SAR simulation for large scenes by ray tracing technique based on GPU

Liu, Tingting; Wang, Kaizhi; Liu, Xingzhao

doi:10.1109/igarss.2013.6721364

Cited by 5 publications

(4 citation statements)

References 11 publications

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“…where R k is half of the total distance of multiple scattering of EM wave transmission; S ′ is the instantaneous sensor position; P ′ 0 -P ′ k is the intersection point of multiple scattering; Pha(k) is the multiple scattering phase; f 0 and K r are the signal carrier frequency and chirp rate, respectively; τ and η are the fast time and slow time, respectively. Combining Equations ( 7)-( 9) can simultaneously obtain the amplitude and phase of the EM wave when scattering occurs, specifically referring to Equation (10) to vectorially superpose the amplitude and phase of the multiple scattering field to obtain the backscatter field of the EM wave, including multiple scattering.…”

Section: Calculation Of the Multiple Backscatter Fieldmentioning

confidence: 99%

“…Franceschetti'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]. Lu 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 directly to the SAR slant range coordinate system to quickly generate the target SAR simulation image [10]. Xia 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].…”

Section: Introductionmentioning

confidence: 99%

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Bounding Volume Hierarchy-Assisted Fast SAR Image Simulation Based on Spatial Segmentation

Wu,

Jin,

Xiong

et al. 2024

Applied Sciences

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In order to improve the simulation efficiency under the premise of ensuring the fidelity of synthetic aperture radar (SAR) simulation images, we propose a BVH-assisted fast SAR image simulation method based on spatial segmentation. The beam scanning model is established based on RD imaging geometric relation, and the bounding volume hierarchy (BVH) algorithm is used to assist in obtaining the time-varying latticed radiation and shadow areas within the radar beam, combining them with the real-time position of the sensors to complete the simulation of the electromagnetic (EM) wave transmission. The ray tracing algorithm is used to calculate the multiple backscatter fields of EM waves, including various material properties of the target surface. The SAR spatial traversal is adopted to spatially segment the latticed radiation area, and the compute unified device architecture (CUDA) kernel function is designed using the echo matrix cell method to make each cell of the target echo matrix as a subfield of the backscattering field, and the position of the echo matrix cell is traversed to obtain the target backscattering field. The target simulated echo is processed by the range Doppler (RD) imaging algorithm to obtain the SAR-simulated image. The simulation results show that compared with a CPU single-thread simulation, the simulation speed of the proposed method is significantly improved, and the SAR simulation image has high structural similarity with the real image, which fully verifies the effectiveness of the proposed method.

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Section: Calculation Of the Multiple Backscatter Fieldmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Bounding Volume Hierarchy-Assisted Fast SAR Image Simulation Based on Spatial Segmentation

Wu,

Jin,

Xiong

et al. 2024

Applied Sciences

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“…Point target model CPU SARSIM (Pike, 1985) [8] GPU (Zhang, 2014) [13] (Yu, 2014) [15] (Wang, 2013) [16] (Chen, 2011) [18] Scene area Physical model background CPU (Holtzman, 1978) [7] SARAS (Franceschetii, 1992) [9] Target and background separated CPU GRECOSAR (Margarit, 2006) [10] Reflectivity map CPU (Zhu, 2009) [11] Image Point target model CPU (Sheng, 2005) [2] GPU [17] Scene area Ray-tracing with rendering CPU (Mametsa, 2002) [5] GPU (Lu, 2009) [12] (Liu, 2013) [14] Rasterization by look-up tables CPU SARViz (Balz, 2009) [3] From the above reviews, it is clear that there is a need for an efficient SAR signal and image simulator, including the SAR echo signal generation considering the coherent integration of the target and background. This simulator can also simulate incident wave rays and the propagation into the inter-and intra-interactions of targets and background clutter.…”

Section: Raw Datamentioning

confidence: 99%

SAR Image Simulation of Complex Target including Multiple Scattering

et al. 2021

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We present a GPU-based computation for simulating the synthetic aperture radar (SAR) image of the complex target. To be more realistic, we included the multiple scattering field and antenna pattern tracking in producing the SAR echo signal for both Stripmap and Spotlight modes. Of the signal chains, the computation of the backscattering field is the most computationally intensive. To resolve the issue, we implement a computation parallelization for SAR echo signal generation. By profiling, the overall processing was identified to find which is the heavy loading stage. To further accommodate the hardware structure, we made extensive modifications in the CUDA kernel function. As a result, the computation efficiency is much improved, with over 224 times the speed up. The computation complexity by comparing the CPU and GPU computations was provided. We validated the proposed simulation algorithm using canonical targets, including a perfectly electric conductor (PEC), dielectric spheres, and rotated/unrotated dihedral corner reflectors. Additionally, the targets can be a multi-layered dielectric coating or a layered medium. The latter case aimed to evaluate the polarimetric response quantitively. Then, we simulated a complex target with various poses relative to the SAR imaging geometry. We show that the simulated images have high fidelity in geometric and radiometric specifications. The decomposition of images from individual scattering bounce offers valuable exploitation of the scattering mechanisms responsible for imaging certain target features.

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“…Auer et al carried out a simulation study of high-resolution SAR images by improving the illumination model using the ray tracing algorithm to map the 3D scene to the SAR slant range coordinate system [29,30]. Some studies have built some backscattering models using ray tracing with the help of the CUDA platform to carry out experiments on the multiple scattering energy tracking of scenes in the SAR slant range coordinate system [31][32][33]. Such studies usually obtain SAR simulation images with clear texture and high timeliness, which are convenient for establishing SAR target datasets.…”

Section: Introductionmentioning

confidence: 99%

Fast SAR Image Simulation Based on Echo Matrix Cell Algorithm Including Multiple Scattering

Jin

Xiong

et al. 2023

Remote Sensing

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We present a novel fast synthetic aperture radar (SAR) image simulation method based on the echo matrix cell algorithm including multiple scattering. To improve the efficiency of SAR image simulation while ensuring the fidelity of the simulated results, we first discretized the target facets set in the SAR beams footprint into lattice targets using the range-Doppler (RD) imaging geometry model and provided the basis for simulating electromagnetic wave transmission. Based on the simulation of electromagnetic waves transmission, we used the ray tracing algorithm to calculate the multiple backscattering field including multi-polarimetric information and various material properties. Then, based on the echo matrix cell algorithm, we set the echo matrix cell as the subfield of the target backscattering field and designed the CUDA kernel function to implement a computation parallelization for SAR echo generation. All the echo matrix cells are traversed in parallel to obtain the total backscattering field of the target, reproducing the time-varying characteristic of the backscatter coefficient for each lattice target within the synthetic aperture time. The echo signal is processed using the RD imaging algorithm to obtain the simulated SAR image. Finally, we select some targets including aircraft carrier and airplane models for simulation tests. The computation efficiency is improved over 170-fold by comparing the computations of the proposed method and CPU single-thread. We also performed some qualitative and quantitative evaluations on the fidelity of the simulated SAR images. The experimental results verify the effectiveness of the proposed method.

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SAR simulation for large scenes by ray tracing technique based on GPU

Cited by 5 publications

References 11 publications

Bounding Volume Hierarchy-Assisted Fast SAR Image Simulation Based on Spatial Segmentation

Bounding Volume Hierarchy-Assisted Fast SAR Image Simulation Based on Spatial Segmentation

SAR Image Simulation of Complex Target including Multiple Scattering

Fast SAR Image Simulation Based on Echo Matrix Cell Algorithm Including Multiple Scattering

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