Multi-Satellite Scheduling Using Genetic Algorithms

ISRO Telemetry Tracking and Command Network (ISTRAC) operate a fleet of Indian remote Sensing Satellites (IRS) in the low earth polar sun-synchronous orbits. Satellite Operations Scheduling of ground stations is one of the important tasks performed at Spacecraft Control Centre (SCC). In the prevailing multiple-satellite operations scenario, scheduling becomes complex, because of satellite-specific constraints, ground station configuration, satellite priorities and priorities of payload and special operations. Further, radio visibility conflicts are to be taken in to consideration, while generating the weekly operations schedule. Resolving the visibility clash at a ground station and allocating Telemetry, Tracking and Command (TTC) resources optimally for multiple satellites meeting the requirements of each mission are the key aspects of scheduling. Optimal resolution of visibility clashes is performed using Genetic Algorithms. The software, “Intelligent Multi-Objective Priority Activated Task Optimizer (IMPACT)” uses Artificial Intelligence and constraint directed search to generate weekly optimal schedule of spacecraft support. IMPACT is designed to resolve spacecraft controller clashes as well, thus enabling a single controller to perform multiple spacecraft operations. This software also ensures that the operations load is distributed uniformly to all the ground stations in the TTC network. This paper presents the multi-satellite operations scenario of Indian Remote Sensing satellites at ISTRAC and the details of operations scheduling scheme adopted. The variants of visibility clash topologies, the optimization scheme based on genetic algorithm including the mathematical model for gain function, scheduling software architecture and its salient features are described. Important design features of this operational software system are highlighted with examples.