Jiwoong Yu

Ground-based optical tracking for space situational awareness is evolving rapidly in response to the sharp growth of the number of resident space objects and the rise of commercial actors in the New Space era. We synthesize qualitative advances over the last five years and outline development priorities for Korea’s ground-based optical tracking sensor systems. Current situation feature commercial off-the-shelf (COTS)-driven miniaturization and networked operations via simplified observatory infrastructure; the emergence of short-wave infrared (SWIR)-enabled cathemeral (day-and-night) tracking as a core capability; and the adoption of artificial intelligence (AI) data processing and autonomous operations. These advances have reopened the low-Earth-orbit (LEO) regime to optical tracking and reduced warning latency through persistent monitoring. Based on these findings, we recommend prioritizing cathemeral performance—centered on SWIR sensing and end-to-end automation—to secure robust LEO tracking capability. We further assess the expected gains from cathemeral observation of national LEO satellites using an observation-opportunity simulation.

우주기술과 응용(Journal of Space Technology and Applications; J. Space Technol. Appl. 이하 JSTA )은 한국의 우주과학 및 우주 응용 분야에서 가장 권위 있는 학술단체인 한국우주과학회에서 Journal of Astronomy and Space Sciences 와 더불어 발행되고 있는 공식적인 정기 간행물이다. JSTA 는 2021년 5월 창간호를 시작으로 연 4회 분기별로 발간되고 있으며, JSTA 의 논문과 기고문 은 한국어 또는 영어로 게재 가능하며, 각 논문과 기고문에는 고유의 DOI가 부여된다. JSTA 에 게재 되는 모든 논문과 기고문은 Open Access 정책에 따라 JSTA 홈페이지(https://www.jstna.org)를 통해 누구나 전문을 무료로 열람할 수 있다.

Space debris poses significant threats to spacecraft and human activities in space. Accurate modeling of space debris is crucial for understanding and mitigating these risks, ensuring the sustainability of the space environment. This paper discusses the importance of space debris modeling in the space environment, highlighting its critical role in safeguarding assets in orbit. Two primary methods of space debris modeling, namely the 1D and 3D approaches, are discussed in detail, and their respective strengths and limitations are elucidated. Furthermore, a comprehensive review of existing models, including the space debris evolutionary model (MOCAT, SOLEM, DAMAGE, LEODEEM & GEODEEM, DELTA, and LEGEND) and engineering models (MOCAT-MC, NEODEEM, MASTER, ORDEM), are presented. These models offer valuable insights into the dynamics and characteristics of space debris populations, aiding in formulating effective debris mitigation strategies and orbital capacity problems for reducing the possibilities of Kessler’s syndrome. Additionally, the paper provides insights into the ongoing development of the Korean space debris model, focusing on its methodology and space debris cataloging techniques for modeling space debris environments.

한국전자파학회논문지 (The Journal of Korean Institute of Electromagnetic Engineering and Science)

The Korean Institute of Technology Satellite (KITSAT-1) is the first satellite developed by the Satellite Technology Research Center and the University of Surrey. KITSAT-1 is orbiting the Earth’s orbit as space debris with a 1,320 km altitude after the planned mission. Due to its relatively small size and altitude, tracking the KITSAT-1 was a difficult task. In this research, we analyzed the tracking results of KITSAT-1 for one year using the Midland Space Radar (MSR) in Texas and the Poker Flat Incoherent Scatter Radar (PFISR) in Alaska operated by LeoLabs, Inc. The tracking results were analyzed on a weekly basis for MSR and PFISR. The observation was conducted by using both stations at an average frequency of 10 times per week. The overall corrected range measurements for MSR and PFISR by LeoLabs were under 50 m and 25 m, respectively. The ionospheric delay, the dominant error source, was confirmed with the International Reference of Ionosphere-16 model and Global Navigation Satellite System data. The weekly basis orbit determination results were compared with two-line element data. The comparison results were used to confirm the orbital consistency of the estimated orbits.

A compact and lightweight synthetic aperture radar (SAR) that can be loaded on a miniature unmanned aerial vehicle (UAV) was recently developed. The higher the frequency is, the smaller is the antenna size and the microwave characteristics are improved. Thus, a high frequency is favorable for miniaturization and weight reduction. In this chapter, a method of obtaining a radar image through a 94-GHz frequency modulation continuous wave (FMCW) radar is proposed. In addition, a method of motion compensation is described, and the W-band SAR image after motion compensation is confirmed. This kind of SAR imaging can provide geographic information and characteristics of extreme environments, disaster scenes, and information on sites where human access is difficult.

In this letter, we propose a method for estimating the center of rotation on an experimental radar imaging. The experiment is performed with tomographic approach to obtain the radar cross section images of the target on a rotation table. In an ultrahigh-resolution imaging using tomographic reconstruction, precise knowledge of rotation center of the turntable position is necessary since this has a big influence on the image quality. The position of rotation center can be physically measured, but the result is not accurate due to the delay introduced by the RF components and cables. Thus, we present a method to precisely determine the rotation center based on the rotational symmetry of the received data. The proposed method is verified by doing imaging of several targets using ultrawideband radar with picosecond-length pulses. The system bandwidth is larger than 30 GHz, and the imaging results have subcentimeter resolution.

In this paper, we present a novel signal processing method for video synthetic aperture radar (ViSAR) systems, which are suitable for operation in unmanned aerial vehicle (UAV) environments. The technique improves aspects of the system’s performance, such as the frame rate and image size of the synthetic aperture radar (SAR) video. The new ViSAR system is based on a frequency-modulated continuous wave (FMCW) SAR structure that is combined with multiple-input multiple-output (MIMO) technology, and multi-channel azimuth processing techniques. FMCW technology is advantageous for use in low cost, small size, and lightweight systems, like small UAVs. MIMO technology is utilized for increasing the equivalent number of receiving channels in the azimuthal direction, and reducing aperture size. This effective increase is achieved using a co-array concept by means of beat frequency division (BFD) FMCW. A multi-channel azimuth processing technique is used for improving the frame rate and image size of SAR video, by suppressing the azimuth ambiguities in the receiving channels. This paper also provides analyses of the frame rate and image size of SAR video of ViSAR systems. The performance of the proposed system is evaluated using an exemplary system. The results of analyses are presented, and their validity is verified using numerical simulations.

Ultra-high resolution (UHR) radar imaging is used to analyze the internal structure of objects and to identify and classify their shapes based on ultra-wideband (UWB) signals using a vector network analyzer (VNA). However, radar-based imaging is limited by microwave propagation effects, wave scattering, and transmit power, thus the received signals are inevitably weak and noisy. To overcome this problem, the radar may be operated in the near-field. The focusing of UHR radar signals over a close distance requires precise geometry in order to accommodate the spherical waves. In this paper, a geometric estimation and compensation method that is based on the minimum entropy of radar images with sub-centimeter resolution is proposed and implemented. Inverse synthetic aperture radar (ISAR) imaging is used because it is applicable to several fields, including medical- and security-related applications, and high quality images of various targets have been produced to verify the proposed method. For ISAR in the near-field, the compensation for the time delay depends on the distance from the center of rotation and the internal RF circuits and cables. Required parameters for the delay compensation algorithm that can be used to minimize the entropy of the radar images are determined so that acceptable results can be achieved. The processing speed can be enhanced by performing the calculations in the time domain without the phase values, which are removed after upsampling. For comparison, the parameters are also estimated by performing random sampling in the data set. Although the reduced data set contained only 5% of the observed angles, the parameter optimization method is shown to operate correctly.