Adaptive Target Tracking by Noise-Estimated Particle filter
نویسندگان
چکیده
This paper proposes a new radar tracking filter named Noise-estimate Particle Filter (NPF). Kalman filter and particle filter are popular filtering techniques for target tracking. The tracking performance of the Kalman filter severely depends on the setting of several parameters such as system noise and observation noise. However, it is an open problem how to choose proper parameters for various scenarios, and they are often regulated in trial-and-error manner. The proposed filter estimates proper noise parameters of a Kalman filter on-line based on a scheme of particle filter. Simulation results show that the proposed filter has higher tracking performance in various scenarios than conventional Kalman filter and particle filter.
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