A solution to the state estimation problem of systems with unmeasurable non-zero mean inputs/disturbances, which do not satisfy the disturbance decoupling conditions, is given using the Kalman filtering and Bayesian estimation theory. The proposed estimation algorithm, named Supervisory Kalman Filter (SKF), consists of a Kalman filter with an extra update step which is inspired by the particle ...

The joint state is factored into a path component and a map component in the FastSLAM framework, which reduces the computational complexity greatly. Among all the filtering solutions based on the FastSLAM framework, the particle filtering solution and the kalman filtering solution are the two most important series. Analysis of the two filtering SLAM solutions is made in this paper. And the conc...

This paper presents a core approach to design and develop a real-time based Vehicle Tracking System using Kalman filter. It is used to determine the current location of a target device in terms of UTC time , Data status, latitude, longitude, UTC date, Speed over ground in knots, Magnetic variation ,Mode indicators and Checksum information by utilizing the sms features of GSM technology. An atte...

This paper considers the problem of shear building damage estimation subject to earthquake ground excitation using the Kalman filtering approach. The structural damage is assumed to take the form of reduced elemental stiffness. Two damage estimation algorithms are proposed: one is the multiple model approach via the optimal two-stage Kalman estimator (OTSKE), and the other is the robust two-sta...