Moving Human Targets Tracking Method Based on Rotation Kernelized Correlation Filter for Through-the-Wall Radar

Zeyu Ma, Xiaodong Qu*, Hao Zhang, Haoyu Meng, Xiaopeng Yang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Tracking the position of human targets behind obstacles is one of the core functions of through-the-wall radar. Due to the fixed viewing angle of the through-the-wall radar and the complex scattering properties of the human targets, the radar images of human targets will rotate with the human movement, resulting in tracking difficulties. Aiming at solving this problem, a moving human targets tracking method based on rotation kernelized correlation filter (RKCF) is proposed. In the proposed method, the angle of the target region is estimated and then a rotation is performed on the region image to obtain the candidate target region. Next, a filter is utilized to perform correlation operation with the candidate region to locate the target. Finally, the training samples are extracted and a rotational update operation is performed to train a new filter. Numerical simulation and experimental results verify the tracking performance of the proposed algorithm.

Original languageEnglish
JournalIEEE Transactions on Aerospace and Electronic Systems
DOIs
Publication statusAccepted/In press - 2024

Keywords

  • Through-the-wall radar
  • human targets tracking
  • rotation kernelized correlation filter

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