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 language | English (US) |
|---|---|
| Title of host publication | 2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 3449-3453 |
| Number of pages | 5 |
| Volume | 2018-April |
| ISBN (Print) | 9781538646588 |
| DOIs | |
| State | Published - Sep 10 2018 |
| Event | 2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Calgary, Canada Duration: Apr 15 2018 → Apr 20 2018 |
Other
| Other | 2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 |
|---|---|
| Country | Canada |
| City | Calgary |
| Period | 4/15/18 → 4/20/18 |
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Keywords
- Coherence
- Cyclostationarity
- Multiple-channel detection
ASJC Scopus subject areas
- Software
- Signal Processing
- Electrical and Electronic Engineering
Cite this
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 proceeding › Conference contribution
}
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 -