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

共 2100 条记录，以下是1361-1370 订阅

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Selection of fusion operations using rank-score diversity for robot mapping and localization

Selection of fusion operations using rank-score diversity fo...

引用

conference on Multisensor, Multisource Information fusion

作者： Lyons, Damian M. Hsu, D. Frank Ma, Qiang Wang, Liang Fordham Univ Comp Vis & Robot Lab Dept Comp & Informat Sci Bronx NY 10458 USA

ISBN: (纸本)9780819466938

In this paper, we evaluate the use of a rank-score diversity measure for selecting sensory fission operations for a robot localization and mapping application. Our current application involves robot mapping and navigation in art outdoor urban search and rescue situation in which we have many similar and mutually occluding landmarks. The robot is a 4-wheel direct drive platform equipped with visual, stereo depth and ultrasound sensors. In such an application it's difficult to make useful and realistic assumptions about the sensor or environment statistics. Combinatorial fusion Analysis(CFA) is used to develop an approach to fission with unknown sensor and environment statistics. A metric is proposed that will indicate when fission from a set of fission alternatives will produce a more accurate estimation of depth than either sonar or stereo alone and when not. Experimental results are reported to illustrate that two CFA criteria are viable predictors to distinguish between positive fission cases (the combined system performs better than or equal to the individual systems) and negative cases.

关键词： sensors Environmental sensing Associative arrays Ultrasonography sensor fusion Imaging systems Calibration Statistical analysis Stereoscopic cameras Visualization

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Real-time target tracking simulations in large disparate sensor networks

Real-time target tracking simulations in large disparate sen...

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conference on Multisensor, Multisource Information fusion

作者： Lin, Hong Rushing, John Graves, Sara Criswell, Evans Tanner, Steve Univ Alabama Huntsville AL 35799 USA

ISBN: (纸本)9780819466938

Real-time target tracking in large disparate sensor networks has been simulated with a parallelized search based data fusion algorithm using a simulated annealing approach. The networks are composed of large numbers of low fidelity binary and bearing-only sensors, and small numbers of high fidelity position sensors over a large region. The primitive sensors provide limited information, not sufficient to locate targets;the position sensors can report both range and direction of the targets. Target positions are determined through fusing information from all types of sensors. A score function, which takes into account the fidelity of sensors of different types, is defined and used as the evaluation function for the optimization search. The fusion algorithm is parallelized using spatial decomposition so that the fusion process can finish before the arrival of the next set of sensor data. A series of target tracking simulations are performed on a Linux cluster with communication between nodes facilitated by the Message Passing Interface (MPI). The probability of detection (POD), false alarm rate (FAR), and average deviation (AVD) are used to evaluate the network performance. The input target information used for all the simulations is a set of target track data created from a theater level air combat simulation.

关键词： disparate sensor network parallel data fusion simulated annealing real-time target tracking

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A Bayesian framework for ATR decision-level fusion experiments

A Bayesian framework for ATR decision-level fusion experimen...

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conference on Multisensor, Multisource Information fusion

作者： Morgan, Douglas R. Ross, Timothy D. Consultant BAE Mountain View CA USA AFRL SNAR Wright Patterson AFB OH 45433 USA

ISBN: (纸本)9780819466938

The US Air Force Research Laboratory (AFRL) fusion for Identifying Targets Experiment (FITE) program aims to determine the benefits of decision-level fusion (DLF) of Automatic Target Recognition (ATR) products. This paper describes the Bayesian framework used to characterize the trade-space for DLF approaches and applications. The overall fusion context is represented as a Bayesian network and the fusion algorithms use Bayesian probability computations. Bayesian networks conveniently organize the large sets of random variables and distributions appearing in fusion system models, including models of operating conditions, prior knowledge, ATR performance, and fusion algorithms. The relationship between fuser performance and these models may be analytically stated (the FITE equation), but must be solved via stochastic system modeling and Monte Carlo simulation. A key element of the DLF trade-space is the degree to which the various models depend on ATR operating conditions, since these will determine the fuser's complexity and performance and will suggest new requirements on source ATRs.

关键词： Automatic target recognition sensors Monte Carlo methods Performance modeling Data fusion Detection and tracking algorithms Systems modeling Autoregressive models Data modeling Environmental sensing

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E²RINA:: An energy efficient and reliable in-network aggregation for clustered wireless sensor networks

E<SUP>2</SUP>RINA:: An energy efficient and reliable in-netw...

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IEEE Wireless Communications and Networking conference

作者： Necchi, L. Bonivento, A. Lavagno, L. Sangiovanni-Viticentelli, A. Vanzago, L. Politecn Torino Turin Italy Univ Calif Berkeley Berkeley CA 94720 USA STMicroelect Geneva Switzerland

ISBN: (纸本)9781424406586

We present E(2)RINA, an aggregation algorithm for wireless sensor network applications characterized by clustered topologies, such as building automation and manufacturing plants. Thank to an efficient use of the wireless channel, E(2)RINA offers the robustness of the gossip-based algorithms and, at the same time, the energy performance of the faster cluster head-based algorithms. We also developed a mathematical model to predict the performance of the algorithm with respect to the free variables without the need of extensive simulations. We validate our model and the robustness of E(2)RINA by running a simulation model of a test case consisting of a cluster of MICA nodes.

