Kamsing, Patcharin

Preferred name

Kamsing, Patcharin

Main Affiliation

International Academy of Aviation Industry

patcharin.ka@kmitl.ac.th

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Ground software architecture for a lunar particle detector: Implementation with a double-sided silicon strip detector
(2026-04-15)
Panyalert, Thanayuth
;
Manuthasna, Shariff
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Torteeka, Peerapong
;
He, Xu
;
Zhang, Ning
The Moon-Aiming Thai-Chinese Hodoscope (MATCH) is a particle detector developed for the Chang’E-7 mission, designed to support space weather monitoring and cosmic radiation studies within the Sun-Earth-Moon system. The primary observational objectives of MATCH include space weather science and alerts, as well as the detection of cosmic radiation, particularly Jovian and Galactic Cosmic Ray (GCR) electrons. Additionally, MATCH can detect lunar albedo ions (alpha particles and protons) and contribute to understanding cosmic-ray interactions with the lunar surface, including high-energy particle backscattering mechanisms. These studies are essential for improving our knowledge of cosmic ray propagation and energy distribution in the lunar environment. MATCH integrates a double-sided silicon strip detector (DSSD) for precise position tracking of incoming particles, along with a bismuth germanate (BGO) scintillator stack for accurate energy measurements. This study presents the development and validation of a scalable ground software architecture that supports event detection, signal processing, and data calibration, optimized for constrained onboard resources. The system has been validated through hardware-in-the-loop (HIL) testing using alpha-emitting sources under mission-equivalent conditions, demonstrating high accuracy and resource efficiency for on-orbit data acquisition modes. Once deployed, MATCH is expected to provide the first continuous MeV-range cosmic electron measurements from lunar orbit, enabling new insights into Jovian and Galactic cosmic ray propagation, space weather variability, and lunar albedo ion generation. The software architecture developed here plays a critical role in enabling astrophysical investigations during the upcoming Chang’E-7 mission.
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Hardware-in-the-Loop Simulation Testbed for Three-Axis Earth's Magnetic Field Generation Based on 2.4- Meter Square Helmholtz Coils
(2023-01-01)
Chaisakulsurin, Jormpon
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Manuthasna, Shariff
;
Masri, Tanawish
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Panyalert, Thanayuth
;
Palee, Kritsada
This paper proposes a Hardware-in-the-Loop sim-ulation (HiLs) tested via square Helmholtz coils as a relative magnetic field generator. In technical terms, the HiLs is an indispensable tool for engineering design during rapid proto-typing of attitude determination and control algorithms for the turning parameters that control the attitude of the satellite, since most of the satellite's mission relies on its attitude, making this system one of the most essential to the satellite's operation. More-over, performing controlled experiments with the parameters for developing adaptive control algorithms improves the overall efficiency of the satellite's kinematic system. The conceptual design of a proposed system architecture can be composed of the electrical currents of 2.4-meter square Helmholtz coils produced by a low-level microcontroller equipped with a DC-motor driver by a pulse-width modulation (PWM) signal through real-time connection to an orbit propagator using a high-level computer. This research focuses on the attitude dynamic of satellites through the interaction between the Earth's magnetic field (EMF) and the magnetotorque in the satellite. To apply this phenomenon, the intensity and the direction of the magnetic field must be identified through Biot-Savart's law. Along with the EMF, the reference position is calculated using the standard general perturbations satellite orbit model (SGP4), and the intensity is modeled based on coefficients from the 13th edition of the International Geo-magnetic Reference Field (IGRF). Therefore, this paper presents a detailed development of a HiLs testbed for distributed attitude determination and control systems (hardware and software co-design, protocol, and control theory). Furthermore, it discusses a classic cooperative control case for the output of magnetic field intensity and direction, which was undertaken to explain the integrated simulation process and validate the effectiveness of the co-simulation tested to be a primary experiment.
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Wi-Fi Received Signal Strength-based Indoor Localization System Using K-Nearest Neighbors fingerprint integrated D∗algorithm
(2022-01-01)
Jarawan, Tanatthep
;
Kamsing, Patcharin
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Torteeka, Peerapong
;
Manuthasna, Shariff
;
Hematulin, Warunyu
