Radar Calibration via GNSS and Camera Target Detection
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Solution Overview
Problem
Calibrating radar equipment is time-consuming and burdensome due to the need for aligning radar equipment and another sensor at a common target, requiring complex and time-consuming procedures.
Innovation Solution
A calibration system that uses a first sensor, such as a GNSS device, and a radar sensor to determine radar calibration parameters by receiving GNSS and radar parameters at multiple positions, applying transformation matrices, and optimizing for Euclidean differences to minimize calibration errors, thereby determining accurate x, y, and yaw parameters without the need for complex test stations or imaging data correlation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If radar equipment is calibrated by aligning with another sensor at a common target, then calibration accuracy is improved, but calibration time and operational complexity increase significantly
Solution Approach 1:
The patent replaces the mechanical alignment process with a computational approach. Instead of physically aligning radar and camera sensors at a common target, the system uses image processing to detect the target, calculate its position in the image coordinate system, and compute transformation parameters mathematically. This substitution of mechanical alignment with computational geometry resolves the contradiction by maintaining accuracy while eliminating time-consuming manual alignment procedures.
Solution Approach 2:
The patent introduces an image processing intermediary that mediates between the physical target and the calibration process. The target is detected in the camera image, its coordinates are extracted, and these serve as an intermediary reference to compute the transformation between coordinate systems. This intermediary approach allows calibration without direct mechanical alignment between sensors, reducing time while preserving accuracy.
2Measurement precision
If radar equipment is calibrated using complex test stations or laboratory measurements, then calibration precision is improved, but device complexity and ease of operation deteriorate
Solution Approach 1:
The system performs calibration using resources already available on the vehicle - the camera and its image processing capabilities serve the dual purpose of both operation and calibration. The camera image itself is used to detect the target and provide calibration data, eliminating the need for separate complex test stations. This self-service approach maintains precision while reducing overall system complexity.
Solution Approach 2:
The camera system serves multiple functions: it captures images for normal operation and simultaneously provides target detection and position measurement for calibration. This multi-functionality eliminates the need for dedicated calibration equipment, reducing device complexity while maintaining calibration precision through the use of the same sensor for both purposes.
3Measurement precision
If radar equipment is calibrated through manual alignment procedures, then calibration accuracy is improved, but ease of operation and productivity decrease
Solution Approach 1:
The patent replaces manual mechanical alignment operations with automated image processing and computational calculations. The system automatically detects the target in the camera image, extracts its coordinates, and computes the transformation parameters without requiring operators to manually align sensors. This substitution maintains accuracy while dramatically improving ease of operation by eliminating complex manual procedures.
Solution Approach 2:
The system uses feedback from image processing to guide the calibration process. The target detection and position extraction from camera images provide feedback that automatically determines the calibration parameters, replacing manual alignment feedback loops. This automated feedback mechanism improves ease of operation while maintaining accuracy through continuous computational adjustment.
Data Source
AI summary
A calibration system for a radar sensor and a method of using the system are disclosed. The method may comprise (a) receiving, from a first sensor in a vehicle, a plurality of global navigation satellite system (GNSS) parameters, wherein the plurality of GNSS parameters define a unique terrestrial position of the first sensor; (b) receiving, from a radar sensor in the vehicle, a plurality of radar parameters, wherein the plurality of radar parameters define a position of a calibration target relative to the radar sensor; (c) repeating the receiving of (a) and (b) at additional unique terrestrial positions of the first sensor; (d) using the plurality of GNSS parameters received in (a) and (c) and the plurality of radar parameters received in (b) and (c), determining corresponding positions of the calibration target; and (e) using the corresponding positions of the calibration target, determining radar calibration parameters.