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Conference on sensor fusion: architectures, algorithms, and applications IV

作者： Gatepaille, S Brunessaux, S Abdulrab, H Matra Syst & Informat F-27106 Val De Reuil France

ISBN: (纸本)0819436771

This paper describes a work currently in progress whose aim is to design, develop and evaluate a Multi-Agent Framework for Data fusion (DFMAF). This is being done with the support of a battlefield surveillance demonstrator application, named TA-10 [3,6]. Through the following chapters, we will describe the benefits of using such a Framework for data fusion problems. Firstly, we will briefly present the multi-agent research domain. Then, we will go into further details to describe DFMAF, the multi-agent framework designed to help solving data fusion problems. The appropriateness of DFMAF to data fusion problems will also be pointed out. Next, the implementation and use of DFMAF in the support application will be detailed as well as the assessment procedure followed. Finally, we will conclude and expose the future work which will be done.

关键词： data fusion battlefield surveillance multi-sensor multiple target tracking multi-agent systems distributed systems

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sensor fusion options for ballistic missile defense interceptor applications

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Proceedings of SPIE - The International Society for Optical Engineering 1999年 3719卷 92-102页

作者： Bjork, Charles Morris, Norman Dasarathy, Belur V. Smith, Bart Allen, Doug Prestwood, William T. Nichols Research Corp Huntsville United States

Critical elements of future exoatmospheric interceptor systems are intelligent processing (IP) techniques which can effectively combine sensor data from disparate sensors. This paper summarizes the impact on discrimination performance of several feature and classifier fusion techniques, which can be used as part of the overall IP approach. These techniques are implemented either within the Fused sensor Discrimination (FuSeD) Testbed, or off-line as building blocks that can be modified to assess differing fusion approaches, classifiers and their impact on interceptor requirements. Several optional approaches for combining the data at the different levels, i.e, feature and classifier levels, are discussed in this paper and a comparison of performance results is shown. Approaches yielding promising results must still operate within the timeline and memory constraints on board the interceptor. A hybrid fusion approach is implemented at the feature level through the use of feature sets input to specific classifiers (currently two classifiers are employed). The output of the fusion process contains an estimate of the confidence in the data and the discrimination decisions. The confidence in the data and decisions can be used in real time to dynamically select different sensor feature data, classifiers, or to request additional sensor data on specific objects that have not been confidently identified as 'lethal' or 'non-lethal'. However, dynamic selection requires an understanding of the impact of various combinations of feature sets and classifier options. Accordingly, the paper presents the various tools for exploring these options and illustrates their usage with data sets generated to realistically simulate the world of Ballistic Missile Defense (BMD) interceptor applications.

关键词： sensor data fusion

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fusion of imaging and non-imaging sensor information for airborne surveillance

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Proceedings of SPIE - The International Society for Optical Engineering 1999年 3719卷 126-138页

作者： Valin, Pierre Jouan, Alexandre Bosse, Eloi Lockheed Martin Canada Montreal Canada

This paper presents results from an Adaptable Data fusion Testbed (ADFT) which has been constructed to analyze simulated or real data with the help of modular algorithms for each of the main fusion functions and image interpretation algorithms. The results obtained from data fusion of information coming from an imaging Synthetic Aperture Radar (SAR) and non-imaging sensors (ESM, IFF, 2-D radar) on-board an airborne maritime surveillance platform are presented for two typical scenarios of Maritime Air Area Operations and Direct Fleet Support. An extensive set of realistic databases has been created that contains over 140 platforms, carrying over 170 emitters and representing targets from 24 countries. A truncated Dempster-Shafer evidential reasoning scheme is used that proves robust under countermeasures and deals efficiently with uncertain, incomplete or poor quality information. The evidential reasoning scheme can yield both single ID with an associated confidence level and more generic propositions of interest to the Commanding Officer. For nearly electromagnetically silent platforms, the Spot Adaptive mode of the SAR, which is appropriate for naval targets, is shown to be invaluable in providing long range features that are treated by a 4-step classifier to yield ship category, type and class. Our approach of reasoning over attributes provided by the imagery will allow the ADFT to process in the next phase (currently under way) both FLIR imagery and SAR imagery in different modes (RDP for naval targets, Strip Map and Spotlight Non-Adaptive for land targets).

