The increasing complexity and extended operational lifetimes of modern space infrastructure have significantly intensified the demand for reliable structural health monitoring (SHM) systems. However, the extreme space environment, characterized by radiation exposure, microgravity, ultra-high vacuum, and severe thermal cycling, imposes critical limitations on conventional electrical sensing technologies, leading to reduced measurement accuracy, instability, and long-term degradation. This review presents a comprehensive analysis of fiber Bragg grating (FBG)-based sensing technologies as a promising solution for deformation monitoring in space infrastructure. The study investigates the fundamental operating principles of FBG sensors under space conditions and systematically classifies existing FBG-based SHM architectures, including point-based, multiplexed, long-distance, and hybrid sensing systems. Furthermore, the advantages of FBG sensors—such as immunity to electromagnetic interference, passive operation, and high-resolution multipoint sensing—are critically evaluated in comparison with traditional electrical sensors. In addition, key challenges affecting the performance of FBG systems in space environments are analyzed, including radiation-induced wavelength drift, temperature–strain cross-sensitivity, signal attenuation, and long-term stability issues. The paper also highlights recent advances in interrogation techniques and network architectures that enable reliable in situ and real-time deformation monitoring of space structures. The results demonstrate that FBG-based sensing systems provide a scalable and robust framework for SHM in extreme environments while also revealing existing limitations and open research challenges. This work establishes a structured foundation for the development of next-generation intelligent monitoring systems for space infrastructure.

Spacecraft and launch-vehicle structures require lightweight multipoint monitoring under combined mechanical, thermal, and environmental loads. This study presents an analytical fiber Bragg grating (FBG) sensor-network workflow integrating reference-grating temperature compensation, regional strain assessment, opposite-surface curvature sensing, wavelength-division-multiplexing allocation, and strain-to-shape reconstruction. The deterministic compensation case is used only as a self-consistency check, whereas practical robustness is assessed through 10,000 Monte Carlo trials incorporating packaged-coefficient mismatch, temperature nonuniformity, wavelength noise, strain-transfer variation, drift, and calibration uncertainty. The calibrated estimator achieved a median strain mean absolute error of 1.73 με and a 95th-percentile error of 4.22 με. The defined finite-element benchmarks produced a maximum engine-mount truss strain of 456.2 με under the defined loads and a median full-field panel-reconstruction normalized root-mean-square error of 1.29% for 18 sensing locations with 2 με noise. Conservative WDM analysis yielded 54, 13, and 16 channels for three operating envelopes, and the prescribed random-vibration spectrum produced 6.78 g_rms. These results demonstrate a reproducible numerical proof of concept and define practical limits for compensation, spectral allocation, curvature interpretation, and inverse reconstruction; they do not constitute experimental validation or flight qualification.

Comparative evaluation of commercially available fiber-optic gyroscopes (FOGs) is complicated by heterogeneous technical specifications and the methodological assumptions underlying multi-criteria ranking. This study develops and systematically evaluates the Fiber Optic Gyroscope Performance Index (FOGPI), a six-criterion, specification-based framework integrating Bias Stability, Angle Random Walk, Maximum Input Rate, Bandwidth, Operating Temperature Range Width, and Power Consumption. The framework employs normalized technical characteristics and explicitly defined engineering preference weights and is applied to eleven commercial FOG models. Its methodological sensitivity is examined through linear, logarithmic, and fixed-reference normalization; local and global weight sensitivity analyses; mission-oriented Analytic Hierarchy Process (AHP) scenarios; intercriterion correlation and CRITIC weighting; leave-one-out analysis; hypothetical Monte Carlo input perturbations; and comparison with TOPSIS and VIKOR. Under baseline linear Min–Max normalization, DSP-1760 achieved the highest FOGPI score (0.816965). However, logarithmic normalization of accuracy-related criteria changed the highest-ranked device to S-F120HA, while increasing the Accuracy group weight beyond approximately 0.592 produced a similar rank reversal. Global weight-space analysis showed that DSP-1760 occupied first place in 50.72% of uniformly sampled configurations, compared with 87.39% under baseline-centered sampling. FOGPI and VIKOR produced identical rankings, although their agreement does not constitute independent validation because of their mathematical relationship. Application-specific screening further demonstrated that aggregate rankings cannot replace mandatory technical requirements. The findings establish FOGPI as a transparent decision-support framework whose rankings depend on normalization, weighting assumptions, comparison-set composition, and the comparability of manufacturer-reported specifications, rather than as an absolute measure of gyroscope performance.