Vehicle Sensor Calibration Using Detection Alignment
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Solution Overview
Problem
Current methods for calibrating radar transceivers in vehicles, especially for forward-looking sensors with a field of view below 180°, are inaccurate due to dependence on vehicle speed and require ground truth values based on minimum detected distances, which can be challenging to obtain, leading to significant errors in bearing estimation, particularly in safety-critical applications like autonomous driving.
Innovation Solution
A vehicle sensor system that processes a sequence of detections to align them along a common line, estimating an error angle between the common line and the movement direction, allowing for calibration without relying on ground truth values based on minimum detected distances, and can handle curvatures and pre-determined calibration areas for efficient error determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If ground truth values are determined based on minimum detected distance from the vehicle to the stationary target, then calibration accuracy is improved, but the method cannot be applied to forward-looking sensors with field of view below 180°
Solution Approach 1:
Instead of determining ground truth based on minimum distance (which requires passing the target), the patent inverts the approach by using maximum distance observations. The calibration is performed by observing the target at the farthest point in the sensor's field of view, which is always accessible for forward-looking sensors regardless of their narrow field of view.
Solution Approach 2:
The patent performs preliminary alignment of the vehicle's movement direction with the target object before calibration. By ensuring the vehicle moves directly toward or away from the target, the system establishes a known geometric relationship that enables accurate calibration without requiring the vehicle to pass the target or achieve minimum distance observations.
2Device complexity
If velocity of the vehicle is used for calibration, then the process is simplified, but calibration accuracy deteriorates due to errors in vehicle speed determination
Solution Approach 1:
The patent extracts and eliminates the dependency on vehicle velocity measurements from the calibration process. By using purely geometric relationships based on sensor observations of a stationary target and vehicle position changes, the method removes the error-prone velocity measurement component while maintaining calibration effectiveness.
Solution Approach 2:
The patent introduces the stationary target as an intermediary reference object that mediates the calibration process. Instead of directly using vehicle velocity, the system uses the target's known stationary position and the vehicle's observed changes in range and bearing to the target as intermediate measurements that lead to accurate calibration without requiring direct velocity input.
3Measurement precision
If sequence of detections is processed to align along common line, then calibration accuracy for narrow field of view sensors is improved, but computational complexity increases
Solution Approach 1:
The patent uses a simplified geometric model that processes only the essential elements needed for calibration: the sequence of detections, the identified common line, and the error angle. By focusing on this minimal sufficient set of computations rather than comprehensive processing, the system achieves accurate calibration with limited computational resources suitable for embedded automotive systems.
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 enables accurate calibration of angle measurements for forward-looking sensors with reduced computational complexity, allowing for the use of sensors with narrower fields of view and quick error determination, even in complex vehicle paths, thereby improving safety in autonomous driving applications.
Implementation Method 1
radar transceivers are configured to estimate distances between a radar transceiver and detected objects, for instance based on transmission of a frequency modulated continuous wave (FMCW) signal. The relative velocity of the detected object with respect to the radar transceiver can also be determined based on a Doppler shift in received waveforms.
Implementation Method 2
The relative velocity of the detected object with respect to the radar transceiver can also be determined based on a Doppler shift in received waveforms.
Implementation Method 3
This bearing estimation can be achieved by using array antennas configured to determine relative phases of waveform components received at the different antenna elements in the antenna array.
Data Source
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AI summary
The present disclosure relates to a method for calibrating an angle measurement (122) of a vehicle sensor (110) in a vehicle (100) travelling in a movement direction (D). The method comprises obtaining (S100) a sequence of detections (210) associated with a target object (140), and aligning (S200) the detections (210) along a common line (245). The method further comprises estimating (S300) an error angle (α) between the common line (245) and the movement direction (D), and calibrating (S400) the angle measurement (122) based on the estimated error angle (α).