Simulations of the millimeter-wave interferometric signature of walking humans

Nanzer, Jeffrey A.

doi:10.1109/aps.2012.6349159

Cited by 6 publications

(4 citation statements)

References 5 publications

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“…The micro-Doppler signature refers to a unique characteristic with respect to a distinguished change in the frequency that is caused by the movement of a target. Micro-Doppler signatures have been researched in various fields, which include human behavior, biosignals, and distinction from animals, and they are widely utilized in real life [ 28 , 29 ].…”

Section: Micro-doppler Systemmentioning

confidence: 99%

Hand Gesture Recognition Using FSK Radar Sensors

Yang,

Kim,

Jung

et al. 2024

Sensors

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Hand gesture recognition, which is one of the fields of human–computer interaction (HCI) research, extracts the user’s pattern using sensors. Radio detection and ranging (RADAR) sensors are robust under severe environments and convenient to use for hand gestures. The existing studies mostly adopted continuous-wave (CW) radar, which only shows a good performance at a fixed distance, which is due to its limitation of not seeing the distance. This paper proposes a hand gesture recognition system that utilizes frequency-shift keying (FSK) radar, allowing for a recognition method that can work at the various distances between a radar sensor and a user. The proposed system adopts a convolutional neural network (CNN) model for the recognition. From the experimental results, the proposed recognition system covers the range from 30 cm to 180 cm and shows an accuracy of 93.67% over the entire range.

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Section: Micro-doppler Systemmentioning

confidence: 99%

Hand Gesture Recognition Using FSK Radar Sensors

Yang,

Kim,

Jung

et al. 2024

Sensors

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“…A micro‐Doppler system and efficient classifier were demonstrated to identify different individuals and gender [90]. An interferometric radar was shown to have advantages in the case of slow‐moving humans for classification [91]. Multistatic micro‐Doppler signatures can improve the performance of oblique‐angle classification [92] using mutual information to find the degree of importance of features for the target classification issue [93].…”

Section: Review Of Micro‐doppler Effect In Radarmentioning

confidence: 99%

Review of micro‐Doppler signatures

Tahmoush

2015

IET Radar, Sonar & Navigation

122

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“…The measurement of target velocity by this method is based on the Doppler frequency of the target [13]. However, the Doppler frequency is insensitive to targets with only a tangential velocity or weak radial velocity [14], the reason being that the velocity of a moving object is a vector, and the position of the target relative to the observation radar will affect the radial and transverse components of its velocity. Therefore, when the radial velocity of the target is weak or the moving direction is perpendicular to the line of sight (LOS) of the radar, the radar cannot effectively estimate the target velocity by the Doppler frequency.…”

Section: Introductionmentioning

confidence: 99%

A New Side-Looking Scheme for Speed Estimation and Detection of Tangential Slow-Moving Targets

Huang

2022

Sensors

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A single-beam radar system cannot adopt a side-looking installation scheme, which is completely perpendicular to the moving direction of the target in an intelligent transportation system (ITS), because of its own limitations. In this paper, a side-looking radar velocity measurement system that utilizes a new signal processing method and multi-channel radar scheme is proposed. Constant false alarm rate (CFAR) and generalized likelihood ratio test (GLRT) detectors are used to detect the data processing results in different stages in order to reduce the false alarm rate of targets. At the same time, a deconvolution-based clutter map algorithm is proposed to solve the problem of clutter interference in the test environment, and its theoretical performance is verified by simulation. Finally, 77 G commercial radar is used to test the system, and the results show that this algorithm can effectively detect and accurately estimate the speed of tangential low-speed targets under clutter interference.

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Simulations of the millimeter-wave interferometric signature of walking humans

Cited by 6 publications

References 5 publications

Hand Gesture Recognition Using FSK Radar Sensors

Hand Gesture Recognition Using FSK Radar Sensors

Review of micro‐Doppler signatures

A New Side-Looking Scheme for Speed Estimation and Detection of Tangential Slow-Moving Targets

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