Indian Journal of Science and Technology
DOI: 10.17485/ijst/2016/v9i7/85557
Year: 2016, Volume: 9, Issue: 7, Pages: 1-4
Original Article
B. Omkar Lakshmi Jagan* , S. Koteswara Rao, A. Jawahar, S. K. B. Karishma
School of Electrical Sciences, KL University, Vaddeswaram, Guntur – 522502, Andra Pradesh, India; [email protected], [email protected], [email protected], [email protected]
*Author for Correspondence
B. Omkar Lakshmi Jagan
School of Electrical Sciences, KL University, Vaddeswaram, Guntur – 522502, Andra Pradesh, India; [email protected]
Background/Objectives: An Algorithm, the Particle filter, is proposed for implementing the bearings only Torpedo Motion Analysis (TMA).The required density of the state vector is represented as a set of random samples, which are updated and propagated by the algorithm. The method is not restricted by assumptions of linearity or Gaussian noise. Methods/Statistical analysis: The particle filter is combined with Modified Gain Bearings Only Extended Kalman Filter and the results are compared with that of Extended Kalman Filter or Unscented Kalman Filters. Findings: Almost similar performance is obtained. The algorithm is applied to track a torpedo using measurements available from towed array. Application/Improvements: The results in simulation mode and with sea trial data are presented.
Keywords: Algorithm,Estimation,Gaussianity,Kalman Filter, Linearity,Simulation,Towed Array
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