logo

SCIENCE CHINA Information Sciences, https://doi.org/10.1007/s11432-020-2962-9

Stability of the Distributed Kalman Filter Using General Random Coefficients

More info

Abstract

In this paper, we propose a distributed Kalman Filter (DKF) for the dynamical system with general random coefficients. In the proposed method, each estimator shares local innovation pairs with its neighbors to collectively complete the estimation task. Further, we introduce a collective random observability condition by which the $L_p$-stability of the covariance matrix and the $L_p$-exponential stability of the homogeneous part of the estimation error equation can be established. In contrast, the stringent conditions on the coefficient matrices, such as independency and stationarity are not required. Besides, the stability of the DKF, i.e., the boundedness of the filtering errors, can be established. Finally, from the simulation result, we demonstrate the cooperative effect of the sensors.

Copyright 2020  CHINA SCIENCE PUBLISHING & MEDIA LTD.  中国科技出版传媒股份有限公司  版权所有

京ICP备14028887号-23       京公网安备11010102003388号