Ground-based Radar Three-Dimensional Imaging for Moon under Sparse Observations

Ground-based radar system (GBRs) is a powerful tool to obtain three-dimensional (3-D) imagery of the interested celestial bodies, such as the moon. However, in 3-D moon imaging with GBRs, positions for observation are distributed sparsely, and it will lead to imaging ambiguity in height dimension. In this article, a ground-based radar 3-D imaging method for moon under sparse observation is proposed. First, baseline distribution is analyzed, and an optimal baseline selection algorithm based on spatial baseline density maximization is applied. Then, a tomographic 3-D imaging algorithm is discussed, and compressive sensing (CS) technique is used to recover the elevation signal under sparse observation. Moreover, computer simulations are conducted and validate the proposed method.