Parallel structure based on multi-core computing for radar system simulation

被引：0

作者：

Wang, Lei ^{[1
,2
]}

Lu, Xian-Liang ^{[2
]}

Chen, Ming-Yan ^{[1
]}

Zhang, Wei ^{[1
]}

Zhang, Shun-Sheng ^{[1
]}

机构：

[1] Research Institute of Electronic Science and Technology, University of Electronic Science and Technology of China

[2] School of Computer, University of Electronic Science and Technology of China

来源：

Dianzi Keji Daxue Xuebao/Journal of the University of Electronic Science and Technology of China | 2014年 / 43卷 / 01期

关键词：

All-digital radar simulation; Data division; Multi-data links; Task allocation;

D O I：

10.3969/j.issn.1001-0548.2014.01.019

中图分类号：

学科分类号：

摘要：

To solve the bottle-neck problem of lower efficiency existed in radar echo generation and signal processing with serial simulation architecture, a multi-data links computing model based on multi-core memory-shared platform is proposed. This method could greatly promote simulation efficiency by taking advantage of multi-core. According to the independent characteristic between radar tasks in the same scheduling interval, the model takes data division, task allocation, time synchronization, and load monitoring with measurement into account to discuss its parallel characteristic. The Pentium(R) Dual-Core E5200 CPU with 2 GB memory is used to test the target scene with 20 batches. Simulation results demonstrate that, compared with serial simulation, the data frame average processing time of parallel model decreases 37.5% and the data frame processing speedup ratio curve has good acceleration performance. This parallel algorithm can reduce the simulation time greatly.

引用

页码：113 / 118

页数：5

共 17 条

[1]

Zhang L.-B., Chi X.-B., Mo Z.-Y., Et al., Introduction to Parallel Computing, (2006)

[2]

Zhao F., Wang X.-S., Xiao S.-P., Et al., Analysis of phased array radar system simulation parallel procession based on HLA, Journal of System Simulation, 18, 8, pp. 2170-2173, (2006)

[3]

Chen G.-L., Sun G.-Z., Xu Y., Et al., Methodology of research on parallel algorithm, Chinese Journal of Computers, 31, 9, pp. 1493-1500, (2008)

[4]

Wang N.-B., Song Y.-B., Yao N.-M., Et al., A parallel data processing middleware based on clusters, Journal of Computer Research and Development, 44, 10, pp. 1702-1708, (2007)

[5]

Xu L., Wu S.-L., Li H., Parallel computing in phased array radar system simulation, Transactions of Beijing Institute of Technology, 28, 6, pp. 517-520, (2008)

[6]

Zhao F., Zhou Y., Zhou J., Et al., Real time optimization analysis of phased array radar system simulation, Journal of System Simulation, 17, 8, pp. 2001-2003, (2005)

[7]

Huang Z.-H., Li X.-M., Data paralleling and pipeline processing in the modular visualization environment, Journal of Computer Research & Development, 37, 8, pp. 962-968, (2000)

[8]

Lai S.-J., Wang B.-Z., Huang T.-Z., High efficient parallel FDTD algorithm scheme in shared memory systems, Journal of University of Electronic Science and Technology of China, 39, 5, pp. 681-683, (2010)

[9]

Chen S., Li G., Zhang H., Et al., A GPU-based parallel implementation of compressive sampling reconstruction for SAR image compression, Journal of Electronics & Information Technology, 33, 3, pp. 610-614, (2011)

[10]

Zhang B., Han J.-L., Parallel computing methods for CFD using a GPU and implicit scheme, Acta Aeronautica et Astronautica Sinica, 31, 2, pp. 249-254, (2010)

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