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检索条件"任意字段=Conference on Sensor Fusion - Architectures, Algorithms, and Applications III"

共 369 条记录，以下是321-330 订阅

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Study of a modified Dempster-Shafer approach using an expected utility interval decision rule

Study of a modified Dempster-Shafer approach using an expect...

引用

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

作者： Cheaito, Ali Lecours, Michel Bosse, Eloi Universite Laval Que Canada

The Combination operation of the conventional Dempster-Shafer algorithm has a tendency to increase exponentially the number of propositions involved in bodies of evidence by creating new ones. The aim of this paper is to explore a 'modified Dempster-Shafer' approach of fusing identity declarations emanating from different sources which include a number of radars, IFF and ESM systems in order to limit the explosion of the number of propositions. We use a non-ad hoc decision rule based on the expected utility interval (EUI) to select the most probable object in a comprehensive Platform Data Base (PDB) containing all the possible identity values that a potential target may take. We study the effect of the redistribution of the confidence levels of the eliminated propositions which otherwise overload the real-time data fusion system;these eliminated confidence levels can in particular be assigned to ignorance, or uniformly added to the remaining propositions and the ignorance. A scenario has been selected to demonstrate the performance of our modified Dempster-Shafer method of evidential reasoning.

关键词： sensor data fusion

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General software design for multisensor data fusion

General software design for multisensor data fusion

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

作者： Junliang, Zhang Yuming, Zhao 54th Research Inst of Electronic Industry Shijiazhuang China

In this paper a general method of software design for multisensor data fusion is discussed in detail, which adopts object-oriented technology under UNIX operation system. The software for multisensor data fusion is divided into six functional modules: data collection, database management, GIS, target display and alarming data simulation etc. Furthermore, the primary function, the components and some realization methods of each modular is given. The interfaces among these functional modular relations are discussed. The data exchange among each functional modular is performed by interprocess communication IPC, including message queue, semaphore and shared memory. Thus, each functional modular is executed independently, which reduces the dependence among functional modules and helps software programming and testing. This software for multisensor data fusion is designed as hierarchical structure by the inheritance character of classes. Each functional modular is abstracted and encapsulated through class structure, which avoids software redundancy and enhances readability.

关键词： Computer software

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Bio-fusion for intelligent system control

Bio-fusion for intelligent system control

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

作者： Norseen, John D. Kropotov, Juri D. Kremen, Inna Z. Lockheed Martin Aeronautical Co

We present a realistic neural network - the canonical cortical module - built on basic principles of cortical organization. These principles are: opponent cells principle, assembly principle, canonical cortical circuit principle and modular principle. When applied to visual images, the network explains orientational and spatial frequency filtering functions of neurons in the striate cortex. Two patterns of joint distribution of opponent cells in the inhibitory cortical layer are presented: pinwheel and circular. These two patterns provide two Gestalt descriptions of local (within the frames of one module) visual image: circle-ness and cross-ness. These modules were shown to have a power for shape detection and texture discrimination. They also provide an enhancement of signal-to-noise ratio of input images. Being modality independent, the canonical cortical module seems to be good tool for bio-fusion for intelligent system control.

关键词： Neural networks

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Distributed event driven architectures for evolutionary sensor fusion

Distributed event driven architectures for evolutionary sens...

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conference on sensor fusion - architectures, algorithms, and applications II

作者： Lake, RT Dynam Control Syst Inc Delta BC Canada

ISBN: (纸本)0819428256

The next decade will require the development of complex sensor systems that integrate data from a large number of sensor elements. Such systems will play important roles in a wide variety of industrial and defense systems, as the fusion of multiple sources of information is crucial to sensor operation in noisy environments, and in complex decision making. The arrival of ubiquitous processing elements is one requirement for the development of such systems;however, the ability to connect and integrate these elements at the logical level is the more limiting aspect of their development. Furthermore, it is unlikely that such systems can be developed in a single linear process. It is much more probable that such systems will need to be evolved over time, perhaps a substantial period of time, and as result the ability to logically interconnect heterogeneous elements in an evolutionary manner will be of great importance. This paper outlines some approaches to this problem based on the distributed object-computing model as introduced in the OMG CORBA. It is our belief that this technology is maturing to the point that it could form the foundations for a sensor architecture that would support the evolutionary development of complex sensor networks.

关键词： distributed objects sensor networks embedded CORBA event-driven evolution

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A maximum likelihood approach for multisensor data fusion applications

A maximum likelihood approach for multisensor data fusion ap...

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conference on sensor fusion - architectures, algorithms, and applications II

作者： Zhou, YF Leung, H Telexis Corp Canada Ottawa ON K1V 7P2 Canada

ISBN: (纸本)0819428256

In this paper, we proposed a maximum likelihood fusion approach for multisensor fusion applications. The proposed approach was based on a parametric modeling of the noise covariance and formulated in the transformed noise subspace. It could solve the fusion problems when the sensor noises are correlated and the scaling coefficients unknown. The approach could also deal with nonstationary signals. We showed that in the optimization process, the computation of the noise parameters and the scaling coefficients were separable leading to a reduced optimization dimensionality and computational complexity. Computer simulations were used to demonstrate the effectiveness of the proposed fusion approach.

