Joint Vital Signs and Position Estimation of Multiple Persons Using SIMO Radar

• Published in: Electronics (Basel) Vol. 10; no. 22; p. 2805
• Main Authors: Kakouche, Ibrahim, Abadlia, Hamza, El Korso, Mohammed Nabil, Mesloub, Ammar, Maali, Abdelmadjid, Azzaz, Mohamed Salah
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.11.2021; MDPI
• Subjects: Algorithms; Antennas; Bioengineering; Engineering Sciences; Fourier transforms; Human subjects; Life Sciences; Mathematical models; Noise; Phased arrays; Radar data; Radar systems; Receivers & amplifiers; Respiration; Signal and Image processing; Signal processing; Subspace methods; Ultrawideband radar; single-input multiple-output (SIMO); respiration rate; generalized Goertzel algorithm (GGA); impulse-response ultra-wideband (IR-UWB) radar; direction of arrival (DOA)
• ISSN: 2079-9292; 2079-9292
• DOI: 10.3390/electronics10222805

Respiration rate monitoring using ultra-wideband (UWB) radar is preferred because it provides contactless measurement without restricting the person’s privacy. This study considers a novel non-contact-based solution using a single-input multiple-output (SIMO) UWB impulse radar. In the proposed system, the collected radar data are converted to several narrow-band signals using the generalized Goertzel algorithm (GGA), which are used as the input of the designed phased arrays for position estimation. In this context, we introduce the incoherent signal subspace methods (ISSM) for the direction of arrivals (DOAs) and distance evaluation. Meanwhile, a beam focusing approach is used to determine each individual and estimate their breathing rate automatically based on a linearly constrained minimum variance (LCMV) beamformer. The experimental results prove that the proposed algorithm can achieve high estimation accuracy in a variety of test environments, with an error of 2%, 5%, and 2% for DOA, distance, and respiration rate, respectively.