An Accelerated SBR Method for RCS Prediction of Electrically Large Target

Meng, Wei; Li, Juan; Guo, Lixin; Yang, Qing

doi:10.1109/lawp.2022.3185329

Cited by 12 publications

(1 citation statement)

References 15 publications

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“…Among them, time-domain methods mainly include clutter simulation methods based on statistical models [8], backscatter simulation methods based on measured SAR images, and SAR image simulation methods based on digital elevation models (DEMs) [9,10], which are mainly aimed at simulating large-scene SAR images and have the advantage of low algorithm complexity. Frequency-domain methods mainly include finite-difference time-domain (FDTD) [11][12][13], method of moments (MOM) [14][15][16], physical optics (PO), geometric optics (GO), and SBR methods [17][18][19]. These methods calculate the frequency-domain response of the target to obtain the SAR image and have the characteristics of high algorithm complexity and high calculation accuracy [20].…”

Section: Introductionmentioning

confidence: 99%

High-Precision GPU-Accelerated Simulation Algorithm for Targets under Non-Uniform Cluttered Backgrounds

Zhang,

Zhou,

Song

et al. 2023

Remote Sensing

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This article presents a high-precision airborne video synthetic aperture radar (SAR) raw echo simulation method aimed at addressing the issue of simulation accuracy in video SAR image generation. The proposed method employs separate techniques for simulating targets and ground clutter, utilizing pre-existing SAR images for clutter simulation and employing the shooting and bouncing rays (SBR) approach to generate target echoes. Additionally, the method accounts for target-generated shadows to enhance the realism of the simulation results. The fast simulation algorithm is implemented using the C++ programming language and the Accelerated Massive Parallelism (AMP) framework, providing a fusion technique for integrating clutter and target simulations. By combining the two types of simulated data to form the final SAR image, the method achieves efficient and accurate simulation technology. Experimental results demonstrate that this method not only improves computational speed but also ensures the accuracy and stability of the simulation outcomes. This research holds significant implications for the development of algorithms pertaining to video SAR target detection and tracking, providing robust support for practical applications.

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