Panyalert T.Manuthasna S.Torteeka P.He X.Zhang N.Zheng J.Zhang B.Yang D.Yang H.Xian J.Bao Y.Lu S.Puprasit K.Chaiwongkhot K.Marsri T.Zhao H.Pittayang Y.Jamlongkul P.Charoenvicha P.Khonsri P.Anuchit K.Amratisha K.Burom S.Lakronwat J.Mitthumsiri W.Pattarakijwanich P.Kamsing P.Ruffolo D.Zhang S.Rujopakarn W.Mahidol University2025-06-292025-06-292025-01-01IEEE Sensors Letters (2025)https://repository.li.mahidol.ac.th/handle/123456789/110973This paper 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 (MATCH), 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 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 AIC wins. In contrast, Gaussian fits showed higher fitting errors (e.g., X²/DoF up to 10.5) and the poorest resolution. Akaike Information Criterion (AIC) selection further confirms Hyper-EMG's robustness, while Gaussian fits were consistently inadequate. These findings support the use of tail-aware models like Hyper-EMG for accurate energy reconstruction in spaceborne silicon detectors.Physics and AstronomyEngineeringArticleSCOPUS10.1109/LSENS.2025.35804332-s2.0-10500866147024751472