Mission scheduling optimization of SAR satellite constellation for minimizing system response time

Abstract A Synthetic Aperture Radar (SAR) satellite constellation can be used in Intelligence, Surveillance and Reconnaissance (ISR) missions such as the detection of abnormal activities by repeatedly observing an area of interest (AoI). In order to cover an AoI more efficiently, coverage overlap should be avoided. Mission scheduling optimization can be greatly beneficial in increasing the observation efficiency of a constellation of satellites equipped with SAR payloads. This paper describes an optimal scheduling algorithm developed for such missions and the proposed Concept of Operation (CONOP). The optimization of constellation operation was performed by minimizing the system response time which is defined as the time it takes from the user image request to final distribution of the data. An optimizing algorithm based on a genetic algorithm is introduced in order to reduce the system response time. In this paper, the modeling and mission scheduling algorithm for this type of mission has been developed and described. The results show that the mission planning using the optimal scheduler can reduce the system response time, and this reduction is more pronounced when the coverage criterion (required area coverage %) is higher.