## 1 Introduction  
Most underground geotechnical engineering is carried out near the surface. Unfortunately, the near-surface geological conditions are highly complex due to the abundance of joints, faults, boulders, caves, and so on. Encountering unexplored weak formations and caves can cause a variety of geological disasters, such as uneven settlement or collapse, which can inflict immense economic losses and even death [1, 2]. According to the report [3] of the current status of sinkhole collapses in the karst area in China, more than 1500 karst collapsing events have been recorded and these events formed more than 45,000 sinkholes. More than 75% sinkholes were triggered by human activities. These activities are mainly around the near-surface, including mine drainage, foundation engineering, and tunnel constructions. Subsidence sinkholes result from both subsurface dissolution and the downward gravitational movement of the undermined overlying material. These sinkholes, which are invisible from the surface, are the most important from a hazard and engineering perspective [4]. Hence, to provide guidance for construction and design efforts, geophysical prospecting methods are often used in engineering to detect underground structures as an important supplement to drilling and excavation. However, the near-surface is complex and traditional migration imaging methods may suffer from types of artifacts and interferences. High-precision prospecting in near-surface detection is quite challenging since surface waves and S-waves are powerful near the surface. There is an urgent need to deal with the artifacts and interferences. Furthermore, the detection capability is limited by the construction site and time frame [5]. Therefore, the development of accurate geophysical prospecting methods for near-surface detection is of great significance to geotechnical engineering. Seismic methods are among the most commonly used geophysical techniques for near-surface detection with the advantages of a high efficiency, a high accuracy, and a low cost; moreover, seismic techniques are nondestructive [6]. Seismic reflection is extensively used in both academic and practical engineering [7]. One of the main goals of seismic data processing is seismic imaging. For instance, seismic migration imaging [8] is used to map underground structures. Although advanced imaging methods have emerged in recent decades, such as reverse time migration [9; 10] and Gaussian beam migration [11; 12; 13], Kirchhoff migration [14] is still the most popular approach due to its ability to provide an image of sufficient quality and at an affordable computational cost. [PERSON] et al. [15] processed a model example and seismic field data to demonstrate the validity of prestack Kirchhoff time migration. [PERSON] et al. [16] applied Kirchhoff prestack time migration to seismic data of coal seam reflections and obtained better images than with poststack time migration. [PERSON] et al. [17] used tomographic travel-time inversion and prestack Kirchhoff depth migration-based migration velocity analysis (MVA) and obtained a precise, high-resolution migration velocity model. [PERSON] and [PERSON] [18] proposed a novel approach that attached a prediction shaping filter to Kirchhoff prestack time migration to mitigate the stretching effect and demonstrated their method with a numerical example and field data. [PERSON] et al. [7] applied Kirchhoff poststack migration to a case of seismic scattered wave imaging and obtained reliable imaging results in both the synthetic data and field data. Nevertheless, in near-surface seismic exploration, where the depth of the target area is usually less than a hundred meters, Kirchhoff migration still suffers from the following problems: (1) Kirchhoff migration relies on the preprocessing of signals to deal with noise and interference such as white noise, S-wave signals, and multiples; (2) Kirchhoff migration is affected by high-energy surface waves, which appear as massive artifacts in the imaging results.