Speaker
Description
The increasing availability, ease of deployment, and simple masking of optical surveillance systems persistently raise the challenge of detecting such systems. This study explores the potential of active detection based on the retroreflection (cat-eye) effect, even under challenging illumination conditions such as bright daylight.
The proposed method relies on active laser retroreflection, which produces a back-reflected signal from the target device's optical elements, thus enhancing detection efficiency. The analysis considers common surveillance optics, including smartphone cameras with apertures up to 2 mm and photographic lenses up to 20 mm in diameter. We assess the system's operational performance by calculating the maximum functional ranges based on the emitter's power.
The viability of this approach is confirmed by field experiments conducted over real atmospheric paths (up to 200 m), with results showing strong agreement with predictive computational models. The findings confirm that active retroreflection-based detection is a robust and practical tool for identifying concealed surveillance systems, even under the most challenging daylight conditions.
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