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Target Tracking in WSN Using Dynamic Neural Network Techniques

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Smart and Innovative Trends in Next Generation Computing Technologies (NGCT 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 828))

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Abstract

Wireless Sensor Networks (WSN) are increasingly being envisioned for the collection of data, such as physical or environmental properties. Unlike detection of an event, tracking requires ensuring continuous monitoring. Resource constrained nature of wireless sensor networks makes energy efficient tracking a challenging task. Prediction based approaches try to save energy by reducing an avoidable communication. A Kalman-based approach has been widely used for target tracking but is inaccurate in the case of maneuvering target due to its inability to incorporate nonlinearity. In this paper, dynamic neural network based approaches called Time Delay Neural Network (TDNN) and Nonlinear Autoregressive network with Exogenous inputs (NARX) are proposed for non-cooperative target tracking application. The performance of NARX is compared with Kalman based approach and TDNN in terms of tracking accuracy. Simulation results show that NARX outperforms both Kalman approach and TDNN for target tracking applications.

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Authors and Affiliations

  1. Sarvajanik College of Engineering and Technology, Surat, Gujarat, India

    Moxanki A. Bhavsar & Maulin Joshi

  2. Chhotubhai Gopalbhai Patel Institute of Technology, Surat, Gujarat, India

    Jayesh H. Munjani

Authors
  1. Moxanki A. Bhavsar
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  2. Jayesh H. Munjani
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  3. Maulin Joshi
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Corresponding author

Correspondence to Jayesh H. Munjani .

Editor information

Editors and Affiliations

  1. Indian Institute of Technology Patna, Patna, Bihar, India

    Pushpak Bhattacharyya

  2. University of Petroleum and Energy Studies, Dehradun, India

    Hanumat G. Sastry

  3. University of Petroleum and Energy Studies, Dehradun, India

    Venkatadri Marriboyina

  4. University of Petroleum and Energy Studies, Dehradun, India

    Rashmi Sharma

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Bhavsar, M.A., Munjani, J.H., Joshi, M. (2018). Target Tracking in WSN Using Dynamic Neural Network Techniques. In: Bhattacharyya, P., Sastry, H., Marriboyina, V., Sharma, R. (eds) Smart and Innovative Trends in Next Generation Computing Technologies. NGCT 2017. Communications in Computer and Information Science, vol 828. Springer, Singapore. https://doi.org/10.1007/978-981-10-8660-1_58

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  • DOI: https://doi.org/10.1007/978-981-10-8660-1_58

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-8659-5

  • Online ISBN: 978-981-10-8660-1

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