Under space-based angle-only observations, the admissible region (AR) algorithm often yields erroneous solutions in initial orbit determination (IOD) for near-circular orbit objects. This paper analyzes the mechanism generating these erroneous solutions and proposes a suppression method based on screening multi-direction solution sets using dispersion analysis. The study first points out that, under near-circular orbit constraints, the traditional AR algorithm, due to specific relative geometric configurations between the platform and the object, generates mathematically indistinguishable erroneous solutions in the range–rate space, severely affecting the reliability of solving orbital parameters such as the semi-major axis. To address this, this paper proposes a Relative Variance-based Single-Parameter Solution Screening (RV-SPSS) method. By constructing multiple observation point pairs with different geometric characteristics, the semi-major axis is solved for each pair to form a solution set. Leveraging the property that the true solution is remains consistent across different observation geometries, whereas erroneous solutions vary significantly with geometric changes, the method uses the relative variance of the solution set as a criterion to identify and eliminate erroneous solutions. Additionally, a slant range threshold is introduced to filter out trivial solutions, and polynomial fitting is applied to preprocess the observation sequence to suppress noise effects. Experimental results show that the proposed method effectively suppresses erroneous solutions. In historical data simulations based on Two-Line Element sets (TLEs), the convergence ratio to erroneous solutions was reduced from 88.8% for the original method to below 5.5%. In large-scale random orbit simulations, the erroneous solution suppression rate exceeded 94% for Low Earth Orbit (LEO), Medium Earth Orbit (MEO), and Geostationary Earth Orbit (GEO) objects. The method significantly enhances the reliability and practicality of space-based very-short-arc initial orbit determination.
Accurate star detection and centroiding are critical for attitude determination in space missions, especially under challenging environments like the lunar surface. This study presents an enhanced centroiding algorithm designed to improve robustness and accuracy in the presence of noise. The method incorporates thresholding and intensity-weighted centroid calculations, optimized through testing on synthetic star images affected by Salt-and-Pepper and Gaussian noise. Validation is conducted via affine transformation and star matching with a known star catalogue. The proposed algorithm is benchmarked against conventional Centre of Mass (COM) and Sieve Search Algorithm (SSA) techniques, showing superior performance in terms of Euclidean distance and computational efficiency. The results show accurate detection by visual validation and the detected stars are within 1 to 3 pixels Euclidian distances from the actual stars input. The proposed method demonstrates high accuracy and strong noise resilience, compared to benchmark methods, making it suitable for future lunar missions.
In this study, we present analysis of revisit-time characteristics of low Earth orbit (LEO) satellite constellations intended for Earth observation missions. The objective of this work is to evaluate and compare the revisit-time performance of heterogeneous payloads—including automatic identification system (AIS), electro-optic/infra-red (EO/IR), synthetic aperture radar (SAR), and radio-frequency (RF) sensors—operating over a common region of interest near the Korean Peninsula. To address this problem, we construct a constellation simulation framework entirely within a MATLAB environment, enabling consistent orbit propagation, payload modeling, access analysis, and revisit-time evaluation. A common geometric representation based on conical sensors is adopted to model different payload types, while mission-specific constraints such as wide-area reception for AIS, incidence-angle-dependent access for SAR, and formation-flight requirements for RF payloads are incorporated at the access-analysis level. To ensure stable constellation geometry under J2 perturbations, a pilot-satellite-based orbit initialization strategy is employed, allowing satellites within the same orbit plane to share identical realized orbital periods. A geometric interpretation of constellation ground trajectories is introduced to explain revisit-time behavior in terms of trajectory bands, intra-band spacing, inter-band separation, and Earth-rotation-induced drift. Based on this interpretation, a 48-satellite constellation distributed across 12 orbit planes at a 500 km circular orbit is identified as an effective configuration for EO/IR missions, minimizing coverage gaps at mid-latitudes. Simulation results demonstrate that AIS revisit-time performance exhibits saturation beyond moderate constellation sizes due to its wide field of view, whereas EO/IR, SAR, and RF payloads show structured revisit-time distributions with quasi-periodic patterns at individual ground points. These results indicate that revisit-time characteristics are dominated by the periodic recurrence of favorable ground trajectory alignments rather than by satellite count alone. The proposed framework and analysis provide a practical reference for constellation design and revisit-time assessment for regional Earth observation missions.
The Korea Pathfinder Lunar Orbiter (KPLO) magnetometer (KMAG) is a triaxial racetrack fluxgate magnetometer with a 1.2-meter-long boom for the KPLO mission. Previous studies on KMAG data processing and calibration have demonstrated that the quality of processed data is sufficient for general scientific research. However, additional calibration is necessary to remove residual noise fields that make it difficult to distinguish small-amplitude signals. As some magnetic interferences induced by the space environment are not fully covered by ground-based calibration, which is conducted before launch, in-orbit calibration performed during the mission phase is necessary. Although we applied several in-orbit calibration procedures, residual interference noise fields that follow a similar periodic trend of sensor temperature prominently remain during orbital phases with large temperature variations. In this study, we conducted in-orbit temperature calibration based on the fluxgate sensor characteristics, in which the measured field has an offset related to temperature variations. The variations in the observed magnetic field and sensor temperature of the KMAG measurements followed similar trends not only in the relatively short time interval, but also in the long term more than two years. We applied three approaches based on this similarity and validated the calibration performance of the best one. The temperature coefficient from the ground test was 0.2 nT/°C, while a larger value of up to 1.2 nT/°C was obtained in this study. Despite this difference, residual noise significantly reduced by applying the newly derived in-orbit temperature coefficient to the actual data. This demonstrates that it can be applied to the in-orbit calibration of fluxgate magnetometers.
This study examines the ionospheric response to the extreme geomagnetic storm of May 11, 2024, (Dst ≈ −400 nT) using GNSS derived vertical total electron content (VTEC) from four stations distributed from northern mid-latitudes to southern low latitude. Disturbances are quantified using the relative deviation parameter (ΔVTEC) and interpreted together with GUVI/TIMED thermospheric O/N2 ratio maps. The results highlight a strong latitudinal dependence and a clear spatiotemporal evolution. At northern mid-latitudes, intense and prolonged negative storms (down to −60%) developed mainly during recovery, consistent with storm-induced thermospheric composition changes (O/N2 depletion). At the equatorial station, rapid alternations between negative and positive phases indicate dominant electrodynamic forcing through prompt penetration and disturbance dynamo electric fields. In contrast, the southern low-latitude station experienced extremely intense positive storms, including an exceptional +400% peak during the main phase and persistent enhancements during recovery. A clear latitudinal latency is identified, supporting a two-stage response: rapid electrodynamic forcing followed by delayed equatorward propagation of thermospheric composition disturbances. These findings highlight the coupled role of electrodynamic and thermospheric processes in extreme storm-time ionospheric variability affecting GNSS systems.
