The Deconvolution of Lunar Brightness Temperature based on Maximum Entropy Method using Chang'E-2 Microwave Data

TL;DR

This paper applies the maximum entropy method to deconvolve lunar brightness temperature data from Chang'E-2 microwave observations, improving the accuracy of lunar surface property analysis.

Contribution

It introduces and verifies the maximum entropy method for deconvolving lunar brightness temperature data, enhancing data resolution and accuracy.

Findings

MEM effectively deconvolves microwave data

Results improve understanding of lunar surface properties

Method verified through simulations and real data

Abstract

A passive and multi-channel microwave sounder onboard Chang'E-2 orbiter has successfully performed microwave observation of the lunar surface and subsurface structure. Compared with Chang'E-1 orbiter, Chang'E-2 orbiter obtained more accurate and comprehensive microwave brightness temperature data which is helpful for further research. Since there is a close relationship between microwave brightness temperature data and some related properties of the lunar regolith, such as the thickness, temperature and dielectric constant, so precise and high resolution brightness temperature is necessary for such research. However, through the detection mechanism of the microwave sounder, the brightness temperature data acquired from the microwave sounder is weighted by the antenna radiation pattern, so the data is the convolution of the antenna radiation pattern and the lunar brightness temperature. In order to obtain the real lunar brightness temperature, a deconvolution method is needed. The aim of this paper is to solve the problem in performing deconvolution of the lunar brightness temperature. In this study, we introduce the maximum entropy method(MEM) to process the brightness temperature data and achieve excellent results. The paper mainly includes the following aspects: firstly, we introduce the principle of the MEM, secondly, through a series of simulations, the MEM has been verified an efficient deconvolution method, thirdly, the MEM is used to process the Chang'E-2 microwave data and the results are significant.