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Deep belief networks (DBN) which is an important method in deep learning has a good learning ability to get the characteristics from data. By using DBN to learn the consistency of the innovation sequence in Kalman filtering (KF), the accuracy and robustness of KF can be improved. Through the simulation of the positioning system in Automated Guided Vehicle (AGV), the new algorithm that combines KF...
Although the GNSS/GPS had become the primary source for Positioning, Navigation and Timing (PNT) information in maritime applications, the ultimate performance of the system can strongly degrade due to space weather events, deliberate interference, shadowing, multipath and overall system failures. Within the presented work the development of an affordable integrated PNT unit for future on-board integrated...
Recent technological advances in both GPS and low-cost microelectromechanical-system (MEMS)-based inertial sensors have enabled the monitoring of the location of moving platforms for numerous positioning and navigation (POS/NAV) applications. GPS is presently widely used in land vehicles. However, in some environments, the GPS signal may suffer from signal blockage and multipath effects that deteriorate...
In this article, we propose a method for improving the estimates of the absolute positions of cars. In the proposed method, each car measures its velocity, the absolute position, and the relative distance to a car in front, and uploads these measurements to a server. Using these measurements, the server computes the estimates of the cars' positions by means of the Kalman filter. This method can estimate...
This paper presents the problematic of localization under the IMM (Interacting Multiple Model) approach. The localization is often tackled under the accuracy problem. In order to achieve the goal of the assessment of an accurate ego localization, one often uses the merging of data coming from both exteroceptive and proprioceptive sensors. In our approach, we don't focuss much on the accuracy, but...
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