Radar compressed sampling with longtime pre-coherent integration via RFT

Xiao Li, Hao Huan, Zonghan Wei, Yue Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Compressed sampling is generally used in ultra-wideband radar, in which the moving targets' radial velocity would easily cause the across range unit (ARU) effect due to the high refined range resolution. Meanwhile, the noise-folding effect caused by under-sampling reduces the signal-to-noise ratio (SNR) of compressed sampled signals apparently. Therefore, traditional pre-coherent integration via discrete Fourier transform (DFT) are very likely to be unable to provide enough SNR gain for reliable reconstruction. In this paper we propose a novel radar compressed sampling system with longtime pre-coherent integration via Radon Fourier transform (RFT). The compressed sampled signals are firstly decompressed, then integrated by RFT filter banks, and finally reconstructed on each velocity bin respectively. The integration time of the proposed system is no longer restricted by the velocity of targets and range resolution as in the traditional pre-coherent integration via DFT, but could be greatly extended to satisfy the actual SNR requirements of system. Numerical simulation results show that the rate of successful reconstruction of provided system with high targets velocity is significantly improved, compared with the previous method using DFT integration.

Original languageEnglish
Title of host publication2017 IEEE Radar Conference, RadarConf 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1367-1372
Number of pages6
ISBN (Electronic)9781467388238
DOIs
Publication statusPublished - 7 Jun 2017
Event2017 IEEE Radar Conference, RadarConf 2017 - Seattle, United States
Duration: 8 May 201712 May 2017

Publication series

Name2017 IEEE Radar Conference, RadarConf 2017

Conference

Conference2017 IEEE Radar Conference, RadarConf 2017
Country/TerritoryUnited States
CitySeattle
Period8/05/1712/05/17

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