A Mission Planning Modeling Method of Multipoint Target Imaging Within a Single Pass for Super-Agile Earth Observation Satellite

Abstract

The existing mission planning models for conventional agile Earth observation satellites assuming stable push-broom imaging cannot be directly adapted to newly developed superagile Earth observation satellites (SA-EOS) with dynamic imaging capabilities. To guarantee the application efficiency of SA-EOS, a novel mission planning modeling method for multipoint target imaging within a single pass (MTI-SP) is proposed. First, a two-step preprocessing method for point targets based on the “nonalong-track” characteristic of SA-EOS converts multiple point targets into imaging strips as an atomic mission for further planning. Then, a triple of decision variables is defined, i.e., the index of the imaging sequence of multiple strips, indices of the push-broom direction of the strips, and normalization coefficients of the imaging time of each endpoint of the strips, on the basis of the one-to-one correspondence between the triple and the imaging time. Third, an optimal MTI-SP mission planning model with two objective functions, namely maximizing the mission coverage benefit (MCB) and minimizing the mission completion time (MCT), is established by considering the imaging time window and attitude transition time. An improved particle swarm optimization algorithm is used for the MTI-SP solution. The results of comparison experiments indicate that the proposed model can achieve the maximum MCB with lower computational consumption. Compared with the two fixed push-broom sequence models and the independent point targets model, the MCT of the proposed model is improved by 47.1%, 24.56%, and 89.45%, respectively. The experiment results show that the proposed modeling method can be further applied in ground operational systems of SA-EOS.