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