TY - GEN
T1 - Fabric Surface Defect Detection Based on GMRF Model
AU - Xu, Yichen
AU - Meng, Fanwu
AU - Wang, Lizhong
AU - Zhang, Mingyi
AU - Wu, Changshuo
N1 - Publisher Copyright:
© 2021 Association for Computing Machinery. All rights reserved.
PY - 2021/5/28
Y1 - 2021/5/28
N2 - Frequency Hopping communication is widely used in communication countermeasures. In order to realize effective tracking interfere to frequency hopping signal, it is necessary to estimate parameters of frequency hopping signal quickly and accurately. In this paper, an estimation method of hopping rate of frequency hopping Signal based on wavelet transform is proposed. Under the background of strong computing power of the current processor, the smooth pseudo Wigner-Ville distribution with high precision and good attenuation of cross terms is used to obtain the time-frequency distribution of the signal. The peak value of time-frequency distribution in the time axis is extracted as the signal for further processing. Then, the wavelet transform of appropriate scale is selected to carry out on the signal. Finally, Fourier transform is carried out to extract the peak value and estimate hopping rate of the signal. Experimental results show that this method has strong anti-noise performance and high stability.
AB - Frequency Hopping communication is widely used in communication countermeasures. In order to realize effective tracking interfere to frequency hopping signal, it is necessary to estimate parameters of frequency hopping signal quickly and accurately. In this paper, an estimation method of hopping rate of frequency hopping Signal based on wavelet transform is proposed. Under the background of strong computing power of the current processor, the smooth pseudo Wigner-Ville distribution with high precision and good attenuation of cross terms is used to obtain the time-frequency distribution of the signal. The peak value of time-frequency distribution in the time axis is extracted as the signal for further processing. Then, the wavelet transform of appropriate scale is selected to carry out on the signal. Finally, Fourier transform is carried out to extract the peak value and estimate hopping rate of the signal. Experimental results show that this method has strong anti-noise performance and high stability.
KW - Frequency hopping signal
KW - Hopping rate estimation
KW - Wavelet transform
UR - http://www.scopus.com/inward/record.url?scp=85113511745&partnerID=8YFLogxK
U2 - 10.1145/3469213.3471336
DO - 10.1145/3469213.3471336
M3 - Conference contribution
AN - SCOPUS:85113511745
T3 - ACM International Conference Proceeding Series
BT - Proceedings of 2021 2nd International Conference on Artificial Intelligence and Information Systems, ICAIIS 2021
PB - Association for Computing Machinery
T2 - 2nd International Conference on Artificial Intelligence and Information Systems, ICAIIS 2021
Y2 - 28 May 2021 through 30 May 2021
ER -