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检索条件"任意字段=Multisensor, Multisource Information Fusion: Architecture, Algorithms, and Applications 2005"

共 73 条记录，以下是41-50 订阅

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Enhancing image fusion performance and utility for defence and security applications

Enhancing image fusion performance and utility for defence a...

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multisensor, multisource information fusion: architectures, algorithms, and applications 2009

作者： Sadler, J. Smith, M.I. Waterfall Solutions Ltd Parklands Guildford Surrey GU2 9JX United Kingdom

ISBN: (纸本)9780819476111

The real-time fusion of imagery from two or more complementary sensors offers significant operational benefits for both operator-in-the-loop and automated processing systems. This paper reports on a new image fusion framework that can be used to maximise detection, recognition and identification performance within the context of low false-alarm rate operation. The Intelligent Image fusion (I2F) architecture presented here allows exploitation of data at the information level as well as at the pixel-level, and can do so in an adaptable and intelligent manner. In this paper the architecture is examined in terms of design, applicability to a range of tasks, and performance factors such as adaptability, flexibility and utility. The relationship between algorithm design and hardware implementation, and the consequential impact on system performance, is also reviewed. Particular consideration is given to size, weight and power constraints that exist for some systems and their implications for processing optimisation and implementation on different processing platforms. Results are presented from the outcome of quantitative studies, development programmes and system trials. © 2009 SPIE.

关键词： Image fusion

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Navigation of uncertain terrain by fusion of information from real and synthetic imagery

Navigation of uncertain terrain by fusion of information fro...

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Conference on multisensor, multisource information fusion - architectures, algorithms, and applications

作者： Lyons, Damian M. Nirmal, Paramesh Benjamin, D. Paul Fordham Univ Robot & Comp Vis Lab Bronx NY 10458 USA Pace Univ Dept Comp Sci New York NY 10023 USA

ISBN: (纸本)9780819490858

We consider the scenario where an autonomous platform that is searching or traversing a building may observe unstable masonry or may need to travel over unstable rubble. A purely behaviour-based system may handle these challenges but produce behaviour that works against long-terms goals such as reaching a victim as quickly as possible. We extend our work on ADAPT, a cognitive robotics architecture that incorporates 3D simulation and image fusion, to allow the robot to predict the behaviour of physical phenomena, such as falling masonry, and take actions consonant with long-term goals. We experimentally evaluate a cognitive only and reactive only approach to traversing a building filled with various numbers of challenges and compare their performance. The reactive only approach succeeds only 38% of the time, while the cognitive only approach succeeds 100% of the time. While the cognitive only approach produces very impressive behaviour, our results indicate how much better the combination of cognitive and behaviour-based can be.

关键词： cognitive robotics navigation sensory fusion

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FuzzyfusionTM, an application architecture for multisource information fusion

FuzzyFusionTM, an application architecture for multisource i...

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multisensor, multisource information fusion: architectures, algorithms, and applications 2009

作者： Fox, Kevin L. Henning, Ronda R. Harris Corporation Melbourne FL 32902 United States

ISBN: (纸本)9780819476111

The correlation of information from disparate sources has long been an issue in data fusion research. Traditional data fusion addresses the correlation of information from sources as diverse as single-purpose sensors to all-source multi-media information. information system vulnerability information is similar in its diversity of sources and content, and in the desire to draw a meaningful conclusion, namely, the security posture of the system under inspection. FuzzyfusionTM A data fusion model that is being applied to the computer network operations domain is presented. This model has been successfully prototyped in an applied research environment and represents a next generation assurance tool for system and network security. © 2009 SPIE.

关键词： Data fusion

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Considerations for Multiple Hypothesis Correlation on Tactical Platforms

Considerations for Multiple Hypothesis Correlation on Tactic...

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Conference on multisensor, multisource information fusion - architectures, algorithms, and applications

作者： Thomas, Alan M. Turpen, James E. Georgia Inst Technol Georgia Tech Res Inst Atlanta GA 30318 USA

ISBN: (纸本)9780819495471

Tactical platforms benefit greatly from the fusion of tracks from multiple sources in terms of increased situation awareness. As a necessary precursor to this track fusion, track-to-track association, or correlation, must first be performed. The related measurement-to-track fusion problem has been well studied with multiple hypothesis tracking and multiple frame assignment methods showing the most success. The track-to-track problem differs from this one in that measurements themselves are not available but rather track state update reports from the measuring sensors. Multiple hypothesis, multiple frame correlation systems have previously been considered;however, their practical implementation under the constraints imposed by tactical platforms is daunting. The situation is further exacerbated by the inconvenient nature of reports from legacy sensor systems on bandwidth-limited communications networks. In this paper, consideration is given to the special difficulties encountered when attempting the correlation of tracks from legacy sensors on tactical aircraft. Those difficulties include the following: covariance information from reporting sensors is frequently absent or incomplete;system latencies can create temporal uncertainty in data;and computational processing is severely limited by hardware and architecture. Moreover, consideration is given to practical solutions for dealing with these problems in a multiple hypothesis correlator.

