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检索条件"任意字段=Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2007"

共 282 条记录，以下是231-240 订阅

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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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Cognitive engineering in algorithm development for multisensor data fusion in military applications

Cognitive engineering in algorithm development for multisens...

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Conference on multisensor, multisource information fusion

作者： Kight, AC Narayanan, S Wright State Univ Dept Biomed Ind & Human Factors Engn Dayton OH 45435 USA

ISBN: (纸本)0819453579

In battlefield situations, human operators are bombarded with substantial amounts of information and expected to make near-instantaneous decisions. The large amounts of information, coupled with short decision times and the need to reduce the potential of making incorrect decisions, create the possibility for information overload. This problem is especially prominent in military applications involving imagery from multiple sensors. Computer-based algorithms for fusing pertinent sets of imagery have proven somewhat useful for alleviating this problem. However, little research has been done on designing multisensor data fusion systems using principles of cognitive engineering, which involves the consideration of human cognition during the design process. The design of a sensor fusion system using principles from cognitive engineering would create a more natural relationship between human and machine, and would thus be extremely effective in reducing operator error in military situations. This paper explores the need for integrating human reasoning and cognition in algorithm development for multisensor fusion applications.

关键词： Algorithm development Data fusion Defense technologies Cognition Image fusion Error analysis Image sensors Sensor fusion Sensors

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Data fusion in road traffic engineering: An overview

Data fusion in road traffic engineering: An overview

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Conference on multisensor, multisource information fusion

作者： El Faouzi, NE ENTPE INRETS Transport & Traff Engn Lab F-69675 Bron France

ISBN: (纸本)0819453579

The objective of this paper is to present an analysis of recent applications of data fusion (DF) in road traffic engineering. First, we report the most significant applications of data fusion techniques in road traffic engineering area: traffic monitoring, signal control, Automatic Incident Detection, traffic forecasting, Intelligent Transportation Systems..., as well as the extent and direction of DF interest it the field. Second, a classification including applications, fusion goals and mathematical tools is proposed.

关键词： traffic engineering data fusion ITS theory of evidence Lalman filtering estimation fusion

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Sensor management and Bayesian networks

Sensor management and Bayesian networks

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Conference on multisensor, multisource information fusion

作者： Yilmazer, N Osadciw, LA Syracuse Univ Dept Elect Engn & Comp Sci Syracuse NY 13244 USA

ISBN: (纸本)0819453579

This paper introduces the sensor management problem and uses Bayesian networks as a scalable approach to handling the operational decisions concerning the sensor network. In general, single sensor systems only provide partial information on the state of the event or environment while multisensor systems provide a synergistic effect, which improves the quality and availability of information. Data fusion techniques can effectively combine this environmental information from similar and/or dissimilar sensors. Until recently, the operator could manage the systems easily, but current systems are more complex and produce data more quickly than earlier versions. A sensor manager becomes necessary when this occurs to assist the operators. Researchers have developed many single point sensor management solutions. General sensor management algorithms that can handle a variety of sensor network applications have yet to emerge.

关键词： sensor management Bayesian networks fusion

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multisensor, multisource information fusion: Architect uses, algorithms, and application 2004

Multisensor, multisource information fusion: Architect uses,...

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multisensor, multisource information fusion: architectures, algorithms, and applications 2004

The proceedings contains 43 papers from the multisensor, multisource information fusion: Architect uses, algorithms, and Application 2004. The topics discussed include: DEI-DEO fusion as a tool for improving decision robustness across metrics in similarity-measure-based classifiers;quantitative analysis of spatio-temporal decision fusion based on the majority voting technique;a mathematical framework for the optimization of rejection and ROC thresholds in the fusion of correlated sensor data and further results on fault-tolerant distributed classification using error-correcting codes.

关键词： Sensor data fusion

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A scalable, portable, object-oriented framework for parallel multi-sensor data-fusion applications in HPC systems

A scalable, portable, object-oriented framework for parallel...

