## 1 Introduction  
Microtremor is a faint vibration that occurs naturally and is always present on the Earth's surface; in the area of shallow surface wave investigation, it is often known as \"ground pulsation\". The microtremor propagates through the ground as a wave with a frequency range of 0.1 to 50 Hz and a very modest amplitude, typically between \(10^{-4}\) and \(10^{-2}\) mm. The origins of microtremor are numerous and diverse, ranging from man-made activities such as traffic and mechanical vibrations to natural occurrences such as tides, volcanic activity, wind, and rain [1, 2, 3]. Therefore, microtremor can be thought of as a collection of waves with various amplitudes and frequencies. These waves have different transmission characteristics in different media at the surface, so the microtremors contain a wealth of information about the surface media and can be analyzed to obtain geological structures [4, 5]. The flow of the microtremor survey is shown in Figure 1, where the stations are positioned in an array to gather surface microtremor signals from all directions. Then, the dispersion curve is extracted from microtremor signals. Finally, the subsurface S-wave velocity structure and the underground geotechnical medium can be obtained using inversion or conversion with dispersion curve [6, 7]. Due to the benefits of being rapid, ecologically friendly, devoid of electromagnetic interference, and having no artificial seismic source, the microtremor survey is crucial to urban subterranean surveys [8]. The extraction of the dispersion curve is the vital stage in the microtremor survey. At present, the algorithms of dispersion curve extraction that are commonly used include the spatial autocorrelation method(SPAC), the extended spatial autocorrelation method (ESPAC) [9; 10], frequency-wavenumber method(FK) [11], and seismic interferometry method (SI). The SPAC needs to place the seismometers in triangular or circular arrays; however, the actual field is complex, and it may be difficult to meet its array conditions. For this reason, the ESPAC method was proposed to accommodate arbitrary arrangement of geometry. The FK method has no restrictions on arrangement of arrays, but it needs more seismometers to achieve better detection results [12]. The SI method extracts the dispersion curve from two microtremor signals. The arrangement of the array is flexible, and more dispersion information can be extracted through pairwise operation, which is helpful to obtain a higher resolution and more precise underground S-wave velocity structure [13]. Therefore, SI has been the subject of much investigation and application by numerous academics. SI was often used in large-scale, deep geophysical exploration at first. In 2005, [PERSON] used SI to analyze the data recorded by the US-Array station and successfully obtained the deep velocity structure in southern California [14]. [PERSON] applied SI to the study of mantle-scale lithospheric structures in a dense array in Tibet [15]. Subsequently, some scholars introduced SI into shallow, small-scale surface wave exploration. [PERSON] detected the stratigraphic structure at 0-105 m depth in the Valhall area [16]. [PERSON] compared the inversion results of the SI with the SPAC in YuXi and found that their velocity structure change trends are basically consistent [17]. Figure 1: Flowchart of microtremor survey. In addition to the application practice, many academics concentrate their studies on the dispersion curve processing techniques. [PERSON] combined SI and signal-to-noise ratio theory, indicating that after signal-to-noise ratio compensation, the shape of the coherence coefficient curve obtained using SI is more similar to that of the Bessel function and more accurate [18]. [PERSON] investigated the effect of correlation between measurement points and common centroids on the quality of the dispersion curves in a double circular array and pointed out that the direct averaging method would reduce the depth of exploration [19].