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RangeSRN: Range Super-Resolution Network Using mmWave FMCW Radar
Conference paper

RangeSRN: Range Super-Resolution Network Using mmWave FMCW Radar

Hsin-Yuan Chang, Yi-Yan Chen and Wei-Ho Chung
2022 IEEE Global Communications Conference, GLOBECOM 2022 - Proceedings, pp.729-734
2022

Abstract

deep learning Frequency-modulated continuous-wave radar mmWave super-resolution Artificial Intelligence Computer Networks and Communications Hardware and Architecture Signal Processing Renewable Energy Sustainability and the Environment Safety Risk Reliability and Quality
Designing a signal-processing algorithm for frequency-modulated continuous-wave (FMCW) radar applications with advanced functionality remains a challenging problem. Specifically, traditional algorithms improve detection resolution by increasing bandwidth and contribute to inefficient spectral use and maximum range reduction. To strike a balance between the maximum detection range and range resolution, we propose a resolution improvement algorithm based on super-resolution techniques. The low-resolution detection results were used to infer the high-resolution data by emphasizing the hidden spatial correlations. Simulation results confirmed that the proposed algorithm possesses an outstanding ability to achieve high-resolution detection while employing reduced bandwidth, leading to two advantages: spectral efficiency and maximum detectable range.

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