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Alternative TitleSampling Optimization Method for Acoustic Field Reconstruction Based on Genetic Algorithm
许锋1; 孙洁2,3; 刘世杰2,3
Source Publication计算机科学
Contribution Rank2
Funding Organization国家科技重大专项(2017YFC0821004) ; 公安部技术研究计划(2016JSYJC59)
Keyword压缩感知 遗传算法 测量优化 水下机器人 声场重构


Other Abstract

The spatial field of ocean acoustic channel parameters can describe the spatial distribution law of underwater acoustic signal propagation in the ocean,which has important guiding significance for underwater acoustic communication location selection, underwater target detection and stealth.For the problem of sampling trajectory optimization in the application of compressive sensing(CS)methods on the acoustic field reconstruction,a sampling optimization method based on a genetic algorithm (GA)is proposed to improve the CS reconstruction accuracy in this paper combining the characteristics of sound field,compressed sensing and the motion characteristics of underwater robot.Firstly,the structure of the CS sampling matrix is analyzed. Then,combining with the kinematic constraint of underwater vehicles,the gene expression and generation method as well as the GA fitness function are defined to support the sampling of underwater vehicles.In simulations,the traveling salesman problem (TSP)- based path from Gaussian random sampling points and the lawnmower sampling path are used for comparison.The results demonstrate that the proposed GA-based sampling method can significantly improve the reconstruction accuracy of acoustic fields.The influences of different sampling rates and different acoustic filed distributions are discussed,which further illustrates the superior performance of the proposed method.

Document Type期刊论文
Corresponding Author许锋
Recommended Citation
GB/T 7714
许锋,孙洁,刘世杰. 基于遗传算法的声场重构测量优化方法[J]. 计算机科学,2020,47(11):304-309.
APA 许锋,孙洁,&刘世杰.(2020).基于遗传算法的声场重构测量优化方法.计算机科学,47(11),304-309.
MLA 许锋,et al."基于遗传算法的声场重构测量优化方法".计算机科学 47.11(2020):304-309.
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