Abstract
Background/Objectives: The Extended Kalman Filter (EKF) using range and bearing measurements is analyzed for undersea target tracking. The Input estimation technique, developed by Bar-Shalom and Fortmann for radar applications is implemented for sonar applications. Methods/Statistical Analysis: Input estimation is used to estimate the target acceleration whenever the target makes a maneuver. Findings: The algorithm estimates target kinematics using zero mean chi-square distributed random sequence residual. Upon detection of target maneuver, this algorithm corrects the velocity and position components using acceleration components. Application/Improvements: Finally, the performance of this algorithm is evaluated in Monte-Carlo simulations and results conform the effectiveness of input estimation technique.
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