A novel radar imaging method based on random illuminations using FMCW radar

Prateek Nallabolu, Changzhi Li

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

Abstract

Compressed Sensing (CS) has provided a viable approach to undersample a sparse signal and reconstruct it perfectly. In this paper, the simulation results of a frequency-modulated continuous-wave (FMCW) radar, which employs a CS based data acquisition and reconstruction algorithm to recover a sparse 2-D target frame using fewer number of scans are presented. A 16-element antenna array based on digital beamforming approach is used on the receiver end to obtain random spatial measurements of the target frame, which is the key to compressed sensing. A linear relationship is established between the total received FMCW beat signal for each scan and the 2-D sparse target frame using a basis transform matrix. Simulations of the proposed radar are performed in MATLAB and the reconstruction results for different noise levels are presented.

Original languageEnglish
Title of host publication2020 IEEE Topical Conference on Wireless Sensors and Sensor Networks, WiSNeT 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages27-29
Number of pages3
ISBN (Electronic)9781728133553
DOIs
StatePublished - Jan 2020
Event2020 IEEE Topical Conference on Wireless Sensors and Sensor Networks, WiSNeT 2020 - San Antonio, United States
Duration: Jan 26 2020Jan 29 2020

Publication series

Name2020 IEEE Topical Conference on Wireless Sensors and Sensor Networks, WiSNeT 2020

Conference

Conference2020 IEEE Topical Conference on Wireless Sensors and Sensor Networks, WiSNeT 2020
Country/TerritoryUnited States
CitySan Antonio
Period01/26/2001/29/20

Keywords

  • Compressed sensing
  • Digital beamforming
  • Frequency-modulated continuous-wave radar
  • Radar imaging
  • Random illumination
  • Target localization

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