LiDAR Sensor Binning Layout for Noise-Compensated Distance Sensing
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Solution Overview
Problem
Current LIDAR systems for autonomous vehicles face limitations in detecting objects at a distance due to eye safety regulations, which restrict the maximum illumination power, and struggle with environmental conditions like rain, fog, and snow, affecting their reliability in providing accurate data.
Innovation Solution
A LIDAR system that includes a processor to control light sources, receive signals from sensors both within and outside the light spot boundary, determine light noise, and compensate for noise to accurately calculate object distances, while also detecting obstructions and adjusting light projection to improve visibility through protective windows.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the maximum illumination power of LIDAR systems is increased to improve detection of far-away objects, then the detection distance and reliability are improved, but the eye safety regulations are violated causing thermal damage to the retina
Solution Approach 1:
The sensor array is divided into multiple individual sensors, each capturing a portion of the reflected light. This segmentation allows the system to distribute the light collection across multiple sensors rather than requiring a single sensor to handle all light, enabling improved detection capability without increasing illumination power to unsafe levels.
Solution Approach 2:
The patent transitions from analyzing light intensity alone to analyzing the spatial distribution pattern of light across multiple sensors. By adding the spatial dimension of light distribution across the sensor array, the system can distinguish between reflected light from objects and noise from protective windows, improving detection accuracy without increasing power.
2Reliability
If LIDAR systems operate in environmental conditions like rain, fog, and snow, then the system must maintain reliability, but environmental particles cause light scattering and noise that reduce detection accuracy
Solution Approach 1:
The system analyzes the spatial distribution pattern of light across the sensor array and uses this information to distinguish between reflected light from objects and noise from environmental particles. The processor compares the observed light distribution against expected patterns to identify and filter out noise, maintaining detection accuracy in challenging environmental conditions.
Solution Approach 2:
The patent detects changes in the spatial distribution pattern of light across the sensor array, analogous to detecting color changes. By monitoring how the light distribution pattern varies across different sensors and time periods, the system can identify environmental noise and distinguish it from genuine object reflections, maintaining reliability in rain, fog, and snow.
3Measurement precision
If LIDAR systems use sensors only within the light spot boundary to maximize signal-to-noise ratio, then detection accuracy is improved, but light noise from protective windows and environmental conditions cannot be effectively identified and compensated
Solution Approach 1:
The sensor array is segmented into multiple individual sensors that can be selectively used. Sensors both within and outside the light spot boundary are utilized, with each sensor contributing to different aspects of the detection process. This segmentation enables the system to separate signal from noise by comparing readings across multiple sensors.
Solution Approach 2:
Sensors located outside the light spot boundary serve as intermediary elements that detect only noise from protective windows and environmental conditions. By using these intermediary sensors to characterize the noise environment, the system can then compensate for this noise in the readings from sensors within the light spot, improving overall reliability.
4Strength
If LIDAR systems project light through protective windows, then the system is protected from environmental damage, but obstructions on the protective window cause light scattering and detection errors
Solution Approach 1:
The system continuously monitors the spatial distribution pattern of light across the sensor array and uses this feedback to detect obstructions on the protective window. When obstructions are detected, the system adjusts its processing to compensate for the light scattering caused by these obstructions, maintaining detection accuracy while preserving the protective function of the window.
Solution Approach 2:
The system performs preliminary detection of obstructions on the protective window by analyzing the light distribution pattern before conducting main object detection. By identifying and characterizing window obstructions in advance, the system can pre-compensate for their effects, improving the accuracy of subsequent object detection without compromising the protective function.
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
Enhances the reliability and accuracy of LIDAR systems in various environmental conditions by effectively compensating for light noise and detecting obstructions, thereby improving the detection of objects at a distance while ensuring eye safety.
Implementation Method 1
receive from at least one first sensor first signals associated with light projected by the at least one light source and reflected from an object in the field of view
Data Source
AI summary
In some embodiments, a LIDAR system may include at least one processor configured to control at least one light source for projecting light toward a field of view and receive from at least one first sensor first signals associated with light projected by the at least one light source and reflected from an object in the field of view, wherein the light impinging on the at least one first sensor is in a form of a light spot having an outer boundary. The processor may further be configured to receive from at least one second sensor second signals associated with light noise, wherein the at least one second sensor is located outside the outer boundary; determine, based on the second signals received from the at least one second sensor, an indicator of a magnitude of the light noise; and determine, based on the indicator the first signals received from the at least one first sensor and, a distance to the object.