Adaptive Holographic Light Patterns for Reliable LIDAR Point Clouds
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Solution Overview
Problem
Conventional LIDAR systems face challenges in obtaining reliable point cloud data due to issues such as interference from background light, signal loss, and crosstalk, which affect the integrity of light return signals, leading to sub-optimal data quality.
Innovation Solution
The method involves optimizing the holographic light pattern by adjusting the density of light spots in the projected array based on signal validation criteria, such as signal-to-noise ratio and crosstalk, using a holographic projector to dynamically reconfigure the light patterns and adapt the illumination power distribution to improve data integrity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If the density of light spots in the holographic light pattern is increased, then the coverage area of the LIDAR system is improved, but the intensity of each individual light spot decreases leading to signal loss
Solution Approach 1:
The patent implements dynamic reconfiguration of the holographic light pattern by adjusting the density of light spots based on signal validation criteria. The system can switch between different light pattern densities (n spots vs m spots) to optimize performance for different scene conditions, making the light spot density a dynamic parameter rather than a fixed one.
Solution Approach 2:
The patent changes the parameter of light spot density in the holographic pattern to optimize the balance between coverage area and individual light spot intensity. By varying this parameter based on signal quality assessment, the system adapts to different operational conditions and maintains reliable point cloud data acquisition.
2Illumination intensity
If the density of light spots in the holographic light pattern is decreased, then the intensity of each light spot is improved, but the coverage area and data completeness deteriorate
Solution Approach 1:
The system dynamically adjusts light spot density based on real-time signal validation. When signal quality is insufficient, the system transitions to a pattern with fewer, more intense light spots (m < n) to improve signal-to-noise ratio, thereby maintaining coverage quality in challenging lighting conditions.
Solution Approach 2:
The patent modifies the light spot density parameter in response to signal validation outcomes. By changing this parameter adaptively, the system optimizes the trade-off between individual spot intensity and overall coverage, ensuring reliable measurements across varying scene conditions.
3Device complexity
If conventional LIDAR systems use fixed light patterns, then the system complexity is reduced, but the reliability of point cloud data deteriorates due to background light interference and signal loss
Solution Approach 1:
The patent implements a feedback mechanism where the system assesses signal validation criteria (such as signal-to-noise ratio and crosstalk levels) and uses this information to dynamically adjust the holographic light pattern. This closed-loop control improves data reliability by adapting to actual scene conditions rather than using fixed patterns.
Solution Approach 2:
The system transitions from static, fixed light patterns to dynamic, adaptive light patterns that reconfigure based on signal quality assessment. This dynamic behavior enables the system to maintain high reliability point cloud data by responding to changing environmental conditions such as background light interference.
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 the reliability of point cloud data by ensuring that each light spot intensity is optimized, reducing interference and signal loss, thereby improving the accuracy and efficiency of LIDAR systems.
Implementation Method 1
The spatial light modulator may be a liquid crystal device in which case each pixel is an individually-addressable liquid crystal cell having birefringence. Each pixel may modulate the amplitude and/or phase of light in accordance with a corresponding hologram pixel.
Implementation Method 2
The light is diffracted by the spatial light modulator. The complex light pattern emanating from the display device interferes at a replay plane to form a holographic reconstruction corresponding to the target image.
Implementation Method 3
The pattern captured on the photosensitive plate or film is referred to as a holographic recording or hologram. The hologram may be used to form a reconstruction of the object. The complex light pattern emanating from the display device interferes at a replay plane to form a holographic reconstruction corresponding to the target image.
Implementation Method 4
The fifth step comprises determining a time-of-flight in association with each light spot of the second light pattern.
Data Source
AI summary
A method for light detection and ranging that includes forming a first light pattern within a region of a scene by holographic projection. The first light pattern includes n light spots arranged in a regular array. A light return signal is received from each light detection element of an array of light detection elements directed at the region of the scene. The intensity of the light return signals is assessed. If the light return signals do not meet at least one signal validation criterion, a second light pattern is formed within the region of the scene by holographic projection. The second light pattern includes m light spots arranged in a regular array, wherein m≠n. A time-of-flight in association with each light spot of the second light pattern is then determined.