Fast estimation algorithm for living body radar

Sasakawa, Dai; Konno, Kouichi; Honma, Naoki; Nishimori, Kentaro; Takemura, Noriko; Matsumoto, Tsutomu; Tsunekawa, Yoshitaka

doi:10.1109/isanp.2014.7026785

Cited by 5 publications

(4 citation statements)

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“…The authors previously proposed a fast localization algorithm that estimates subject locations by using the time-variant channel in multi-path environments [17]. In this study, we apply the localization method to the observation channel, and the 3-dimensional location of the subject is estimated by MIMO radar.…”

Section: Human Posture Identification Based On Height Doppler Rcs Of mentioning

confidence: 99%

“…Unwanted path components consist of the direct wave from transmitter to receiver and waves reflected from the walls, floor, and furniture, and these components are static. Therefore, we exclude the undesired components by applying the fast localization algorithm [17] to the converted SIMO channel; the time-differential channel is defined as…”

Section: Three Dimensional Localization Of Human Subjectmentioning

confidence: 99%

“…The authors have proposed a fast living-body localization algorithm where the time-differential channel is used to attain rapid DOA/DOD estimation in multi-path environments [17]. This algorithm identifies the differences among observation times that correspond to cyclic human body activities such as respiration and heartbeat.…”

Section: Introductionmentioning

confidence: 99%

“…This method estimates a three-dimensionally target location by using the time-differential channel technique [17]; the Doppler radar cross section (RCS) is calculated from the power reflected from the target and the distance between the estimated location and the receiver/transmitter. The human posture is identified by applying the nearest neighbor algorithm [19] to the estimated height and the Doppler RCS information.…”

Section: Introductionmentioning

confidence: 99%

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Human Posture Identification Using a MIMO Array

et al. 2018

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Abstract:The elderly are constantly in danger of falling and injuring themselves without anyone realizing it. A safety-monitoring system based on microwaves can ease these concerns. The authors have proposed safety-monitoring systems that use multiple-input multiple-output (MIMO) radar to localize persons by capturing their biological activities such as respiration. However, our studies to date have focused on localization, which is easier to achieve than an estimation of human postures. This paper proposes a human posture identification scheme based on height and a Doppler radar cross section (RCS) as estimated by a MIMO array. This scheme allows smart home applications to dispense with contact and wearable devices. Experiments demonstrate that this method can identify the supine position (i.e., after a fall) with 100% accuracy, and the average identification rate is 95.0%.

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Section: Human Posture Identification Based On Height Doppler Rcs Of mentioning

confidence: 99%

Section: Three Dimensional Localization Of Human Subjectmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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