This paper is concerned with globally optimal sequential and distributed fusion estimation
algorithms in the linear minimum variance (LMV) sense for multi-sensor systems with cross …

The Kalman filter for linear systems with colored measurement noises is revisited. Besides
two well-known approaches, ie, Bryson's and Petovello's, another measurement time …

Benefiting from high mobility and robust mechanical structure, ground mobile robots are
widely adopted in the outdoor environment. The mobility of skid-steered mobile robots highly …

This paper proposes a general framework solution of Gaussian filter (GF) for both linear and
nonlinear dynamic systems with correlated noises at the same epoch. Detailed discussions …

An improved Gaussian Filter (GF) is designed for nonlinear Dynamic Positioning (DP) ships
with cross-correlated colored noises and random measurements loss. For the actual …

For the problem of multi-mode state estimation in actual train operation, this paper proposes
a nonlinear non-gaussian high-precision parallel Kalman filter group (NN-HEKFG) …

Robust autonomy stacks require tight integration of perception, motion planning, and control
layers, but these layers often inadequately incorporate inherent perception and prediction …

The Kalman filtering (KF) is optimal under the assumption that both process and observation
noises are independent white Gaussian noise. However, this assumption is not always …

This study presents the distributed fusion estimation of discrete-time Markovian jump linear
systems with random parameter matrices and cross-correlated noises in sensor networks …

The velocity of the odometer (OD) and Doppler velocity log (DVL) is easily contaminated by
non-Gaussian noise, and the prior information of the state vector is usually hard to estimate …