Detection of cyclostationarity using generalized coherence

Songsri Sirianunpiboon, Stephen D. Howard, Douglas Cochran

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A class of detectors for cyclostationarity is introduced. These detectors are based on the use of generalized coherence to measure correlation among two or more collections of random vectors. The generalized coherence framework allows any finite collection of pertinent samples of the cyclic auto-correlation function estimates formed from the measured signal data to be combined into the detection statistic. The performance of this approach is demonstrated and compared against other established cyclostationarity detectors in both a cognitive radio scenario and a multi-channel passive surveillance scenario.

Original languageEnglish (US)
Title of host publication2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3449-3453
Number of pages5
Volume2018-April
ISBN (Print)9781538646588
DOIs
StatePublished - Sep 10 2018
Event2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Calgary, Canada
Duration: Apr 15 2018Apr 20 2018

Other

Other2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018
CountryCanada
CityCalgary
Period4/15/184/20/18

Fingerprint

Detectors
Cognitive radio
Autocorrelation
Statistics

Keywords

  • Coherence
  • Cyclostationarity
  • Multiple-channel detection

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

Cite this

Sirianunpiboon, S., Howard, S. D., & Cochran, D. (2018). Detection of cyclostationarity using generalized coherence. In 2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings (Vol. 2018-April, pp. 3449-3453). [8462367] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICASSP.2018.8462367

Detection of cyclostationarity using generalized coherence. / Sirianunpiboon, Songsri; Howard, Stephen D.; Cochran, Douglas.

2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings. Vol. 2018-April Institute of Electrical and Electronics Engineers Inc., 2018. p. 3449-3453 8462367.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Sirianunpiboon, S, Howard, SD & Cochran, D 2018, Detection of cyclostationarity using generalized coherence. in 2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings. vol. 2018-April, 8462367, Institute of Electrical and Electronics Engineers Inc., pp. 3449-3453, 2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018, Calgary, Canada, 4/15/18. https://doi.org/10.1109/ICASSP.2018.8462367
Sirianunpiboon S, Howard SD, Cochran D. Detection of cyclostationarity using generalized coherence. In 2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings. Vol. 2018-April. Institute of Electrical and Electronics Engineers Inc. 2018. p. 3449-3453. 8462367 https://doi.org/10.1109/ICASSP.2018.8462367
Sirianunpiboon, Songsri ; Howard, Stephen D. ; Cochran, Douglas. / Detection of cyclostationarity using generalized coherence. 2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings. Vol. 2018-April Institute of Electrical and Electronics Engineers Inc., 2018. pp. 3449-3453
@inproceedings{6654fa571c3b404eb82d1a1b33ed52b2,
title = "Detection of cyclostationarity using generalized coherence",
abstract = "A class of detectors for cyclostationarity is introduced. These detectors are based on the use of generalized coherence to measure correlation among two or more collections of random vectors. The generalized coherence framework allows any finite collection of pertinent samples of the cyclic auto-correlation function estimates formed from the measured signal data to be combined into the detection statistic. The performance of this approach is demonstrated and compared against other established cyclostationarity detectors in both a cognitive radio scenario and a multi-channel passive surveillance scenario.",
keywords = "Coherence, Cyclostationarity, Multiple-channel detection",
author = "Songsri Sirianunpiboon and Howard, {Stephen D.} and Douglas Cochran",
year = "2018",
month = "9",
day = "10",
doi = "10.1109/ICASSP.2018.8462367",
language = "English (US)",
isbn = "9781538646588",
volume = "2018-April",
pages = "3449--3453",
booktitle = "2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

TY - GEN

T1 - Detection of cyclostationarity using generalized coherence

AU - Sirianunpiboon, Songsri

AU - Howard, Stephen D.

AU - Cochran, Douglas

PY - 2018/9/10

Y1 - 2018/9/10

N2 - A class of detectors for cyclostationarity is introduced. These detectors are based on the use of generalized coherence to measure correlation among two or more collections of random vectors. The generalized coherence framework allows any finite collection of pertinent samples of the cyclic auto-correlation function estimates formed from the measured signal data to be combined into the detection statistic. The performance of this approach is demonstrated and compared against other established cyclostationarity detectors in both a cognitive radio scenario and a multi-channel passive surveillance scenario.

AB - A class of detectors for cyclostationarity is introduced. These detectors are based on the use of generalized coherence to measure correlation among two or more collections of random vectors. The generalized coherence framework allows any finite collection of pertinent samples of the cyclic auto-correlation function estimates formed from the measured signal data to be combined into the detection statistic. The performance of this approach is demonstrated and compared against other established cyclostationarity detectors in both a cognitive radio scenario and a multi-channel passive surveillance scenario.

KW - Coherence

KW - Cyclostationarity

KW - Multiple-channel detection

UR - http://www.scopus.com/inward/record.url?scp=85054217930&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85054217930&partnerID=8YFLogxK

U2 - 10.1109/ICASSP.2018.8462367

DO - 10.1109/ICASSP.2018.8462367

M3 - Conference contribution

AN - SCOPUS:85054217930

SN - 9781538646588

VL - 2018-April

SP - 3449

EP - 3453

BT - 2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

ER -