In exploration and earthquake seismology, most sources used in subsurface structure imaging and rock property estimation are fixed in certain positions. Continuously moving seismic sources, such as vehicles and the metro, are one kind of important passive sources in ambient noise research. Commonly, seismic data acquisition and processing for moving sources are based on the assumption of simple point passive sources, and the dispersion curve inversion is applied to constrain near-surface velocity. This workflow neglects the Doppler effects. Considering the continuously moving properties of the sources, we first derive the analytical solution for the Rayleigh waves excited by heavy vehicles and then analyze their Doppler effects and dispersion curves. We observe that the moving source data have the Doppler effect when compared with the changes in the frequency of the source intensity, but this effect does not affect the frequency dispersion of Rayleigh waves. The dispersion curves computed for moving source records are consistent with the analytical dispersion solutions, which provide a theoretical foundation for velocity estimation using moving source data.

The application of Rayleigh waves in geological prospecting and engineering has been widely tested and used as a new method of shallow seismic exploration. The previous method of surface wave inversion needed to calculate the corresponding phase velocity that satisfied the dispersion function. This process increases the computation amount and reduces the surface wave inversion efficiency. This paper proposes a method to solve the problem by using different definition methods of the objective function. The method greatly reduces the amount of computation while results in approximately equal results with traditional method. This cuts the inversion time to 1% of conventional methods and provides favorable conditions for multiple inversions to suppress multiple solutions. We set artificial initial parameters with linear constraints in our velocity increasing model test to accelerate the convergence rate of the target function and obtain accurate results quicker. Finally, this method is applied to the microtremor dispersion data with a strong disturbance, and the inversion results are consistent with the high-density electrical profile and geological survey data.

Continuously moving seismic sources, such as vehicles and train cars, play a crucial role as passive sources for nondestructive exploration in urban areas. Seismic interferometry is commonly used in field data acquisition and processing using linear arrays. However, the simultaneous recording of high-energy noise, excited by buildings and factories, cannot be overlooked. We simulate moving-source seismic records with strong noises using orthogonal arrays. When strong noise originates from specific angles, the energy-phase velocity curves of arrays in different directions significantly diverge. We determine that an L-shaped array, formed by orthogonal arrays, can effectively mitigate this effect, yielding more consistent results. Nonetheless, spatial constraints often preclude the deployment of L-shaped arrays. To mitigate this issue, we develop a new parallel observation system. Field tests conducted on a main road validate that the new array is comparable with the L-shaped array in terms of dispersion extraction. Similar to synthetic data, the phase velocity extracted from the linear array field data is found to be unreliable. Drilling data align well with the inversion results of the parallel observation system. Given the challenges of urban traffic-induced signal acquisition, deploying multiazimuth arrays to minimize noise impact is essential. Considering the spatial limitations, the convenient parallel observation system emerges as a good choice.

In passive source exploration, seismic records are typically assumed to satisfy the equipartition condition. However, in urban environments, buildings and factories act as strong, directionally biased seismic sources, causing recorded signals to deviate from equipartition. To investigate this effect, we numerically simulate seismic records received by orthogonal arrays under varying source distributions. The influence of the wavefield propagation direction is analyzed by MUSIC (multiple signal classification), energy-phase velocity curves, and extracted dispersion. Our results demonstrate that strong directional sources introduce significant discrepancies in energy-phase velocity spectra across different array orientations. However, optimizing the observation system can mitigate this effect. When the illumination angle between two receivers sufficiently covers the dominant propagation directions, the extracted dispersion aligns more closely with theoretical predictions. We carry out the field test in Qingdao with the L-shaped array. Because of the influence of the village and factories, the recorded data also show the same phenomena. Dispersion obtained by linear arrays in different directions are not accurate. The observation system should be optimized and the illumination of the estimated two receivers’ path should cover the propagation directions. Therefore, it is necessary to design new observation system and calculate the illumination of the two receivers’ path to obtain accurate dispersion data in passive source exploration.