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检索条件"任意字段=Multisensor. Multisource Information Fusion: Architectures, Algorithms, and Applications 2003"

共 284 条记录，以下是61-70 订阅

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Combat air identification fusion algorithm (CAIFA)

Combat air identification fusion algorithm (CAIFA)

引用

Conference on multisensor. multisource information fusion - architectures, algorithms and applications 2003

作者： Butler, CA Baker, JE Crowe, JA Kierstead, DP Mauro, CA Daniel H Wagner Associates Inc Hampton VA 23669 USA

ISBN: (纸本)0819449598

The Combat Air Identification fusion Algorithm (CAIFA), developed by Daniel H. Wagner, Associates, is a prototype, inferential reasoning algorithm for air combat identification. Bayesian reasoning and updating techniques are used in CAIFA to fuse multi-source identification evidence to provide identity estimates-allegiance, nationality, platform type, and intent-of detected airborne objects in the air battle space, enabling positive and rapid Combat Identification (CID) decisions. CAIFA was developed for the Composite Combat Identification (CCID) project under the Office of Naval Research (ONR) Missile Defense (MD) Future Naval Capability (FNC) program. CAIFA processes identification (ID) attribute evidence generated by surveillance sensors and other information sources over time by, updating the identity estimate for each target using Bayesian inference. CAIFA exploits the conditional interdependencies of attribute variables by constructing a context-dependent Bayesian Network (BN). This formulation offers a well-established, consistent approach for evidential reasoning, renders manageable the potentially large CID state space, and provides a flexible and extensible representation to accommodate requirements for model reconfiguration/restructuring. CAIFA enables reasoning across and at different levels of the Air Space Taxonomy.

关键词： combat identification Bayesian networks multi-source integration

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Minimizing both dropped formulas and concepts in knowledge fusion

Minimizing both dropped formulas and concepts in knowledge f...

引用

Conference on multisensor. multisource information fusion

作者： Gregoire, Eric Univ Artois CRIL CNRS F-62307 Lens France

ISBN: (纸本)0819462985

In this paper, a new family of approaches to fuse inconsistent knowledge sources is introduced in a standard logical setting. They combine two preference criteria to arbitrate between conflicting information: the minimization of falsified formulas and the minimization of the number of the different atoms that are involved in those formulas. Although these criteria exhibit a syntactical flavor, the approaches are semantically-defined.

关键词： logic-based fusion knowledge fusion syntactical fusion operators

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Use of multi sensor fusion technology to meet the challenges of emerging EO & RF threats to a combat aircraft

Use of multi sensor fusion technology to meet the challenges...

引用

Conference on multisensor. multisource information fusion - architectures, algorithms and applications 2003

作者： Shukla, AK Parthasarathy, T Rao, PNAP Govt India Minist Def Aeronaut Dev Agcy Bangalore 560017 Karnataka India

ISBN: (纸本)0819449598

The pilot on-board a combat aircraft encounters during any mission a dynamically varying threat environment of diverse EO and RF threats. Different sensors are carried on-board the aircraft to combat these threats. However, these sensors have their own limitations and no single sensor is able to perform in all kinds of situations. In addition, the technological advances in the threat scenario - in terms of higher speeds, small signatures and multimode guidance - and increased complex threats in the battlefield leading to generation of large amount of data input to the pilot make his decision making task very difficult due to increased workload. These challenges can be efficiently handled by deployment of a system on-board the aircraft with a comprehensive goal of autonomous target detection and tracking, situation and threat assessment and decision making based on multi-sensor data fusion techniques. In this paper, major emerging EO and RF threats for a combat aircraft and some important EO and RF sensors on-board the aircraft have been discussed. A design approach for the development of a multi-sensor data fusion system for a combat aircraft to provide better threat assessment than that provided by any single stand alone sensor has also been presented.

关键词： Multi-Sensor Data fusion Electro-Optical (EO) Radio Frequency (RF) Moving Target Image (MTTM) Multiple Hypothesis Tracking (MHT) Probabilistic Data Association (PDA)

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Generalized information fusion and Visualization Using Spatial Voting and Data Modeling

Generalized Information Fusion and Visualization Using Spati...

