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This paper presents a kinematic ephemeris generator for Korea Pathfinder Lunar Orbiter (KPLO) and its performance test results. The kinematic ephemeris generator consists of a ground ephemeris compressor and an onboard ephemeris calculator. The ground ephemeris compressor has to compress desired orbit propagation data by using an interpolation method in a ground system. The onboard ephemeris calculator can generate spacecraft ephemeris and the Sun/Moon ephemeris in onboard computer of the KPLO. Among many interpolation methods, polynomial interpolation with uniform node, Chebyshev interpolation, Hermite interpolation are tested for their performances. As a result of the test, it is shown that all the methods have some cases that meet requirements but there are some performance differences. It is also confirmed that, the Chebyshev interpolation shows better performance than other methods for spacecraft ephemeris generation, and the polynomial interpolation with uniform nodes yields good performance for the Sun/Moon ephemeris generation. Based on these results, a Kinematic ephemeris generator is developed for the KPLO mission. Then, the developed ephemeris generator can find an approximating function using interpolation method considering the size and accuracy of the data to be transmitted.

The deep space orbit determination software (DSODS) is a part of a flight dynamic subsystem (FDS) for the Korean Pathfinder Lunar Orbiter (KPLO), a lunar exploration mission expected to launch after 2018. The DSODS consists of several sub modules, of which the orbit determination (OD) module employs a weighted least squares algorithm for estimating the parameters related to the motion and the tracking system of the spacecraft, and subroutines for performance improvement and detailed analysis of the orbit solution. In this research, DSODS is demonstrated and validated at lunar orbit at an altitude of 100 km using actual Lunar Prospector tracking data. A set of a priori states are generated, and the robustness of DSODS to the a priori error is confirmed by the NASA planetary data system (PDS) orbit solutions. Furthermore, the accuracy of the orbit solutions is determined by solution comparison and overlap analysis as about tens of meters. Through these analyses, the ability of the DSODS to provide proper orbit solutions for the KPLO are proved.

We present simulations of the optical-band images of high-redshift galaxies utilizing 845 near-ultraviolet (NUV) images of nearby galaxies obtained through the Galaxy Evolution Explorer (GALEX). We compute the concentration (C), asymmetry (A), Gini (G), and M20 parameters of the GALEX NUV/Sloan Digital Sky Survey r-band images at z ~ 0 and their artificially redshifted optical images at z = 0.9 and 1.6 in order to quantify the morphology of galaxies at local and high redshifts. The morphological properties of nearby galaxies in the NUV are presented using a combination of morphological parameters, in which earlytype galaxies are well separated from late-type galaxies in the G–M20, C–M20, A–C, and A–M20 planes. Based on the distribution of galaxies in the A–C and G–M20 planes, we examine the morphological K-correction (i.e., cosmological distance effect and bandshift effect). The cosmological distance effect on the quantitative morphological parameters is found to be significant for early-type galaxies, while late-type galaxies are more greatly affected by the bandshift effect. Knowledge of the morphological K-correction will set the foundation for forthcoming studies on understanding the quantitative assessment of galaxy evolution.

This paper presents an overview of deep space orbit determination software (DSODS), as well as validation and verification results on its event prediction capabilities. DSODS was developed in the MATLAB object-oriented programming environment to support the Korea Pathfinder Lunar Orbiter (KPLO) mission. DSODS has three major capabilities: celestial event prediction for spacecraft, orbit determination with deep space network (DSN) tracking data, and DSN tracking data simulation. To achieve its functionality requirements, DSODS consists of four modules: orbit propagation (OP), event prediction (EP), data simulation (DS), and orbit determination (OD) modules. This paper explains the highest-level data flows between modules in event prediction, orbit determination, and tracking data simulation processes. Furthermore, to address the event prediction capability of DSODS, this paper introduces OP and EP modules. The role of the OP module is to handle time and coordinate system conversions, to propagate spacecraft trajectories, and to handle the ephemerides of spacecraft and celestial bodies. Currently, the OP module utilizes the General Mission Analysis Tool (GMAT) as a third-party software component for highfidelity deep space propagation, as well as time and coordinate system conversions. The role of the EP module is to predict celestial events, including eclipses, and ground station visibilities, and this paper presents the functionality requirements of the EP module. The validation and verification results show that, for most cases, event prediction errors were less than 10 millisec when compared with flight proven mission analysis tools such as GMAT and Systems Tool Kit (STK). Thus, we conclude that DSODS is capable of predicting events for the KPLO in real mission applications.

The current study designs the mission orbit of the lunar CubeSat spacecraft to measure the lunar local magnetic anomaly. To perform this mission, the CubeSat will impact the lunar surface over the Reiner Gamma swirl on the Moon. Orbit analyses are conducted comprising ΔV and error propagation analysis for the CubeSat mission orbit. First, three possible orbit scenarios are presented in terms of the CubeSat’s impacting trajectories. For each scenario, it is important to achieve mission objectives with a minimum ΔV since the CubeSat is limited in size and cost. Therefore, the ΔV needed for the CubeSat to maneuver from the initial orbit toward the impacting trajectory is analyzed for each orbit scenario. In addition, error propagation analysis is performed for each scenario to evaluate how initial errors, such as position error, velocity error, and maneuver error, that occur when the CubeSat is separated from the lunar orbiter, eventually affect the final impact position. As a result, the current study adopts a CubeSat release from the circular orbit at 100 km altitude and an impact slope of 15°, among the possible impacting scenarios. For this scenario, the required ΔV is calculated as the result of the ΔV analysis. It can be used to practically make an estimate of this specific mission’s fuel budget. In addition, the current study suggests error constraints for ΔV for the mission.