAR irradiates laser light on a target and receives the light reflected from the surface of the target, thereby performing measurement of the distance to the irradiation point based on the time difference between irradiation of the laser light and reception of the reflected light
Implementation Method 2
LiDAR irradiates laser light on a target and receives the light reflected from the surface of the target
Data Source
AI summary
A monitoring system according to the present disclosure includes: a straight line calculation unit configured to calculate a straight line connecting three-dimensional coordinates of a light source and three-dimensional coordinates of a three-dimensional measuring device configured to measure a target to be measured; an invalid region determination unit configured to define a three-dimension invalid region in which point cloud data acquired by the three-dimensional measuring device is invalid based on the straight line; and a point cloud data processing unit configured to monitor the target to be measured based on the acquired point cloud data and the three-dimension invalid region.