Adaptive filters for two-dimensional target tracking Online publication date: Mon, 22-May-2023
by Manav Kumar; Sharifuddin Mondal
International Journal of Space Science and Engineering (IJSPACESE), Vol. 6, No. 4, 2023
Abstract: In this work, well known existing estimation algorithms like extended Kalman filter (EKF) and unscented Kalman filter (UKF) with different adaptive extensions are implemented on target tracking problem for passive tracking. To deal with model uncertainty and uncertain noises, the process and measurement noise covariances are adapted based on innovation and residual sequences. Different adaptation rules for adjusting the noise covariance are examined. For the robustness performance analysis of each algorithm, target loss that occurred at last time of simulation is accounted for with consideration of a 2% estimation error. The effectiveness of filter performance is evaluated on the basis of root mean square error, average target loss and relative computational time with Monte Carlo simulation. Simulation results demonstrate that adaptive version of traditional filters have improved tracking performance with a significant computational burden in terms of estimation accuracy and track loss.
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