Cross-Correlation Wavelet-Domain-Based Particle Swarm Optimization for Lightning Mapping
Source abstract
Abstract
Several processing methods have been proposed for estimating the real pattern of the temporal location and spatial map of the lightning strikes. However, due to the complexity of lightning signals, providing accurate lightning maps estimation remains a challenging task. This paper presents a cross-correlation wavelet-domain-based particle swarm optimization (CCWD-PSO) technique for an accurate and robust representation of lightning mapping. The CCWD method provides an initial estimate of the lightning map, while the PSO attempts to optimize the trajectory of the lightning map by finding the optimal sliding window of the cross-correlation. The technique was further enhanced through the introduction of a novel lightning event extraction method that enables faster processing of the lightning mapping. The CCWD-PSO method was validated and verified using three narrow bipolar events (NBEs) flashes. The observed results demonstrate that this technique offers high accuracy in representing the real lightning mapping with low estimation errors.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Lightning and Electromagnetic Phenomena · Fire effects on ecosystems · Plant Water Relations and Carbon Dynamics
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Institute of Sustainable Energy (ISE), Universiti Tenaga Nasional (UNITEN), Selangor 43000, Malaysia
Atmospheric and Lightning Research Laboratory, Center for Telecommunication Research and Innovation (CeTRI), Fakulti Kejuruteraan Elektronik dan Kejuruteraan Komputer (FKEKK), Universiti Teknikal Malaysia Melaka (UTeM), Melaka 76100, Malaysia
Department of Science, Technology, Engineering and Mathematics, American University of Afghanistan, Darul Aman, Kabul 4001, Afghanistan
School of Information Technology, Monash University Malaysia, Selangor 47500, Malaysia
Graduate School of Engineering, Osaka University, 1-1 Yamadaoka, Suita, Osaka 565-0871, Japan
References (27)
Show source-provided references
1. Lightning Mapping: Techniques, Challenges, and Opportunities10.1109/ACCESS.2020.3031810 ↗
2. A GPS-based Three-Dimensional Lightning Mapping System: Initial Observations in Central New Mexico W10.1029/1999GL010856 ↗
3. Alammari, A., Alkahtani, A.A., Ahmad, M.R., Noman, F., Esa, M.R.M., Sabri, M.H.M., Mohammad, S.A., Al-Khaleefa, A.S., Kawasaki, Z., and Agelidis, V. (2020). Kalman Filter and Wavelet Cross-Correlation for VHF Broadband Interferometer Lightning Mapping. Appl. Sci., 10.10.3390/app10124238 ↗
4. Continuous broadband digital interferometry of lightning using a generalized cross-correlation algorithm10.1002/2013JD020217 ↗
5. Data processing procedure using distribution of slopes of phase differences for broadband VHF interferometer10.1002/2013JD020378 ↗
6. Lightning VHF radiation location system based on short-baseline TDOA—Validation in rocket-triggered lightning10.1016/j.atmosres.2012.11.010 ↗
7. Review of the Location of VHF Pulses Associated with Lightning Discharge
8. Stock, M., and Krehbiel, P. (2014, January 11–18). Multiple baseline lightning interferometry—Improving the detection of low amplitude VHF sources. Proceedings of the 2014 International Conference on Lightning Protection (ICLP), Shanghai, China.10.1109/ICLP.2014.6973139 ↗
9. Kernels on structured objects through nested histograms
10. Particle swarm optimization: A new tool to invert geophysical data10.1190/1.2432481 ↗
11. Optimal power flow by a fuzzy based hybrid particle swarm optimization approach10.1016/j.epsr.2011.02.011 ↗
12. Optical and electrical observations of an abnormal triggered lightning event with two upward propagations10.1007/s13351-012-0411-x ↗
13. Application of particle swarm optimization to interpret Rayleigh wave dispersion curves10.1016/j.jappgeo.2012.05.011 ↗
14. Experiments of artificially triggered lightning and its application in Conghua, Guangdong, China10.1016/j.atmosres.2013.02.010 ↗
15. Optimal power flow using particle swarm optimization10.1016/S0142-0615(01)00067-9 ↗
16. Characteristics of the initial stage and return stroke currents of rocket-triggered lightning flashes in southern China10.1002/2016JD026235 ↗
17. A hybrid firefly and particle swarm optimization algorithm for computationally expensive numerical problems10.1016/j.asoc.2018.02.025 ↗
18. Use of PSO to determine lightning channelbase-current function parameters for standard severe negative first and subsequent return stroke approximation10.1049/iet-smt.2018.5320 ↗
19. EEG Signals Denoising Using Optimal Wavelet Transform Hybridized with Efficient Metaheuristic Methods10.1109/ACCESS.2019.2962658 ↗
20. Freitas, D., Lopes, L.G., and Morgado-Dias, F. (2020). Particle Swarm Optimisation: A Historical Review Up to the Current Developments. Entropy, 22.10.3390/e22030362 ↗
21. Hu, Z., Wen, Y., Zhao, W., and Zhu, H. (2010, January 10–12). Particle swarm optimization-based algorithm for lightning location estimation. Proceedings of the 2010 Sixth International Conference on Natural Computation, Yantai, China.10.1109/ICNC.2010.5582925 ↗
22. Guo, X., Zhu, Y., Chen, H., Zhao, L., Chen, X., and Gao, Y. (2015, January 11–13). Research and Validation of Lightning Location Based on Particle Swarm Optimization Algorithm. Proceedings of the 2015 International Conference on Intelligent Systems Research and Mechatronics Engineering, Zhengzhou, China.10.2991/isrme-15.2015.166 ↗
23. Parametric Reconstruction Method for the Long Time-Series Return-Stroke Current of Triggered Lightning Based on the Particle Swarm Optimization Algorithm10.1109/ACCESS.2020.3004202 ↗
24. The evaluation of parallel plate antenna with variation of air gaps separation and copper plate area
25. Abeywardhana, R., Sonnadara, U., Abegunawardana, S., Fernando, M., and Cooray, V. (2018, January 2–7). Lightning Localization Based on VHF Broadband Interferometer Developed in Sri Lanka. Proceedings of the 2018 34th International Conference on Lightning Protection (ICLP), Rzeszow, Poland.10.1109/ICLP.2018.8503396 ↗
26. Single-Station-Based Lightning Mapping System With Electromagnetic and Thunder Signals10.1109/TPS.2019.2891087 ↗
27. Ghazvinian, H., Mousavi, S.-F., Karami, H., Farzin, S., Ehteram, M., Hossain, S., Fai, C.M., Bin Hashim, H., Singh, V.P., and Ros, F.C. (2019). Integrated support vector regression and an improved particle swarm optimization-based model for solar radiation prediction. PLoS ONE, 14.10.1371/journal.pone.0217634 ↗