Radar Resolution Increase Model Using Reference Data
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Solution Overview
Problem
Current radar sensors in advanced driver assistance systems (ADAS) face limitations in resolution due to cost and hardware constraints, restricting the detail and accuracy of object detection and environment mapping, especially in varying environmental conditions.
Innovation Solution
A method involving a radar data processing system that uses a resolution increase model, combining input radar data with reference data from other sensors to enhance the resolution of radar images, allowing for higher detail in object detection and environment mapping, including the use of neural networks and generative adversarial networks to improve image resolution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If radar sensors with higher resolution are used to improve object detection accuracy, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent combines input radar data with reference data from other sensors (such as cameras, LIDAR, or infrared sensors) to generate enhanced radar output data with higher resolution. This merging of multiple data sources allows the system to achieve high measurement precision without requiring a single complex high-resolution radar sensor, thereby reducing device complexity and cost.
Solution Approach 2:
The patent introduces a resolution increase model as an intermediary component that processes low-resolution radar data and reference data to produce high-resolution output. This intermediary model acts as a bridge, transforming limited radar data into enhanced resolution data without requiring direct hardware upgrades to the radar sensor itself.
2Measurement precision
If multiple sensors are integrated to improve measurement precision, then object detection accuracy is improved, but device complexity increases
Solution Approach 1:
The resolution increase model serves multiple functions: it processes reference data from various sensor types (camera, LIDAR, infrared), aligns them with radar data, and generates enhanced output. This multi-functional approach allows the system to integrate multiple sensors without proportionally increasing complexity, as the same model handles diverse data sources.
Solution Approach 2:
The system changes the resolution parameter of the radar output by processing it through the resolution increase model. Instead of physically changing sensor parameters or integrating complex multi-sensor arrays, the system achieves improved detection accuracy by transforming the resolution parameter through computational processing of combined sensor data.
Data Source
AI summary
A method with radio detection and ranging (radar) data processing may include: obtaining, by a radar sensor, input radar data; and generating, using a resolution increase model, output radar data from the input radar data and reference data, wherein the output radar data has a resolution greater than a resolution of the input radar data.