Results 41 to 50 of about 5,844 (217)
Remote SensingMicro-Doppler signatures play a crucial role in capturing target features for the radar classification task, and the time–frequency distribution method is widely used to represent micro-Doppler signatures in many applications including human activities ...
Beili Ma, Baixiao Chen
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Attention‐enhanced Alexnet for improved radar micro‐Doppler signature classification
IET Radar, Sonar & Navigation, 2023 This work introduces an attention mechanism that can be integrated into any standard convolution neural network to improve model sensitivity and prediction accuracy with minimal computational overhead.
Shelly Vishwakarma +5 more
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Micro-Doppler Signature Analysis for Space Domain Awareness Using VHF Radar
Remote SensingThe large quantity of resident space objects orbiting Earth poses a threat to safety and efficient operations in space. Radar sensors are well suited to detecting objects in space including decommissioned satellites and debris, whereas the more commonly ...
Emma Heading +3 more
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Advanced Materials Technologies, EarlyView.This study explores how machine learning models, trained on small experimental datasets obtained via Phase Doppler Anemometry (PDA), can accurately predict droplet size (D32) in ultrasonic spray coating (USSC). By capturing the influence of ink complexity (solvent, polymer, nanoparticles), power, and flow rate, the model enables precise droplet control
Pieter Verding +5 more
wiley +1 more source
Orientation-Independent Human Activity Recognition Using Complementary Radio Frequency Sensing
Sensors, 2023 RF sensing offers an unobtrusive, user-friendly, and privacy-preserving method for detecting accidental falls and recognizing human activities. Contemporary RF-based HAR systems generally employ a single monostatic radar to recognize human activities ...
Muhammad Muaaz +2 more
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Metasurface‐Enabled Active‐Like Passive Radar
Advanced Science, EarlyView.A programmable space‐time‐coding metasurface embeds distinct spatiotemporal tags into ambient wireless signals, allowing passive radar to operate in an active‐like manner. By enabling code‐correlated reconstruction under interference, the approach supports robust real‐time UAV tracking in complex environments and points to intelligent, low‐power ...
Mingyi Li +7 more
wiley +1 more source
Dynamic Hand Gesture Classification Based on Multistatic Radar Micro-Doppler Signatures Using Convolutional Neural Network [PDF]
, 2019 We propose a novel convolutional neural network (CNN) for dynamic hand gesture classification based on multistatic radar micro-Doppler signatures. The timefrequency spectrograms of micro-Doppler signatures at all the receiver antennas are adopted as ...
Griffiths, Hugh +7 more
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Sensors, 2020 We present a technique for the identification of human and animal movement and height using a low power millimeter-wave radar. The detection was based on the transmission of a continuous wave and heterodyning the received signal reflected from the target
Yael Balal +3 more
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Extraction of jet engine parameters from micro‐Doppler signatures using continuous wavelet transform
IET Radar, Sonar & Navigation, 2021 Micro‐Doppler signatures in jet engine modulated (JEM) radar signals are used to extract jet engine features for automatic target recognition. Herein, a novel algorithm based on the continuous wavelet transform (CWT) is used to determine the spool rate ...
Shreya Ramakanth +4 more
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Advanced Science, EarlyView.A DLN dataset was built to analyze MABS composition versus in vitro/in vivo osteogenesis and angiogenesis. An MLP neural network, taking BG morphological parameters as input, extracts bioactive features from these datasets. A rabbit tibial defect model then validates 4D‐printed MABS for adaptability and bone regeneration in critical defects.
Xiongjie Liang +12 more
wiley +1 more source