关键词： Data Association Multiple Hypothesis Correlation Multiple Hypothesis Tracking Avionics information fusion Sensors

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multisource information fusion for Logistics

Multisource Information Fusion for Logistics

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Conference on multisensor, multisource information fusion - architectures, algorithms, and applications

作者： Woodley, Robert Petrov, Plamen Noll, Warren 21st Century Syst Inc Omaha NE 68106 USA

ISBN: (纸本)9780819486387

Current Army logistical systems and databases contain massive amounts of data that need an effective method to extract actionable information. The databases do not contain root cause and case-based analysis needed to diagnose or predict breakdowns. A system is needed to find data from as many sources as possible, process it in an integrated fashion, and disseminate information products on the readiness of the fleet vehicles. 21st Century Systems, Inc. introduces the Agent-Enabled Logistics Enterprise Intelligence System (AELEIS) tool, designed to assist logistics analysts with assessing the availability and prognostics of assets in the logistics pipeline. AELEIS extracts data from multiple, heterogeneous data sets. This data is then aggregated and mined for data trends. Finally, data reasoning tools and prognostics tools evaluate the data for relevance and potential issues. Multiple types of data mining tools may be employed to extract the data and an information reasoning capability determines what tools are needed to apply them to extract information. This can be visualized as a push-pull system where data trends fire a reasoning engine to search for corroborating evidence and then integrate the data into actionable information. The architecture decides on what reasoning engine to use (i.e., it may start with a rule-based method, but, if needed, go to condition based reasoning, and even a model-based reasoning engine for certain types of equipment). Initial results show that AELEIS is able to indicate to the user of potential fault conditions and root-cause information mined from a database.

关键词： Expert systems information fusion Knowledge based systems Vehicle health monitoring Data reasoning Intelligent agent software Data mining and clustering

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Affordable Non-Traditional Source Data Mining for Context Assessment to Improve Distributed fusion System Robustness

Affordable Non-Traditional Source Data Mining for Context As...

引用

Conference on multisensor, multisource information fusion - architectures, algorithms, and applications

作者： Bowman, Christopher Haith, Gary Data Fusion & Neural Networks LLC (United States) Georgia Tech Research Institute (United States) Arctan Group LLC (United States)

ISBN: (纸本)9780819495471

This paper describes methods to affordably improve the robustness of distributed fusion systems by opportunistically leveraging non-traditional data sources. Adaptive methods help find relevant data, create models, and characterize the model quality. These methods also can measure the conformity of this non-traditional data with fusion system products including situation modeling and mission impact prediction. Non-traditional data can improve the quantity, quality, availability, timeliness, and diversity of the baseline fusion system sources and therefore can improve prediction and estimation accuracy and robustness at all levels of fusion. Techniques are described that automatically learn to characterize and search non-traditional contextual data to enable operators integrate the data with the high-level fusion systems and ontologies. These techniques apply the extension of the Data fusion & Resource Management Dual Node Network (DNN) technical architecture at Level 4. The DNN architecture supports effectively assessment and management of the expanded portfolio of data sources, entities of interest, models, and algorithms including data pattern discovery and context conformity. Affordable model-driven and data-driven data mining methods to discover unknown models from non-traditional and 'big data' sources are used to automatically learn entity behaviors and correlations with fusion products, [14 and 15]. This paper describes our context assessment software development, and the demonstration of context assessment of non-traditional data to compare to an intelligence surveillance and reconnaissance fusion product based upon an IED POIs workflow.

关键词： Data fusion Data modeling Sensors Systems modeling Intelligence systems Data processing Performance modeling Control systems Data acquisition Data mining

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Reduced data projection slice image fusion using principal component analysis

Reduced data projection slice image fusion using principal c...

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Conference on multisensor, multisource information fusion

作者： Riasati, VR Zhou, H Sci Applicat Int Corp San Diego CA 92121 USA

ISBN: (纸本)0819457981

In this paper we discuss the utilization of Principal Component Analysis, PCA, with projection slice synthetic discriminant function (PSDF) filters to reduce a data set that represents images from different sensor systems in order to extract relative information and features from the image set. The PCA helps to emphasize the differences in each of the training images in a given class. These differences are encoded into the PSDF filters. The PSDF filters provide a premise for data fusion by utilization of the projection-slice theorem. The PSDF is implemented with a few training images generated from the PCA, containing relevant information from all of the training images. The data in the principle components that are used to represent the entire data set can be emphasized by conditioning the eigen-values of the basis vectors used to corroborate important data packets in the entire data set. ne method of data fusion, and preferred data emphasis in conjunction with the PST is discussed and the fused images are presented.

