| 1. |
- Arkkä, A. S., et al.
(författare)
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On the relation between Gaussian process quadratures and sigma-point methods
- 2016
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Ingår i: Journal of Advances in Information Fusion. - 1557-6418. ; 11:1, s. 31-46
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Tidskriftsartikel (refereegranskat)abstract
- This article is concerned with Gaussian process quadratures, which are numerical integration methods based on Gaussian process regression methods, and sigma-point methods, which are used in advanced non-linear Kalman filtering and smoothing algorithms. We show that many sigma-point methods can be interpreted as Gaussian process quadrature based methods with suitably selected covariance functions. We show that this interpretation also extends to more general multivariate Gauss-Hermite integration methods and related spherical cubature rules. Additionally, we discuss different criteria for selecting the sigma-point locations: exactness of the integrals of multivariate polynomials up to a given order, minimum average error, and quasi-random point sets. The performance of the different methods is tested in numerical experiments.
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| 2. |
- Arnborg, Stefan, 1945-
(författare)
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Robust Bayesianism : Relation to Evidence Theory
- 2006
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Ingår i: Journal of Advances in Information Fusion. - : International Society of Information Fusion (ISIF). - 1557-6418. ; 1:1, s. 75-90
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Tidskriftsartikel (refereegranskat)abstract
- We are interested in understanding the relationship between Bayesian inference and evidence theory. The concept of a set of probability distributions is central both in robust Bayesian analysis and in some versions of Dempster-Shafer’s evidence theory. We interpret imprecise probabilities as imprecise posteriors obtainable from imprecise likelihoods and priors, both of which are convex sets that can be considered as evidence and represented with, e.g., DS-structures. Likelihoods and prior are in Bayesian analysis combined with a place’s parallel composition. The natural and simple robust combination operator makes all pairwise combinations of elements from the two sets representing prior and likelihood. Our proposed combination operator is unique, and it has interesting normative and factual properties. We compare its behavior with other proposed fusion rules, and earlier efforts to reconcile Bayesian analysis and evidence theory. The behavior of the robust rule is consistent with the behavior of Fixsen/Mahler’s modified Dempster’s (MDS) rule, but not with Dempster’s rule. The Bayesian framework is liberal in allowing all significant uncertainty concepts to be modeled and taken care of and is therefore a viable, but probably not the only, unifying structure that can be economically taught and in which alternative solutions can be modeled, compared and explained.
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| 3. |
- Brynielsson, Joel, 1974-, et al.
(författare)
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An Information Fusion Game Component
- 2006
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Ingår i: Journal of Advances in Information Fusion. - 1557-6418. ; 1:2, s. 108-121
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Tidskriftsartikel (refereegranskat)abstract
- Higher levels of the data fusion process call for prediction and awareness of the development of a situation. Since the situations handled by command and control systems develop by actions performed by opposing agents, pure probabilistic or evidential techniques are not fully sufficient tools for prediction. Game-theoretic tools can give an improved appreciation of the real uncertainty in this prediction task, and also be a tool in the planning process. Based on a combination of graphical inference models and game theory, we propose a decision support tool architecture for command and control situation awareness enhancements.This paper outlines a framework for command and control decision-making in multi-agent settings. Decision-makers represent beliefs over models incorporating other decision-makers and the state of the environment. When combined, the decision-makers’ equilibrium strategies of the game can be inserted into a representation of the state of the environment to achieve a joint probability distribution for the whole situation in the form of a Bayesian network representation.
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| 4. |
- Granström, Karl, 1981, et al.
(författare)
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Extended OBJECT TRACKING: Introduction, overview, and applications
- 2017
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Ingår i: Journal of Advances in Information Fusion. - 1557-6418. ; 12:2, s. 139-174
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Tidskriftsartikel (refereegranskat)abstract
- This article provides an elaborate overview of current research in extended object tracking. We provide a clear definition of the extended object tracking problem and discuss its delimitation to other types of object tracking. Next, different aspects of extended object modelling are extensively discussed. Subsequently, we give a tutorial introduction to two basic and well used extended object tracking approaches-the random matrix approach and the Kalman filter-based approach for star-convex shapes. The next part treats the tracking of multiple extended objects and elaborates how the large number of feasible association hypotheses can be tackled using both Random Finite Set (RFS) and Non-RFS multi-object trackers. The article concludes with a summary of current applications, where four example applications involving camera, X-band radar, light detection and ranging (LIDAR), and red-green-blue-depth (RGB-D) sensors are highlighted.
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| 5. |
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| 6. |
- Johansson, Fredrik, et al.
(författare)
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Real-time Allocation of Firing Units To Hostile Targets
- 2011
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Ingår i: Journal of Advances in Information Fusion. - : ISIF, International Society of Information Fusion. - 1557-6418. ; 6:2, s. 187-199
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Tidskriftsartikel (refereegranskat)abstract
- The protection of defended assets such as military bases and population centers against hostile targets (e.g., aircrafts, missiles, and rockets) is a highly relevant problem in the military conflicts of today and tomorrow. In order to neutralize threats of this kind, they have to be detected and engaged before causing any damage to the defended assets. We review algorithms for solving the resource allocation problem in real-time, and empirically investigate their performance using the open source testbed SWARD. The reults show that many of the tested algorithms produce high quality solutions for small-scale problems. A novel vaiant of particle swarm optimization seeded with an enhanced greedy algorithm is described and is shown to perform best for large instances of the real-time allocation problem.
