Method of Estimating Human Orientation Using Array Antenna

Shiraki, Nobuyuki; Chen, Zhixiong; Sasakawa, Dai; Honma, Naoki; Nakayama, Tomohiro; Iizuka, Satoshi

doi:10.3390/electronics7060092

Cited by 3 publications

(2 citation statements)

References 10 publications

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“…As for the computational complexity, in the first step of the proposed method, just a single multiplication is required; in the second step, the calculation of 𝒘 T 𝒙 requires 𝑀 multiplications, resulting in a total of 𝑀 + 1 multiplications. A comparison with other state-ofthe-art methods is presented in Table 4, in which [14] is based on a classification instead of a regression for classes of angles 0, 60 • , 120 • , • • • , 300 • ; [18] is based on a classification for three classes (supine, prone, side) using an effective radar cross section; [19] requires eight radar systems, whereas our method requires only a single radar system, which demonstrates the advantage of our approach.…”

Section: B Performance Evaluation Of Proposed Methodsmentioning

confidence: 99%

Radar-Based Estimation of Human Body Orientation Using Respiratory Features and Hierarchical Regression Model

Sun,

Iwata,

Tanaka

et al. 2023

IEEE Sens. Lett.

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This study proposes an accurate method to estimate human body orientation using a millimeter-wave radar system. Body displacement is measured from the phase of the radar echo, which is analyzed to obtain features associated with the fundamental and higher-order harmonic components of the quasi-periodic respiratory motion. These features are used in body-orientation estimation invoking a novel hierarchical regression model in which a logistic regression model is adopted in the first step to determine whether the target person is facing forwards or backwards; a pair of ridge regression models are employed in the second step to estimate body-orientation angle. To evaluate the performance of the proposed method, respiratory motions of five participants were recorded using three millimeter-wave radar systems; cross-validation was also performed. The average error in estimating body orientation angle was 38.3 • and 23.1 • using respectively a conventional method with only the fundamental frequency component and our proposed method, indicating an improvement in accuracy by factor 1.7 when using the proposed method. In addition, the coefficient of correlation between the actual and estimated body-orientation angles using the conventional and proposed methods are 0.74 and 0.91, respectively. These results show that by combining the characteristic features of the fundamental and higher-order harmonics from the respiratory motion, the proposed method offers better accuracy.

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Section: B Performance Evaluation Of Proposed Methodsmentioning

confidence: 99%

Radar-Based Estimation of Human Body Orientation Using Respiratory Features and Hierarchical Regression Model

Sun,

Iwata,

Tanaka

et al. 2023

IEEE Sens. Lett.

View full text Add to dashboard Cite

show abstract

“…Experimental results showed that the human location and posture identification achieved an accuracy of over 90%. Another method for the estimation of the human body orientation was proposed by Shiraki et al [10]. To this aim, they analyzed the temporal responses captured by multiple antennas of a Multiple-Input Multiple-Output time-variant channel radar.…”

Section: The Present Special Issuementioning

confidence: 99%