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Application of PFMGBEKF for Bearings-Only Tracking using Roughening
Y. Bala Treeza1, K. Kesavanadh2, S. Koteswara Rao3, Kausar Jahan4

1Y.Bala Treeza, Department of Electronics and Communication Engineering, Koneru Lakshmaiah Education Foundation, Guntur (Andhra Pradesh), India.
2K.Kesavanadh, Department of Electronics and Communication Engineering, Koneru Lakshmaiah Education Foundation, Guntur (Andhra Pradesh), India.
3S.Koteswara Rao, Department of Electronics and Communication Engineering, Koneru Lakshmaiah Education Foundation, Guntur (Andhra Pradesh), India.
4Kausar Jahan, Department of Electronics and Communication Engineering, Koneru Lakshmaiah Education Foundation, Guntur (Andhra Pradesh), India.
Manuscript received on 07 April 2019 | Revised Manuscript received on 20 April 2019 | Manuscript published on 30 April 2019 | PP: 1293-1297 | Volume-8 Issue-6, April 2019 | Retrieval Number: F3808048619/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Detection and estimation of a target in motion plays an important role in tracking. In underwater object parameters such as course, range and speed is estimated by passive sonar. In this paper particle filter is combined with modified gain bearings only extended Kalman filter (PFMGBEKF) and roughening are used. Our main assumption is that the target is moving with constant velocity. Bearing measurements are nonlinear. For such nonlinear approach sub-optimal filter is Unscented Kalman Filter (UKF). But UKF is unreliable under non-Gaussian noise environment. So, Particle Filter (PF) coupled with MGBEKF is applied and the operation analysis is based on the convergence time of the solution.. Simulations are done using MATLAB.
Keyword: Bearings-only Tracking, Particle Filter, Modified Gain Bearings Only Extended Kalman Filter, Roughening.
Scope of the Article: Internet and Web Applications