Drone Detection via Low Complexity Zadoff-Chu Sequence Root Estimation

The fast growth of drone applications in industrial, commercial and consumer domains in recent years has caused great security, safety and privacy concerns. For this reason, a demand for solutions of drone detection and monitoring in consumer market can be foreseen in the near future. For detecting drones that employ Zadoff-Chu (ZC) sequences for synchronization, these ZC sequences can be used to determine their presence in the air. However, it is a great challenge to blindly detect thousands of unknown ZC sequences possibly used by the drones in real time. Existing solutions mainly developed for LTE systems cannot be directly applied to the blind detection of ZCs in drones without incurring huge cost. In this paper, a low-complexity cost effective blind ZC detection method based on double differential is proposed for low-cost drone detection and monitoring systems. Signal-to-noise ratio (SNR) lower bounds are analytically derived for low and high SNR regimes. Monte Carlo simulations show the proposed scheme performs well in moderate and high SNR.