Development of Hybrid Genetic Algorithm for Automated Task Planning in Multi-Satellite System

In order to meet the various demands within the satellite broadband industry and to make better use of the available spectrum, communications satellites are becoming more versatile and capable. Mobile robots are frequently located using the Global Navigation Satellite System (GNSS) in an accurate and consistent manner. More monitored satellites can be utilising for multi-GNSS location calculations as GNSS continues to develop and modernise, which can increase positioning accuracy and performance. An enhanced genetic approach for satellite selection was suggested in this work. By arranging the MF (maturity factor) to lead the hybrid and mutation operators, the search execution is ensured while decreasing needless hybrid and mutation activities, therefore shrinking search time. Under continuous epochs, the satellite selection outcomes for subsequent epochs have been enhanced by employing the prior epoch optimal individual inheritance approach. The findings from the experiments validate the efficacy of the proposed strategy.