IET International Radar Conference 2013 2013
DOI: 10.1049/cp.2013.0132
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SAR echo simulation from numerous scattering cells based on GPU

Abstract: A comprehensive and novel SAR echo simulation method for a great deal of scattering cells is presented in this paper. In order to greatly reduce the processing time, we apply the Graphics Processing Units (GPU). Modern GPUs are very efficient at manipulating computer graphics, and their highly parallel structure makes them more effective than generalpurpose CPUs in processing large blocks of data. Especially when facing the complicated scene of many scattering cells, high-speed operation in parallel based on G… Show more

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Cited by 5 publications
(3 citation statements)
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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%
“…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%
“…Chen et al proposed an airborne bistatic SAR echo simulator based on multi-GPUs, which effectively improves the simulation echo simulation speed [20]. Sheng et al used the existing SAR amplitude image as a backscatter coefficient matrix to bring it into the echo model and based it on the CUDA platform to implement the parallel echo simulation task for the used discrete units and subsequently proposed a local optimization algorithm to further improve the simulation efficiency [21,22]. Zhang et al proposed a time domain SAR raw data simulation method based on multi-GPUs, which cannot only simulate a large area of raw data through task division and scheduling but also improve the efficiency of current GPU-based algorithms through access conflict optimization and fine-grained parallel pipelines [23].…”
Section: Introductionmentioning
confidence: 99%
“…The CPU multi-threads were used to control the multi-GPUs platform for echo simulation, which improves the speed of SAR echo simulation [7]. Sheng et al proposed a fast echo simulation method for complex scenes, calling each thread of the GPU to be responsible for the echo simulation of a single scattering unit, but the backscatter coefficient was set in advance [8,9]. Yu et al proposed a GPU-based Circular Synthetic Aperture Radar echo simulation method to improve the simulation efficiency of large scenes, and simplified the backscatter coefficient calculation process [10].…”
Section: Introductionmentioning
confidence: 99%