关键词： sensor data fusion

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Cross band pixel selection in multi-resolution image fusion

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Proceedings of SPIE - The International Society for Optical Engineering 1999年 3719卷 319-326页

作者： Petrovic, Vladimir Xydeas, Costas Univ of Manchester Manchester United Kingdom

The work described in this paper focuses on cross band pixel selection as applied to pixel level multi-resolution image fusion. In addition, multi-resolution analysis and synthesis is realised via QMF sub-band decomposition techniques. Thus cross-band pixel selection is considered with the aim of reducing the contrast and structural distortion image artefacts produced by existing wavelet based, pixel level, image fusion schemes. Preliminary subjective image fusion results demonstrate clearly the advantage which the proposed cross-band selection technique offers, when compared to conventional area based pixel selection.

关键词： Image processing

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Fuzzy logic approach for data association

Fuzzy logic approach for data association

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Proceedings of the 1999 sensor fusion: architectures, algorithms, and applications iiI

作者： Stubberud, Stephen C. Lugo, Kristi A. ORINCON Corp San Diego CA United States

A fuzzy logic based data association routine has been developed. The concept is based on very simple fuzzy logic implementation. The resulting technique is intended as an enhancement to current data association routines when added information such as sensor blockage and forbidden terrain knowledge can be incorporated into the system.

关键词： sensor data fusion

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Combined force and position Polyvinylidene Fluoride (PVDF) Robotic tactile sensing system

Combined force and position Polyvinylidene Fluoride (PVDF) R...

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Conference on sensor fusion - architectures, algorithms, and applications

作者： Dargahi, J Eastwood, AR Kemp, IJ Glasgow Caledonian Univ. (United Kingdom)

ISBN: (纸本)081942482X

This paper reports on a tactile sensing system with only three sensing elements. The magnitude and position of the applied force is obtained by utilising triangulation approach combined with membrane stress, some information about shape of the contact object is obtained. The sensor is designed to overcome the problems of cross-talk between sensing elements, complexity and fragility which is associated with some PVDF tactile sensors arranged in matrix form. The theoretical analysis of the sensor is made and compared with experimental results. The limitation of the sensor is also reported.

关键词： tactile sensor robotics polyvinylidene fluoride piezoelectric cross talk sensing element

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ELIPS: Toward a sensor fusion processor on a chip

ELIPS: Toward a sensor fusion processor on a chip

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Conference on sensor fusion - architectures, algorithms, and applications iiI

作者： Daud, T Stoica, A Thomas, T Li, WT Fabunmi, J CALTECH Jet Prop Lab Pasadena CA 91109 USA

ISBN: (纸本)0819431931

The paper presents the concept and initial tests from the hardware implementation of a low-power, high-speed reconfigurable sensor fusion processor. The Extended Logic Intelligent Processing System (ELIPS) processor is developed to seamlessly combine rule-based systems, fuzzy logic, and neural networks to achieve parallel fusion of sensor in compact low power VLSI. The first demonstration of the FLIPS concept targets interceptor functionality;other applications, mainly in robotics and autonomous systems are considered for the future. The main assumption behind ELIPS is that fuzzy, rule-based and neural forms of computation can serve as the main primitives of an "intelligent" processor. Thus, in the same way classic processors are designed to optimize the hardware implementation of a set of fundamental operations, ELIPS is developed as an efficient implementation of computational intelligence primitives, and relies on a set of fuzzy set, fuzzy inference and neural modules, built in programmable analog hardware. The hardware programmability allows the processor to reconfigure into different machines, taking the most efficient hardware implementation during each phase of information processing. Following software demonstrations on several interceptor data three important ELIPS building blocks (a fuzzy set preprocessor, a rule-based fuzzy system and a neural network) have been fabricated in analog VLSI hardware and demonstrated microsecond-processing times.

