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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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Volume 5, issue 11
Atmos. Meas. Tech., 5, 2859–2866, 2012
https://doi.org/10.5194/amt-5-2859-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
Atmos. Meas. Tech., 5, 2859–2866, 2012
https://doi.org/10.5194/amt-5-2859-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 26 Nov 2012

Research article | 26 Nov 2012

Using particle filter to track horizontal variations of atmospheric duct structure from radar sea clutter

X. F. Zhao1,2, S. X. Huang1, and D. X. Wang2 X. F. Zhao et al.
  • 1College of Meteorology and Oceanography, PLA University of Science and Technology, Nanjing, China
  • 2State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou, China

Abstract. This paper addresses the problem of estimating range-varying parameters of the height-dependent refractivity over the sea surface from radar sea clutter. In the forward simulation, the split-step Fourier parabolic equation (PE) is used to compute the radar clutter power in the complex refractive environments. Making use of the inherent Markovian structure of the split-step Fourier PE solution, the refractivity from clutter (RFC) problem is formulated within a nonlinear recursive Bayesian state estimation framework. Particle filter (PF), which is a technique for implementing a recursive Bayesian filter by Monte Carlo simulations, is used to track range-varying characteristics of the refractivity profiles. Basic ideas of employing PF to solve RFC problem are introduced. Both simulation and real data results are presented to confirm the feasibility of PF-RFC performances.

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