引用

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

作者： Jaenisch, Holger M. Handley, James W. SPIE Bellingham WA 98227 USA Licht Strahl Engn INC Toney AL 35773 USA Johns Hopkins Univ Baltimore MD 21218 USA

ISBN: (纸本)9780819495471

We present a novel and innovative information fusion and visualization framework for multi-source intelligence (multiINT) data using Spatial Voting (SV) and Data Modeling. We describe how different sources of information can be converted into numerical form for further processing downstream, followed by a short description of how this information can be fused using the SV grid. As an illustrative example, we show the modeling of cyberspace as cyber layers for the purpose of tracking cyber personas. Finally we describe a path ahead for creating interactive agile networks through defender customized Cyber-cubes for network configuration and attack visualization.

关键词： Spatial Voting Data Modeling information fusion Agile networks Cyber defense Cyber Persona Tracking

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Context based gait recognition

Context based gait recognition

引用

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

作者： Bazazian, Shermin Gavrilova, Marina Univ Calgary Dept Comp Sci Calgary AB T2N 1N4 Canada

ISBN: (纸本)9780819490858

Gait recognition has recently become a popular topic in the field of biometrics. However, the main hurdle is the insufficient recognition rate in the presence of low quality samples. The main focus of this paper is to investigate how the performance of a gait recognition system can be improved using additional information about behavioral patterns of users and the context in which samples have been taken. The obtained results show combining the context information with biometric data improves the performance of the system at a very low cost. The amount of improvement depends on the distinctiveness of the behavioral patterns and the quality of the gait samples. Using the appropriate distinctive behavioral models it is possible to achieve a 100% recognition rate.

关键词： Biometrics gait recognition information fusion context-based model behavioral patterns

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Integrated Multi-sensor fusion for Mapping and Localization in Outdoor Environments for Mobile Robots

Integrated Multi-sensor Fusion for Mapping and Localization ...

引用

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

作者： Emter, Thomas Petereit, Janko Fraunhofer Inst Optron Syst Technol & Image Explo Karlsruhe Germany

ISBN: (纸本)9781628410587

An integrated multi-sensor fusion framework for localization and mapping for autonomous navigation in unstructured outdoor environments based on extended Kalman filters (EKF) is presented. The sensors for localization include an inertial measurement unit, a GPS, a fiber optic gyroscope, and wheel odometry. Additionally a 3D LIDAR is used for simultaneous localization and mapping (SLAM). A 3D map is built while concurrently a localization in a so far established 2D map is estimated with the current scan of the LIDAR. Despite of longer run-time of the SLAM algorithm compared to the EKF update, a high update rate is still guaranteed by sophisticatedly joining and synchronizing two parallel localization estimators.

关键词： multi-sensor fusion extended Kalman filter particle filter SLAM autonomous mobile robot asynchronous fusion 3D LIDAR mapping

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Investigation of automated feature extraction using multiple data sources

Investigation of automated feature extraction using multiple...

引用

Conference on multisensor. multisource information fusion - architectures, algorithms and applications 2003

作者： Harvey, NR Perkins, SJ Pope, PA Theiler, J David, NA Porter, RB Los Alamos Natl Lab Space & Remote Sensing Sci Grp Los Alamos NM 87545 USA

ISBN: (纸本)0819449598

An increasing number and variety of platforms are now capable of collecting remote sensing data over a particular scene. For many applications, the information available from any individual sensor may be incomplete, inconsistent or imprecise. However, other sources may provide complementary and/or additional data. Thus, for an application such as image feature extraction or classification, it may be that fusing the mulitple data sources can lead to more consistent and reliable results. Unfortunately, with the increased complexity of the fused data, the search space of feature-extraction or classification algorithms also greatly increases. With a single data source, the determination of a suitable algorithm may be a significant challenge for an image analyst. With the fused data, the search for suitable algorithms can go far beyond the capabilities of a human in a realistic time frame, and becomes the realm of machine learning, where the computational power of modern computers can be harnessed to the task at hand. We describe experiments in which we investigate the ability of a suite of automated feature extraction tools developed at Los Alamos National Laboratory to make use. of multiple data sources for various feature extraction tasks. We compare and contrast this software's capabilities on 1) individual data sets from different data sources 2) fused data sets from multiple data sources and 3) fusion of results from multiple individual data sources.

