Environment Sensor Calibration Check Using Periodic Feature Frequency
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Solution Overview
Problem
Calibration of surroundings sensors in transportation vehicles degrades over time due to geometric changes and environmental influences, affecting the accuracy of driver assistance systems and object detection.
Innovation Solution
A method and device that synchronize sensor data from surroundings sensors, transform it into a frequency domain, and compare frequency and phase angles to detect decalibration by identifying differences in detected periodic features, such as guardrails or crosswalks, using Fourier transforms and threshold values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensor calibration is performed during vehicle production, then initial measurement precision is achieved, but calibration accuracy degrades over time due to geometric changes and environmental influences
Solution Approach 1:
The system performs preliminary detection of periodic features (guardrails, crosswalks, lane markings) in the environment before calibration degradation becomes critical. By continuously monitoring these known periodic structures, the system can detect calibration drift early and trigger recalibration procedures, preventing complete loss of measurement precision during the vehicle's service life.
Solution Approach 2:
The invention implements a feedback mechanism where sensor data is continuously analyzed to detect periodic features, compare detected parameters against expected values, and identify calibration deviations. This feedback loop enables real-time detection of calibration degradation and triggers appropriate corrective actions, maintaining measurement precision throughout the operational period.
2Measurement precision
If Fourier transformation is applied to sensor data for calibration checking, then detection precision of decalibration is improved, but computational complexity increases
Solution Approach 1:
The system extracts only the essential periodic features from complex sensor data using Fourier transformation, focusing on specific frequency components that correspond to known environmental structures (guardrails, crosswalks). By isolating and analyzing only these relevant periodic signals rather than processing entire datasets, the method achieves high decalibration detection precision while reducing unnecessary computational complexity.
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
Effectively checks the calibration of surroundings sensors by identifying decalibration through frequency and phase angle comparisons, ensuring accurate sensor data fusion and maintaining the functionality of driver assistance systems.
Implementation Method 1
a control unit (4), wherein the control unit (4) is designed for receiving sensor data (3-x) of the surroundings sensors (2-x), detecting periodic features at least for at least one distinguished area in the sensor data (3-x) of the surroundings sensors (2-x) belonging to the same surroundings, carrying out a transformation, in each case, of sensor data (3-x) corresponding to the at least one distinguished area to a frequency domain at least for the at least one distinguished area
Data Source
AI summary
A device, transportation vehicle, and method for checking a calibration of surroundings sensors, wherein the surroundings sensors at least partially detect similar surroundings and provide mutually time-synchronized sensor data, periodic features at least for at least one distinguished area are detected in the sensor data of the surroundings sensors belonging to the same surroundings, a transformation of the sensor data corresponding to the at least one distinguished area to a frequency domain is carried out at least for the at least one distinguished area, a frequency and/or a phase angle of the periodic features is determined in the sensor data transformed to the frequency domain, a decalibration of the surroundings sensors is detected based on a comparison of the determined frequencies and/or of the determined phase angles, and a result of the check is provided.