This paper describes the implementation of an intelligent navigation system, based on the
integrated use of the global positioning system (GPS) and several inertial navigation system …

Presents a method for sensor fusion based on adaptive fuzzy Kalman filtering. The method
is applied in fusing position signals from Global Positioning Systems (GPS) and inertial …

Presents a method of sensor fusion based on adaptive fuzzy Kalman filtering. This method
has been applied to fuse position signals from the Global Positioning System (GPS) and …

Modern autonomous underwater vehicles (AUVs) are currently involved in complex tasks
and scenarios, and require accurate and robust navigation systems to estimate their …

Robust and performing navigation systems for Autonomous Underwater Vehicles (AUVs)
play a discriminant role towards the success of complex underwater missions involving one …

In the conventional integrated navigation systems, such as direct Kalman filter, the statistical
information of the process and measurement noises is considered constant. In real …

Most of the present navigation systems rely on Kalman filtering to fuse data from global
positioning system (GPS) and the inertial navigation system (INS). In general, INS/GPS …

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 …

The Kalman filter (KF) is a form of optimal estimator characterized by recursive evaluation,
which has been widely applied to the navigation sensor fusion. Utilizing the KF requires that …

When considering the working conditions under which an unmanned surface vehicle (USV)
operates, the navigational sensors, which already have inherent uncertainties, are subjected …