Stochastic stability of a modified unscented Kalman filter with stochastic nonlinearities and multiple fading measurements

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• 作者：Li Li^a ; ^{lili@ysu.edu.cn} ; Dongdong Yu^a ; ^{dongdoyu@163.com} ; Yuanqing Xia^b ; ^{xia_yuanqing@bit.edu.cn} ; Hongjiu Yang^a ; ^{yanghongjiu@ysu.edu.cn}
• 刊名：Journal of the Franklin Institute
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：354
• 期：2
• 页码：650-667
• 全文大小：783 K
• 卷排序：354

文摘

Stochastic stability of a modified unscented Kalman filter is investigated for a class of nonlinear systems with stochastic nonlinearities and multiple fading measurements. Note that the stochastic nonlinearities are represented by statistical means which indicate multiplicative stochastic disturbances. The fading probability of fading measurements is individual for each sensor. Convergence on the modified unscented Kalman filter is established if there exists a lower bound for the mean of fading probability. Sufficient conditions are obtained to ensure stochastic stability of the modified unscented Kalman filter. The effectiveness of the filtering algorithm is verified by an illustrative numerical example.