Radar micro-doppler signature analysis and its application on gait recognition

Jianfeng Ren, Xudong Jiang

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

2 Citations (Scopus)


Micro-Doppler signature (mDS) was often utilized for radar target recognition in literature. Most existing approaches focus on extracting visual features for human operators. In this paper, we provide a complete solution to gait recognition using radar micro-Doppler analysis. Gait recognition is challenging due to the time-varying nature of micro-Doppler signature and the small differences of human gaits among different people. To align two mDSs in time, we propose to utilize dynamic time warping (DTW). To uncover the tiny differences among people, we propose to treat the distances of a sample to all gallery samples as the feature vector, and classify it using a support vector machine. To evaluate the performance of the proposed approach, we create an mDS-gait database. On this database, the proposed approach demonstrates superior performance compared with existing ones.

Original languageEnglish
Title of host publicationThird International Workshop on Pattern Recognition
EditorsZhenxiang Chen, Xudong Jiang, Guojian Chen
ISBN (Print)9781510622685
Publication statusPublished - 2018
Externally publishedYes
Event3rd International Workshop on Pattern Recognition, IWPR 2018 - Jinan, China
Duration: 26 May 201828 May 2018

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X


Conference3rd International Workshop on Pattern Recognition, IWPR 2018


  • Automatic Target Recognition
  • Dynamic Time Warping
  • Gait Recognition
  • Micro-Doppler Signature
  • Support Vector Machine

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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