A Novel Autonomous Lunar Self-Localization Technique Based on Local Surrounding Horizon Mask

Due to the absence of vegetation, seasons, weather, and artificial human-made structures, the surrounding horizon mask (SHM) at each location on the Moon remains unchanged. Because the lunar surface temperature is higher than the cold sky, the SHM signature can be extracted distinguishably using an onboard infrared sensor or camera. This process can be completed quickly and independently of lighting conditions, regions, and lunar phases. The fact that landscapes at the lunar South Pole are full of features and lack oceans and plateaus helps create the SHM at each location with a unique signature. Modeling and constructing SHMs for the Lunar South Pole using NASA's LOLA Digital Elevation Map have started since 2019 to support several lunar architecture studies. A simple correlation or matching of the user's SHM with the precomputed SHM of a known region can pinpoint the user's location. This paper investigates the feasibility of using local SHM to identify the location and orientation of a surface user. Numerical simulations of local SHM, including random tilting biases and instrument errors, are implemented. Our preliminary results show that, with appropriate instrument calibration and performance, the average self-localization errors can be a few meters to tens of meters, and the average orientation errors are within half a degree.