基于最大熵方法月球表面亮温度数据处理模拟  

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

作　　者：邢树果[1,2] 苏彦[1] 周建锋[3] 刘建忠[1] 

机构地区：[1]中国科学院国家天文台,北京100012 [2]中国科学院大学,北京100049 [3]清华大学工程物理系天体物理中心,北京100084

出　　处：《天文研究与技术》2013年第3期255-263,共9页Astronomical Research & Technology

基　　金：国家自然科学基金(11173038)资助

摘　　要：由天线成像原理可知,通过密云50 m天线、"嫦娥一号"卫星(CE-1)和"嫦娥二号"卫星(CE-2)所搭载微波探测仪获取的月球亮温度图是微波天线方向图与真实亮温度图的卷积,所以想清晰准确地还原亮温度图,就必须采取反卷积方法。在处理过程中引入最大熵方法,选择基于Bonavito提出的直接迭代法求解方式,并论证了其作为反卷积方法的可行性,通过一系列的模拟仿真验证其反卷积的有效性。仿真结果理想,对后期处理真实数据(密云50 m天线观测数据,微波探测仪观测数据)打下坚实的基础。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.

关 键 词：射电天文学 最大熵方法 反卷积 亮温度 

分 类 号：P184.5[天文地球—天文学]