R
Richard L. Moose
Researcher at Virginia Tech
Publications - 18
Citations - 774
Richard L. Moose is an academic researcher from Virginia Tech. The author has contributed to research in topics: Kalman filter & Tracking system. The author has an hindex of 10, co-authored 18 publications receiving 767 citations.
Papers
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Modeling andEstimation for Tracking Maneuvering Targets
TL;DR: Preliminary testing with actual radar measurements indicates both improved tracking accuracy and increased filter stability in response to rapid target accelerations in elevation, bearing, and range.
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Modeling and Estimation for Tracking Maneuvering Targets
TL;DR: In this paper, a new approach to the three-dimensional airborne maneuvering target tracking problem is presented, which combines the correlated acceleration target model of Singer [3] with the adaptive semi-Markov maneuver model of Gholson and Moose [8].
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Maneuvering Target Tracking Using Adaptive State Estimation
TL;DR: Two approaches to a nonlinear state estimation problem of tracking a maneuvering target in three-dimensional space using spherical observations (radar data) rely on semi-Markov modeling of target maneuvers and result in effective algorithms that prevent the loss of track when a target makes a sudden, radical change in its trajectory.
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Digital Control of High Performance Aircraft Using Adaptive Estimation Techniques
TL;DR: In this paper, an adaptive signal processing algorithm is combined with gain-scheduling to produce an effective scheme for controlling the dynamics of high performance aircraft, where the actual controller views the nonlinear behavior of the aircraft as being equivalent to a randomly switching sequence of linear models taken from a preliminary piecewise-linear fit of the system nonlinearities.
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A modified Gaussian sum approach to estimation of non-Gaussian signals
M.J. Caputi,Richard L. Moose +1 more
TL;DR: A modified Gaussian sum estimation algorithm using an adaptive filter is developed that avoids the growing memory problem of the previous algorithm while providing effective state estimation.