Multi-Radar Image Synthesis for Autonomous Vehicle Detection
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Solution Overview
Problem
Current radar systems for autonomous vehicles face challenges in generating high-resolution images of surroundings in real-time, especially when detecting objects at high speeds or in varying environments, due to limitations in beamforming and signal processing capabilities.
Innovation Solution
The method involves synchronizing multiple radars to perform beamforming on the same point simultaneously, synthesizing overlapping images to achieve a 360-degree field of view, and adjusting gains and beamforming ranges based on vehicle modes (e.g., highway or city driving) to enhance object detection and recognition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple radars are used to improve detection range and resolution, then measurement precision and detection range are improved, but device complexity increases
Solution Approach 1:
Multiple radar captured images are merged into a single synthesized image through coordinate transformation and overlapping region integration. This combining approach achieves high-resolution imaging with extended detection range while managing system complexity through unified processing architecture
Solution Approach 2:
The radar image processing apparatus performs multiple functions including coordinate transformation, image synthesis, object detection, and high-resolution image generation using a single integrated system. This multi-functionality reduces the need for separate specialized components
2Measurement precision
If radars perform beamforming on the same point simultaneously, then measurement precision and image quality are improved, but loss of time occurs due to synchronization requirements
Solution Approach 1:
Transmission times for transmitting transmission signals from the radars toward a target are synchronized in advance, and reception times for receiving reflection signals are synchronized beforehand. This preliminary synchronization ensures precise simultaneous beamforming without real-time delays
Solution Approach 2:
The system uses synchronized transmission and reception timing with feedback mechanisms to coordinate multiple radars. The synchronization information is used to adjust beamforming operations to achieve precise spatial-temporal alignment
3Measurement precision
If the beamforming range is extended to cover all directions, then detection range is improved, but use of energy increases
Solution Approach 1:
The beamforming range is dynamically adjusted based on vehicle mode (highway or city driving). During highway driving, the beamforming range is limited to the front side to reduce energy consumption, while during city driving it covers all directions for comprehensive detection
Solution Approach 2:
The system changes operational parameters including beamforming range and gain settings based on driving conditions. Transmission signals are coded differently and gains are adjusted to optimize energy usage while maintaining detection performance
Data Source
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AI summary
A radar image processing method includes acquiring captured images from radars synchronized to perform beamforming on a same point at a same time, synthesizing the captured images based on at least one overlapping area of the captured images, and generating a high-resolution image based on the synthesized images.