The CANYVAL-C (CubeSat Astronomy by NASA and Yonsei using a virtual telescope alignment for coronagraph) is a space science demonstration mission that involves taking several images of the solar corona with two CubeSats—1U CubeSat (Timon) and 2U CubeSat (Pumbaa)—in formation flying. In this study, we developed and evaluated structural and thermal designs of the CubeSats Timon and Pumbaa through finite element analyses, considering the nonlinearity effects of the nylon wire of the deployable solar panels installed in Pumbaa. On-orbit thermal analyses were performed with an accurate analytical model for a visible camera on Timon and a micro propulsion system on Pumbaa, which has a narrow operating temperature range. Finally, the analytical models were correlated for enhancing the reliability of the numerical analysis. The test results indicated that the CubeSats are structurally safe with respect to the launch environment and can activate each component under the space thermal environment. The natural frequency of the nylon wire for the deployable solar panels was found to increase significantly as the wire was tightened strongly. The conditions of the thermal vacuum and cycling testing were implemented in the thermal analytical model, which reduced the differences between the analysis and testing.

In this study, we describe an analytical process for designing a low Earth orbit constellation for discontinuous regional coverage, to be used for a surveillance and reconnaissance space mission. The objective of this study was to configure a satellite constellation that targeted multiple areas near the Korean Peninsula. The constellation design forms part of a discontinuous regional coverage problem with a minimum revisit time. We first introduced an optimal inclination search algorithm to calculate the orbital inclination that maximizes the geometrical coverage of single or multiple ground targets. The common ground track (CGT) constellation pattern with a repeating period of one nodal day was then used to construct the rest of the orbital elements of the constellation. Combining these results, we present an analytical design process that users can directly apply to their own situation. For Seoul, for example, 39.0° was determined as the optimal orbital inclination, and the maximum and average revisit times were 58.1 min and 27.9 min for a 20-satellite constellation, and 42.5 min and 19.7 min for a 30-satellite CGT constellation, respectively. This study also compares the revisit times of the proposed method with those of a traditional Walker-Delta constellation under three inclination conditions: optimal inclination, restricted inclination by launch trajectories from the Korean Peninsula, and inclination for the sun-synchronous orbit. A comparison showed that the CGT constellation had the shortest revisit times with a non-optimal inclination condition. The results of this analysis can serve as a reference for determining the appropriate constellation pattern for a given inclination condition.

The optical wide-field patrol network (OWL-Net) is a Korean optical surveillance system that tracks and monitors domestic satellites. In this study, a batch least squares algorithm was developed for optical measurements and verified by Monte Carlo simulation and covariance analysis. Potential error sources of OWL-Net, such as noise, bias, and clock errors, were analyzed. There is a linear relation between the estimation accuracy and the noise level, and the accuracy significantly depends on the declination bias. In addition, the time-tagging error significantly degrades the observation accuracy, while the time-synchronization offset corresponds to the orbital motion. The Cartesian state vector and measurement bias were determined using the OWL-Net tracking data of the KOMPSAT-1 and Cryosat-2 satellites. The comparison with known orbital information based on two-line elements (TLE) and the consolidated prediction format (CPF) shows that the orbit determination accuracy is similar to that of TLE. Furthermore, the precision and accuracy of OWL-Net observation data were determined to be tens of arcsec and sub-degree level, respectively.