Monte-Carlo Based Estimation Methods for Rapidly-Varying Sea Clutter

Author

Li, Ying ; Moran, William ; Sira, Sandeep P. ; Papandreou-Suppappola, Antonia ; Morrell, Darryl

Author_Institution

Dept. of Electr. Eng., Arizona State Univ., Tempe, AZ

fYear

2009

fDate

4-7 Jan. 2009

Firstpage

256

Lastpage

261

Abstract

We consider two Monte-Carlo based methods for characterizing the scattering function of rapidly-varying sea clutter. The first method uses multiple particle filtering to estimate the clutter space-time covariance matrix by exploiting the structure of the matrix. This method is then compared to a baseline approach that estimates the clutter covariance matrix based on the Weibull distribution approximation. Both methods are evaluated by formulating a detection problem that simulates a small moving target in heavy sea clutter.

Keywords

Monte Carlo methods; Weibull distribution; covariance matrices; filtering theory; geophysical signal processing; oceanographic techniques; radar clutter; Monte Carlo based estimation methods; Weibull distribution approximation; clutter space-time covariance marix; multiple particle filtering; rapidly-varying sea clutter; Clutter; Covariance matrix; Filtering; Layout; Particle scattering; Radar detection; Radar scattering; Reflectivity; Statistical distributions; Weibull distribution; Monte Carlo simulations; Multiple particle filtering; Weibull distribution; covariance matrix estimation;

fLanguage

English

Publisher

ieee

Conference_Titel

Digital Signal Processing Workshop and 5th IEEE Signal Processing Education Workshop, 2009. DSP/SPE 2009. IEEE 13th

Conference_Location

Marco Island, FL

Print_ISBN

978-1-4244-3677-4

Electronic_ISBN

978-1-4244-3677-4

Type

conf

DOI

10.1109/DSP.2009.4785931

Filename

4785931