The indoor localization system is essential since the Global Positioning System cannot give an accurate position indoors, especially when several floor plans are considered. WiFi received signal strength becomes an alternative indicator for indoor localization systems. The experiment proposed a localization system created by integrating and working between the K-Nearest Neighbors algorithm and the D∗algorithm. The result illustrates the optimal path from the start point to the target point by avoiding the obstacle performing exceptionally well. The K-Nearest Neighbors algorithm provide the result for localization with Root Mean Square Errors of displacement at 1.190 meters, 2.491 meters, and 1.363 meters of X-Axis Y-Axis, respectively. The proposed indoor localization system can have various applications considering different environmental factors in different applications, such as the size of unmanned aerial vehicles when applying indoor unmanned aerial vehicles.
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Wi-Fi Received Signal Strength-based Indoor Localization System Using K-Nearest Neighbors fingerprint integrated D*algorithm
(2021-02-07)
Jarawan, Tanatthep
;
Kamsing, Patcharin
;
Tortceka, Peerapong
;
Manuthasna, Shariff
;
Hematulin, Warunyu
The indoor localization system is essential since the Global Positioning System cannot give an accurate position indoors, especially when several floor plans are considered. Wi-Fi received signal strength becomes an alternative indicator for indoor localization systems. The experiment proposed a localization system created by integrating and working between the K-Nearest Neighbors algorithm and the D*algorithm. The result illustrates the optimal path from the start point to the target point by avoiding the obstacle performing exceptionally well. The K-Nearest Neighbors algorithm provide the result for localization with Root Mean Square Errors of displacement at 1.190 meters, 2.491 meters, and 1.363 meters of X-Axis Y-Axis, respectively. The proposed indoor localization system can have various applications considering different environmental factors in different applications, such as the size of unmanned aerial vehicles when applying indoor unmanned aerial vehicles.
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Signal Calibration and Energy Resolution Optimization of a Double-Sided Silicon Strip Detector for Lunar-Based Particle Detection
(2025-01-01)
Panyalert, Thanayuth
;
Manuthasna, Shariff
;
Torteeka, Peerapong
;
He, Xu
;
Zhang, Ning
This letter presents a signal calibration and energy resolution analysis of a double-sided silicon strip detector (DSSD) developed for charged particle detection in a lunar-based space environment. The detector is part of the Moon-Aiming Thai-Chinese Hodoscope, i.e., a proposed scientific payload for the Chang'E-7 lunar orbiter, aimed at monitoring space weather and lunar-surface particle interactions. To evaluate the DSSD's performance under vacuum conditions, alpha sources (Am-241 and Pu-239) were used to generate energy spectra, which were processed through baseline correction and histogram generation. Four peak models, i.e., Gaussian, Gaussian + Exponential Tail, exponentially modified Gaussian (EMG), and Hyper-EMG, were compared using nonlinear least squares. Results show that the Hyper-EMG model yields superior fits, especially for Am-241, achieving an average reduced chi-squared of 1.64 ± 4.44 and energy resolution of 3.09% ± 0.45%, with 22 out of 32 Akaike Information Criterion (AIC) wins. In contrast, Gaussian fits showed higher fitting errors (e.g., x<sup>2</sup>/DoF up to 10.5) and the poorest resolution. AIC selection further confirms Hyper-EMG's robustness, while Gaussian fits were consistently inadequate. These findings support the use of tail-aware models, such as Hyper-EMG, for accurate energy reconstruction in spaceborne silicon detectors.
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Generating Large-Scale Datasets for Spacecraft Pose Estimation via a High-Resolution Synthetic Image Renderer
(2025-04-01)
Hematulin, Warunyu
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Kamsing, Patcharin
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Phisannupawong, Thaweerath
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Panyalert, Thanayuth
;
Manuthasna, Shariff
The trend toward conducting vision-based spacecraft pose estimation using deep neural networks, which necessitates accurately labeled datasets for training, is addressed in this paper. A method for generating an image regression-labeled dataset for spacecraft pose estimation through simulations involving Unreal Engine 5 is proposed herein. This work provides detailed algorithms for pose sampling and image generation, making it easy to reproduce the employed dataset. The dataset consists of images obtained under harsh lighting conditions and high-resolution backgrounds, featuring spacecraft models including Dragon, Soyuz, Tianzhou, and the ascent vehicle of Chang’E-6. The dataset comprises 40,000 high-resolution images, which are evenly distributed, with 10,000 images for each spacecraft model in scenes with both the Earth and the Moon. Each image is labeled with multivariate pose vectors that represent the relative position and attitude of the corresponding spacecraft with respect to the camera. This work emphasizes the critical role of realistic simulations in creating cost-effective synthetic datasets for training neural network-based pose estimators and publicly available for further study.

Kamsing, Patcharin

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