Swarm Intelligence Based Tuning of Extended Kalman Filter for Manoeuvring Target Tracking
نویسنده
چکیده
Abstract: Kalman filter is a well known adaptive filtering Algorithm, widely used for target tracking applications. When the system model and measurements are non linear, variation of Kalman filter like extended Kalman filter (EKF) is used. For obtaining reliable estimate of the target state, filter has to be tuned before the operation (off line).Tuning an EKF is the process of estimation of the noise covariance matrices from process data [1]. In practical applications, due to unavailable measurements of the process noise and high dimensionality of the problem tuning of the filter is left for engineering intuition. In this paper, tuning of the EKF is investigated using Particle Swarm Optimization (PSO). The simulation results show the superiority of the PSO tuned EKF over the conventional EKF.
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