Deep Learning for Accurate Indoor Human Tracking with a mm-Wave Radar

We address the use of backscattered mm-wave radio signals to track humans as they move within indoor environments. The common approach in the literature leverages the extended Kalman filter (EKF) method, which however undergoes a severe performance degradation when the system evolution model is high...

Celý popis

Podrobná bibliografia

Vydané v:	Proceedings of the IEEE National Radar Conference (1996) s. 1 - 6
Hlavní autori:	Pegoraro, Jacopo, Solimini, Domenico, Matteo, Federico, Bashirov, Enver, Meneghello, Francesca, Rossi, Michele
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 21.09.2020
Predmet:	denoising autoencoders Extraterrestrial measurements human tracking indoor sensing mm-wave radar Neural networks Noise reduction Radar tracking sequence-to-sequence autoencoders Spaceborne radar Target tracking Trajectory
ISSN:	2375-5318
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!