Results 271 to 280 of about 6,134,429 (306)

FISST-SLAM: Finite Set Statistical Approach to Simultaneous Localization and Mapping

The International Journal of Robotics Research, 2009
The solution to the problem of mapping an environment and at the same time using this map to localize (the simultaneous localization and mapping, SLAM, problem) is a key prerequisite in the synthesis of truly autonomous vehicles. By far the most common formulation of the SLAM problem is founded on a vector based stochastic framework, where the sensor ...
Bharath Kalyan, K. W. Lee, W. Sardha Wijesoma   +2 more
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Bayesian hybrid estimation of LTI networked systems using finite set statistics

2013 American Control Conference, 2013
In this paper, we develop a Bayesian approach to estimating the state and connectivity topology of a set of networked linear time invariant systems. The connectivity of the network is assumed simple, undirected and constant in time. Each node's state, in turn, is assumed to satisfy linear discrete-time dynamics corrupted by Gaussian process noise ...
Islam I. Hussein, Francesco Sorrentino 0001, Richard Scott Erwin   +2 more
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Multiple-Object Space Surveillance Tracking Using Finite-Set Statistics

Journal of Guidance, Control, and Dynamics, 2015
The dynamic tracking of objects is, in general, concerned with state estimation using imperfect data. Multiple object tracking adds the difficulty of encountering unknown associations between the collected data and the objects. State estimation of objects necessitates the prediction of uncertainty through nonlinear (in the general case) dynamical ...
Kyle J. DeMars, Islam I. Hussein, Carolin Frueh, Moriba K. Jah, R. Scott Erwin   +4 more
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Nonadditive probability, finite-set statistics, and information fusion

Proceedings of 1995 34th IEEE Conference on Decision and Control, 2002
Information fusion is the name given to military expert-systems problems. In this paper we summarize recent work proposing a fully probabilistic theoretical unification for much of information fusion based on the theory of random sets. Our approach unifies detection, localization, classification, and prior knowledge with respect to these.
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Joint Target Detection Tracking and Classification Based on Finite-Set Statistics Theory

Applied Mechanics and Materials, 2014
In traditional target tracking methods, the target number, target states and target class can not be estimated in same time. This paper investigated the joint target detection, tracking and classification method which is based on finite-set statistics theory.
Hong Wei Quan, Jun Hua Li, Xiao Juan Zhang   +2 more
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Subdimensional geo-localization from finite set statistics

SPIE Proceedings, 2013
In practical circumstances, a problem that often occurs is to geo-localize an entity from surfacelevel imagery given wide area overhead information and other a priori information that might be used to relate the two views. Given a finite set of GMTI returns and surface-level imagery of a common region of space, we propose a statistical algorithm for ...
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Finite set statistics with applications to data fusion

1995
Data fusion is concerned with the following general problem: Locate and identify objects of many different types on the basis of different kinds of evidence. The evidence is collected on an ongoing basis by many sensors having varying capabilities. Some evidence might be (i) probabilistic, e.g., estimated location with Gaussian distribution supplied by
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Advances in the Use of Finite-Set Statistics for Multitarget Tracking.

2021
Doctor of ...
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Multitarget-Multisensor Information-driven Planning via Finite Set Statistics (FISST)

2021
Recent work on information-driven sensor path planning has shown that the performance of mobile and remote sensors can be significantly improved by planning their motions based on probabilistic sensor models and the geometric characteristics of the sensor field-of-view (FOV).
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Two schemes of the random walk of the sufficient statistic of the jump process with finite set of states

Journal of Mathematical Sciences, 1998
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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