@inproceedings{bb9a060159e049a297496f66e1bd4213,
title = "RF Compressed Sensing Based Radar for 2-D Localization and Mapping",
abstract = "This paper presents the simulation results of a radio frequency (RF) compressed sensing (CS) radar for 2-D localization and mapping. In contrast to many existing literatures, this paper deals with the RF front-end compressive sensing, which is achieved by illuminating the target scenario with pseudo random multi-beam radiation patterns. The spatial sparsity of the target frame enables the use of compressed sensing to recover the scene from fewer number of scans compared with a conventional beam scanning radar. Preliminary simulations are performed, and the results of the reconstructed target frame are presented.",
keywords = "2-D localization, compressed sensing, multi-beam radiation pattern, spatial sparsity",
author = "Prateek Nallabolu and Changzhi Li",
year = "2019",
month = may,
doi = "10.1109/IMBIOC.2019.8777784",
language = "English",
series = "IEEE MTT-S 2019 International Microwave Biomedical Conference, IMBioC 2019 - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "IEEE MTT-S 2019 International Microwave Biomedical Conference, IMBioC 2019 - Proceedings",
note = "2019 IEEE MTT-S International Microwave Biomedical Conference, IMBioC 2019 ; Conference date: 06-05-2019 Through 08-05-2019",
}