关键词： supervised classification data fusion support vector machines feature extraction machine learning multispectral

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Level 5: User refinement to aid the fusion process

Level 5: User refinement to aid the fusion process

引用

Conference on multisensor. multisource information fusion - architectures, algorithms and applications 2003

作者： Blasch, EP Plano, S Wright State Univ Dept Elect Engn Dayton OH 45435 USA

ISBN: (纸本)0819449598

The revised JDL fusion model Level 4 "process refinement" covers a broad spectrum of actions such as sensor management and control. A limitation of Level 4 is the purpose of control - whether it be for user needs or system operation. Level 5, User Refinement, is a modification to the Revised JDL model that distinguishes between machine process refinement and user refinement. User refinement can either be human control actions or refinement of the user's cognitive model. In many cases, fusion research concentrates on the machine and does not take full advantage of the human as not only a qualified expert to refine the fusion process, but also as customer for whom the fusion system is designed. Without user refinement, sensor fusion is incomplete, inadequate, and the user neglects its worthiness. To capture user capabilities, we. explore the concept of user refinement through decision and action based on situational leadership models. We develop a Fuse-Act Situational User Refinement (FASUR) model that details four refinement behaviors: Neglect, Consult, Rely, and Interact and five refinement functions: Planning, Organizing, Coordinating, Directing, and Controlling. Process refinement varies for different systems and different user information needs. By designing a fusion system with a specific user in mind, vis 'Level 5', a fusion architecture can meet user's information needs for varying situations, extend user sensing capabilities for action, and increase the human-machine interaction.

关键词： Sensors Data modeling Data fusion Sensor fusion Cognitive modeling Control systems Telecommunications Systems modeling Environmental sensing Surveillance

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Signal-to-noise ratio for cross-sensor fusion approach

Signal-to-noise ratio for cross-sensor fusion approach

引用

Conference on multisensor. multisource information fusion

作者： Kozaitis, S. P. Ouendeno, M. Florida Inst Technol Dept Elect & Comp Engn 150 W Univ Blvd Melbourne FL 32901 USA

We determined the signal-to-noise ratios for an image fusion approach that is suitable for application to systems with disparate sensors. We found there was reconstruction error present when the forward and reverse tr... 详细信息

ISBN: (纸本)9780819466938

关键词： image fusion image transform signal-to-noise ratio wavelet wavelet transform

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Multiple algorithm fusion in a corrosion detection algorithm used with shipboard tank and void inspection systems

Multiple algorithm fusion in a corrosion detection algorithm...

引用

Conference on multisensor. multisource information fusion - architectures, algorithms and applications 2003

作者： Nelson, BN Slebodnick, P Lemieux, EJ CEO CENTERS Inc Newton Ctr MA 02459 USA

ISBN: (纸本)0819449598

Over the last several years the Naval Research Laboratory has developed video based systems for inspecting tanks (ballast, potable water, fuel, etc.) and other voids on ships. Over this past year, we have extensively utilized the Insertable Stalk Inspection System (ISIS) to perform inspections of shipboard tanks and voids. This system-collects between 15 and 30 images of the tank or void being inspected as well as a video archive of the complete inspection process. A corrosion detection algorithm analyzes the collected imagery. The corrosion detection algorithm output is the percent coatings damage in the tank being inspected. The corrosion detection algorithm consists of four independent algorithms that each separately assesses the coatings damage in each of the images that are analyzed. The algorithm results are fused to attain a single coatings damage value for each of the analyzed images. The damage values for each of the images are next aggregated in order to develop a single coatings damage value for the tank being inspected. This paper concentrates on the methods used to fuse the results from the four independent algorithms that assess corrosion damage at the individual image level as well as the methods used to aggregate the results from multiple images to attain a single coatings damage level. Results from both calibration tests and double blind testing are provided in the paper to demonstrate the advantages of the video inspection systems and the corrosion detection algorithm.

关键词： information fusion image processing automatic corrosion detection

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