Dynamic reflectivity modeling of Cat's-Eye photosensitive surfaces for low-SNR single-photon detection

Single-photon detection technology, owing to its exceptionally high sensitivity, has become a core method of target detection in extreme-low-light environments, such as deep-space exploration. However, the diffuse reflection characteristics of target surfaces result in extremely weak return signals, and the presence of complex background noise further degrades the signal-to-noise ratio (SNR), making it difficult for optoelectronic systems to effectively extract target information. In contrast, the cat-eye effect, owing to the retroreflection and beam collimation characteristics of the reflected light, yields a number of returned photons several orders of magnitude higher than that of diffuse reflection, offering significant advantages in low-SNR environments. Therefore, the cat-eye effect holds significant application value for target detection under low-SNR conditions. Conventional cat-eye effect models typically approximate the photosensitive surface as an ideal reflector, neglecting the influence of its photoelectric response on the returned photons. To address this issue, this study systematically analyzes how the structural design, quantum efficiency, temporal response characteristics, and operational modes of the photosensitive surface affect photon absorption, reflection, and energy loss. The modulation behavior of returned signals by different device types in typical operational stages is quantitatively revealed, and a physical model is established to characterize the impact of photosensitive surface working states on the reflectivity of the cat-eye system. This study clarifies the evolutionary behavior of cat-eye effective reflectivity as governed by the dynamic mechanisms of the photosensitive surface, providing theoretical support and technical reference for identifying the operational state of cat-eye targets based on echo characteristics and enabling detection under low-SNR conditions.