Accurate ship detection and tracking has become increasingly vital due to the growth of global maritime trade and complex oceanic activities. Passive acoustic or seismic-based tracking methods, though proven effective, require extensive deployment of sensors, posing challenges in terms of range and accuracy. The recently developed Distributed Acoustic Sensing (DAS) technology offers a dense sampling, cost-effective and real-time solution by using optical fiber cables for wide-area vibration monitoring. This study investigates DAS technology for ship tracking by analyzing the Doppler shift characteristics of ship-generated wavefields. First, ships were detected by the seismic energy maps in spatial and spectral domains. Utilizing the Fourier Synchrosqueezing Transform (FSST), the Doppler shift characteristics of ship signals are examined, and ship trajectories are determined. The inverted trajectory of a ship aligns closely with the actual GPS-based trajectory, thereby validating the effectiveness and accuracy of our approach. These results demonstrate the potential of DAS for reliable ship detection and tracking, providing a robust and reliable tool for maritime surveillance and monitoring in future.

Reservoir monitory technology based on Distributed Acoustic Sensing (DAS) technology provides a new means to characterize and monitor the underground structure, so as to achieve rapid and real-time monitoring and identification of underground target structure changes, which has been widely used in hydraulic fracturing micro-seismic monitoring and precision engineering monitoring. When micro-seismic monitoring technology is used for source location imaging, it is necessary to consider the influence of many factors on the location results, among which the velocity model error is one of the most important factors, so it is a key step to correct the initial velocity model to obtain an accurate velocity model. On the basis of receiving the arrival time data of the perforating source by the distributed optical fiber sensing, the underground horizon is divided according to the acoustic logging curve, the micro-seismic velocity model is corrected by using the perforation event, the travel-time relationship formula based on the velocity model and the propagation path is studied, and a more accurate velocity model is further solved and corrected by the particle swarm optimizatio (PSO) in the global optimization method. The accuracy of the method was validated through numerical simulations, which demonstrated small calibration errors that were almost uniformly below 3%. The method was subsequently applied to real DAS perforation data, achieving satisfactory inversion results.

Acoustic-seismic coupling is a prominent phenomenon in seismology. Seismologists can track airborne traffic events by analyzing the Doppler curves in acoustic-seismic coupled signals. We conducted a theoretical analysis to explain the phenomenon of multiple-mode Doppler curves seen in the actual data and point out that the multiple-mode Doppler curves in seismic signals originate from the periodic signals generated during the flight of flying objects. Numerical simulations further confirm this theoretical viewpoint: when the signals generated during aircraft flight can be decomposed into multiple single-frequency periodic signals, we can observe a corresponding number of Doppler curves in seismic signals. Conversely, if the airplane signals cannot be decomposed into periodic single-frequency signals, we cannot observe the presence of Doppler curves in the seismic record. If the frequency of the signals generated by the aircraft varies linearly with time, i.e., exhibits the characteristics of linear frequency modulation, a regular frequency shift curve may still appear in the time–frequency spectrum of the seismic record. In such cases, the Doppler curves need to be corrected to be used for accurate tracking of the aircraft. These research findings provide a solid theoretical foundation for seismologists to utilize Doppler curves in seismic data to track airborne events.

The Doppler shift of sound signals has been widely studied. However, monitoring and analyzing the Doppler shift characteristics of aircraft-generated seismic signals is still a relatively new field that requires further exploration. We studied the air-to-ground coupled seismic waves generated by moving aircraft, which were measured by 12 short-period seismometers installed near the Beijing Capital International Airport. The coupled seismic signals generated by 127 aircrafts flying over the observation system were effectively recorded, which confirms the feasibility of using seismic methods to monitor air traffic. We clearly observed the Doppler shift of the coupled signals, which is most noticeable in the frequency range above 500 Hz and serves as important input for analyzing aerial trajectories. Based on the theoretical formula of the Doppler shift, we analyzed the influence of various parameters on the curve shape. Then we proposed a new algorithm for tracking aircraft trajectories using Simulated Annealing inversion method. Finally, using the data collected during the experiment and the proposed trajectory inversion method, we successfully calculated the aircraft trajectory. The implications of our research are significant in integrating seismic technology and data analysis for detecting and monitoring aircraft signals in the field of air traffic.

A high-speed train can be regarded as a moving seismic source when it travels along a railway. Seismic waves from such sources have strong energy and can be used for near-surface characterization, safety monitoring of high-speed railways, and detection of urban underground spaces. Distributed acoustic sensing (DAS) is a newly developed seismic acquisition technology. It has attracted widespread attention due to its advantages of low cost, high sensitivity, high efficiency, and dense sampling. This study investigated near-surface characterization using high-speed train seismic data recorded by DAS. The data were processed to obtain surface waves by seismic interferometry. Thereafter, the extracted surface waves were inverted to obtain the near-surface shear-wave velocity model using a multichannel analysis method. The inverted model is consistent with the subsurface geology of the study area. Our results demonstrate the effectiveness and reliability of DAS-based acquisition and data analysis in near-surface characterization using the high-speed train type of moving sources.