Computer Science

Computer Science ›› 2020, Vol. 47 ›› Issue (11): 304-309.doi: 10.11896/jsjkx.200600167

• Computer Network • Previous Articles     Next Articles

Sampling Optimization Method for Acoustic Field Reconstruction Based on Genetic Algorithm

XU Feng1, SUN Jie2,3, LIU Shi-jie2,3   

  1. 1 College of Public Security Information Technology and Information,Criminal Investigation Police University of China,Shenyang 110035,China
    2 State Key Laboratory of Robotics,Shenyang Institute of Automation,Chinese Academy of Sciences,Shenyang 110016,China
    3 Institutes for Robotics and Intelligent Manufacturing,Chinese Academy of Sciences,Shenyang 110169,China
  • Received:2020-06-28 Revised:2020-08-25 Online:2020-11-15 Published:2020-11-05
  • About author:XU Feng,born in 1977,Ph.D,associate professor. His main research interests include robot,virtual reality and audio-visual data.
  • Supported by:
    This work was supported by the National Science and Technology Major Project of the Ministry of Science and Technology of China (2017YFC0821004) and Technical Research Plan of the Ministry of Public Security (2016JSYJC59).

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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.

Key words: Acoustic field reconstruction, Compressive sensing, Genetic algorithm (GA), Sampling optimization, Underwater vehicle

CLC Number: 

  • TP249
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