AUTHORS: Hao Li, Yongwei Gu, Shumei Guo, Guochao Zhang

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ABSTRACT: In this paper, the ill-conditioning diagnosis and processing of Kalman filter are combined. First, the ill-conditioning of Kalman filter and the disadvantage of ridge-type Kalman filter are analyzed. Then t he signal-to-noise ratio(SNR) statistic is introduced to measure how much each parameter suffers from the ill-conditioning. Accordingly, all parameters are divided into two parts, named involved parameters and n on-involved parameters respectively. Then, the two parts of parameters are corrected with two ridge para meters of different size. This method is named double-parameter ridge-type Kalman filter and can reduce the bias introduced in ridge-type Kalman filter while reducing the variance of the state parameter estimati on. Combined with the idea of generalized ridge estimation, the selection method of two ridge parameters are given. Finally, the example illustrates the new algorithm can effectively overcome the influence of th e ill-condition on Kalman filter and the reduce the bias in ridge-type Kalman filter, which improves the a ccuracy of the estimates of parameters.

KEYWORDS: Kalman filter; ill-conditioning; double-parameter ridge estimation; signal-to-noise ratio

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