Bistatic human micro-Doppler signatures for classification of indoor activities
暂无分享,去创建一个
[1] Michael Inggs,et al. Multistatic radar: System requirements and experimental validation , 2014, 2014 International Radar Conference.
[2] Francesco Fioranelli,et al. Centroid features for classification of armed/unarmed multiple personnel using multistatic human micro-Doppler , 2016 .
[3] Gustaf Hendeby,et al. Features for micro-Doppler based activity classification , 2015 .
[4] Francesco Fioranelli,et al. Performance Analysis of Centroid and SVD Features for Personnel Recognition Using Multistatic Micro-Doppler , 2016, IEEE Geoscience and Remote Sensing Letters.
[5] Ram M. Narayanan,et al. Radar micro-Doppler signatures of various human activities , 2015 .
[6] Youngwook Kim,et al. Human Activity Classification Based on Micro-Doppler Signatures Using a Support Vector Machine , 2009, IEEE Transactions on Geoscience and Remote Sensing.
[7] Sevgi Zubeyde Gurbuz,et al. Operational assessment and adaptive selection of micro-Doppler features , 2015 .
[8] Marjorie Skubic,et al. Doppler Radar Fall Activity Detection Using the Wavelet Transform , 2015, IEEE Transactions on Biomedical Engineering.
[9] Boualem Boashash,et al. Human gait recognition with cane assistive device using quadratic time–frequency distributions , 2015 .
[10] Dave Tahmoush,et al. Review of micro-Doppler signatures , 2015 .
[11] Francesco Fioranelli,et al. Aspect angle dependence and multistatic data fusion for micro-Doppler classification of armed/unarmed personnel , 2015 .
[12] H. Wechsler,et al. Micro-Doppler effect in radar: phenomenon, model, and simulation study , 2006, IEEE Transactions on Aerospace and Electronic Systems.
[13] Marco Mercuri,et al. Embedded DSP-Based Telehealth Radar System for Remote In-Door Fall Detection , 2015, IEEE Journal of Biomedical and Health Informatics.
[14] Wenbing Tao,et al. Radar-based fall detection based on Doppler time-frequency signatures for assisted living , 2015 .
[15] Francesco Fioranelli,et al. Feature Diversity for Optimized Human Micro-Doppler Classification Using Multistatic Radar , 2017, IEEE Transactions on Aerospace and Electronic Systems.
[16] V. Chen,et al. Radar Micro-Doppler signatures : processing and applications , 2014 .
[17] Branka Jokanovic,et al. Multi-window time–frequency signature reconstruction from undersampled continuous-wave radar measurements for fall detection , 2015 .
[18] Robert Tibshirani,et al. The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2nd Edition , 2001, Springer Series in Statistics.
[19] Yimin Zhang,et al. Radar Signal Processing for Elderly Fall Detection: The future for in-home monitoring , 2016, IEEE Signal Processing Magazine.
[20] Alessio Balleri,et al. Recognition of humans based on radar micro-Doppler shape spectrum features , 2015 .
[21] Gang Li,et al. Dynamic hand gesture classification based on radar micro-Doppler signatures , 2016, 2016 CIE International Conference on Radar (RADAR).