Determination of torso and main limp features of human gait from micro-Doppler radar measurements based on envelope detection and Kalman filtering

Onur Tekir; Caner Özdemir

doi:10.1515/freq-2024-0247

Article

Determination of torso and main limp features of human gait from micro-Doppler radar measurements based on envelope detection and Kalman filtering

Onur Tekir and Caner Özdemir

Published/Copyright: September 15, 2025

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From the journal Frequenz Volume 79 Issue 11-12

Abstract

This paper proposes a practical method for detecting the dominant motion characteristics of human walk and run based on micro-Doppler radar measurements. The method consists of two stages: In the first stage, the main body, i.e. torso, characteristics are identified by the help of Kalman Filtering based detection algorithm. Then, the detected torso signature is extracted from the two-dimensional (2D) range-Doppler image such that the residual image contains signatures from other body parts. In the second stage of the method, a human-Doppler threshold based envelope detection routine is employed to identify the micro-Doppler signatures from dominant swinging limps; i.e. arms and/or legs. To demonstrate the effectiveness and the validity of the proposed techniques, two measured examples from real world experiments are presented. These examples show that the signatures of main body and swinging arms are successfully detected and classified with good fidelity such that the velocity of the torso and the period/speed values of the arms are precisely estimated for much better classification of the human motion thanks to the proposed Kalman Filtering based detection, and human-Doppler threshold based envelope detection routines.

Keywords: signal processing; micro Doppler; radar signature extraction; Kalman filtering; spectrogram

Corresponding author: Onur Tekir, Department of Electrical-Electronics Engineering, Mersin University, Mersin, Türkiye, E-mail: onur_tek@hotmail.com

Funding source: Mersin University Scientific Research Unit

Award Identifier / Grant number: Project No. 2018-2-TP3-2924

Acknowledgments

Authors would like to thank Mr. Rasheed Khankan for his help during experiments.

Research ethics: Not applicable.
Informed consent: Not applicable.
Author contributions: The authors have accepted responsibility for the entire content of this manuscript and approved its submission.
Use of Large Language Models, AI and Machine Learning Tools: None declared.
Conflict of interest: There is no conflict of this work with any other author or research. The authors declare no conflicts of interest regarding this article.
Research funding: This work was supported by Mersin University Scientific Research Unit under Project No. 2018-2-TP3-2924.
Data availability: There is no data or material is available separately.

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Received: 2024-07-30

Accepted: 2025-09-01

Published Online: 2025-09-15

Published in Print: 2025-12-17

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Articles in the same Issue

https://doi.org/10.1515/freq-2024-0247

Keywords for this article

signal processing; micro Doppler; radar signature extraction; Kalman filtering; spectrogram