Simulations of Processing of Data of Brightness Temperature Map of the Lunar Surface with the Maximum Entropy Method

As understandable from the data acquisition processes a brightness temperature map of the lunar surface recorded by the microwave detector on the Miyun 50m radio telescope, CE-1, or CE-2 is the convolution of the actual brightness temperature distribution by the antenna pattern. If we want to accurately restore the brightness temperature distribution a deconvolution method is needed. Among the deconvolution methods of the radio astronomy, the CLEAN method and the Maximum Entropy Method (MEM) are the most popular. Though the results of the CLEAN method in processing data of point sources are satisfactory, the MEM has more advantages in dealing with those of extended sources. This paper chooses the MEM for this reason. The paper first describes the MEM and a direct iterative solution algorithm proposed by Bonavito. The paper shows the feasibility of the Bonavita algorithm and validates it through a series of simulations. The satisfactory simulation results provide the basis for future use of the MEM to deconvolve actual data observed by the Miyun 50m radio telescope, CE-1, and CE-2. Currently, the data processing method for the Chang E Series CELME detection uses the linear method. The application of the MEM can effectively open new opportunities for improving data quality and leading to potential discoveries.