K. Lakshmiprasanna ¹, S. Koteswara Rao ¹, A. Jawahar ¹, Sk. B. Karishma ¹

Affiliations
1 School of Electrical Sciences, KL University, Vaddeswaram – 522502, Andhra Pradesh, IN

Abstract

Background/Objectives: The necessity of ownship stratagies is essential during the attack of enemy torpedo. Methods/Statistical Analysis: Torpedo tacking using advanced particle filter is proposed in bearings-only tracking environment for underwater applications. The observer platform has to perform evasive maneuver as well as perform target motion analysis to track the incoming hostile torpedo. Particle Filter (PF) combined with Modified Gain Bearings-Only Extended Kalman Filter (MGBEKF) is proposed technique. Findings: Monte-Carlo simulation is carried out for performance evaluation of the algorithm and the obtained results are presented which agree that PF-MGBEKF is most suitable as a part of ownship strategy.

Keywords

Bearing Measurements, Estimation, Simulation, Sonar, Torpedo, Tracking

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K. Lakshmiprasanna ¹, S. Koteswara Rao ¹, A. Jawahar ¹, Sk. B. Karishma ¹

Affiliations
1 School of Electrical Sciences, KL University, Vaddeswaram, Guntur – 522502, Andhra Pradesh, IN

Abstract

Background/Objectives: Pseudo Linear Estimator (PLE) is developed for active sonar applications. Methods/Statistical analysis: The PLE offers features of Extended Kalman Filter (EKF). Findings: The results of PLE are compared with that of EKF. The results of MC simulation are presented for typical scenarios. Application/Improvements: In PLE, there is no need to initialize target state vector and its covariance matrix with prior (approximate) knowledge and hence its performance is found to be better than that of EKF.

Keywords

Estimation, Kalman Filter, Pseudo Linear Estimator, Simulation, Target Tracking

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