Indian Journal of Automation and Artificial Intelligence

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Advanced Statistically Robust Estimation Algorithm for Underwater Vehicle Localization and Ranging for Sonar Applications


Affiliations
1 Department of Basic Sciences and Humanities, Sanketika Institute of Technology and Management, Visakhapatnam, Andhra Pradesh-530041, India
2 Department of Electrical and Electronics Engineering, Sanketika Institute of Technology and Management, Visakhapatnam, Andhra Pradesh-530041, India
3 Department of Electronics and Communication Engineering, Sanketika Institute of Technology and Management, Visakhapatnam, Andhra Pradesh-530041, India
 

Objectives: Range and bearing measurements of underwater vehicle is obtained by helicopter which uses dunking sonar. Considering range and bearing measurements the target position is identified and target motion parameters are available to guide the weapon on the target vehicle.

Methods/Statistical analysis: Target motion parameters are finally found by using Extended Kalman filter. Present weapon parameters are initial turning angle, straight run distance and many other which are obtained using the known parameters like speed, course of the helicopter and the target motion parameters.

Findings: Results of Monte Carlo simulation are shown which gives the better performances of the algorithm for typical scenarios using Matlab.

Application/Improvements: The proposed algorithm can be used for undersea sonar based applications.


Keywords

Estimation, Stochastic, Bearing, Line of Sight, Kalman Filter, Sonar, Weapon.
User
Notifications

  • S.T. Pork, J.G Lee. Design of a practical tracking algorithm with radar measurements. IEEE transactions on Aerospace and Electronic systems. 1998; 34(4), 1337-1344.

  • Y. Bar –shalom, Fortman. Tracking and data association. Academic Press. 1991.

  • Y. Bar-shalmon, X.R. Lee. Estimation and tracking principles techniques and software. Artech House, London. 1993.

  • A.Jawahar, S. K. Rao. Recursive multistage estimator for bearings only passive target tracking in esmew systems. Indian Journal of Science and Technology. 2015; 8(26), 1-5.

  • B.O.L. Jagan, S. K. Rao, A. Jawahar, S.K.B. Karishma. Application of bar-shalom and fortmann’s input estimation for underwater target tracking. Indian Journal of Science and Technology. 2016; 9(21), 1-5.

  • B.L. Kumari, S.R. Rao, K.P. Raju. Simplified target location estimation for underwater vehicles. Ocean Electronics (SYMPOL). 2013, 1-9.

  • M.N.V.S.S. Kumar, G. S. Rao. A new approach for tracking moving objects in underwater environment. Current Science. 2016; 110(7), 1-9.


Abstract Views: 376

PDF Views: 158




  • Advanced Statistically Robust Estimation Algorithm for Underwater Vehicle Localization and Ranging for Sonar Applications

Abstract Views: 376  |  PDF Views: 158

Authors

G. Chinna Rao
Department of Basic Sciences and Humanities, Sanketika Institute of Technology and Management, Visakhapatnam, Andhra Pradesh-530041, India
A. Jawahar
Department of Electrical and Electronics Engineering, Sanketika Institute of Technology and Management, Visakhapatnam, Andhra Pradesh-530041, India
S. S. Kiran
Department of Electronics and Communication Engineering, Sanketika Institute of Technology and Management, Visakhapatnam, Andhra Pradesh-530041, India

Abstract


Objectives: Range and bearing measurements of underwater vehicle is obtained by helicopter which uses dunking sonar. Considering range and bearing measurements the target position is identified and target motion parameters are available to guide the weapon on the target vehicle.

Methods/Statistical analysis: Target motion parameters are finally found by using Extended Kalman filter. Present weapon parameters are initial turning angle, straight run distance and many other which are obtained using the known parameters like speed, course of the helicopter and the target motion parameters.

Findings: Results of Monte Carlo simulation are shown which gives the better performances of the algorithm for typical scenarios using Matlab.

Application/Improvements: The proposed algorithm can be used for undersea sonar based applications.


Keywords


Estimation, Stochastic, Bearing, Line of Sight, Kalman Filter, Sonar, Weapon.

References