Chandrayaan-2 Dual Frequency SAR Data Preprocessing and Analysis for Lunar Crater Detection

Lunar Craters are crucial features to understand the moon’s geology. Lunar craters provide us with various information about the composition of the lunar surface. Detection and classification of these craters is essential in studying and analyzing them. This paper presents a comprehensive study on the processing and analysis of Chandrayaan-2 Dual Frequency Synthetic Aperture Radar (DFSAR) data for lunar crater detection. The DFSAR data offers unique advantages, including enhanced penetration through lunar regolith and improved target discrimination. A methodology that combines data preprocessing, CFAR-based edge detection, ratio edge detection, and post-processing techniques to identify lunar craters is analyzed in the paper and future improvements are suggested.