Application Of Statistical Estimators For Underwater Target Tracking

S. Koteswara Rao

Abstract:	In the ocean environment, two dimensional bearingsonly target motion analysis is used. An observer monitors noisy sonar bearings from a radiating target in passive listening mode, processes the measurements and finds out target motion parameters. As range measurement is not available and the bearing measurement is related to the target states, the whole process becomes non-linear. In addition, the bearing measurements are extracted from single passive sonar and the process remains unobservable, till the observer executes a proper maneuver. The author has developed Pseudo Linear Estimator, Maximum Likelihood Estimator (both in sequential approach), Modified Gain Bearings only Extended Kalman Filter, Unscented Kalman Filter. Particle Filter is at the stage of final verification of the results. The advantages and disadvantages of all these statistical filters are discussed. The results in Monte- Carlo Simulation are presented for a typical scenario.
Published in:	Proceedings of IEEE/ION PLANS 2006 April 25 - 27, 2006 Loews Coronado Resort Hotel San Diego, CA
Pages:	1040 - 1044
Cite this article:	Rao, S. Koteswara, "Application Of Statistical Estimators For Underwater Target Tracking," Proceedings of IEEE/ION PLANS 2006, San Diego, CA, April 2006, pp. 1040-1044. https://doi.org/10.1109/PLANS.2006.1650707
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