Abstract

The increasing number of agile earth observation satellites (AEOSs) in orbit have advanced maneuverable capabilities, enabling the AEOS constellation to provide richer observation services. Therefore, observation scheduling in the AEOS constellation is crucial for improving the performance of satellite remote sensing systems. This paper focuses on the problem of distributed observation scheduling in the AEOS constellation, where a period of transition time is required between two consecutive observations, and this constraint depends on the start time of observations. We define a new fitness function that not only maximizes the profit sum but also considers system load balancing. Based on the fundamental idea of a distributed performance impact (PI) algorithm, we develop a PI-based distributed scheduling method (PIDSM) that runs concurrently on all AEOSs via local inter-satellite link (ISL)-based communications. The PIDSM iterates between two phases: target inclusion and consensus and target removal. The first phase aims to select the optimal task for each AEOS, while the second phase reaches a consensus over all AEOSs and removes targets that may decrease overall fitness. Experimental results demonstrate that the PIDSM can schedule more targets, reduce communication overhead, and achieve higher fitness values than existing algorithms. Sensitivity analyses further validate the effectiveness of the PIDSM.

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