An Information Entropy-Based Sensitivity Analysis of Radar Sensing of Rough Surface

Yu Liu,Kun-Shan Chen

doi:10.3390/rs10020286

Abstract

We apply Shannon entropy, an information content measure, in sensitivity analysis (SA), stemming from the fact that the essence of SA is to preserve the maximum information content of the parameters of interest that are inverted from the radar response. Then, the sensitivity to the observation configuration and surface parameters is subsequently analyzed. Attempts are also made to explore advantages, by maximizing the information content, of dual-polarization and multi-angle in improving the parameter retrieval from radar sensing of rough surface. Simulation results show that the entropy is a good indicator of the sensitivity of the radar response to the surface parameter, as it contains information on not only the probability distribution of the scattering coefficient but also on its deviation. By information entropy, richer details, to large extent, on the scattering behavior are offered through quantitatively predicting the scattering signal saturation, evaluating the effect of using multi-polarization and multi-angle observation configuration, and identifying non-significant variables. It is found that Shannon entropy, compared to Renyi entropy, appears to better represent the sensitivity with respect to monotonic variation and narrower parameter ranges. The proposed entropy-based SA method helps to deepen our understanding of the microwave scattering behavior in response to surface parameters.

Highlights

Parameter sensitivity analysis (SA) of electromagnetic waves scattering from a randomly rough surface is pivotal in the field of remote sensing of surface geometrical and dielectric parameters [1,2,3]
One of the critical issues in the estimation of surface parameters from radar responses is that the surface parameters, including surface roughness and dielectric constant, are strongly coupled under a certain set of radar parameters [4,5,6,7,8]
The results show that information entropy is a good indicator of sensitivity of radar response to surface parameters because it reflects probabilistic distribution, and the deviation

Summary

Introduction

Parameter sensitivity analysis (SA) of electromagnetic waves scattering from a randomly rough surface is pivotal in the field of remote sensing of surface geometrical and dielectric parameters [1,2,3]. One of the critical issues in the estimation of surface parameters from radar responses is that the surface parameters, including surface roughness (rms height and correlation length) and dielectric constant, are strongly coupled under a certain set of radar parameters (wavelength, incident angle and polarization) [4,5,6,7,8]. It has been both theoretically and practically motivated to conduct a parameter SA to determine an optimal observation configuration and to determine an appropriate approach for sensing and decoupling, to an optimal level, the surface roughness and dielectric constant. These studies generally focus on the average impact of the input factors on the model outputs, and show difficulty, to certain extent, in accurately coming up with the sensitivity when the model input is uncertain or when the model is nonlinear [12,13]

Methods

Discussion

Conclusion