Motor-Scan LiDAR Threshold Switching for Solar Noise Filtering
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Solution Overview
Problem
High-sensitivity motor scan type LiDAR systems face challenges in noise removal due to physical signal processing time limitations and high power consumption, making it difficult to effectively remove solar noise without using multi-light transmission algorithms.
Innovation Solution
A LiDAR noise removal apparatus that dynamically adjusts a threshold voltage based on the number of signal receptions, allowing for effective noise removal without a separate analog-digital converter, and reduces manufacturing costs by varying the threshold voltage for long-range and short-range targets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multi-light transmission algorithm is used to remove solar noise in high-sensitivity LiDAR, then noise removal effectiveness is improved, but signal processing time increases and power consumption increases
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing threshold values for different distance ranges before actual signal processing. The controller has previously established a mapping between distance ranges and threshold values, so during operation it only needs to lookup and apply the appropriate threshold without performing complex multi-light transmission algorithms, thus removing noise effectively while maintaining fast processing speed.
Solution Approach 2:
The patent applies local quality by using different threshold values for different distance ranges (local regions of the detection space). Instead of applying a uniform complex noise removal algorithm across all signals, the system divides the detection range into multiple distance bands and applies locally optimized thresholds to each band, achieving effective noise removal in each local region while reducing overall computational burden.
2Reliability
If multi-light transmission algorithm is used to remove solar noise in high-sensitivity LiDAR, then noise removal effectiveness is improved, but power consumption increases
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing threshold values for different distance ranges before actual signal processing. The controller has previously established a mapping between distance ranges and threshold values, so during operation it only needs to lookup and apply the appropriate threshold without performing complex multi-light transmission algorithms, thus removing noise effectively while maintaining fast processing speed.
Solution Approach 2:
The patent applies local quality by using different threshold values for different distance ranges (local regions of the detection space). Instead of applying a uniform complex noise removal algorithm across all signals, the system divides the detection range into multiple distance bands and applies locally optimized thresholds to each band, achieving effective noise removal in each local region while reducing overall computational burden.
3Reliability
If threshold voltage is adjusted dynamically based on signal reception count, then noise removal effectiveness is improved, but device complexity increases
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing threshold values for different distance ranges before actual signal processing. The controller has previously established a mapping between distance ranges and threshold values, so during operation it only needs to lookup and apply the appropriate threshold without performing complex multi-light transmission algorithms, thus removing noise effectively while maintaining fast processing speed.
Solution Approach 2:
The patent applies parameter changes by dynamically adjusting the threshold voltage parameter based on the counted number of signal receptions. The controller monitors the signal reception count and switches between different pre-established threshold values corresponding to different reception ranges, thereby adapting the noise removal sensitivity to current environmental conditions without requiring complex real-time calculations.
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 apparatus efficiently removes noise in limited time, reducing power consumption and manufacturing costs, while maintaining high sensitivity for both long-range and short-range targets, thus overcoming the limitations of traditional LiDAR noise removal methods.
Implementation Method 1
a light receiving device provided in a lidar to output an electrical signal corresponding to an input light signal
Data Source
AI summary
A lidar noise removal apparatus outputs an electrical signal corresponding to an input light signal and compares the electrical signal with a threshold voltage to detect an electrical signal greater than the threshold voltage. The apparatus variably adjusts the threshold voltage based on a result of comparing the number of receptions of the electrical signal detected through the comparative device with a preset first reference number of times.