Radar Profile Annotation for Camera-Independent Object Identification
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Solution Overview
Problem
Existing radar systems struggle to accurately identify objects due to limitations in distinguishing similar-sized objects based solely on radar returns, especially when a camera system is damaged or inoperable, leading to challenges in autonomous vehicle operation.
Innovation Solution
A radar-data collection system that integrates a camera and radar to annotate radar-profiles with object identities, using image analysis to enhance radar data interpretation, enabling reliable object identification even without a functional camera.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If radar systems rely solely on radar returns for object identification, then the system can operate independently of camera systems, but the ability to accurately distinguish similar-sized objects deteriorates
Solution Approach 1:
The system performs preliminary actions by capturing images with the camera and processing radar returns in advance to create annotated radar profiles before actual object identification is needed. This preliminary processing stores enriched radar data with visual references, enabling accurate object distinction without requiring the camera to be operational during the actual identification task.
Solution Approach 2:
The patent introduces an intermediary approach by creating annotated radar profiles that serve as a bridge between radar data and visual identification. These annotated profiles act as a mediator that encapsulates both radar characteristics and visual references, allowing the system to achieve camera-level identification accuracy while maintaining radar-based operation independence.
2Reliability
If the camera system is damaged or inoperable, then the autonomous vehicle can still use radar for navigation, but the ability to identify objects accurately deteriorates
Solution Approach 1:
The system performs preliminary action by pre-processing radar returns and associating them with reference images before the camera becomes non-functional. This creates a pre-computed database of annotated radar profiles that maintains high object identification precision even when the camera is damaged, as the enrichment data is already prepared in advance.
Solution Approach 2:
The patent applies the copying principle by creating a copy of the camera's identification capability through annotated radar profiles. These profiles replicate the visual identification function by encoding both radar characteristics and visual references into a single data structure, enabling the radar system to perform functions previously exclusive to the camera system.
3Measurement precision
If the system integrates both camera and radar systems, then object identification accuracy is improved, but the system becomes more complex and vulnerable to single-point failures
Solution Approach 1:
The patent merges the camera and radar systems by combining their data streams into a unified annotated radar profile structure. This merging integrates the high-precision object identification capability of cameras with the robustness of radar systems, creating a hybrid approach that achieves superior identification precision while managing system complexity through a unified data representation framework.
Data Source
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AI summary
A radar-data collection system (10) a radar (16), a camera (14), and a controller-circuit (30). The radar (16) and the camera (14) are intended for mounting on a host-vehicle (12). The radar (16) is configured is to indicate a radar-profile (22) of an object (18) detected by the radar (16). The camera (14) is configured to render an image (24) of the object (18). The controller-circuit (30) is in communication with the radar (16) and the camera (14). The controller (30) is configured to determine an identity (26) of the object (18) in accordance with the image (24), and annotate the radar-profile (22) in accordance with the identity (26).