Distributed acoustic sensing (DAS) enables dense acoustic measurements using existing optical fiber networks, making it attractive for large-scale sensing applications. Previous DAS-based Doppler tracking methods have primarily focused on extracting source velocity from the direct acoustic arrival. However, in multipath environments, the direct application of such a method makes motion tracking even more challenging, limiting its robustness without further modifications. The proposed method recursively utilizes the motion prediction to guide beamforming, thereby isolating the direct arrival for Doppler-based velocity estimation. A steering vector that accounts for the directional strain sensitivity of the fiber is used within an adaptive beamformer to extract the direct-path signal and reject the higher-order arrivals. Applying the Doppler-based velocity-position estimation further innovates the source state in a bootstrapping-like fashion. By iteratively refining the state estimate, the approach enables robust tracking of source motion despite the presence of multipath interference. The framework will be evaluated in simulation using the Bellhop acoustic propagation model across various DAS array geometries, and its performance will be compared with that of the existing Doppler-based tracking method that assumes a sole direct arrival.
Sakakura et al. (Wed,) studied this question.