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检索条件"任意字段=Sensor Fusion: Architectures, Algorithms and Applications II"

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Impact of expanding the multiplicity of information sources on fusion system architecture and fusion logic options

Impact of expanding the multiplicity of information sources ...

引用

Conference on Multisensor, Multisource Information fusion - architectures, algorithms and applications 2003

作者： Dasarathy, BV

ISBN: (纸本)0819449598

Various fusion system architectures postulated and studied previously for environments with two and three data sources are further explored in this study to bring out the expanding scope for delineating the architecture options for multiple data source environments. A spectrum of single and multi-stage fusion architecture options are defined. The potential for such expansion of choices is illustrated using the scenario with four data sources as an example. Potential problem environments corresponding to this range of two to four data sources are identified. Various fusion logic strategies that can be brought to bear for the analysis of these fusion architecture options, when these fusion architectures are employed for Decisions In - Decision Out (DEI-DEO) fusion, are also discussed.

关键词： sensor fusion decision fusion fusion strategies multi-sensor suites

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A simple test-bed for real-time sensor-to-shooter applications of decentralised data fusion

A simple test-bed for real-time sensor-to-shooter applicatio...

引用

Conference on Multisensor, Multisource Information fusion - architectures, algorithms and applications 2003

作者： Binns, L Cooke, A Fryers, S Greenway, P Mullin, D Nicholson, D Valachis, D BAE Syst Adv Technol Ctr Bristol BS34 7QW Avon England

ISBN: (纸本)0819449598

In this paper we describe a simple physical test-bed, developed to allow practical experimentation in the use of Decentralised Data fusion (DDF) in sensor-to-shooter applications. Running DDF over an ad hoc network of distributed sensors produces target location information. This is used to guide a Leica laser-tracker system to designate currently tracked targets. We outline how the system is robust to network and/or node failure. Moreover, we discuss the system properties that lead to it being completely "plug-and-play", as, like the distributed sensor nodes, the "shooter" does not require knowledge of the overall network topology and can connect at any point.

关键词： data fusion network centric warfare ad-hoc networks sensor-to-shooter

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Multi-sensor fusion using an adaptive multi-hypothesis tracking algorithm

Multi-sensor fusion using an adaptive multi-hypothesis track...

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Conference on Multisensor, Multisource Information fusion - architectures, algorithms and applications 2003

作者： Kester, LJHM TNO Phys & Elect Lab NL-2509 JG The Hague Netherlands

ISBN: (纸本)0819449598

The purpose of a tracking algorithm is to associate data measured by one or more (moving) sensors to moving objects in the environment. The state of these objects that can be estimated with the tracking process depends on the type of data that is provided by these sensors. It is discussed how the tracking algorithm can adapt itself, depending on the provided data, to improve data association. The core of the tracking algorithm,is an extended Kalman filter using multiple hypotheses for contact to track association. Examples of various sensor suites of radars, electro-optic sensors and acoustic sensors are presented.

关键词： sensor fusion tracking data association MHT

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Recursive algorithm of the optimal estimation fusion

Recursive algorithm of the optimal estimation fusion

引用

Multisensor. Multisource Information fusion: architectures, algorithms, and applications 2003

作者： Zhou, Jie Zhu, Yunmin College of Mathematics Sichuan University Chengdu Sichuan 610064 China

In a distributed estimation or tracking system, the global estimate are generated by the local estimates. Under the assumption of independence cross sensor noises, Bar-shalom proposed a two sensor tracking fusion formula, which used only the inverses of covariances of single sensor estimation errors. In this paper, we present more general multi-sensor estimation fusion formula, where the assumption of independence cross sensor noises and the direct computation of the generalized inverse of joint covariance of multiple sensor estimation errors are not necessary. Instead, as the number of sensors increases, a recursive algorithm is presented, in which only the inverses or the generalized inverses of the matrices having the same dimension as that of the covariance matrices of single sensor estimate errors are required.

关键词： sensor data fusion

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Proceedings of SPIE: Multisensor, Multisource Information fusion: architectures, algorithms, and applications 2003

Proceedings of SPIE: Multisensor, Multisource Information Fu...

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Multisensor. Multisource Information fusion: architectures, algorithms, and applications 2003

This Volume 5099 of the conference proceedings contains 45 papers. Topics discussed include classification and decision fusion, image level fusion, approximate reasoning methodologies, estimation and tracking, fusion methodologies, evolving concepts and methodologies, architectures and related topics, industrial, medical and speech applications, defense applications, sensor/resource management and related topics.

关键词： sensor data fusion

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The system parameter fusion principle and its application to fuzzy pattern recognition

The system parameter fusion principle and its application to...

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Conference on Multisensor, Multisource Information fusion - architectures, algorithms and applications 2003

作者： Pu, QG Univ Sci & Technol Ctr Comp Suzhou 215011 Jiangsu Peoples R China

ISBN: (纸本)0819449598

Modern technology provides a great amount of information. In computer monitoring systems or computer control systems, especially real-time expert systems, in order to have the situation in hand, we need one or two parameters to express the quality and/or security of the whole system. This paper presents a principle for synthesizing measurements of multiple system parameters into a single parameter and its application to fuzzy pattern recognition.

