Cloud characterization by computed tomography methods using a satellite formation of 10 small satellites for improved climate prediction

The CloudCT mission aims to enhance climate predictions by studying warm clouds using a sensor network based on self-organizing small satellites. Warm clouds play a crucial role in the Earth’s radiative budget and the transport of heat, humidity, pollutants, and aerosols from the boundary layer to the free atmosphere. This mission employs ten cooperating nano-satellites to perform polarization sensitive computed tomography (CT) of cloud interiors, using backscattered sunlight. The satellite formation faces the challenge of cooperative attitude and orbit control, as well as camera payload coordination. To address these, the attitude and orbit control system (AOCS) features a modular design and uses a leader-follower configuration for joint cloud observation, which enables autonomous distribution of target information between the satellites. This autonomy reduces pre-processing and operational requirements on the ground and streamlines mission management. Planned for launch in 2026 the mission is in implementation phase and currently undergoing intensive ground performance tests. These tests employ adaptive control models to simulate noisy multi-view space borne images, optimizing CT strategies, and data acquisition. The satellites’ AOCS undergoes extensive testing, involving several simulators and hardware-in-the-loop (HIL) testbeds to ensure reliable operation in-orbit. In the article, the developed AOCS is presented, covering crucial aspects like its mode design, a rule-based, hierarchic redundancy and fault detection, isolation and recovery (FDIR) software approach and the test strategy and environments. The interdisciplinary CloudCT mission combines atmospheric modeling, image processing, and satellite formation flying to improve climate and weather predictions.