Radar Angle Compensation Using Stationary Object Speed Errors
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Solution Overview
Problem
Conventional methods for compensating misalignment in radar devices are time-consuming and resource-intensive, leading to inaccurate target information due to errors in mounting, which affects the performance of driver assistance systems.
Innovation Solution
An angle compensation device and method that uses linear regression analysis of speed sensor errors to quickly and accurately determine misalignment and compensate for estimation angles, by calculating the difference between the relative speed of stationary objects and the host vehicle's speed, and determining linear regression coefficients for accurate angle compensation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional methods are used to compensate misalignment by collecting data of multiple objects, then measurement precision may be improved, but loss of time and device complexity increase significantly
Solution Approach 1:
The patent extracts the essential information needed for misalignment compensation by focusing solely on stationary objects rather than requiring data from multiple moving objects. This extraction approach reduces data collection time while maintaining the ability to accurately determine misalignment angle through linear regression analysis of speed sensor errors from stationary objects only.
Solution Approach 2:
The patent changes the parameter used for misalignment determination from traditional angle-based methods to speed sensor error-based methods. By utilizing the linear relationship between speed sensor errors and misalignment angle, the system achieves rapid and accurate compensation without requiring extensive data collection from multiple objects over time.
2Measurement precision
If conventional methods collect data of multiple objects for misalignment estimation, then measurement precision improves, but device complexity and computational resources increase
Solution Approach 1:
The patent extracts only the necessary information from stationary objects (speed sensor errors) rather than processing comprehensive data from multiple moving objects. This extraction simplifies the computational process while maintaining accurate misalignment estimation through linear regression analysis.
Solution Approach 2:
The patent replaces complex computational algorithms with a simpler linear regression approach. By substituting traditional complex misalignment estimation methods with linear regression analysis of speed sensor errors, the system reduces computational resource requirements while maintaining measurement precision.
3Measurement precision
If more data of multiple objects is collected for misalignment compensation, then measurement precision improves, but loss of time increases
Solution Approach 1:
The patent extracts essential misalignment information from stationary objects alone, eliminating the need to collect and process data from multiple moving objects. This extraction method maintains angle compensation accuracy while significantly improving processing speed and productivity.
Solution Approach 2:
The patent skips the time-consuming process of collecting data from multiple moving objects by directly utilizing stationary objects for misalignment determination. This approach rushes through the essential measurement process efficiently, achieving both high accuracy and fast processing.
Data Source
AI summary
An angle compensation device and method for a radar device may detect a stationary object around a host vehicle if the host vehicle is driving in a straight line, determine a relative speed of the stationary object with respect to the host vehicle and a driving speed of the host vehicle, determine a linear regression coefficient of a speed sensor error by calculating a difference between the relative speed of the stationary object and the driving speed of the host vehicle, determine an angle compensation value according to misalignment of the radar device using the linear regression coefficient, and compensate an angle of a target using the angle compensation value.