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The estimation of a vehiclepsilas dynamic state is one of the most fundamental data fusion tasks for intelligent traffic applications. For that, motion models are applied in order to increase the accuracy and robustness of the estimation. This paper surveys numerous (especially curvilinear) models and compares their performance using a tracking tasks which includes the fusion of GPS and odometry data...
A computationally efficient, grid-based estimation method is presented for multiple source identification from distributed sensor data. Under the assumption that the sources are located on a grid over the region of interest, the solution to the problem of multiple source identification, that is, estimation of the number, locations, and intensities of the sources, is represented by a large sparse vector...
In this paper, a scaled unscented Kalman filter (SUKF) based on the quaternion concept is designed for integrating inertial navigation system (INS) aided by GPS measurements under large attitude error conditions. In this feedback filter, only the bias effects are considered to be independent states and are used to compensate for navigation errors. To preserve the nonlinear nature of the unit quaternion,...
In the future, the American GPS and the European Galileo Satellite Systems together will offer around 60 satellites for positioning and navigation. Despite technical differences between these two systems, the commonality of the center frequencies they use creates the potential to develop an interoperable navigation satellite receiver. Firstly, we evaluate the performance of both systems separately...
Aiming at naval cooperative engagement problem, a decentralized fusion architecture based on geodetic coordinate system is presented. To increase the performance of maneuvering target tracking and fusion four efforts are made. Firstly, a more appropriate multiple model method is used in describing movement properties of the maneuvering warship, Secondly, the Unscented Kalman filter in an interacting...
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