Approximate Path Searching Method for Single‐Satellite Observation and Transmission Task Planning Problem

Abstract

Satellite task planning not only plans the observation tasks to collect images of the earth surface, but also schedules the transmission tasks to download images to the ground station for users’ using, which plays an important role in improving the efficiency of the satellite observation system. However, most of the work to our knowledge, scheduling the observation and transmission tasks separately, ignores the correlation between them in resource (e.g., energy and memory) consumption and acquisition. In this paper, we study the single-satellite observation and transmission task planning problem under a more accurate resource usage model. Two preprocessing strategies including graph partition and nondominated subpaths selection are used to decompose the problem, and an improved label-setting algorithm with the lower bound cutting strategy is proposed to maximize the total benefit. Finally, we compare the proposed method with other three algorithms based on three data sets, and the experimental result shows that our method can find the near-optimal solution in much less time.

A network flow approach for constellation planning

“…Some works have considered both the image collection and data relay problems within the same framework and provided various solutions to solve them [31][32][33] . However, Hu et al dedicated most of their paper to evaluating a branch and price technique for finding a solution instead of also providing an in-depth explanation of the problem itself [32] .…”

“…Additionally, Hu et al simulated a small LEO constellation of only 3 satellites and did not evaluate the solution methodology in the proliferated LEO context that the industry is beginning to witness today [34] . Similarly, Peng et al only formulated their planning problem for a single satellite and neglected its application to a multi-agent cooperative system [33] . It is the opinion of the authors of this paper that a truly applicable solution to the GEOINT constellation scheduling problem must be capable of simultaneously planning operations for at least 100 Earth imaging satellites and delivering a robust solution for each of the individual spacecraft elements.…”