Lidar Internal Reference Target Calibration via Diffuser and IIR Filtering
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Solution Overview
Problem
Lidar systems face challenges due to temperature drifts and external factors affecting laser power and pulse delay, leading to inaccuracies in distance measurements and radiometry in point clouds, especially with internal reference targets being close to detectors and under acute angles, causing speckle noise and challenging accurate measurements.
Innovation Solution
The implementation of laser power monitoring (LPM) and laser pulse delay compensation techniques using an internal reference target, which involves sampling and signal processing to extract accurate pulse energy and range information, and employing a sequential state machine with an infinite impulse response (IIR) filter to filter out noise and adaptively adjust sampling based on scan patterns and horizon tracking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If an internal reference target is used for laser power monitoring, then measurement accuracy is improved, but speckle noise increases due to the target being close to detectors and under acute angles
Solution Approach 1:
A diffuser is introduced as an intermediary element between the internal reference target and the detector. The diffuser scatters the reflected light, transforming the coherent speckle pattern into a more uniform distribution, thereby reducing speckle noise while preserving the calibration function of the reference target
Solution Approach 2:
The system transitions from direct optical path calibration to a multi-dimensional approach by incorporating temporal filtering (IIR filter) and spatial processing (scan pattern analysis). This adds time and processing dimensions to the calibration process, enabling noise reduction while maintaining measurement accuracy
2Stability of the object's composition
If temperature drift compensation is implemented, then radiometric stability is improved, but device complexity increases due to additional monitoring and processing components
Solution Approach 1:
The lidar system performs self-calibration by using its own internal reference target and processing capabilities to monitor and compensate for temperature drifts. The system automatically adjusts radiometric characteristics without requiring external calibration equipment, making the system self-sufficient
Solution Approach 2:
A feedback loop is established where the internal reference target provides continuous monitoring data on laser power and pulse delay variations. This information is fed back to the processing system, which applies real-time corrections to maintain radiometric stability despite temperature changes
3Measurement precision
If selective sampling with IIR filter is used, then noise reduction is improved, but processing time increases due to adaptive filtering and scan pattern analysis
Solution Approach 1:
The system pre-defines scan patterns and prepares filtering parameters in advance based on expected operational conditions. By anticipating typical scanning scenarios and pre-configuring processing parameters, the system reduces real-time processing requirements while maintaining effective noise filtering
Solution Approach 2:
The filtering and sampling parameters are made dynamic rather than static. The IIR filter coefficients and sampling rates are adaptively adjusted based on the actual scan pattern and detected signal characteristics, allowing the system to optimize processing speed for different operational scenarios
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 stabilizes radiometric characteristics in lidar point clouds, effectively compensating for temperature drifts and external factors, reducing noise and improving measurement accuracy by accurately monitoring and correcting laser power and pulse delay variations.
Implementation Method 1
a light source configured to emit light pulses
Implementation Method 2
The scanner is configured to scan the emitted light pulses across an internal reference target internal to the system. A detector is configured to detect light that is at least a portion of light scattered by the internal reference target
Implementation Method 3
employing a sequential state machine with an infinite impulse response (IIR) filter to filter out noise and adaptively adjust sampling based on scan patterns and horizon tracking
Data Source
AI summary
A lidar system is disclosed. The system comprises a light source configured to emit light pulses. The system comprises a scanner configured to scan the emitted light pulses across an internal reference target internal to the system. The system comprises a detector configured to detect light that is at least a portion of light scattered by the internal reference target from at least a portion of the emitted light pulses. The system comprises a processor configured to selectively gather detected optical property values of the detected light corresponding to a selective portion of the emitted light pulses scanned across the internal reference target and use the selectively gathered detected optical property values to determine one or more calibration values.