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2009-10-13
Retrieving Evaporation Duct Heights from Radar Sea Clutter Using Particle Swarm Optimization (PSO) Algorithm
By
Progress In Electromagnetics Research M, Vol. 9, 79-91, 2009
Abstract
Particle Swarm Optimization algorithm (PSO) is a popular stochastic searching optimization algorithm to solve complicated optimization problems. The approach of retrieving duct parameters from the sea-surface reflected radar clutter is also known as Refractivity From Clutter (RFC) technique. RFC technique provides the near-real-time duct parameters to evaluate the radio system performance, without adding any hardware. Basic principles of PSO and its applications and RFC technique are introduced. Evaporation duct is retrieved based on RFC technique using PSO. The performance of PSO is validated using experiment data launched at East China Sea, and compared with those of genetic algorithm (GA) and ant colony algorithm (ACA). The results indicate that PSO has the advantages of faster convergence and higher retrieval precision than the other two methods.
Citation
Bo Wang Zhen-Sen Wu Zhenwei Zhao Hong-Guang Wang , "Retrieving Evaporation Duct Heights from Radar Sea Clutter Using Particle Swarm Optimization (PSO) Algorithm," Progress In Electromagnetics Research M, Vol. 9, 79-91, 2009.
doi:10.2528/PIERM09090403
http://www.jpier.org/PIERM/pier.php?paper=09090403
References

1. Rogers, L. T., C. P. Hattan, and J. L. Krolik, "Using radar sea echo to estimate surface layer refractivity profiles," IGARSS'99 Proceeding, IEEE 1999 Internation, Vol. 1, 658-662, 1999.

2. Gerstoft, P., et al., "Inversion for refractivity parameters from radar sea clutter," Radio Science, Vol. 38, No. 3, 1-22, 2003.
doi:10.1029/2002RS002640

3. Yardim, C., Statistical estimation and tracking of refractivity from radar clutter, Ph.D. Dissertation, Electrical Engineering, University of California, San Diego, 2007.

4. Li, G., et al., "Necessary conditions for forming duct propagation and simulation of electromagnetic wave propagation," Journal of Nanjing Institute of Meteorology, Vol. 26, No. 5, 631-637, 2003.

5. Zhao, X.-L., "Study of the electromagnetic field distribution under evaporation duct environment," Master Dissertation, 2005.

6. Hu, X., et al., "Effect of meteorological conditions on atmospheric duct," Scientia Meteorologica Sinica, Vol. 27, No. 3, 349-354, 2007.

7. Zhang, X. and X.-L. Zhang, "Influence of atmospheric ducts on radar ranging and height-finding," Fire Control and Command Control, Vol. 31, No. 8, 84-87, 2006.

8. Liu, C.-G., et al., "Characteristics of the lower atmospheric duct in China," Journal of Xidian University, Vol. 29, No. 1, 119-122, 2002.

9. Lin, F.-J., et al., "Statistical analysis of marine atmospheric duct," Chinese Journal of Radio Science, Vol. 20, No. 1, 64-68, 2005.

10. Wang, H., Y. Zhao, and X.-M. Huang, "A study on the performance of radar detection in presence of atmospheric waveguide," Modern Radar, Vol. 26, No. 4, 5-8, 2006.

11. Han, J., "Study on inversion the low-altitude atmospheric refractivity profile from radar sea clutter ," Master Dissertation, China Academy of Electronics and Information Technology, Beijing, 2008.

12. Tian, M.-J., "Intelligent inversion algorithms and applications,".

13. Yang, Z.-X., et al., "Application of particle swarm optimization to multi-parameters fitting," Journal of Zhejiang Normal University (Natural Sciences), Vol. 31, No. 2, 173-177, 2008.

14. Wei, J.-X. and Y.-P. Wang, "Smooth scheme and line search based particle swarm optimization for constrained optimization problems," Systems Engineering and Electronics, Vol. 30, No. 4, 739-742, 2008.

15. Panduro, M. A., C. A. Brizuela, L. I. Balderas, and D. A. Acosta, "A comparison of genetic algorithms, parti-cle swarm optimization and the di®eren-tial evolution method for the design of scannable circular antenna arrays," Progress In Electromagnetics Research B, Vol. 13, 171-186, 2009.
doi:10.2528/PIERB09011308

16. Isaakidis, S. A. and T. D. Xenos, "Parabolic equation solution of tropospheric wave propagation using FEM," Progress In Electromagnetics Research, Vol. 49, 257-271, 2004.
doi:10.2528/PIER04042701

17. Semnani, A. and M. Kamyab, "An enhanced method for inverse scattering problems using fourier series expansion in conjunction with FDTD and PSO," Progress In Electromagnetics Research, Vol. 76, 45-64, 2007.
doi:10.2528/PIER07061204

18. Wu, Z.-S., J.-P. Zhang, and L.-X. Guo, "An improved two-scale model with volume scattering for the dynamic ocean surface," Progress In Electromagnetics Research, Vol. 89, 39-56, 2009.
doi:10.2528/PIER08111803

19. Zainud-Deen, S. H., E. El-Deen, M. S. Ibrahim, K. H. Awadalla, and A. Z. Botros, "Electromagnetic scattering using gpu-based finite difference frequency domain method," Progress In Electromagnetics Research B, Vol. 16, 351-369, 2009.
doi:10.2528/PIERB09060703

20. Bourlier, C., H. He, J. Chauveau, R. Hemon, and P. Pouliguen, "RCS of large bent waveguide ducts from a modal analysis combined with the kirchhoff approximation," Progress In Electromagnetics Research, Vol. 88, 1-38, 2008.
doi:10.2528/PIER08101708

21. Song, H. N., W. D. Hu, W. J. Yu, and J. H. Wu, "Model and simulation of low grazing angle radar sea clutter," Chinese Journal of National University of Defense Technology, Vol. 22, No. 3, 30-34, 2000.

22. Morchin, W. C., "Airborne Early Warning Radar," Artech House, Norwood, MA, 1990.

23. Peng, S. R. and Z. R. Tang, "Reflectivity model of ground/sea clutter," Journal of Air Force Radar Academy, Vol. 14, No. 4, 1-4, 2000.

24. Horst, M. M., F. B. Dyer, and M. T. Tuley, Radar sea clutter model, 6, International Conference on Antennas and Propagation, London, England, November 28-30, 6-10, 1978.

25. Lin, F.-J., C.-G. Liu, and Z.-W. Pan, "The measurements of atmospheric duct near sea surface and its comparison with other study results," Chinese Journal of Radio Science, Vol. 17, No. 3, 269-272, 2002.

26. Paulus, R. A., "Practical application of an evaporation duct model," Radio Science, Vol. 20, No. 4, 887-896, 1985.
doi:10.1029/RS020i004p00887