UAV Target Enhancement for PPM-Coded Free-Running Single-Photon Range Imaging in Building Background

Single-photon detection is a promising approach for low–slow–small Unmanned Aerial Vehicle (UAV) detection, holding great value in urban air defense and security monitoring. In complex urban environments, intense non-uniform building clutter and multi-echo aliasing easily submerge weak target signals, severely limiting traditional single-photon systems under low signal-to-background ratios. To address this, this paper proposes an urban-oriented detection strategy based on a free-running single-photon array, and designs a dual-optimized pulse position modulation laser detection and range image enhancement algorithm. By establishing temporal correlations via pulse sequence convolution, the algorithm effectively isolates weak UAV echoes from strong background clutter to break through detection limitations. Compared with the popular Markov correction method that often suppresses overlapping weak targets under strong reflections, the proposed method significantly improves small-target feature retention, successfully balancing background elimination and detection sensitivity. Field tests and quantitative evaluations demonstrate that the system reliably eliminates building clutter and achieves stable continuous tracking of weak UAV signals within 1.5 km, providing a highly robust and effective technical solution for urban low-altitude surveillance.