An Improved Adaptive Noise Estimation in Kalman Filtering
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Graphical Abstract
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Abstract
An Improved weighted least square method is proposed to estimate the noise statistics Q and R from the sub-optimal estimation by incorporating the autocorrelation functions of the innovation, determine the weight, deduce the optimal gain and finally get the noise statistics. The deduction of Q is also simplified. The simulation result shows the estimation has better convergence rate and precision.
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