Radar DoA Processing With ROI-Based Local Resolving Power
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Solution Overview
Problem
Existing radar systems face challenges in efficiently processing radar data with high computational complexity and time consumption, particularly in determining direction-of-arrival (DoA) information, which affects the accuracy and efficiency of advanced driver assistance systems (ADAS) in vehicles.
Innovation Solution
A method and device for radar data processing that involves predicting a region of interest (ROI) based on a generated radar image map, adjusting steering information and local range resolving power, and determining DoA information by allocating candidate steering vectors intensively within the ROI, while reducing computational complexity through localized adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If candidate steering vectors are uniformly distributed across the entire sensing range, then the resolving power is maintained evenly throughout, but the computational complexity increases and processing efficiency decreases
Solution Approach 1:
The patent applies local quality by distributing candidate steering vectors non-uniformly across the sensing range, with higher density in regions of interest (ROI) and lower density in non-ROI areas. This allows the system to maintain high resolving power where needed while reducing computational complexity in less critical regions, thereby improving overall processing efficiency without sacrificing measurement precision in important areas.
Solution Approach 2:
The sensing range is segmented into regions of interest (ROI) and non-ROI based on radar image map analysis. Different densities of candidate steering vectors are allocated to different segments, with intensive distribution in ROI and sparse distribution in non-ROI. This segmentation approach enables the system to focus computational resources on critical areas while maintaining acceptable performance elsewhere.
2Measurement precision
If the number of candidate steering vectors is increased to improve DoA determination accuracy, then measurement precision improves, but computational complexity and time consumption increase
Solution Approach 1:
Instead of uniformly increasing the number of candidate steering vectors across the entire sensing range, the patent applies local quality by concentrating more vectors in regions of interest while using fewer vectors in non-ROI areas. This selective distribution maintains high DoA determination accuracy in critical regions while avoiding the computational complexity burden of uniformly high-density vector distribution throughout the entire range.
3Productivity
If computational resources are reduced to improve processing speed, then productivity increases, but the accuracy of radar data processing may deteriorate
Solution Approach 1:
The patent reconciles the trade-off between processing speed and accuracy by applying local quality - using intensive candidate steering vector distribution in regions of interest to maintain high accuracy, while using sparse distribution in non-ROI areas to reduce computational load and improve processing speed. This selective approach ensures that accuracy is maintained where it matters most while achieving overall processing efficiency improvements.
Solution Approach 2:
The system performs preliminary analysis of the radar image map to identify regions of interest before allocating candidate steering vectors. This preliminary action allows the system to pre-determine where high accuracy is needed, enabling subsequent processing to focus computational resources appropriately and avoid unnecessary calculations in non-critical areas, thereby improving both speed and accuracy.
Data Source
AI summary
A radar data processing device and method is provided. The method generates a radar image map, predicts a region of interest (ROI) based on the generated radar image map, senses radar data with a radar sensor, identifies the sensed radar data based on steering information, adjusts the steering information based on the predicted ROI, and determines direction-of-arrival (DoA) information corresponding to the sensed radar data based on the adjusted steering information. The radar data processing device may locally adjust at least one of a range resolving power, an angular resolving power, or a Doppler velocity resolving power based on the ROI predicted based on a radar image map, and generate an accurate radar data processing result of a major region.