关键词： maximum likelihood minimum variance least squares data fusion multisensor tracking nonstationarity unknown noise sensory information statistical consistency

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fusion of LWIR sensor data by Bayesian methods

Fusion of LWIR sensor data by Bayesian methods

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conference on sensor fusion - architectures, algorithms, and applications II

作者： Inguva, R Garrison, G EW Enterprises Inc Dba Sci & Technol Consultants Huntsville AL 35805 USA

ISBN: (纸本)0819428256

Using Bayesian statistical methods a formulation is setup for fusing multi band data from LWIR sensors. This formulation is illustrated with applications to synthetic data consisting of 100 signatures in the wavelength bands 6-10 mu m, 11-16 mu m and 17-21 mu m. Following the works of Jaynes, and Bretthorst, a Bayesian formulation is given for detrending the time seriesdata for the emissive area, followed by estimations of frequencies and their amplitudes. This formulation is illustrated with analysis of the synthetic data.

关键词： sensors Data modeling sensor fusion Long wavelength infrared Data fusion Infrared sensors Statistical analysis Data analysis Signal to noise ratio Statistical methods

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Proceedings of SPIE: sensor fusion: architectures, algorithms, and applications II

Proceedings of SPIE: Sensor Fusion: Architectures, Algorithm...

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sensor fusion: architectures, algorithms and applications II

This Volume 3376 of the conference proceedings contains 22 papers. Topics discussed include sensor fusion, sensor fusion architectures, feature and decision level fusion, data and image level fusion and sensor fusion ... 详细信息

关键词： sensor data fusion

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Atmospheric attenuation reduction through multi-sensor fusion

Atmospheric attenuation reduction through multi-sensor fusio...

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conference on sensor fusion - architectures, algorithms, and applications II

作者： Grewe, L Brooks, RR Calif State Univ Monterey Bay Inst Commun Sci & Technol Seaside CA 93955 USA

ISBN: (纸本)0819428256

The visualization of a scene in murky atmospheric conditions is improved by fusing multiple images. A key feature of this system is the use of the wavelet domain in the fusion process. Many possible fusion formulas in this domain exist and to find the "best" formula, we formulate an optimization problem. We assume a set of training data consisting of a sequence of images with the presence of atmospheric effects and the corresponding image with no atmospheric effects present (ground truth). Next, we perform a search over the parameter space of our "generic fusion formula" attempting to minimize the error between the original ground truth image and the image created by fusing the noisy data. Using the resulting "best" fusion formula, we have created a system for pixel level fusion. Experimental results are shown and discussed. Possible applications of this system include processing of outdoor security system data, filters for outdoor vehicle image data and use in heads-up displays.

关键词： sensor fusion wavelets tabu search fog atmospheric attenuation

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The data fusion system architecture for unattended ground sensors

The data fusion system architecture for unattended ground se...

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conference on sensor fusion - architectures, algorithms, and applications II

作者： Zhang, JL Zhao, YM 54 Res Inst Elect Ind Shijiazhuang 050081 Hebei Province Peoples R China

ISBN: (纸本)0819428256

In this paper,it develops an artificial intelligence method that uses object-oriented approach to construct the blackboard of data fusion for unattented ground sensors including geophone sensor, acoustic sensor, pressure sensor, infra-red sensor, magnetic sensor, image sensor etc.. It can perform detection, correlation, association and estimation to the sensors' output and obtain the exact recognition of targets, the number of target groups and the estimation for both the states of targets and the situation and threat. The whole blackboard is divided into three regions, including: single sensor fusion region, multisensor fusion region and threat estimation region. The three regions are expressed in classes. Knowledges of each domain in three regions are also expressed by classes and encapsulated in class hierarchy structure. Thus the whole blackboard can be viewed as object forest, the distributed knowledge inference can be realized by object reference. Both statistics and hierarchy inference approaches are used in the blackboard structure so as to efficiently perform fusion and inference. Furthermore,The method is realized in C++ language and demonstrated by the simulation of sensor alarming datum under battlefield environment.

关键词： sensor data fusion data association target recognition state estimation

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To fuse or not to fuse: Fuser versus best classifier

To fuse or not to fuse: Fuser versus best classifier

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conference on sensor fusion - architectures, algorithms, and applications II

作者： Rao, NSV Oak Ridge Natl Lab Oak Ridge TN 37831 USA

ISBN: (纸本)0819428256

A sample from a class defined on a finite-dimensional Euclidean space and distributed according to an unknown distribution is given. We are given a set of classifiers each of which chooses a hypothesis with least misclassification error from a family of hypotheses. We address the question of choosing the classifier with the best performance guarantee versus combining the classifiers using a fuser. We first describe a fusion method based on isolation property such that the performance guarantee of the fused system is at least as good as the best of the classifiers. For a more restricted case of deterministic classes, we present a method based on error set estimation such that the performance guarantee of fusing all classifiers is at least as good as that of fusing any subset of classifiers.

关键词： classification finite sample analysis distributed detection fusion of classifiers

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