The functions and characteristics of the 1 st to 9 th Reticon signals used to measure positions of reticle/slit images in the LLMC are described in this paper. According to their characteristics, we present a new method to process these Reticon signals, which consists of a filtering algorithm and a centering algorithm. The filtering algorithm is developed to process the 5 th to 9 th Reticon signals, because in these signals there are obvious disturbance components caused by the background light in the microscopes. An auto-estimating technique is developed to estimate and eliminate the disturbance signal of the background light by a piecewise-linear fitting. The centering algorithm is used to determine the positions of all the reticle/slit images in 3 steps. The first is to search all the wave crests and troughs of a Reticon signal, the next is to determine a threshold for each wave and then to center the wave by a modified moment method so as to get the position of the reticle/slit image, and the last step is to average all the position data of the waves in a Reticon signal to get an integrate position data of a group of reticles/slits in the corresponding reading microscope. The technique of implementation of the method in C++ programming language is also described in the paper.