Multiple Satellite

Multiple satellite systems are revolutionizing data acquisition and analysis across diverse applications, from Earth observation and space situational awareness to deep space exploration. Current research emphasizes efficient data management and processing using onboard machine learning, including convolutional neural networks (CNNs) for image classification and compression, and federated learning (FL) for collaborative model training across distributed satellite constellations. These advancements improve data throughput, reduce reliance on ground stations, and enable real-time decision-making, impacting fields ranging from disaster response and environmental monitoring to improved space traffic management.