@inproceedings{Adilson2017GNSSb,

title = {GNSS Signal Acquisition Below Shannon-Nyquist: A Perspective on Sparse Recovery},

author = {Adilson Chinatto and Naiallen Carolyne Rodrigues Lima Carvalho and Cynthia Junqueira},

url = {https://www.sige.ita.br/edicoes-anteriores/2017/st/ST_05_2.pdf},

year  = {2017},

date = {2017-01-01},

booktitle = {Simp\'{o}sio de Aplica\c{c}\~{o}es Operacionais em \'{A}reas de Defesa 2017 (SIGE2017)},

abstract = {Acquisition is a crucial process in GNSS systems as it determines which satellites are visible, a course estimation of the Doppler shift and an initial estimation of the time delay between the transmitter and the receiver. Commonly, acquisition is performed by serial search or by circular correlation search. Both processes, although very understood and deployed in practical systems are very time and computational consuming. In this work it is shown that acquisition process is intimately related to the compressive sensing framework, enabling under- sampling of the received signal yet keeping recovery guarantees. Simulation results presented points towards a new and interesting direction in which the GNSS acquisition can be performed using sampling rates far below the Shannon-Nyquist limits, leading to simplification of hardware and software.},

keywords = {compressive sensing, GNSS, Sparse Optimization},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Adilson2015Radarb,

title = {Compressive Sensing: Uma Ferramenta Alternativa para Estima\c{c}\~{a}o de Dire\c{c}\~{a}o de Chegada},

author = {Adilson Chinatto and Cynthia Junqueira and Jo\~{a}o Marcos T Romano and Pascal Larzabal},

url = {https://www.sige.ita.br/edicoes-anteriores/2015/st/ST_1_1.pdf},

year  = {2015},

date = {2015-01-01},

booktitle = {Simp\'{o}sio de Aplica\c{c}\~{o}es Operacionais em \'{A}reas de Defesa 2015 (SIGE2015)},

abstract = {Este trabalho apresenta ferramentas baseadas no conceito de esparsidade, com aplica\c{c}\~{a}o no problema de estima\c{c}\~{a}o de dire\c{c}\~{a}o de chegada (DOA) em arranjos de antenas. As t\'{e}cnicas tratadas pertencem ao conhecido escopo do compressive sensing e representam uma alterna- tiva realista e menos custosa aos m\'{e}todos de estima\c{c}\~{a}o de DOA tradicionais como o MUSIC e o ESPRIT, permitindo estima\c{c}\~{a}o precisa mesmo em cen\'{a}rios com poucas antenas e uso de poucos snapshots.},

keywords = {compressive sensing, DOA, Radar},

pubstate = {published},

tppubtype = {inproceedings}

}