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Robust estimation algorithm based on prior probability statistics
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DOI：10.1002/rnc.5724.png)
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Abstract
En 中文
For the nonlinear systems with uncertain system parameters, based on the recursive linear minimum variance estimation framework, the effect of the system parameters on the mean squared error (MSE) is analyzed, that is, the greater the system parameters deviation (whether they are positive or negative deviation) is, the greater the MSE is. Based on the analysis results and prior probability statistics (probability distributions or sampling distributions), an innovative robust estimation algorithm is proposed for nonlinear systems with uncertain system parameters. Three examples verify the effectiveness of the proposed algorithm.
Keywords:
mean squared error
nonlinear filter
recursive linear minimum variance estimation
robust estimation
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