Radar Signal Processing Reducing Arithmetic Load via Spectrum Cutout
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Solution Overview
Problem
Radar devices using high-resolution algorithms face challenges in reducing the load and time required for arithmetic processing, which is essential for efficient target detection and tracking.
Innovation Solution
The implementation of an information processing device and method that includes a Fourier transform unit, a cutout unit to generate a second spectrum by cutting out a processing range from the first spectrum, a steering matrix generation unit, and a processing unit that applies a high-resolution algorithm based on the second spectrum and the steering matrix, allowing for targeted high-resolution processing only in specific scanning ranges.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a high-resolution algorithm is applied to the entire scanning range, then measurement precision is improved, but productivity deteriorates due to increased arithmetic processing load and time
Solution Approach 1:
The scanning range is divided into multiple regions of interest (ROIs) based on low-resolution detection results. The high-resolution algorithm is then applied only to these segmented ROI portions rather than the entire scanning range, reducing the arithmetic processing load while maintaining high detection precision where needed.
Solution Approach 2:
Different processing qualities are applied to different regions: low-resolution processing is applied to regions where targets are not detected, while high-resolution processing is applied only to regions where targets are detected. This local differentiation optimizes the balance between measurement precision and processing productivity.
2Measurement precision
If a high-resolution algorithm is applied to the entire scanning range, then measurement precision is improved, but loss of time increases due to extended processing duration
Solution Approach 1:
The scanning range is divided into multiple regions of interest (ROIs) based on low-resolution detection results. The high-resolution algorithm is then applied only to these segmented ROI portions rather than the entire scanning range, reducing the arithmetic processing load while maintaining high detection precision where needed.
Solution Approach 2:
A low-resolution algorithm is applied first to the entire scanning range to identify potential target regions. Based on these preliminary results, regions of interest are determined before applying the high-resolution algorithm, thereby avoiding unnecessary high-resolution processing in empty regions and reducing overall processing time.
3Productivity
If the processing range is reduced to specific regions, then productivity is improved by reducing arithmetic processing load, but measurement precision may deteriorate in undetected regions
Solution Approach 1:
A low-resolution algorithm is applied first to the entire scanning range to identify potential target regions. Based on these preliminary results, regions of interest are determined before applying the high-resolution algorithm, thereby avoiding unnecessary high-resolution processing in empty regions and reducing overall processing time.
Solution Approach 2:
The low-resolution detection results serve as feedback to guide the high-resolution processing. Regions where targets are detected in the low-resolution stage are identified as regions of interest and subjected to high-resolution processing, ensuring that measurement precision is maintained in areas where it matters most.
Data Source
AI summary
The present technique relates to an information processing device and an information processing method that can reduce the load and time required for arithmetic processing in a radar device that uses a high-resolution algorithm. Fourier transform processing is executed on a received signal received by an antenna, a second spectrum is generated by cutting out a processing range from a first spectrum obtained by executing the Fourier transform processing, a steering matrix corresponding to the processing range is generated, and a high-resolution algorithm is applied based on the second spectrum and the steering matrix.