# Bounding Volume Hierarchy-Assisted Fast SAR Image Simulation Based on Spatial Segmentation
## 1 Introduction  
SAR is an active and high-resolution microwave imaging sensor that has been widely used in military and civilian applications [1, 2]. At present, it is time consuming and laborious to obtain some typical target SAR images by actual measurement means, and with the help of SAR image simulation technology, SAR simulated images with different imaging parameters can be obtained in a computerized virtual environment, which has a very high application value [3]. Current SAR image simulation methods can be broadly categorized into two types: physical mechanism-driven forward simulation and data-driven inverse simulation-based. The physical mechanism-driven forward simulation method builds a SAR image simulation model based on the scattering mechanism and signal propagation of radar, which can simulate the SAR image of a real target or scene, but the computational complexity is high and requires more computational resources. [PERSON] et al. developed a SAR image simulator for 3D targets that effectively modeled the effects of multiple scattering of EM waves occurring with complex targets or scenes, which is still widely used today [4, 5, 6]. [PERSON]'s team proposed a series of SAR image simulation methods for urban building targets, achieved better simulation results, and developed a set of 3D target SAR image simulators [7, 8, 9]. [PERSON] et al. used the GPU multi-threaded parallel to transmit EM waves into the simulation scene and utilized ray tracing algorithms to map the 3D target directlyto the SAR slant range coordinate system to quickly generate the target SAR simulation image [10]. [PERSON] et al. proposed a SAR image simulation method for urban structures based on incremental length diffraction coefficients (ILDCs) and shooting and bouncing rays (SBRs) and performed SAR image simulation for building models with sloped and flat roofs, respectively [11]. [PERSON] et al. used a combination of physical optics (POs), geometrical optics (GOs), and the physical theory of diffraction (PTD) for target backscatter field calculations, which were then combined with the frequency domain pulsed coherence method for echo simulation and imaging processing [12]. [PERSON] open-sourced a basic echo-based SAR image simulation infrastructure designed to facilitate collaboration on SAR image simulator development among interested researchers [13]. [PERSON] et al. combined POs and GOs to carry out the target multiple backscatter field calculation, combined them with the frequency domain echo model to generate the original echo signals, acquired the tank SAR data set by focusing imaging processing, and achieved better simulation results [14]. [PERSON] et al. based on the physical illumination model of high-frequency ray theory, carried out the echo-based SAR image simulation on a typical military target to achieve some good simulation results, and then a fast simulation architecture based on the CUDA was established to effectively improve the efficiency of the SAR image simulation [15; 16]. [PERSON] et al. utilized an improved physical illumination model to simulate the SAR image of a 3D scene and used the GPU to simulate the multiple scattering effects of the EM wave in multi-thread parallel, achieving a good result and better simulation results [17]. Compared with the physical mechanism-driven forward simulation method, the data-driven inverse simulation method simplifies the backscatter field calculation process to a certain extent, mostly utilizing the existing SAR image data as a known backscatter coefficient matrix to participate in the echo simulation and then performing two-dimensional focusing imaging processing on the generated echo signal. The phase of the echo signals generated by this type of method is misaligned, and most of the existing studies have been carried out to improve the simulation efficiency based on the inverse simulation method. Some representative studies have been presented successively. [PERSON] et al.