Target Type Tracking with PCR5 and Dempster's rules: A Comparative Analysis

Dezert, Jean; Tchamova, Albena; Smarandache, Florentín; Konstantinova, Pavlina

doi:10.1109/icif.2006.301556

Cited by 28 publications

(12 citation statements)

References 4 publications

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“…Beginning in 2005, efforts were made to extend traditional DS tracking methods [39] to that of advanced techniques using the proportional conflict redistribution rule (PCR5) [40]. Other tracking methods included multisensor [41], activity analysis [42], and out-of-sequence methods [43].…”

Section: Tracking Methods Using Dempster-shafer Theorymentioning

confidence: 99%

Overview of Dempster-Shafer and belief function tracking methods

Blasch

Dezert²,

Pannetier³

2013

SPIE Proceedings

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Over the years, there have been many proposed methods in set-based tracking. One example of set-based methods is the use of Dempster-Shafer (DS) techniques to support belief-function (BF) tracking. In this paper, we overview the issues and concepts that motivated DS methods for simultaneous tracking and classification/identification. DS methods have some attributes, if applied correctly; but there are some pitfalls that need to be carefully avoided such as the redistribution of the mass associated with conflicting measurements. Such comparisons and applications are found in Dezert-Smarandache Theory (DSmT) methods from which the Proportional Conflict Redistribution (PCR5) rule supports a more comprehensive approach towards applying evidential and BF techniques to target tracking. In the paper, we overview two decades of research in the area of BF tracking and conclude with a comparative analysis of Bayesian, Dempster-Shafer, and the PCR5 methods.

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Section: Tracking Methods Using Dempster-shafer Theorymentioning

confidence: 99%

Overview of Dempster-Shafer and belief function tracking methods

Blasch

Dezert²,

Pannetier³

2013

SPIE Proceedings

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“…This highlights the importance high conflict can have on belief assignment when DS is applied. [11]. 2) Reliability Discounting: In Tables VI and VII we present results obtained when the reliability discounting technique is implemented with the combination rules approaches Dempster-Shafer and PCR5 respectively.…”

Section: B Implementation Of Scenariomentioning

confidence: 99%

Information fusion and discounting techniques for decision support in Aerospace

Browne

Jin

Bell

et al. 2012

IEEE 10th International Conference on Industrial Informatics

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Decision makers are required to make critical decisions throughout all stages of a life-cycle in large-scale projects. These decisions are important as they impact upon the outcome and the success of projects. In this paper we present an evidential reasoning framework to aid decision-makers in the decision making process. This approach utilizes the Dezert-Smarandache Theory (DSm) to fuse heterogeneous evidence sources that suffer from levels of uncertainty, imprecision and conflicts to provide beliefs for decision options. To analyze the impact that source reliability and priority has upon the decision making process a reliability discounting technique along with a priority discounting technique are applied. Application of the evidential reasoning framework is illustrated using a Case Study based in the Aerospace domain.

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“…In classical/quantitative DSmT framework, the Proportional Conflict Redistribution rule no. 5 (PCR5) has been proven to provide very good and coherent results for combining (quantitative) belief masses [32,19,9]. When dealing with qualitative beliefs and using Dempster-Shafer Theory (DST), we unfortunately can not normalize, since it is not possible to divide linguistic labels by linguistic labels.…”

Section: Qualitative Pcr5 Rule (Q-pcr5)mentioning

confidence: 99%

“…Ronald Yager suggested in his rule to transfer the total conflicting mass to the total ignorance instead using normalization as with Dempster's rule 9. Indeed (DP) rule has been developed for static fusion only while (DSmH) has been developed to take into account the possible dynamicity of the frame itself and also its associated model.…”

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confidence: 99%

Introduction to the Fusion of Quantitative and Qualitative Beliefs

Dezert¹,

Smarandache²

2006

ISIJ

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The efficient management and combination of uncertain and conflicting sources of information remain of primal importance for the development of reliable information fusion systems. Advanced fusion systems must deal both with quantitative and qualitative aspects of beliefs expressed by the different sources of information (sensors, expert systems, human reports, etc). This paper introduces the theory of plausible and paradoxical reasoning, known as DSmT (Dezert-Smarandache Theory) in literature, developed originally for dealing with imprecise, uncertain and potentially highly conflicting sources of information providing quantitative beliefs on a given set of possible solutions of a given problem. We also propose in this paper new ideas on a possible extension of DSmT for the combination of uncertain and conflicting qualitative information in order to deal directly with beliefs expressed with linguistic labels instead of numerical values to be closer to the nature of information expressed in natural languages and available directly from human experts.

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Target Type Tracking with PCR5 and Dempster's rules: A Comparative Analysis

Cited by 28 publications

References 4 publications

Overview of Dempster-Shafer and belief function tracking methods

Overview of Dempster-Shafer and belief function tracking methods

Information fusion and discounting techniques for decision support in Aerospace

Introduction to the Fusion of Quantitative and Qualitative Beliefs

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