Analysis and applications of backscattered frequency correlation function

作     者：Sarabandi, K Nashashibi, A 

作者机构：Univ Michigan Dept Elect Engn & Comp Sci Ann Arbor MI 48109 USA 

出 版 物：《IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING》 (IEEE Trans Geosci Remote Sens)

年 卷 期：1999年第37卷第4期

页      面：1895-1906页

核心收录：

学科分类：0808[工学-电气工程] 1002[医学-临床医学] 08[工学] 0708[理学-地球物理学] 0816[工学-测绘科学与技术] 

基　　金：Institute for Remote Sensing Applications Joint Research Center of European Commission 

主　　题：frequency correlation function radar backscatter random media 

摘      要：In this paper, the application of the radar backscatter frequency correlation for classification and inversion of physical parameters of terrestrial targets is investigated. Traditionally, in radar remote sensing, the backscattering coefficients and the backscatter phase difference statistics of a distributed target are considered for estimating the biophysical parameters of interest. Because of the complex nature of random media scattering problems, however, target classification and parameter inversion algorithms are very convoluted. One obvious way of enhancing the success and accuracy of an inversion algorithm is to expand the dimension of the input vector space. Depending on the radar parameters, such as footprint (pixel) size, incidence angle, and the target attributes (physical parameters), the backscatter signal decorrelates as function of frequency. In this paper, analytical and experimental procedures are developed to establish a relationship between the complex frequency correlation function (FCF) of the backscatter and the radar and target attributes. Specifically, two classes of distributed targets are considered: 1) rough surfaces and 2) random media. Analytical expressions for the frequency correlation function are derived and it is shown that the effect of radar parameters can be expressed explicitly and thus removed from the measured correlation functions. The University of Michigan wideband polarimetric scatterometer systems are used to verify the theoretical models and inversion algorithms developed in this study.