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Conference on multisensor, multisource information fusion

作者： Gupta, P Prasad, G Univ Cent Florida Sch Comp Sci Orlando FL 32816 USA

ISBN: (纸本)0819453579

Multi-sensor Data fusion is synergistic integration of multiple data sets. Data fusion includes processes for aligning, associating and combining data and information in estimating and predicting the state of objects, their relationships, and characterizing situations and their significance. The combination of complex data sets and the need for real-time data storage and retrieval compounds the data fusion problem. The systematic development and use of data fusion techniques are particularly critical in applications requiring massive, diverse, ambiguous, and time-critical data. Such conditions are characteristic of new emerging requirements;e.g., network-centric and information-centric warfare, low intensity conflicts such as special operations, counter narcotics, antiterrorism, information operations and CALOW (Conventional Arms, Limited Objectives Warfare), economic and political intelligence. In this paper, Aximetric presents a novel, scalable, object-oriented, metamodel framework for parallel, cluster-based data-fusion engine on High Performance Computing (HPC) Systems. The data-clustering algorithms provide a fast, scalable technique to sift through massive, complex data sets coming through multiple streams in real-time. The load-balancing algorithm provides the capability to evenly distribute the workload among processors on-the-fly and achieve real-time scalability. The proposed data-fusion engine exploits unique data-structures for fast storage, retrieval and interactive visualization of the multiple data streams.

关键词： sensor fusion HPC systems meta-modefing object-oriented simulation data fusion

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Real time sensor validation and fusion for distributed autonomous sensors

Real time sensor validation and fusion for distributed auton...

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Conference on multisensor, multisource information fusion

作者： Yuan, XJ Li, XS Buckles, B Tulane Univ EECS Dept New Orleans LA 70118 USA

ISBN: (纸本)0819453579

Multi-sensor data fusion has found widespread applications in industrial and research sectors. The purpose of real time multi-sensor data fusion is to dynamically estimate an improved system model from a set of different data sources, i.e., sensors. This paper presented a systematic and unified real time sensor validation and fusion framework (RTSVFF) based on distributed autonomous sensors. The RTSVFF is an open architecture which consists of four layers - the transaction layer, the process fusion layer, the control layer, and the planning layer. This paradigm facilitates distribution of intelligence to the sensor level and sharing of information among sensors, controllers, and other devices in the system. The openness of the architecture also provides a platform to test different sensor validation and fusion algorithms and thus facilitates the selection of near optimal algorithms for specific sensor fusion application. In the version of the model presented in this paper, confidence weighted averaging is employed to address the dynamic system state issue noted above. The state is computed using an adaptive estimator and dynamic validation curve for numeric data fusion and a robust diagnostic map for decision level qualitative fusion. The framework is then applied to automatic monitoring of a gas-turbine engine, including a performance comparison of the proposed real-time sensor fusion algorithms and a traditional numerical weighted average.

关键词： real time sensor validation and fusion distributed sensor system design dynamic validation curve file based knowledge system confidence weighted averaging robust diagnostic maps

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An information system for target recognition

An information system for target recognition

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Conference on multisensor, multisource information fusion

作者： Horney, T Ahlberg, J Grönwall, C Folkesson, M Silvervarg, K Fransson, J Klasén, L Jungert, E Lantz, F Ulvklo, M Swedish Def Res Agcy FOI Dept Data & Informat Fus Div Command & Control Syst SE-58111 Linkoping Sweden

