Remote sensing of atmospheric duct parameters using simulated annealing

doi:10.1088/1674-1056/20/9/099201

Abstract Simulated annealing is one of the robust optimization schemes. Simulated annealing mimics the annealing process of the slow cooling of a heated metal to reach a stable minimum energy state. In this paper, we adopt simulated annealing to study the problem of the remote sensing of atmospheric duct parameters for two different geometries of propagation measurement. One is from a single emitter to an array of radio receivers (vertical measurements), and the other is from the radar clutter returns (horizontal measurements). Basic principles of simulated annealing and its applications to refractivity estimation are introduced. The performance of this method is validated using numerical experiments and field measurements collected at the East China Sea. The retrieved results demonstrate the feasibility of simulated annealing for near real-time atmospheric refractivity estimation. For comparison, the retrievals of the genetic algorithm are also presented. The comparisons indicate that the convergence speed of simulated annealing is faster than that of the genetic algorithm, while the anti-noise ability of the genetic algorithm is better than that of simulated annealing.

Keywords: remote sensing refractivity estimation electromagnetic wave propagation simulated annealing

Received: 19 January 2011
Revised: 19 May 2011
Accepted manuscript online:

PACS:	92.60.Ta	(Electromagnetic wave propagation)
	78.20.Ci	(Optical constants (including refractive index, complex dielectric constant, absorption, reflection and transmission coefficients, emissivity))
	02.30.Zz	(Inverse problems)

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Zhao Xiao-Feng(赵小峰), Huang Si-Xun(黄思训), Xiang Jie(项杰), and Shi Wei-Lai(施伟来) Remote sensing of atmospheric duct parameters using simulated annealing 2011 Chin. Phys. B 20 099201

[1]	Halvey R A 1983 Proc. IEEE Part F 130 643
[2]	Richter J H 1969 Radio Sci. 4 1261
[3]	Rogers L T, Hattan C P and Stapleton J K 2000 Radio Sci. 35 955
[4]	Gerstoft P, Rogers L T, Krolik J L and Hodgkiss W S 2003 Radio Sci. 38 8053
[5]	Gerstoft P, Rogers L T, Hodgkiss W S and Wagner L J 2003 IEEE J. Oceanic Eng. 28 513
[6]	Barrios A E 2004 Radio Sci. 39 RS6013
[7]	Vasudevan S, Anderson R H, Kraut S, Gerstoft P, Rogers L T and Krolik J 2007 Radio Sci. 42 RS2014
[8]	Yardim C 2007 Statistical Estimation and Tracking of Refractivity from Radar Clutter (Ph.D. Dissertation) (San Diego: University of California San Diego)
[9]	Douvenot R, Fabbro V, Gerstoft P, Bourlier C and Saillard J 2008 Radio Sci. 43 RS6005
[10]	Douvenot R, Fabbro V, Gerstoft P, Bourlier C and Saillard J 2010 Radio Sci. 45 RS1007
[11]	Huang S X, Zhao X F and Sheng Z 2009 Chin. Phys. B 18 5084
[12]	Sheng Z, Huang S X and Zhao X F 2009 Acta Phys. Sin. 58 6627 (in Chinese)
[13]	Wang B, Wu Z S, Zhao Z W and Wang H G 2009 Prog. Electromagn. Res. M 9 79
[14]	Zhao X F, Huang S X and Sheng Z 2010 Chin. Phys. B 19 049201
[15]	Gingras D F, Gerstoft P and Gerr N L 1997 IEEE Trans. Antennas Propagat. 45 1536
[16]	Tabrikian J and Krolik J L 1999 IEEE Trans. Antennas Propag. 47 1727
[17]	Gerstoft P, Gingras D F, Rogers L T and Hodgkiss W S 2000 IEEE Trans. Antennas Propagat. 48 345
[18]	Valtr P and Pechac P 2005 XXVIIIth General Assembly of International Union of Radio Science, October 23—29, 2005, New Delhi, India
[19]	Zhao X F, Huang S X and Du H D 2011 Radio Sci. 46 RS1006
[20]	Kirkpatrick S, Gelatt C D and Vecchi M P 1983 Science 220 671
[21]	Lam J 1988 An Efficient Simulated Annealing Schedule (Ph.D. Dissertation) (New Haven: Yale University)
[22]	Hitney H V and Vieth R 1990 IEEE Trans. Antennas Propag. 38 794
[23]	Rogers L T 1997 Radio Sci. 32 79
[24]	Metropolis N, Rosenbluth A W, Rosenbluth M N, Teller A H and Teller E 1953 J. Chem. Phys. 21 1087
[25]	Goffe W L, Ferrier G D and Rogers J 1994 J. Econometrics 60 65
[26]	http://emlab.berkeley.edu/Software/abstracts/goffe895.html
[27]	Kuttler J R and Dockery G D 1991 Radio Sci. 26 381
[28]	Barrios A E and Patterson W L 2002 Advanced Propagation Model (APM) Ver. 1.3.1 Computer Software Configuration Item (CSCI) Documents Technical Document 3145, San Diego, California
[29]	Wang B, Wu Z S, Zhao Z W and Wang H G 2009 Chin. J. Radio Sci. 24 598 (in Chinese)

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