Successful implementation of many control strategies is mainly based on accurate
knowledge of the system and its parameters. Besides the stochastic nature of the systems …

The vehicle dynamic state is essential for stability control and decision-making of intelligent
vehicles. However, these states cannot usually be measured directly and need to be …

Monostatic and bistatic position and Doppler measurements used in radar and sonar
systems are nonlinear transformations of a Cartesian state. These nonlinearities pose a …

In this work, we developed a framework for identifying frame-type structures regarding the
measurement uncertainty and the uncertainty involved in inherent and structural parameters …

This paper presents two new trajectory probability hypothesis density (TPHD) and trajectory
cardinality probability hypothesis density (TCPHD) filters for joint tracking and classification …

This thesis presents a new estimation strategy called the lattice Kalman filter (LKF) which is
based on the nonlinear Kalman filtering framework and lattice rules. The proposed LKF …

This paper proposes a new jitter reduction scheme based on double exponential smoothing
(DES). We compare this DES-based method to jitter reduction methods based on the …

The uncertain disturbance in the system signals can lead to biased state estimates and, in
turn, can lead to deterioration in the performance of state estimation for a nonlinear dynamic …

The paper presents a fault-tolerant multi-sensor fusion approach with Fault Detection and
Exclusion (FDE) based on information theory. The Maximum Correntropy Criterion (MCC) in …

A combination of a robust optimality criterion, the Maximum Correntropy Criterion (MCC),
and a powerful Fault Detection and Exclusion (FDE) strategy for a robust and fault-tolerant …