【摘 要】
：
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,
【机 构】
：
Key Laboratory of Systems and Control,Academy of Mathematics and Systems Science,Chinese Academy of
论文部分内容阅读
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 observ-ability condition by which the Lp-stability of the covariance matrix and the Lp-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.
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