LiDAR Detection Threshold Control for Solar Noise Rejection
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Solution Overview
Problem
Autonomous vehicles face challenges in accurately detecting objects using LiDAR due to false detections from solar radiation and other light sources, varying noise levels, and the difficulty in setting a consistent detection threshold that accounts for environmental conditions, leading to missed detections of low-reflectivity or distant objects.
Innovation Solution
A dynamic detection threshold system for LiDAR in autonomous vehicles that adjusts the detection threshold based on multiple digital output signals, using a comparator and controller to aggregate data and determine optimal threshold values, reducing false detections and improving object detection accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a low detection threshold is set to detect distant or low-reflectivity objects, then detection sensitivity is improved, but false detections increase due to solar radiation and light sources
Solution Approach 1:
The patent implements a dynamic detection threshold that automatically adjusts based on ambient light conditions. The system monitors environmental factors such as solar radiation and light source intensity, then adaptively modifies the detection threshold to maintain optimal performance. This resolves the contradiction by making the threshold flexible rather than fixed, allowing high sensitivity when noise is low and higher robustness when noise is high.
Solution Approach 2:
The system changes the detection threshold parameter dynamically based on measured environmental conditions. By monitoring ambient light levels and other noise sources, the system adjusts the threshold parameter in real-time to balance between detecting weak signals (distant/low-reflectivity objects) and rejecting noise (solar radiation/light sources).
2Reliability
If a high detection threshold is set to reduce false detections, then reliability is improved, but detection sensitivity decreases causing missed detections of low-reflectivity or distant objects
Solution Approach 1:
The dynamic threshold adjustment mechanism allows the system to maintain high reliability when ambient noise is high by increasing the threshold, while preserving detection sensitivity when noise is low by decreasing the threshold. This resolves the contradiction by making the threshold adaptive to environmental conditions rather than statically high.
Solution Approach 2:
The system incorporates feedback from environmental sensors that monitor solar radiation, light sources, and other noise factors. This feedback loop enables the system to automatically adjust the detection threshold to maintain the appropriate balance between reliability and sensitivity based on current operating conditions.
3Device complexity
If a single fixed threshold is used for all environmental conditions, then device complexity is reduced, but adaptability to varying noise levels throughout the day deteriorates
Solution Approach 1:
The system employs self-service by automatically monitoring environmental conditions and adjusting its own detection threshold without external intervention. The LiDAR system includes built-in sensors and processing capability to autonomously adapt to changing noise levels, eliminating the need for manual threshold configuration while maintaining high adaptability.
Solution Approach 2:
The detection system performs multiple functions: it detects objects while simultaneously monitoring environmental noise conditions and automatically adjusting its detection parameters. This multi-functionality allows a single system to handle both object detection and environmental adaptation, reducing the need for separate threshold management mechanisms.
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 enhances object detection precision by minimizing false positives and negatives, especially under varying environmental conditions, without requiring high-speed ADCs, thus optimizing LiDAR performance.
Implementation Method 1
at least one light emitter configured to emit pulses of light and at least one light detector configured to receive reflected pulses of light
Implementation Method 2
at least one light detector configured to receive reflected pulses of light and generate analog output signals based on the reflected pulses of light
Implementation Method 3
A comparator may be configured to receive the analog output signals from the light detector and generate digital output signals based on the analog output signals and a threshold
Data Source
AI summary
A system for a dynamic detection threshold for a sensor of an autonomous vehicle including a Light Detection and Ranging (LiDAR) system of an autonomous vehicle, the LiDAR system comprising at least one light emitter configured to emit pulses of light and at least one light detector configured to receive reflected pulses of light and generate analog output signals based on the reflected pulses of light, and a comparator configured to receive the analog output signals from the light detector and generate digital output signals based on the analog output signals and a threshold, and a controller configured to adjust the threshold, receive at least one further digital output signal of the digital output signals from the comparator based on the threshold as adjusted, the at least one further digital output signal comprising a plurality of further digital output signals, and repeatedly adjust the threshold and receive a respective further digital output signal of the plurality of further digital output signals based on the threshold as adjusted.