Three-dimensional localization and tracking of drones using fiber-optic distributed acoustic sensing

Distributed acoustic sensing (DAS) based on phase-sensitive optical time-domain reflectometry (𝜑-OTDR) is valuable in environments with strong electromagnetic interference and long-distance signal transmission. This work presents a method for three-dimensional drone positioning and real-time trajectory tracking by combining DAS multi-point sensing with acoustic signal features. To enhance the acousto-optic coupling and improve sensitivity to weak drone signals, we design a helical fiber array by winding fibers around a hollow cylinder at a controlled elevation. An improved Steered Response Power with Phase Transform (SRP-PHAT) algorithm with adaptive bandpass filtering was employed to estimate the time difference of arrival (TDOA) across channels. Multi-channel data is further integrated to build a high-precision angular delay model, mapping sound source direction to delay space for accurate three-dimensional localization. An angular error of less than 2° is achieved, which demonstrates high azimuth accuracy. Optimization of the winding configuration enhances the system resolution from meter to centimeter scale, thereby overcoming the resolution limitations of traditional systems. This approach shows the potential in military reconnaissance, border surveillance, and airspace monitoring applications.