Globally Optimal Multisensor Distributed Random Parameter Matrices Kalman Filtering Fusion with Applications

Globally Optimal Multisensor Distributed Random Parameter Matrices Kalman Filtering Fusion with Applications

This paper proposes a new distributed Kalman filtering fusion with random state transition and measurement matrices, i.e., random parameter matrices Kalman filtering. It is proved that under a mild condition the fused state estimate is equivalent to the centralized Kalman filtering using all sensor measurements; therefore, it achieves the best performance. More importantly, this result can be a...

Applications of Random Parameter Matrices Kalman Filtering in Uncertain Observation and Multi-Model Systems

This paper considers the Linear Minimum Variance recursive state estimation for the linear discrete time dynamic system with random state transition and measurement matrices, i.e., random parameter matrices Kalman filtering. It is shown that such system can be converted to a linear dynamic system with deterministic parameter matrices but state-dependent process and measurement noises. It is pro...

On Kalman Filtering for Conditionally Gaussian Systems with Random Matrices

The optimality for the distributed Kalman filtering fusion with feedback

A rigorous performance analysis is dedicated to the distributed Kalman "ltering fusion with feedback for distributed recursive state estimators of dynamic systems. It is shown that the Kalman "ltering track fusion formula with feedback is, like the track fusion without feedback, exactly equivalent to the corresponding centralizedKalman "ltering formula. Moreover, the so-calledPmatrices in the f...

Improved Vehicle Parameter Estimation Using Sensor Fusion by Kalman Filtering

− Within several applications concerning the improvement of vehicle safety, accurate systems for determination of position, velocity and acceleration are useful. We present a system for accurate determination of these parameters using a sensor fusion technique. The main focus is on how GPS carrier phase data and accelerometer data are modeled and integrated in a Kalman filter that provides both...