Cognitive Radar System for Obstacle Avoidance Using In-Motion Memory-Aided Mapping

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Colleges, School and Institutes

External organisations

  • Beijing Institute of Technology


The paper introduces a radar signal processing method for goal-oriented, collision-free navigation in mobile robotic platforms. The derived algorithm creates an enhanced perception of the area in front of the sensor through accumulating a sequence of radar pulses that is constantly updated, and uses previously obtained perception to inform future robot steering actions on the fly, thus creating a form of working memory. The algorithm is analytically described, and experimentally confirmed in laboratory conditions with a ground mobile robot operating in real-time.

Bibliographic note

Funding Information: This work was supported in part by the National Key R&D Program of China (Grant No. 2018YFE0202101, 2018YFE0202102) and the China Scholarship Council. 978-1-7281-8942-0/20/$31.00 ©2020 IEEE Publisher Copyright: © 2020 IEEE. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.


Original languageEnglish
Title of host publication2020 IEEE Radar Conference, RadarConf 2020
Publication statusPublished - 21 Sep 2020
Event2020 IEEE Radar Conference, RadarConf 2020 - Florence, Italy
Duration: 21 Sep 202025 Sep 2020

Publication series

NameIEEE National Radar Conference - Proceedings
ISSN (Print)1097-5659


Conference2020 IEEE Radar Conference, RadarConf 2020


  • Cognitive radar, Collision avoidance, Map Memory, Vector Field Histogram

ASJC Scopus subject areas