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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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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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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