Results 111 to 120 of about 5,738 (222)

Radar Simulation of Human Micro-Doppler Signature From Video Motion Capture Data

, 2013
The availability of data sets on which signal processing techniques may be tested is critical to the development of human detection, identification, and classification algorithms.
Karabacak, Cesur, Gürbüz, Sevgi Zübeyde, Gürbüz, Ali Cafer   +2 more
core  

Human Micro-Range/Micro-Doppler Signature Extraction, Association, and Statistical Characterization for High-Resolution Radar

, 2011
Recently, the use of micro-Doppler (μD) radar signatures for classification has become an area of focus, in particular for the case of dynamic targets where many components are interacting over time. To fully exploit the signature information, individual
Fogle, Orelle Ryan
core   +1 more source

Radar Micro-Doppler Feature Extraction Using the Spectrogram and the Cepstrogram

, 2014
The radar micro-Doppler signature of a target is determined by parts of the target moving or rotating in addition to the main body motion. The relative motion of parts is characteristic for different classes of targets, e.g. the flapping motion of a bird'
Prémel Cabic, G., G. Premel Cabic, Wit, J.J.M. de, Harmanny, R.I.A., R. I. A. Harmanny, J. J. M. de Wit   +5 more
core   +1 more source

Radar UAV and bird signature comparisons with micro-Doppler [PDF]

, 2021
Ritchie, M, Peters, N, Horne, C
openaire   +2 more sources

Cross-frequency training with adversarial learning for radar micro-Doppler signature classification

This dataset presents the micro-Doppler spectrogram data used in the paper titled "Cross-frequency training with adversarial learning for radar micro-Doppler signature classification"
Rahman, Mahbubur (Mahbub), Fioranelli, Francesco, Kurtoglu, Emre, Gurbuz, Sevgi Zubeyde, Macks, Trevor   +4 more
core  

Radar Micro-Doppler Mini-UAV Classification using Spectrograms and Cepstrograms

, 2015
The radar micro-Doppler signature of a target is determined by parts of the target moving or rotating in addition to the main body motion. The relative motion of these parts is characteristic for different classes of targets, e.g.
Prémel-Cabic, G., Wit, J.J.M. de, Harmanny, R.I.A.   +2 more
core  

Gait Variations in Human Micro-Doppler

, 2011
Gait Variations in Human Micro-DopplerMeasurement of human gait variation is important for security applications such as the indication of unexpected loading due to concealed weapons.
Jerry Silvious, Silvious, J., Tahmoush, D., Dave Tahmoush   +3 more
core   +1 more source

Hand Gesture Recognition Using FSK Radar Sensors

Sensors
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 ...
Kimoon Yang, Minji Kim, Yunho Jung, Seongjoo Lee   +3 more
doaj   +1 more source

Measurement and Analysis of Multiband Bistatic and Monostatic Radar Signatures of Wind Turbines

This paper presents the results of recent measurements taken with two radar systems to measure the simultaneous monostatic and bistatic signature of wind turbines, at S-band and X-band.
Ritchie, MA, Griffiths, H, Fioranelli, F, Balleri, A   +3 more
core  

Knowledge Exploitation for Human Micro-Doppler Classification

, 2015
Micro-Doppler radar signatures have great potential for classifying pedestrians and animals, as well as their motion pattern, in a variety of surveillance applications.
Karabacak, Cesur, Guldogan, Mehmet B., Hendeby, Gustaf, Gurbuz, Sevgi Z., Gurbuz, Ali C., Gustafsson, Fredrik,, Gustafsson, Fredrik, Hendeby, Gustaf,, Gurbuz, Sevgi Z.,, Guldogan, Mehmet B.,, Karabacak, Cesur,, Gurbuz, Ali C.,   +11 more
core   +1 more source