Objective: Ultra-high voltage (UHV) transmission towers play an important role in long-distance power delivery, and their safe operation directly affects the stability and resilience of power systems. Under normal conditions, these towers are susceptible to deformation caused by stress induced by conductor suspension as well as geological hazards, extreme weather, etc. Current methods of routine inspection, including human inspection, unmanned aerial vehicle surveys, and in situ sensors, are costly and inefficient. Spaceborne synthetic aperture radar (SAR) provides large-area coverage and millimeter-level deformation sensitivity for landslide hazard assessment around power towers widely used by the State Grid. Methods: This study developed a high-resolution SAR-based approach to accurately extract the small structural deformation trend of UHV transmission towers. A novel SAR imaging intensity simulation and interferometric phase estimation method for transmission towers was developed. This method integrated three-dimensional light detection and ranging (LiDAR)-derived tower point cloud models with the radar range-Doppler equation to simulate the elevation phase of tower structures containing persistent scatterer (PS) points. To address the multiscattering effects and vertical occlusions inherent in lattice steel towers, a weighted sum model was developed for both intensity and phase simulations. Ascending and descending SAR data acquired by the China C-band Fucheng-1 satellite were processed over 8 months. In total, 39 SAR scenes covering two 500 kV transmission lines in Yubei District, Chongqing, were analyzed to conduct algorithm verification. To achieve subpixel accuracy in SAR geocoding, four corner reflectors (CRs) were deployed near a tower, with their positions precisely measured by a global navigation satellite system. After geometric calibration using CRs, the LiDAR point cloud data in the Fucheng-1 SAR imagery achieved a positioning accuracy within ±0.2 pixels, while the interferometric phase for strong scatterers, such as CRs, reached the sub-millimeter level. CR-based analysis further revealed a gradual settlement of approximately 8 mm over 8 months at one reflector site, highlighting the importance of stable benchmarks for long-term deformation monitoring. Results: Simulation experiments demonstrated that the proposed tower imaging model could reproduce key structural features, including the hollow lattice geometry and the scattering contributions of insulator strings. With a resolution of greater than 0.6 m, the simulated area with the power tower PS points showed favorable agreement with the hollow lattice texture of the power tower. Time-series analysis confirmed that PS points located on the tower structures maintained high coherence throughout the observation period, thereby enabling reliable extraction of deformation signals. Based on simulated tower interferometric phases, differential interferometry was performed without height-induced errors. Violin plots were used for statistically characterizing PS point deformation, and comparative analyses between strain-type and straight-type towers revealed structural differences. Comparative results indicated that strain-type towers exhibited a relatively stable condition, whereas time-series results revealed that straight-type towers exhibited more frequent and pronounced small deformation trend events. The correlation between environmental temperature variations and small deformation trends in transmission towers was weak. Interferograms with large temperature differences did not show an obvious trend in power tower structural deformation either. This trend might be influenced by multiple factors, including structural stiffness, insulator configuration, conductor tension, and external loading. Conclusions: This study verifies the feasibility of using high-resolution China C-band SAR satellites to monitor the small structural deformation trend of UHV transmission towers in time series datasets. Future work should incorporate structural temperature variations, power line stress conditions, and wind loads to develop physical mechanism-based models for explaining power tower deformation trends. Ultimately, the methodology presented in this study provides a foundation for analyzing such trends. It can be applied to assess structural stability under extreme events, such as geological hazards, earthquakes, and typhoons across different regions of China.