ISBN: (纸本)0819453579

We present an approach to a general decision support system. The aim is to cover the complete process for automatic target recognition, from sensor data to the user interface. The approach is based on a query-based information system, and include tasks like feature extraction from sensor data, data association, data fusion and situation analysis. Currently, we are working with data from laser radar, infrared cameras, and visual cameras, studying target recognition from cooperating sensors on one or several platforms. The sensors are typically airborne and at low altitude. The processing of sensor data is performed in two steps. First, several attributes are estimated from the (unknown but detected) target. The attributes include orientation, size, speed, temperature etc. These estimates are used to select the models of interest in the matching step, where the target is matched with a number of target models, returning a likelihood value for each model. Several methods and sensor data types are used in both steps. The user communicates with the system via a visual user interface, where, for instance, the user can mark an area on a map and ask for hostile vehicles in the chosen area. The user input is converted to a query in SigmaQL, a query language developed for this type of applications, and an ontological system decides which algorithms should be invoked and which sensor data should be used. The output from the sensors is fused by a fusion module and answers are given back to the user. The user does not need to have any detailed technical knowledge about the sensors (or which sensors that are available), and new sensors and algorithms can easily be plugged into the system.

关键词： automatic target recognition multisensor fusion query languages

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A Java implementation of the probabilistic argumentation system for data fusion in missile defense applications

A Java implementation of the probabilistic argumentation sys...

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Conference on multisensor, multisource information fusion

作者： Chan, M Hansen, T Monney, PA Baker, T Lockheed Missiles & Space Co Inc Sunnyvale CA 94089 USA

ISBN: (纸本)0819453579

In missile defense target recognition applications, knowledge about the problem may be imperfect, imprecise, and incomplete. Consequently, complete probabilistic models are not available. In order to obtain robust inference results and avoid making inaccurate assumptions, the probabilistic argumentation system (PAS) is employed. In PAS, knowledge is encoded as logical rules with probabilistically weighted assumptions. These rules map directly to Dempster-Shafer belief functions, which allow for uncertainty reasoning in the absence of complete probabilistic models. The PAS can be used to compute arguments for and against hypotheses of interest, and numerical answers that quantify these arguments. These arguments can be used as explanations that describe how inference results are computed. This explanation facility can also be used to validate intelligence information, which can in turn improve inference results. This paper presents a Java implementation of the probabilistic argumentation system as well as a number of new features. A rule-based syntax is defined as a problem encoding mechanism and for Monte Carlo simulation purposes. In addition, a graphical user interface (GUI) is implemented so that users can encode the knowledge database, and visualize relationships among rules and probabilistically weighted assumptions. Furthermore, a graphical representation is used to display these rules, which in turn provides graphical explanations of the inference results. We provide examples that illustrate how classical pattern recognition problems can be solved using canonical rule sets, as well as examples that demonstrate how this new software can be used as an explanation facility to describe how the inference results are determined.

关键词： Java implementation probabilistic argumentation system data fusion rule-based inference graphical user interface

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A mathematical framework for the optimization of rejection and ROC thresholds in the fusion of correlated sensor data

A mathematical framework for the optimization of rejection a...

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Conference on multisensor, multisource information fusion

作者： Laine, TI Bauer, KW USAF Inst Technol Dept Operat Sci Wright Patterson AFB OH 45433 USA

ISBN: (纸本)0819453579

In pattern recognition applications, significant costs can be associated with various decision options and a minimum acceptable level of confidence is often required. Combat target identification is one example where the incorrect labeling of Targets and Non-targets incurs substantial costs: yet, these costs may be difficult to quantify. One way to increase decision confidence is through fusion of data from multiple sources or from multiple looks through time. Numerous methods have been published to determine optimal rules for the fusion of decision labels or to determine the Bayes' optimal decision if prior and posterior probabilities along with decision costs can be accurately estimated. This paper introduces a mathematical framework to optimize multiple decision thresholds subject to a decision maker's preferences. when a continuous measure of class membership is available. Decision variables may include rejection thresholds to specify non-declaration regions and ROC thresholds to explore viable trite positive and false positive Target classification rates, where the feasible space can be partially visualized by a 3D ROC surface. This methodology yields an optimal class declaration rule subject to decision maker preferences without using explicit costs associated with each type of decision. Some properties of this optimization framework are shown for Gaussian distributions representing Target and Non-target classes with various prior probabilities and correlation levels between simulated multiple sensor looks.

关键词： combat identification (CID) fusion receiver operating characteristic (ROC). 3-D ROC surface automatic taraet recosinition (ATR) performance rejection

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