Lidar Intensity Calibration for Uniform Multi-Channel Returns
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Solution Overview
Problem
Lidar intensity values in autonomous vehicles are non-uniform due to signal noise and other factors, leading to inaccuracies in localization, perception, and motion planning.
Innovation Solution
A method for off-line calibration of Lidar intensity values using a data collection stage to gather intensity values at various power levels and angles, with a linear model to compute calibration multipliers and bias values for each channel, allowing for the derivation of calibrated intensity values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If Lidar intensity values are used directly from multiple channels, then the system provides comprehensive environmental mapping capability, but the intensity values are non-uniform due to signal noise and alignment variations
Solution Approach 1:
The patent applies preliminary action by performing calibration computations before actual Lidar operation. During an offline calibration stage, the system collects intensity data from all channels and computes calibration multipliers and bias values using a linear model. These pre-computed calibration parameters are then stored and applied during runtime to correct intensity values, eliminating the need for complex real-time calibration computations and achieving uniform intensity values across channels.
2Measurement precision
If calibration computations are performed in real-time, then intensity values can be corrected for uniformity, but the processing time and computational load increase
Solution Approach 1:
The patent performs all calibration computations during an offline calibration stage before actual Lidar operation. The system collects intensity data from multiple channels and uses a linear model to compute calibration multipliers and bias values. These calibration parameters are stored and automatically applied during runtime without requiring real-time computation, thus achieving accurate intensity calibration while minimizing processing time loss.
3Measurement precision
If multiple calibration parameters are computed for each channel, then intensity uniformity across channels is improved, but the data processing complexity increases
Solution Approach 1:
The patent transforms the raw intensity values into calibrated intensity values by applying parameter changes through calibration multipliers and bias values. The linear model computes these parameters based on collected intensity data from multiple channels, establishing a mathematical relationship between raw and calibrated values. This parameter transformation approach simplifies the calibration process by reducing it to straightforward multiplication and addition operations during runtime.
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 method aligns Lidar intensity returns with the reflectivity of surfaces and objects, providing more accurate information for improved vehicle localization, perception, and motion planning.
Implementation Method 1
The Lidar unit also includes circuitry to measure the time of flight—i.e., the elapsed time from emitting the laser signal to detecting the return signal. The time of flight is used to determine the distance of the Lidar unit to the detected object.
Implementation Method 2
During operation, each channel emits a laser signal into the environment that is reflected off of the surrounding environment back to the detector. Some Lidar units also measure the intensity of the return signal. The intensity of the return signal provides information about the surface reflecting the signal
Data Source
AI summary
Aspects of the present disclosure involve a vehicle computer system comprising a computer-readable storage medium storing a set of instructions, and a method for light detection and ranging (Lidar) intensity calibration. The method includes collecting a data set comprising a plurality of raw intensity values output by a channel of a Lidar unit at a particular power level from among multiple power levels at which the channel is capable of operating. The method further includes using a linear model to compute a calibration multiplier and a bias value for the particular power level of the channel. During operation of the vehicle, calibrated intensity values are determined by applying the linear model to subsequent raw intensity values output by the channel at the particular power using the determined calibration multiplier and bias value.