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Research on the Method of Environmental Perception Based on Millimeter Wave Radar

  • Lei Xing
  • , Fei Peng
  • , Rui Pan*
  • *Corresponding author for this work
  • China Aerospace Science and Technology Corporation
  • China Academy of Information and Communications Technology

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

Abstract

Environmental perception provides essential information for the in-vehicle system. Furthermore, sensors are necessary components to collect data for environmental perception and research on the application of millimeter wave radar has become a hot spot in recent years. In order to improve the environmental perception performance of millimeter wave radar in static situation and in motion, this paper analyzed reasons for the insufficient measurement of millimeter wave radar and improved filter methods to reduce the impact of noise or environment on millimeter wave radar. RCS (Radar Cross Section) filter, sliding window filter and angle filter were used in the experiment. Experiment results show that in static situation, the environmental perception performance of millimeter wave radar could be effectively improved by improving the filter method and adopting the combined filter method. Furthermore, using sliding window filter and adjusting the window size correctly, the environmental perception based on millimeter wave radar performed well in motion.

Original languageEnglish
Title of host publication3rd China International SAR Symposium, CISS 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350398717
DOIs
StatePublished - 2022
Event3rd China International SAR Symposium, CISS 2022 - Shanghai, China
Duration: 2 Nov 20224 Nov 2022

Publication series

Name3rd China International SAR Symposium, CISS 2022

Conference

Conference3rd China International SAR Symposium, CISS 2022
Country/TerritoryChina
CityShanghai
Period2/11/224/11/22

Keywords

  • RCS
  • environmental perception
  • millimeter wave radar
  • sensor

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