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Sensors 2017, 17(1), 113; doi:10.3390/s17010113

A Fast Synthetic Aperture Radar Raw Data Simulation Using Cloud Computing

College of Information Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China
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Academic Editor: Vittorio M.N. Passaro
Received: 23 November 2016 / Revised: 29 December 2016 / Accepted: 31 December 2016 / Published: 8 January 2017
(This article belongs to the Section Remote Sensors)
View Full-Text   |   Download PDF [648 KB, uploaded 8 January 2017]   |  

Abstract

Synthetic Aperture Radar (SAR) raw data simulation is a fundamental problem in radar system design and imaging algorithm research. The growth of surveying swath and resolution results in a significant increase in data volume and simulation period, which can be considered to be a comprehensive data intensive and computing intensive issue. Although several high performance computing (HPC) methods have demonstrated their potential for accelerating simulation, the input/output (I/O) bottleneck of huge raw data has not been eased. In this paper, we propose a cloud computing based SAR raw data simulation algorithm, which employs the MapReduce model to accelerate the raw data computing and the Hadoop distributed file system (HDFS) for fast I/O access. The MapReduce model is designed for the irregular parallel accumulation of raw data simulation, which greatly reduces the parallel efficiency of graphics processing unit (GPU) based simulation methods. In addition, three kinds of optimization strategies are put forward from the aspects of programming model, HDFS configuration and scheduling. The experimental results show that the cloud computing based algorithm achieves 4_ speedup over the baseline serial approach in an 8-node cloud environment, and each optimization strategy can improve about 20%. This work proves that the proposed cloud algorithm is capable of solving the computing intensive and data intensive issues in SAR raw data simulation, and is easily extended to large scale computing to achieve higher acceleration. View Full-Text
Keywords: cloud computing; synthetic aperture radar (SAR); raw data generation; distributed simulation; big data cloud computing; synthetic aperture radar (SAR); raw data generation; distributed simulation; big data
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Li, Z.; Su, D.; Zhu, H.; Li, W.; Zhang, F.; Li, R. A Fast Synthetic Aperture Radar Raw Data Simulation Using Cloud Computing. Sensors 2017, 17, 113.

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