Vehicle Radar Misalignment Estimation Using Global Coordinate Transformation
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Solution Overview
Problem
Current vehicle radar systems face challenges in accurately measuring target bearing angles due to various error sources such as misalignment, environmental influences, and precision issues, necessitating a reliable and uncomplicated error compensation method.
Innovation Solution
A vehicle radar system comprising a radar detector and a processing unit, where the position detector (e.g., accelerometers, cameras, gyrometers, or GPS) helps correct misalignment by applying different error correction factors to detected positions, transforming them into a global coordinate system, and selecting the factor that minimizes the total error, using techniques like interpolation and non-linear optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If vehicle dynamic information (speed, yaw-rate, steering angle) is used to verify trajectories and estimate bearing bias, then misalignment estimation can be achieved, but the success highly depends on the precision of vehicle dynamic data which may be insufficient
Solution Approach 1:
The patent introduces a global coordinate system as an intermediary reference frame that is fixed with respect to the environment and stationary objects. By transforming radar-detected positions into this external reference frame using position detector data (GPS, inertial sensors), the system can objectively evaluate bearing accuracy without relying on potentially imprecise vehicle dynamic information. This intermediary coordinate system acts as a mediator between the radar's local measurements and the true spatial positions of stationary objects.
2Measurement precision
If multiple error correction factors are applied and optimized using interpolation and non-linear optimization techniques, then measurement precision is improved, but device complexity and computational requirements increase
Solution Approach 1:
The patent applies multiple error correction factors to the detected target positions before transforming them into the global coordinate system. This preliminary correction of bearing measurements using optimization techniques (interpolation, non-linear optimization) removes systematic errors such as boresight misalignment and antenna phase center offsets in advance. By performing this error compensation beforehand, the subsequent coordinate transformation and position evaluation work with already-corrected data, improving overall measurement precision while managing computational complexity through structured optimization approaches.
Data Source
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AI summary
The present disclosure relates to a vehicle radar system (2) that comprises a radar detector (3) that is arranged to detect at least one stationary object (10) a plurality of times when a vehicle (1) moves in relation to it. A plurality of detected positions (11, 12, 13) are obtained in a local coordinate system (15), fixed with respect to the radar detector (3). The object (10) is stationary with respect to a global coordinate system (16), fixed with respect to the outside environment. A position detector (14) is arranged to detect its present movement conditions with reference to the global coordinate system (16). Correction factors are applied on each detected position of the object in the local coordinate system (15). All obtained corrected detected positions are then transformed into the global coordinate system (16) and an error/cost value is calculated for each correction factor. The correction factor that results in the smallest error/cost value is chosen.