Results 211 to 220 of about 1,871 (255)

On Tracking a Maneuvering Target in Clutter

IEEE Transactions on Aerospace and Electronic Systems, 1984
A new technique for tracking a maneuvering target in a cluttered environment is developed. This approach does not rely on a statistical description of the maneuver as a random process. Instead, the state model for the target is changed when a maneuver is detected.
K. Birmiwal, Y. Bar-Shelom
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Adaptive tracking of maneuvering targets

IEEE Transactions on Automatic Control, 1968
A means is suggested heuristically by which Kalman sequential estimation can be made adaptive to target maneuvers without the sacrifice of tracking accuracy in the nonmaneuvering portions of a trajectory. The adaptation requires backsliding in the gain schedule and reprocessing of the most recent several measurements.
J. Demetry, H. Titus
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Auxiliary particle filters for tracking a maneuvering target

Proceedings of the 39th IEEE Conference on Decision and Control (Cat. No.00CH37187), 2002
We consider the recursive state estimation of a highly maneuverable target. We apply optimal recursive Bayesian filters directly to the nonlinear target model. We present novel sequential simulation based algorithms developed explicitly for the maneuvering target tracking problem.
Rickard Karlsson, Niclas Bergman
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Particle filters for maneuvering target tracking problem

Signal Processing, 2006
In this paper, we address the target tracking problem for the case of maneuvering target, including single target and multiple target tracking. We propose a suitable model to characterize the maneuvering acceleration and develop a state space model to describe the maneuvering target tracking problem.
Yihua Yu, QianSheng Cheng
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Ensemble of KalmanNets for Maneuvering Target Tracking

2024 27th International Conference on Information Fusion (FUSION)
Tracking a maneuvering target requires the modeling of the target's movements by multiple pre-defined mathematical models. However, the uncertainty in the target's dynamics can lead traditional model-based (MB) tracking algorithms to significant performance degradation when model mismatch occurs.
Mari M., Snidaro L.
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Hierarchical Dirichlet processes for tracking maneuvering targets

2007 10th International Conference on Information Fusion, 2007
We consider the problem of state estimation for a dynamic system driven by unobserved, correlated inputs. We model these inputs via an uncertain set of temporally correlated dynamic models, where this uncertainty includes the number of modes, their associated statistics, and the rate of mode transitions.
Emily B. Fox, Erik B. Sudderth, Alan S. Willsky   +2 more
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Passive tracking of a maneuvering target: an adaptive approach

IEEE Transactions on Signal Processing, 1994
The problem of target tracking using passive sensors is examined. The target is assumed to execute maneuvers at times unknown to the observer. An adaptive algorithm, which takes into account such maneuvers, is derived using the multimodel partitioning approach.
Sokratis K. Katsikas, Assimakis K. Leros, Demetrios G. Lainiotis   +2 more
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Passive depth tracking of underwater maneuvering targets

IEEE Transactions on Acoustics, Speech, and Signal Processing, 1985
As a parallel extension to the adaptive range tracking of underwater targets described by Moose and Dailey [1], this paper discusses the problem of tracking the depth of a maneuvering target using passive time-delay measurements. The target is free to maneuver in velocity and make random depth changes at times unknown to the observer.
Richard L. Moose, P. M. Godiwala
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A guidance law for visual tracking of a maneuvering target

2006 American Control Conference, 2006
This paper presents an adaptive disturbance rejection control architecture for a flying vehicle to track a maneuvering target using a monocular camera as a visual sensor. The derived guidance law is an acceleration command for the follower and enures range regulation with desired precision. Simulations illustrate the performance of the method.
Vahram Stepanyan, Naira Hovakimyan
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IMMGNNF with visibility for multiple maneuvering target tracking

2016 IEEE International Conference on Digital Signal Processing (DSP), 2016
In this paper, we develop the Interacting Multiple Model (IMM) estimator using the constant velocity, constant acceleration and coordinated turn model set with Global Nearest Neighbour (GNN) filter to track multiple maneuvering targets. The performance of this IMMGNN filter is further enhanced by incorporating a recursion of the probability of target ...
Madeleine G. Sabordo, Elias Aboutanios
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