Automated Vehicle Radar Auto-Alignment
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Solution Overview
Problem
Existing radar systems on moving vehicles face challenges in accurately aligning sensors due to pitch, elevation, and azimuth errors caused by cargo, wheel misalignment, and dynamic conditions, leading to inefficiencies and inaccuracies in object detection.
Innovation Solution
A radar system with auto-alignment capabilities, utilizing a radar-sensor, speed-sensor, and controller to simultaneously determine speed-scaling-error, azimuth-misalignment, and elevation-misalignment based on measured-range-rate, azimuth-angle, and elevation-angle of multiple stationary objects, allowing for real-time correction while the vehicle is in motion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If alignment procedures are performed when the host-vehicle is assembled, then initial alignment is achieved, but pitch and elevation errors caused by heavy cargo and yaw or azimuth errors caused by wheel misalignment cannot be compensated
Solution Approach 1:
The system performs alignment procedures dynamically while the vehicle is moving rather than statically during assembly. The controller continuously determines azimuth-misalignment and elevation-misalignment based on real-time radar measurements of stationary objects, allowing the system to adapt to changing vehicle conditions such as cargo weight and wheel alignment variations during actual operation.
Solution Approach 2:
The radar system automatically performs its own alignment correction without requiring external intervention. The controller uses the radar-sensor's measurements of stationary objects and vehicle speed to self-determine misalignment parameters and generate correction signals, enabling the system to compensate for its own errors autonomously during vehicle operation.
2Manufacturing precision
If the radar-sensor is aligned during vehicle assembly, then initial positioning is established, but it cannot account for dynamic changes in vehicle conditions during operation
Solution Approach 1:
The system implements a feedback mechanism where the radar-sensor continuously measures the position and velocity of stationary objects, and the controller uses these measurements to determine ongoing azimuth and elevation misalignment. This real-time feedback loop allows the system to detect and correct alignment drift caused by dynamic vehicle conditions, maintaining reliable detection accuracy throughout operation.
Solution Approach 2:
The system performs preliminary alignment during vehicle assembly, then continuously refines this alignment during operation. By establishing an initial alignment baseline and then applying real-time corrections based on radar measurements, the system ensures both initial positioning accuracy and ongoing reliability under varying operational conditions.
3Loss of time
If alignment is performed statically during assembly, then setup time is reduced, but the system cannot compensate for pitch, elevation, and azimuth errors during vehicle operation
Solution Approach 1:
The system transitions from static alignment during assembly to dynamic alignment during operation. The controller continuously calculates azimuth and elevation corrections based on real-time radar measurements of stationary objects and vehicle speed, enabling the system to maintain high measurement precision despite changes in vehicle conditions such as cargo weight and wheel alignment during actual use.
Solution Approach 2:
The radar system performs self-correction during operation without requiring additional alignment procedures. The controller automatically determines misalignment parameters from radar measurements and generates correction signals, allowing the system to maintain accurate detection despite dynamic changes in vehicle conditions throughout its operational life.
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
The system achieves rapid and accurate auto-alignment, reducing errors and improving radar performance by considering mutual correlations of errors, thus enhancing the accuracy of object detection and tracking.
Implementation Method 1
The radar-sensor (14) is used to detect objects present in a field-of-view proximate to a host-vehicle on which the radar-sensor is mounted
Data Source
AI summary
In accordance with one embodiment, a radar system with auto-alignment suitable for use in an automated vehicle is provided. The system includes a radar-sensor, a speed-sensor, and a controller. The radar-sensor is used to detect objects present in a field-of-view proximate to a host-vehicle on which the radar-sensor is mounted. The radar-sensor is operable to determine a measured-range-rate (dRm), a measured-azimuth-angle (Am), and a measured-elevation-angle (Em) to each of at least three objects present in the field-of-view. The speed-sensor is used to determine a measured-speed (Sm) of the host-vehicle. The controller is in communication with the radar-sensor and the speed-sensor. The controller is configured to simultaneously determine a speed-scaling-error (Bs) of the measured-speed, an azimuth-misalignment (Ba) of the radar-sensor, and an elevation-misalignment (Be) of the radar-sensor based on the measured-range-rate, the measured-azimuth-angle, and the measured-elevation-angle to each of the at least three objects, while the host-vehicle is moving.