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Nonlinear Tracking of Target Submarine Using Extended Kalman Filter (EKF)

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Security in Computing and Communications (SSCC 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 625))

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Abstract

This paper presents the effective method for submarine tracking using EKF. EKF is a Bayesian recursive filter based on the linearization of nonlinearities in the state and the measurement system. Here the sonar system is used to determine the position and velocity of the target submarine which is moving with respect to non moving submarine, and sonar is the most effective methods in finding the completely immersed submarine in deep waters. When the target submarines position and velocity is located from the reflected sonar, an extended Kalman filter is used as smoothening filters that describes the position and velocity of the ship with the noisy measurements given by sonar that is reflected back. By using the algorithm of extended Kalman filter we derived to estimate the position and velocity. Here the target motion is defined in Cartesian coordinates, while the measurements are specified in spherical coordinates with respect to sonar location. When the target submarine is located, the alert signal is sent to the own ship. This can be excessively used in military applications for tracking the state of the target submarine. Prediction of the state of the submarine is possible, with Gaussian noise to the input data. The simulation results show that proposed method is able to track the state estimate of the target, this was validated by plotting SNR vs MSE of state estimates. Here in this algorithm regressive iteration method is used to converge to the actual values from the data received.

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering, Amrita School of Engineering, Coimbatore Amrita Vishwa Vidyapeetham University, Coimbatore, 641112, India

    S. Vikranth, P. Sudheesh & M. Jayakumar

Authors
  1. S. Vikranth
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  2. P. Sudheesh
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  3. M. Jayakumar
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Corresponding author

Correspondence to P. Sudheesh .

Editor information

Editors and Affiliations

  1. IBM ZURICH RESEARCH LABORATORY, IBM ZURICH RESEARCH LABORATORY, RUESCHLIKON, Switzerland

    Peter Mueller

  2. Technology and Management, Indian Institute of Information Technology and Management, Kerala, India

    Sabu M. Thampi

  3. Temple University, New York, New York, USA

    Md Zakirul Alam Bhuiyan

  4. Computer Science, University of Waikato Computer Science, Hamilton, New Zealand

    Ryan Ko

  5. Deakin University , Burwood, Victoria, Australia

    Robin Doss

  6. University of the West of Scotland , Paisley, Glasgow, United Kingdom

    Jose M. Alcaraz Calero

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© 2016 Springer Nature Singapore Pte Ltd.

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Vikranth, S., Sudheesh, P., Jayakumar, M. (2016). Nonlinear Tracking of Target Submarine Using Extended Kalman Filter (EKF). In: Mueller, P., Thampi, S., Alam Bhuiyan, M., Ko, R., Doss, R., Alcaraz Calero, J. (eds) Security in Computing and Communications. SSCC 2016. Communications in Computer and Information Science, vol 625. Springer, Singapore. https://doi.org/10.1007/978-981-10-2738-3_22

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  • DOI: https://doi.org/10.1007/978-981-10-2738-3_22

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-2737-6

  • Online ISBN: 978-981-10-2738-3

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