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Respiration Rate Estimation Using IR-UWB Radar Based on the Second Maximum Eigenvalues | IEEE Conference Publication | IEEE Xplore

Respiration Rate Estimation Using IR-UWB Radar Based on the Second Maximum Eigenvalues


Abstract:

Impulse Radio Ultra-Wide-Band (IR-UWB) radar is a promising technology for contact-less sensing applications, such as Vital Sign (VS) detection of human body. This paper ...Show More

Abstract:

Impulse Radio Ultra-Wide-Band (IR-UWB) radar is a promising technology for contact-less sensing applications, such as Vital Sign (VS) detection of human body. This paper presents a new approach for Respiration Rate (RR) estimation of a stationary person. The particularity of this approach is that does not require any pre-processing techniques. It is based on the estimation of the Second Maximum Eigenvalue (SME) using Singular Value Decomposition (SVD). To extract the VS signal, a packet of eigenvalues is acquired using a moving matrix window over the slow time direction of the radar data. Then applying a Fast Fourier Transform (FFT), the respiration rate can be easily estimated. Experiments are performed using a P440 (IR-UWB) radar. The results are encouraging and show that the proposed method effectively detects the VS with high accuracy even in low Signal to Noise Ratio (SNR) condition, such as in through the wall human detection scenario.
Date of Conference: 16-17 May 2020
Date Added to IEEE Xplore: 29 July 2020
ISBN Information:
Conference Location: El Oued, Algeria
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I. Introduction

Contact-less remote sensing with (IR-UWB) radar is a powerful technology with several advantages, such as low power consumption, good ability of penetration, and high resistance to multi-path fading [1]. Various applications are developed based on (IR-UWB) radar, such as human monitoring [2], through the wall human detection [3], human localization [4], and survivor rescue [5]. The principle of VS detection using (IR-UWB) radar is based on chest movement of human body, which is associated to VS motions [6]. This movement introduce a small phase variation in the received echos. It is difficult to extract this variation, as far as the clutter and noises are concerned.

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