@inproceedings{4b8e0b19f435454894cf12b8b8f9a79c,
title = "Rf compressed sensing radar based on digital beamforming for localization and iot applications",
abstract = "This paper presents the concept of a radio frequency (RF) compressed sensing radar for indoor localization. A digital beamforming architecture for RF physical layer compressed sensing is discussed. Compressed sensing can reconstruct an under-sampled signal provided it is sparse in nature. A pseudo random multi-beam radiation pattern will be used to scan the target frame. The spatial sparsity in the target frame helps in recovering the entire frame using less number of scans compared to the conventional indoor localization system.",
keywords = "compressed sensing, pseudo random multi-beam radiation pattern, sparsity",
author = "Prateek Nallabolu and Changzhi Li",
note = "Publisher Copyright: {\textcopyright} 2019 ACES.; 2019 International Applied Computational Electromagnetics Society Symposium in Miami, ACES-Miami 2019 ; Conference date: 14-04-2019 Through 18-04-2019",
year = "2019",
month = may,
day = "10",
language = "English",
series = "2019 International Applied Computational Electromagnetics Society Symposium in Miami, ACES-Miami 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2019 International Applied Computational Electromagnetics Society Symposium in Miami, ACES-Miami 2019",
}