关键词： sensor fusion hardware sensor fusion processor fuzzy expert system neural networks reconfigurable hardware

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A linearly constrained least squares approach for multisensor data fusion

A linearly constrained least squares approach for multisenso...

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Conference on sensor fusion - architectures, algorithms, and applications

作者： Zhou, YF Leung, H Telexis Corporation Canada Ottawa ON K1V 7P2 2427 Holly Lane Canada Surface Radar Section Defence Research Establishment Ottawa Ottawa ON K1A OK2 Canada

ISBN: (纸本)081942482X

In this paper, we present a linearly constrained least squares (LCLS) algorithm for multisensor data fusion. While fusion is considered in the scope of linear combination, the objective of the LCLS algorithm is to minimize the energy of the linearly fused information based on empirical sensory information. Statistical performance analysis of the LCLS algorithm will be carried out including the consistency and asymptotic covariance of the estimates. Effectiveness of the proposed fusion algorithm will be evaluated numerically based on fusion of signals and images.

关键词： data fusion least squares minimum variance information uncertainty multisensor tracking consistency analysis

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fusion under the closed-world assumption

Fusion under the closed-world assumption

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Conference on sensor fusion - architectures, algorithms, and applications V

作者： Grégoire, E Univ Sci & Tech Lille Flandres Artois CRIL F-62307 Lens France

ISBN: (纸本)0819440809

In this paper, new operators for fusing logical knowledge-bases (KBs) are proposed. They are defined in such a way that they can handle KBs that must be interpreted under forms of the closed-world assumption. Such assumptions implicitly augment the KBs with some additional information that could not be deduced using the standard logical deductive apparatus. More precisely, we extend previous recent works about the logical fusion of knowledge to handle such KBs. We focus on the model-theoretic definition of fusion operators to show their limits. In particular, the basic logical concept of model appears too coarse-grained. We solve this problem and propose new operators that cover a whole family of fusion approaches in the presence of variants of the closed-world assumption.

关键词： data fusion knowledge base fusion CWA nonmonotonic logics

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PERFORMANCE AND LIMITATIONS OF DISTRIBUTED INFERENCE AND INFORMATION fusion IN WIRELESS sensor NETWORK applications

PERFORMANCE AND LIMITATIONS OF DISTRIBUTED INFERENCE AND INF...

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作者： Sherry, Richard Ray PennState University Libraries

学位级别：Doctor of Philosophy

Recent advances in sensor design and miniaturization have provided the opportunity for the creation of large distributed wireless sensor networks. There has been significant progress in combining sensing, processing, data storage and communications capabilities, in network self organization, and in optimizing communication architectures. In contrast to most other network applications, wireless sensor networks face a number of special challenges and constraints resulting from 1) lack of hardwired connections (no external power sources, low communications bandwidths, higher communication error rates), 2) small physical size (small onboard energy supply, small antennas/acoustic transducers, small low energy sensors) and 3) elevated sensor node failure rates. One of the key remaining challenges is in the area of inference and information fusion (aggregating/filtering/interpreting the sensor data into useful high level knowledge). Many authors have advocated the use of local distributed inference and fusion algorithms such as the iterative message-passing belief propagation algorithms employed on probabilistic graphical models (Bayesian Networks and Markov Random Fields). However, little research has been performed to assess the performance of these algorithms under the special constraints imposed by wireless sensor network applications. This dissertation reports on a study investigating issues associated with application of these algorithms to realistic wireless sensor networks configurations. This research has produced results delineating the performance and limitations including communications requirements, energy resource requirements and the impacts of different topologies and architectures such as hierarchical/non-hierarchical topologies, centralized or distributed processing, localized (in local node clusters) or full network models, and node cluster size.

关键词： wireless sensor networks information fusion data fusion

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