10-km passive drone detection using broadband quantum compressed sensing imaging

Remote passive drone detection in the presence of strong background noise is challenging, since they are point objects and cannot be recognized by their contour detection. In this study, we introduce a new passive single-photon dynamic imaging method using quantum compressed sensing. This method utilizes the inherent randomness of photon radiation and detection to construct a compressive imaging system. It captures the broadband dynamic features of the point object through sparse photon detection, achieving a detectable bandwidth up to 2.05 GHz, which is significantly higher than current photon-counting imaging techniques. The method also shows excellent noise resistance, achieving high-quality imaging with a signal-to-background ratio of 1/332. This technique significantly enhances the use of single-photon imaging in real-world applications.