关键词： sensor fusion projection slice theorem principal component analysis synthetic discriminant functions

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Advanced algorithms for distributed fusion

Advanced algorithms for distributed fusion

引用

Conference on multisensor, multisource information fusion

作者： Gelfand, A. Smith, C. Colony, M. Bowman, C. Pei, R. Huynh, T. Brown, C. Decis Analyt Corp 1235 S Clark StSuite 400 Arlington VA 22202 USA Data Fus Neural Networks Broomfield CO 80020 USA US Army CERDEC Intelligence & Informat Warfare Directorat Ft Monmouth NJ USA

ISBN: (纸本)9780819471659

The US Military has been undergoing a radical transition from a traditional "platform-centric" force to one capable of performing in a "Network-Centric" environment. This transformation will place all of the data needed to efficiently meet tactical and strategic goals at the warfighter's fingertips. With access to this information, the challenge of fusing data from across the batttlespace into an operational picture for real-time Situational Awareness emerges. In such an environment, centralized fusion approaches will have limited application due to the constraints of real-time communications networks and computational resources. To overcome these limitations, we are developing a formalized architecture for fusion and track adjudication that allows the distribution of fusion processes over a dynamically created and managed information network. This network will support the incorporation and utilization of low level tracking information within the Army Distributed Common Ground System (DCGS-A) or Future Combat System (FCS). The framework is based on Bowman's Dual Node Network (DNN) architecture that utilizes a distributed network of interlaced fusion and track adjudication nodes to build and maintain a globally consistent picture across all assets.

关键词： distributed data fusion decentralized data fusion consistency assessment performance evaluation resource management Dual Node Network (DNN)

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A controllable sensor management algorithm capable of learning

A controllable sensor management algorithm capable of learni...

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Conference on multisensor, multisource information fusion

作者： Osadciw, L Veeramacheneni, K Syracuse Univ Syracuse NY 13244 USA

ISBN: (纸本)0819457981

Sensor management technology progress is challenged by the geographic space it spans, the heterogeneity of the sensors, and the real-time timeframes within which plans controlling the assets are executed. This paper presents a new sensor management paradigm and demonstrates its application in a sensor management algorithm designed for a biometric access control system. This approach consists of an artificial intelligence (AI) algorithm focused on uncertainty measures, which makes the high level decisions to reduce uncertainties and interfaces with the user, integrated cohesively with a bottom up evolutionary algorithm, which optimizes the sensor network's operation as deter-mined by the AI algorithm. The sensor management algorithm presented is composed of a Bayesian network, the AI algorithm component, and a swarm optimization algorithm, the evolutionary algorithm. Thus, the algorithm can change its own performance goals in real-time and will modify its own decisions based on observed measures within the sensor network. The definition of the measures as well as the Bayesian network determine the robustness of the algorithm and its utility in reacting dynamically to changes in the global system.

关键词： sensor networks sensor management data fusion swarm algorithms Bayesian networks

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SAWA: An assistant for higher-level fusion and situation awareness

SAWA: An assistant for higher-level fusion and situation awa...

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Conference on multisensor, multisource information fusion

作者： Matheus, CJ Kokar, MM Baclawski, K Letkowski, JA Call, C Hinman, M Salerno, J Boulware, D Versatile Informat Syst Inc Framingham MA 01701 USA

ISBN: (纸本)0819457981

Situation awareness involves the identification and monitoring of relationships among level-one objects. This problem in general is intractable (i.e., there is a potentially infinite number of relations that could be tracked) and thus requires additional constraints and guidance defined by the user if there is to be any hope of creating practical situation awareness systems. This paper describes a Situation Awareness Assistant (SAWA) that facilitates the development of user-defined domain knowledge in the form of formal ontologies and rule sets and then permits the application of the domain knowledge to the monitoring of relevant relations as they occur in evolving situations. SAWA includes tools for developing ontologies in OWL and rules in SWRL and provides runtime components for collecting event data, storing and querying the data, monitoring relevant relations and viewing the results through a graphical user interface. An application of SAWA to a scenario from the domain of supply logistics is also presented.

关键词： situation awareness level-two fusion ontologies formal reasoning OWL SWRL

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