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| 7. |
- Karlsson, Alexander, et al.
(författare)
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Characterization and Empirical Evaluation of Bayesian and Credal Combination Operators
- 2011
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Ingår i: Journal of Advances in Information Fusion. - : ISIF, International Society of Information Fusion. - 1557-6418. ; 6:2, s. 150-166
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Tidskriftsartikel (refereegranskat)abstract
- We address the problem of combining independent evidences from multiple sources by utilizing the Bayesian and credal combination operators. We present measures for degree of conflict and imprecision, which we use in order to characterize the behavior of the operators through a number of examples. We introduce discounting operators that can be used whenever information about the reliability of sources is available. The credal discounting operator discounts a credal set with respect to an interval of reliability weights, hence, we allow for expressing reliability of sources imprecisely. We prove that the credal discounting operator can be computed by using the extreme points of its operands. We also perform two experiments containing different levels of risk where we compare the performance of the Bayesian and credal combination operators by using a simple score function that measures the informativeness of a reported decision set. We show that the Bayesian combination operator performed on centroids of operand credal sets outperforms the credal combination operator when no risk is involved in the decision problem. We also show that if a risk component is present in the decision problem, a simple cautious decision policy for the Bayesian combination operator can be constructed that outperforms the corresponding credal decision policy.
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| 8. |
- Roth, Michael, 1984-, et al.
(författare)
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Nonlinear Kalman Filters Explained: A Tutorial on Moment Computations and Sigma Point Methods
- 2016
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Ingår i: Journal of Advances in Information Fusion. - : International society of information fusion. - 1557-6418. ; 11:1, s. 47-70
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Tidskriftsartikel (refereegranskat)abstract
- Nonlinear Kalman filters are algorithms that approximately solve the Bayesian filtering problem by employing the measurement update of the linear Kalman filter (KF). Numerous variants have been developed over the past decades, perhaps most importantly the popular sampling based sigma point Kalman filters.In order to make the vast literature accessible, we present nonlinear KF variants in a common framework that highlights the computation of mean values and covariance matrices as the main challenge. The way in which these moment integrals are approximated distinguishes, for example, the unscented KF from the divided difference KF.With the KF framework in mind, a moment computation problem is defined and analyzed. It is shown how structural properties can be exploited to simplify its solution. Established moment computation methods, and their basics and extensions, are discussed in an extensive survey. The focus is on the sampling based rules that are used in sigma point KF. More specifically, we present three categories of methods that use sigma-points 1) to represent a distribution (as in the UKF); 2) for numerical integration (as in Gauss-Hermite quadrature); 3) to approximate nonlinear functions (as in interpolation). Prospective benefits and downsides are listed for each of the categories and methods, including accuracy statements. Furthermore, the related KF publications are listed.The theoretical discussion is complemented with a comparative simulation study on instructive examples.
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| 9. |
- Vivone, G., et al.
(författare)
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Converted measurements Bayesian extended target tracking applied to x-band marine radar data
- 2017
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Ingår i: Journal of Advances in Information Fusion. - 1557-6418. ; 12:2, s. 189-210
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Tidskriftsartikel (refereegranskat)abstract
- X-band marine radar systems are flexible and low-cost tools for monitoring multiple targets in a surveillance area. They can provide high resolution measurements both in space and time. Such features offer the opportunity to get accurate information not only about the target kinematics, as other conventional sensors, but also about the target size. In this paper we exploit the random matrix framework to track extended targets. Proper measurement models to deal with the radar’s measurement noise and its conversion into Cartesian coordinates are presented here. Benefits of the proposed extended target tracking using converted measurements can be mainly related to the problem of the targets’ size estimation, while advantages on estimation of the targets’ kinematic features can be considered negligible. The validity of the proposed approach has been demonstrated by using both simulated and real data. Gains up to 70% for the targets’ width estimation accuracy and around 65% for the length are observed on real data. The integration of the proposed model into the gamma Gaussian inverse Wishart probability hypothesis density tracker is also provided and tested on real data.
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| 10. |
- Xia, Yuxuan, 1993, et al.
(författare)
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Multiscan implementation of the trajectory poisson multi-Bernoulli mixture filter
- 2019
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Ingår i: Journal of Advances in Information Fusion. - 1557-6418. ; 14:2, s. 213-235
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Tidskriftsartikel (refereegranskat)abstract
- The Poisson multi-Bernoulli mixture (PMBM) and the multi-Bernoulli mixture (MBM) are two multitarget distributions for which closed-form filtering recursions exist. The PMBM has a Poisson birth process, whereas the MBM has a multi-Bernoulli birth process. This paper considers a recently developed formulation of the multitarget tracking problem using a random finite set of trajectories, through which the track continuity is explicitly established. A multiscan trajectory PMBM filter and a multiscan trajectory MBM filter, with the ability to correct past data association decisions to improve current decisions, are presented. In addition, a multiscan trajectory MBM01 filter, in which the existence probabilities of all Bernoulli components are either 0 or 1, is presented. This paper proposes an efficient implementation that performs track-oriented N-scan pruning to limit computational complexity, and uses dual decomposition to solve the involved multiframe assignment problem. The performance of the presented multitarget trackers, applied with an efficient fixed-lag smoothing method, is evaluated in a simulation study.
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