In this paper, the problem of target tracking with glint noise is considered. We apply a radial basis function (RBF) neural network to evaluate the nonlinear score function, which is used as the correction term in the state estimation of robust Kalman filter. Simulation results are presented to demonstrate the performance of the evaluation of the score function.
Target tracking with glint noise using an RBF neural network
1996-01-01
326176 byte
Conference paper
Electronic Resource
English
Target Tracking with Glint Noise Using an RBF Neural Network
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