Abstract Novel materials with high electrical, optical, and thermal functionalities are crucial in next‐generation space missions. Astronauts’ well‐being demands continuous health monitoring, while stray light suppression and heat dissipation are vital for space telescopes. Here, it is demonstrated that laser‐induced graphene (LIG), patterned with femtosecond laser pulses, serves as a versatile material for temperature/strain sensing, stray light absorption, and heat management for smart spacesuits and telescopes. LIG exhibits a superior temperature coefficient of resistance (−0.068% °C⁻¹), gauge factor of 454, optical absorption (97.57%), and heat diffusivity (6.376 mm 2 s −1 ) via a single platform. Furthermore, thermal‐vacuum tests confirm LIG's reliability and readiness for space missions. Under vacuum conditions (≈10 −3 Torr) and repeated temperature changes ranging from −20 to 60 °C over a period of ≈40 h, the temperature/strain sensor, and optical absorbers maintain the functionality.

This paper proposes a scan method to reduce the acquisition time of inter-satellite links based on the satellite position error distribution. The errors are modeled as an anisotropic multivariate Gaussian distribution, and the field of uncertainty (FOU) is defined as the 5-sigma region of this distribution. Due to the significant errors typically found in the along-track direction, the FOU often takes an elliptical shape. We propose a scanning pattern to scan the elliptical FOU efficiently. Our approach was validated through Monte-Carlo simulations and analyses using GPS data from NEXTSat-2. The results indicate that the proposed scan method is more effective than the traditional method when the FOU is more elliptical. In the case of NEXTSat-2, the efficiency of the proposed method was confirmed, with the ratio of the semi-minor to the semi-major axis was less than 0.2 in 70% of cases.

This study presents a deep learning-based model for predicting annual mean sea level (MSL) in the East Sea, with a focus on the Ulleungdo Island region, which maintains an independent vertical datum. To account for long-term tidal variability, the model enables continuous estimation of hourly and annual MSL values. Two recurrent neural network (RNN) architectures—Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU)—were constructed and compared. Observational tide gauge data from 1 January 2000 to 3 August 2018 (covering 18.6 years and a full tidal nodal cycle) were preprocessed through missing-value and outlier treatment, followed by min–max normalization, and then structured for sequential learning. Comparative analysis demonstrated that the GRU model slightly outperformed the LSTM model in predictive accuracy and training stability. As a result, the GRU model was selected to produce annual MSL forecasts for the period 2018–2021. The GRU achieved a mean RMSE of approximately 0.44 cm during this prediction period, indicating robust performance in forecasting hourly sea level variations. The findings highlight the potential of deep learning methods to support vertical datum determination in island regions and to provide reliable sea level estimates for integration into coastal and oceanographic modeling. The proposed approach offers a scalable framework for long-term sea level prediction under evolving geodetic conditions.

Free space optical communication systems on satellites require precise pointing, but mechanical micro-vibrations in the satellite platform can degrade the pointing. The actuator in the pointing system, a fast steering mirror, limits its effectiveness due to the non-constant velocity of the transient motion. This study proposes a multi-rate adaptive algorithm that utilizes a faster sensor rate to capture the transient behavior. The gradient update equation for the error function is derived that incorporates the multi-rate architecture, and its convergence with the stability condition is thoroughly examined. The analysis provides insights into the least-mean-square algorithm's behavior with sinusoidal inputs. Simulation results validate the effectiveness of the multirate approach over the single-rate method in the complex sinusoidal disturbances. Further validation was obtained from experimental data using an optical testbed, which was consistent with simulations. This study validates a multi-rate adaptive control strategy for precise pointing in satellite free space optical communications, offering a solution for resource-constrained platforms.