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

Due to the absence of vegetation, season, 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 has 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.

由于月球表面不存在植被、季节变化、天气扰动以及人工建筑，月球上任意位置的周边地平线掩码（Surrounding Horizon Mask, SHM）均保持恒定。由于月球表面温度高于寒冷的太空背景，可通过星载红外传感器或相机清晰提取出SHM特征。该过程可快速完成，且不受光照条件、观测区域以及月相的影响。月球南极地区地貌丰富且无海洋与高原，这使得每个位置的SHM均具备独特的特征标识。自2019年起，研究团队借助美国国家航空航天局（National Aeronautics and Space Administration, NASA）的LOLA数字高程模型开展南极周边地平线掩码的建模与构建工作，以支撑多项月球基地架构相关研究。将用户获取的SHM与已知区域预先计算得到的SHM进行简单关联或匹配，即可精准确定用户所在位置。本文探究了利用本地SHM识别月面用户位置与姿态的可行性。研究中开展了包含随机倾斜偏差与仪器误差在内的本地SHM数值仿真实验。初步研究结果表明，在仪器校准得当且性能达标时，平均自主定位误差可控制在数米至数十米范围内，平均姿态误差则不超过0.5度。