References: |
-
P. Lu, N. Lalam, M. Badar, B. Liu, B. T. Chorpening, M. P. Buric, and P. R. Ohodnicki, “Distributed optical fiber sensing: Review and perspective,” Appl. Phys. Rev, vol. 6, pp 1-35, 2019.
-
A. Motil, A. Bergman, and M. Tur, “State of the art of Brillouin fiber-optic distributed sensing,” Opt. & Laser Technol., vol. 78, no. A, pp 81-103, 2016.
-
D. Iida, N. Honda, and H. Oshida, “Advances in distributed vibration sensing for optical communication fiber state visualization,” Opt. Fiber Technol. 102263, vol. 57, pp 1-9, 2020.
-
A. Coscetta, A. Minardo, and L. Zeni, “Distributed Dynamic Strain Sensing Based on Brillouin Scattering in Optical Fibers,” Sensors 5629, vol. 20, no. 19, pp 1-23, 2020.
-
X. Angulo-Vinuesa, S. Martin-Lopez, P. Corredera, and M. Gonz ́alez-Herr ́aez, “Raman-assisted Brillouin optical time-domain analysis with sub-meter resolution over 100 km,” Opt. Express, vol. 20, no. 11, pp 12147-12154, 2012.
-
S. Wang, Z. Yang, S. Zaslawski, and L. Thévenaz, “Short spatial resolution retrieval from a long pulse Brillouin optical time-domain analysis trace,” Opt. Lett., vol. 45, no. 15, pp 4152-4155, 2020.
-
A. K. Azad, F. N. Khan, W. H. Alarashi, N. Guo, A. P. T. Lau and C. Lu, “Temperature extraction in Brillouin optical time-domain analysis sensors using principal component analysis based pattern recognition,” Opt. Express, vol. 25, no. 14, pp 16534-16549, 2017.
-
A. K. Azad, L. Wang, N. Guo, H. Y. Tam and C. Lu, “Signal processing using artificial neural network for BOTDA sensor system,” Opt. Express, vol. 24, no. 6, pp 6769-6782, 2016
-
N. D. Nordin, M. S. D. Zan, and F. Abdullah, “Comparative Analysis of the Deployment of Machine Learning Algorithms in the Distributed Brillouin Optical Time Domain Analysis (BOTDA) Fiber Sensor,” Photonics 79, vol. 7, no. 4, pp 1-13, 2020.
-
M. A. Soto, and L. Thévenaz, “Modeling and evaluating the performance of Brillouin distributed optical fiber sensors,” Opt. Express, vol. 21, no. 25, pp 31347-31366, 2013.
-
K. Yu, N. Guo, Z. Cao, S. Lou, C. Shang, and J. He, “Fast information acquisition using spectra subtraction for Brillouin distributed fiber sensors,” Opt. Express, vol. 27, no. 7, pp 9696-9704, 2019.
-
A. K. Azad, “Analysis of 2D Discrete Wavelet Transform Based Signal Denoising Technique in Brillouin Optical Time Domain Analysis Sensors,” The Dhaka University JASE, vol. 5, no. 1 & 2, pp 1-8, 2020.
-
M. A. Farahani, E. Castillo-Guerra, and B. G. Colpitts, “Accurate Estimation of Brillouin frequency shift in Brillouin optical time domain analysis sensors using cross correlation,” Opt. Lett., vol. 36, no. 21, pp 4275-4277, 2011.
-
X. Qian, X. Jia, Z. Wang, B. Zhang, N. Xue, W. Sun, Q. He and H. Wu, “Noise level estimation of BOTDA for optimal non-local means denoising,” Appl. Opt, vol. 56, no. 16, pp 4727-4734, 2017.
-
M. A. Soto, J. A. Ramírez, and L. Thévenaz, “Optimizing Image Denoising for Long-Range Brillouin Distributed Fiber Sensing,” J. Lightwave Technol. vol. 36, no. 4, pp 1168–1177, 2018.
-
K. Luo, B. Wang, N, Guo, K. Yu, C. Yu, and C. Lu, “Enhanced SNR by Anisotropic Diffusion for Brillouin Distributed Optical Fiber Sensors,” J. Lightwave Technol.vol. 38, no. 20, pp 5844–5852, 2020.
-
M. A. Farahani, E. Castillo-Guerra, and B. G. Colpitts, “A Detailed Evaluation of the Correlation-Based Method Used for Estimation of the Brillouin frequency shift in BOTDA sensors,” IEEE Sensors J., vol. 13, no. 12, pp 4589-4598, 2013.
-
M. A. Farahani, M. T. V. Wylie, E. Castillo-Guerra, and F. G. Colpitts, “Reduction in the number of averages required in BOTDA sensors using wavelet denoising techniques,” J. Lightwave Technol. vol. 30, no. 8, pp 1134–1142, 2012.
-
M. A. Soto, J. A. Ramírez, and L. Thévenaz, “Intensifying the response of distributed optical fibre sensors using 2D and 3D image restoration,” Nat. Commun. 10870, 7, pp 1-11, 2016.
-
M. A. A. El-Fattah, M. I. Dessouky, A. M. Abbas, S. M. Diab, E. M. El-Rabaie, W. Al-Nuaimy, S. A. Alshebeili, and F. E. A. El-Samie, 2014, “Speech enhancement with an adaptive Wiener filter,” Int. J. Speech Technol., 17, pp 53-64.
-
S. K. Jadwa, “Wiener Filter based Medical Image Denoising,” Int. J. Sci. & Engg. Applications, vol. 7, no. 9, pp 318-323, 2018.
-
F. Wu, W. Yang, L.Xiao, and J. Zhu, “Adaptive Wiener Filter and Natural Noise to Eliminate Adversarial Perturbation,” Electronics 1634, vol. 9, no. 10, pp 1-14, 2020.
-
C. R. Park, S. H. Kang, and Y. Lee, “Median modified Wiener filter for improving the image quality of gamma camera images,” Nuclear Engg. & Technol., vol. 52, no. 10, pp 2328-2333, 2020.
-
Z. Zhao, A. Zhao, J. Hui, B. Hou, R. Sotudeh, and F. Niu, “A Frequency-Domain Adaptive Matched Filter for Active Sonar Detection,” Sensors 1565, vol. 17, no. 7, pp 1-12, 2017.
-
B. A. Odhavjibhai, and S. Rana, “Analysis of Matched filter based spectrum sensing in cognitive radio,” Int. Research J. Engg, & Technol., vol. 4, no. 4, pp 578-581, 2017.
-
S. Kalhoro, F. A. Umrani, M. A. Khanzada, and L. A. Rahoo, “Matched Filter Based Spectrum Sensing for 4G Cellular Network,” Mehran Univ. Research J. Engg. & Technol., vol. 38, no. 4, pp 973-978, 2019.
-
J. P. Bailey, A. N. Beal, R. N. Dean, and M. C. Hamilton, “A digital matched filter for reverse time chaos,” Chaos 073108, vol. 26, no. 7, pp 1-8, 2016.
-
A. K. Azad, “Effects of pump-pulse width and temperature on experimental Brillouin gain spectrum obtained from Brillouin optical time-domain analysis sensors,” Bangladesh J. Physics, vol. 27, no. 1, pp 69-80, 2020.
|