Vehicle Radar Misalignment Estimation via Doppler-Angle Correlation
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Solution Overview
Problem
Vehicle radar systems face challenges in accurately estimating misalignment angles without precise vehicle dynamic data, which is costly and not always available, affecting the precision of target bearing angle measurements due to environmental and mechanical factors.
Innovation Solution
A method that defines the progression of detected target Doppler velocity as a function of detected target angle using a parabolic relationship, allowing for the estimation of misalignment through zero crossings in the derivative of this function, eliminating the need for exact vehicle data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If vehicle dynamic data (speed, yaw-rate, steering angle) is used to verify trajectories and estimate bearing bias, then measurement precision of target bearing angle is improved, but device complexity and cost increase due to requirements for precise vehicle data sensors and processing systems
Solution Approach 1:
The invention extracts only the essential information needed for misalignment estimation - the relationship between detected target angle and target Doppler velocity - while discarding the complex vehicle dynamic data processing requirements. By focusing on the radar's own measurement data and identifying the angular offset that maximizes velocity correlation, the system achieves bearing angle precision without the complexity of vehicle sensor integration
Solution Approach 2:
Instead of using complex vehicle dynamic models to predict target trajectories, the invention creates a simplified virtual model by correlating detected angles and velocities. The system copies the essential motion relationship through statistical correlation of radar measurements, avoiding the need for precise vehicle speed, yaw-rate, and steering angle data while achieving similar estimation accuracy
2Measurement precision
If exact vehicle data is required for misalignment estimation, then measurement precision of target bearing angle is improved, but ease of operation deteriorates due to data availability constraints and calibration requirements
Solution Approach 1:
The system performs self-calibration by using its own radar measurements to determine misalignment. By analyzing the correlation between detected target angles and Doppler velocities across multiple observations, the system automatically identifies the angular offset that maximizes velocity consistency, eliminating the need for external vehicle data inputs or manual calibration procedures
Solution Approach 2:
The invention transforms the estimation problem by changing the approach from using vehicle dynamic parameters to using radar measurement parameters. Instead of inputting vehicle speed and steering angle, the system processes detected target angles and velocities, applying statistical correlation to derive misalignment. This parameter transformation makes the system easier to operate as it uses data already available from the radar itself
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 approach provides a robust and cost-effective means to estimate vehicle radar system misalignment, improving angle accuracy by identifying zero crossings in the derivative of the Doppler velocity function, thus enhancing the precision of target detection without relying on precise vehicle dynamics.
Implementation Method 1
a radar device may be mounted on a vehicle in order to detect reflections from objects
Implementation Method 2
obtain values for detected target angle and detected target Doppler velocity
Data Source
Figure 1
Figure 2
Figure 3~4
AI summary
The present invention relates to a vehicle radar system (2) arranged to detect objects outside a vehicle (1). The radar system (2) comprises a radar detector (3) and a processing unit (4). The processing unit (4) is arranged to obtain values for detected target angle (Thetaerr) and detected target Doppler velocity (vd) relative the radar detector (3) for each detected object (10a', 10b', 10c', 10d', 10e' ) during a certain time interval. If there is a zero crossing (14) for a derivative (13) of a function (12) describing the progression of detected target Doppler velocity (vd) as a function of detected target angle (©err), the processing unit (4) is arranged to detect said zero crossing (14). This zero crossing (14) is indicative of a radar system misalignment (Thetam). The present invention also relates to a corresponding method.