supported by the National Natural Science Foundation of China(No.61271317);the Aerospace Sci.&Tech.Foundation(No.15GFZ-JJ02-07)
Focusing on the problem of state estimation in the presence of sensor faults and Out-of-sequence measurement(OOSM)observations synchronously,we derive a formulation of Linear minimum mean squared error(LMMSE)filter wi...
This work is supported by the National Natural Science Foundation of China (No.60934009, No.60804064, No.60572051), China Postdoctoral Science Foundation (No.YK 2008061), Project of Science and Technology Department of Zhejiang Province (No.2009C34016), and Zhejiang Graduate Innovation Project (No.YK.2008061).
This paper considers the design of universal delayed Kalman filter for the networked tracking system with arbitrary random delay. Firstly, an equivalent Weighted summation form of the conventional Kalman filter (WSFK...