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Object Detection and Localization Using Compressed Sensing

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Advances in Signal Processing and Intelligent Recognition Systems (SIRS 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 678))

Abstract

Localization is very significant in Underwater Sensor Network (UWSN) applications. The functionality of the network can face challenges by the force of water current and hostile environmental conditions. This work presents a method for localization using Compressed Sensing (CS). It is implemented without using GPS technology which makes the method reliable. CS is employed in the data acquisition module for transmission and reconstruction of audio signal. It is a dictionary based execution exploiting \(l_1\) minimization using Gabor transform. Here, localization using audio is performed using Time Difference of Arrival (TDOA). Moore-Penrose pseudo-inverse is used for matrix operations. An array of audio sensors or hydrophones is assumed while performing this work. The results of simulation indicate that this is an efficient technique for object detection and localization.

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Acknowledgments

The authors would like to thank Sardar Patel Institute of Technology, India for providing the necessary facilities for carrying out this work.

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Authors and Affiliations

  1. Department of Electronics and Telecommunication Sardar Patel Institute of Technology, Mumbai University, Mumbai, India

    Poonam Ashok Deotale & Preetida Vinayakray-Jani

Authors
  1. Poonam Ashok Deotale
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  2. Preetida Vinayakray-Jani
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Corresponding author

Correspondence to Poonam Ashok Deotale .

Editor information

Editors and Affiliations

  1. School of CS/IT, Indian Institute of Information Technology and Management, Trivandrum, Kerala, India

    Sabu M. Thampi

  2. Department of Electrical and Computer Engineering, Ryerson University, Toronto, Ontario, Canada

    Sri Krishnan

  3. Department of Computer Science, University of Salamanca, Salamanca, Salamanca, Spain

    Juan Manuel Corchado Rodriguez

  4. Electronics and Communication Sciences Unit, Indian Statistical Institute, Kolkata, West Bengal, India

    Swagatam Das

  5. Department of Systems and Computer Networks, Wroclaw University of Science and Technology, Wroclaw, Poland

    Michal Wozniak

  6. Faculty of Engineering and Technology, Liverpool John Moores University, Liverpool, United Kingdom

    Dhiya Al-Jumeily

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Deotale, P.A., Vinayakray-Jani, P. (2018). Object Detection and Localization Using Compressed Sensing. In: Thampi, S., Krishnan, S., Corchado Rodriguez, J., Das, S., Wozniak, M., Al-Jumeily, D. (eds) Advances in Signal Processing and Intelligent Recognition Systems. SIRS 2017. Advances in Intelligent Systems and Computing, vol 678. Springer, Cham. https://doi.org/10.1007/978-3-319-67934-1_12

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  • DOI: https://doi.org/10.1007/978-3-319-67934-1_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67933-4

  • Online ISBN: 978-3-319-67934-1

  • eBook Packages: EngineeringEngineering (R0)

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