Radar-Camera Calibration Using Map-Based Global Coordinates

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Solution Overview

Problem

Current calibration methods for single-radar and single-camera sensing systems are inefficient and require manual field calibration, which is time-consuming and reduces overall efficiency.

Innovation Solution

A method for sensor calibration that utilizes radar measurement data and map information to determine the calibration values of both the radar and camera, eliminating the need for manual field calibration by aligning the sensors' coordinates in a unified global system.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual field calibration is used for single-radar and single-camera sensing systems, then calibration accuracy can be achieved, but calibration efficiency is reduced and time consumption increases

Engineering Contradiction:

Improvecalibration accuracyVSAvoidcalibration efficiency

Core Design Contradiction:

Measurement precisionVSProductivity

Solution Approach 1:

The system performs self-calibration by automatically determining calibration parameters through coordinate transformation between radar and camera measurement data of the same target, eliminating the need for manual field calibration operations while maintaining accuracy

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The calibration process is performed preliminarily during system setup or initialization phases using automated algorithms, so that subsequent sensing operations can proceed without repeated manual calibration interventions

Inventive Principle:

Principle #10Preliminary action

2Reliability

If manual field calibration is used for sensor calibration, then calibration can be performed, but the process is time-consuming and labor-intensive

Engineering Contradiction:

Improvecalibration reliabilityVSAvoidcalibration time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

Manual mechanical calibration operations are replaced with automated computational algorithms that perform coordinate transformations and parameter calculations based on measurement data from the radar and camera sensors

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

A fusion processing module serves as an intermediary that automatically processes measurement data from both sensors, performs coordinate transformations, and determines calibration parameters without requiring direct manual intervention

Inventive Principle:

Principle #24Intermediary (Mediator)

3Productivity

If automated calibration methods are implemented, then calibration efficiency is improved, but system complexity increases

Engineering Contradiction:

Improvecalibration efficiencyVSAvoidsystem complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The fusion processing module performs multiple functions including data reception, coordinate transformation, calibration parameter calculation, and result output, making the system versatile while managing complexity through functional integration

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS12372611B2Sensor calibration method and apparatus

Publication Date: 2025.07.29 YINWANG INTELLIGENT TECHNOLOGIES CO LTD

AI summary

A sensor calibration method includes: location information of a target detected by a radar is matched against map information to determine a calibration value of the radar, and then location information of a pixel of a target corresponding to the camera in a global coordinate system is determined based on calibrated radar measurement data so as to further determine a calibration value of the camera. In this way, for a roadside sensing system that includes the single radar and the single camera, manual field calibration is no longer required.