关键词： sensor fusion fuzzy pattern recognition computer monitoring systems computer control systems realtime expert systems

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Optimal interval estimation fusion based on sensor interval estimates and confidence degrees

Optimal interval estimation fusion based on sensor interval ...

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Conference on Multisensor, Multisource Information fusion - architectures, algorithms and applications 2003

作者： Zhu, YM Li, BH Sichuan Univ Dept Math Chengdu 610064 Peoples R China

ISBN: (纸本)0819449598

The interval estimation fusion method based on sensor interval estimates and their confidence degrees is developed. When sensor estimates are independent of each other, a combination rule to merge sensor estimates and their confidence degrees is proposed. Moreover, two popular optimization-criteria: minimizing interval length with an allowable minimum confidence degree, or maximizing confidence degree with an allowable maximum interval length are suggested. In terms of the two criteria, an optimal interval estimation fusion can be obtained based on the combined intervals and their confidence degrees. Then we can extend the results on the combined interval outputs and. their confidence degrees to obtain a conditional combination rule and the corresponding optimal fault-tolerant interval estimation fusion in terms of the-two criteria. It is easy to see that Marzullo's fault-tolerant interval estimation fusion(11) is a special case of our method. We also point out that in some sense, our combination rule is similar to the combination rule in Dempster-Shafer evidence theory. However, the confidence degrees given in this paper is summable, but they (called mass function in Dempster-Shafer evidence theory) are not there;therefore, Dempster-Shafer's combination rule is not applicable to the interval estimation fusion.

关键词： interval estimation confidence degree combination ride optimal interval estimation fusion

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Adaptive multimodal biometric fusion algorithm using particle swarm

Adaptive multimodal biometric fusion algorithm using particl...

引用

Conference on Multisensor, Multisource Information fusion - architectures, algorithms and applications 2003

作者： Veeramachaneni, K Osadciw, LA Varshney, PK Syracuse Univ Dept Elect Engn & Comp Sci Syracuse NY 13244 USA

ISBN: (纸本)0819449598

This paper introduces a new algorithm called Adaptive Multimodal Biometric fusion Algorithm" (AMEBF), which is a combination of Bayesian decision fusion and particle swarm optimization. A Bayesian framework is implemented to fuse decisions received from multiple biometric sensors. The system's accuracy improves for a subset of decision fusion rules. The optimal rule is-a function of the error cost and a priori probability of an intruder This Bayesian framework formalizes the design of a system that can adoptively increase or reduce the security level. Particle swarm optimization searches the decision and sensor operating points (i.e. thresholds) space to achieve the desired security level: The optimization function aims to minimize the cost in a Bayesian decision fusion. The particle swarm optimization algorithm results in the fusion rule and the operating points of sensors at which the system can work This algorithm is important to systems designed with varying security needs and user access requirements. The adaptive algorithm is found to achieve desired security level and switch between different rules and sensor operating points for varying needs.

关键词： Bayesian decision fusion particle swarm optimization multimodal biometrics

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sensor management: Coverage versus survivability - A multiple objective optimization problem

Sensor management: Coverage versus survivability - A multipl...

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Conference on Multisensor, Multisource Information fusion - architectures, algorithms and applications 2003

作者： Ng, GW Ng, KH Chia, EL DSO Natl Labs Informat Exploitat Programme Singapore 118230 Singapore

ISBN: (纸本)0819449598

The sensor Management Team from DSO National Laboratories has developed a Decision Support System (DSS) to assist human operators in determining the most effective employment and/or deployment of a suite of sensors given a particular mission or operational scenario. The key issue addressed by the system is the resource allocation problem accompanied by two contradictory objectives, namely to maximise combined coverage,of the sensor suite and to maximise survivability of the sensor within the suite. Furthermore, the system is to handle operational constraints on the usage of the suite of sensors. In this paper, we will describe how we handle the problem by formulating it as a Multiple Objective Optimization (MOO) problem. This system may be used as a pre-mission planning tool or a real time decision aid for the sensor suite commander. With the increase in size of the sensor suite and the number of possible deployment sites, the feasibility space of the employment/deployment configurations will grow tremendously. In order to allow for near real time decision support, the team has incorporated genetic algorithm to solve the MOO problem.

关键词： sensor management multiple objective optimization genetic algorithms

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Information fusion of large number of sources with support vector machine techniques

Information fusion of large number of sources with support v...

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Conference on Multisensor, Multisource Information fusion - architectures, algorithms and applications 2003

作者： Braun, JJ Jeswani, SP MIT Lincoln Lab Lexington MA 02420 USA

ISBN: (纸本)0819449598

applications of information fusion include cases that involve a large number of information sources. Methods developed in the context of few information sources may not, and often do not, scale well to cases involving a large number of sources. This paper addresses specifically the problem of information fusion of large number of information sources. Performance of Support Vector Machine (SVM) based approach is investigated in input spaces consisting of thousands of information sources. Microarray pattern recognition, an important bioinformatics task with significant medical diagnostics applications, is considered from the information and sensor data fusion viewpoint, and recognition performance experiments conducted on microarray data are discussed. An approach involving high-dimensional input space partitioning is presented and its efficacy is investigated. The aspects of feature-level and decision-level fusion are discussed as well. The results indicate the feasibility of the SVM based information fusion with large number of information sources.

关键词： information fusion multisensor data fusion bioinformatics microarrays Support Vector Machine

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