Concurrent multi-task pre-processing method for LEO mega-constellation based on dynamic spatio-temporal grids

Abstract

The Low Earth Orbit (LEO) remote sensing satellite mega-constellation has the characteristics of large quantity and various types which make it have unique superiority in the realization of concurrent multiple tasks. However, the complexity of resource allocation is increased because of the large number of tasks and satellites. Therefore, the primary problem of implementing concurrent multiple tasks via LEO mega-constellation is to pre-process tasks and observation re-sources. To address the challenge, we propose a pre-processing algorithm for the mega-constellation based on highly Dynamic Spatio-Temporal Grids (DSTG). In the first stage, this paper describes the management model of mega-constellation and the multiple tasks. Then, the coding method of DSTG is proposed, based on which the description of complex mega-constellation observation resources is realized. In the third part, the DSTG algorithm is used to realize the processing of concurrent multiple tasks at multiple levels, such as task space attribute, time attribute and grid task importance evaluation. Finally, the simulation result of the proposed method in the case of constellation has been given to verify the effectiveness of concurrent multi-task pre-processing based on DSTG. The autonomous processing process of task decomposition and task fusion and mapping to grids, and the convenient indexing process of time window are verified.