The application of soft computing techniques can be largely found in engineering sciences.
These include the design and optimization of navigation systems for use in land, sea, and air …

This paper presents two adaptive Kalman filters (KFs) for nonlinear model updating where,
in addition to nonlinear model parameters, the covariance matrix of measurement noise is …

Recently, multi-sensor navigation has emerged as a viable approach in autonomous
vehicles' development. Kalman filtering has been widely applied in multi-sensor data fusion …

In this study, both adaptive and robust one is proposed, considering that the properties of a
classic unscented Kalman filter (UKF) can be degraded severely by the outliers measured in …

The integrated navigation system is the inertial navigation system (INS), corrected by global
navigation satellite system (GNSS) data. The correction could be done algorithmically by …

This article introduces an augmented adaptive unscented Kalman filter (KF). The proposed
novel technique is suitable to simultaneously estimate both the diagonal process noise …

Autonomous underwater vehicle (AUV) acoustic navigation is challenged by unknown
system noise and gross errors in the acoustic observations caused by the complex marine …

One of the most significant challenges in the underwater domain is to retrieve the
autonomous underwater vehicle (AUV) position within the surrounding environment. Indeed …

Robust and reliable 3D multi-object tracking (MOT) is essential for autonomous driving in
crowded urban road scenes. In those scenarios, accurate data association between tracked …

In order to mitigate the interference of impulsive noises in the identification of Wiener-type
nonlinear systems using traditional spline adaptive filter (SAF) algorithm, an enhanced SAF …