关键词： building management systems sensor fusion wireless sensor networks E2RINA MICA nodes clustered wireless sensor networks gossip-based algorithms in-network aggregation algorithm wireless channel Building management systems wireless channels sensor fusion load capacity based algorithm evolutionary algorithm Hash based algorithms CASING INSPECTION Building automation algorithms Energy efficiency

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Novel classification fusion techniques for military target classification

Novel classification fusion techniques for military target c...

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conference on Multisensor, Multisource Information fusion

作者： Liu, Ting Lampropoulos, George A. AUG Signals 73 Richmond St W Toronto ON Canada

ISBN: (纸本)9780819466938

The objective of this paper is to develop novel classification structures for military targets detection and recognition by employing different fusion techniques. In real applications, the great diversity of materials in the background areas and the similarity between the background and target signatures result in high false alarm rates and large miss classification errors. In this paper, three new systems are proposed using different fusion techniques: pixel level fusion, decision fusion, and classification fusion employing confidence vectors. These new developed systems are tested using an experimental data to show its effectiveness.

关键词： hyperspectral detection classification fusion confusion matrix false alarm

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Multisensor fusion and integration: algorithms, applications, and future research directions

Multisensor fusion and integration: Algorithms, applications...

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IEEE International conference on Mechatronics and Automation

作者： Luo, Ren C. Chou, Ying Chih Chen, Ogst Univ Chung Chang Dept Elect Engn Chiayi Taiwan

ISBN: (纸本)9781424408276

Multisensor fusion and integration is a rapidly evolving research area and requires interdisciplinary knowledge in control theory, signal processing, artificial intelligence, probability and statistics, etc. The advantages gained through the use of redundant, complementary, or, more timely information in a system can provide more reliable and accurate information. This paper provides an overview of current sensor technologies and describes the paradigm of multisensor fusion algorithms and applications of multisensor fusion in localization and tracking, robotics, identification and classification, vehicle sensing, and so on. Finally, future research directions of multisensor fusion technologies including microsensors, smart sensors, and adaptive fusion techniques are presented.

关键词： classification of sensors fusion algorithms multisensor fusion multisensor integration

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Multisensor data fusion schemes for wireless sensor networks

Multisensor data fusion schemes for wireless sensor networks

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IEEE 18th International conference Application-specific Systems, architectures and Processors, ASAP07

作者： Aguilar-Ponce, Ruth McNeely, Jason Baker, Abu Kumar, Ashok Bayoumi, Magdy Center for Advanced Computer Studies University of Louisiana at Lafayette PO Box 4330 Lafayette LA 70504-4330 United States

ISBN: (纸本)1424410274

Data fusion systems is an active research field with applications in several fields such as manufacturing, surveillance, air traffic control, robotics and remote sensing. The wide interest in wireless sensor networks has fueled the interest in data fusion as a medium to compress and interpret the collected data from the spatially distributed sensors. The present paper gives a general overview on the current state of data fusion schemes for wireless sensor networks. Specifically this paper presents a review on some of the commonly used techniques such as Kalman filtering, beamforming, transferable belief model, filter-based techniques and linear mean square estimator. ©2006 IEEE.

关键词： Kalman filters

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Convergence rate improvement in NMI-based multi-sensor image registration

Convergence rate improvement in NMI-based multi-sensor image...

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conference on Multisensor, Multisource Information fusion

作者： Lee, Jae Hak Ra, Jong Beom Korea Adv Inst Sci & Technol Sch Elect Engn & Comp Sci Taejon 305701 South Korea

ISBN: (纸本)9780819466938

Recently, a multi-sensor image fusion system has been widely investigated due to its growing applications. In the system, robust and accurate multi-modal image registration is essential and the fast registration is also important for many applications. In this paper, we propose a fast algorithm for registering multi-modal images that are acquired from two different sensors: electro-optic (EO) and infrared (IR). In the registration of multi-modal images, a normalized mutual information (NMI) based registration algorithm is preferred due to its robust and accurate performance. And the downhill simplex optimization scheme is popular in NMI-based registration because of its fast convergence rate. However, since it still suffers from a high computational complexity, the complexity should be reduced further for (semi) real-time applications. In this paper, we attempt to reduce the computational complexity in the registration process. We first modify the searching methodology for unconstrained function minimization in the ordinary downhill simplex algorithm, by suggesting new vertex movements for fast vertex contraction. Thereby, we can reduce the number of function evaluations. We also minimize the function evaluation time by linearizing the projective transformation in the interpolation routine. Simulation results show that the proposed algorithm noticeably reduces the computational complexity by 30% compared to the conventional NMI-based registration algorithm.

关键词： image registration normalized mutual information downhill simplex optimization

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In-situ calibration of sensor networks for distributed detection applications

In-situ calibration of sensor networks for distributed detec...

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3rd Intelligent sensors, sensor Networks and Information Processing conference

作者： Fabeck, Gernot Mathar, Rudolf Univ Aachen Rhein Westfal TH Aachen Inst Theoret Informat Technol Aachen Germany

ISBN: (纸本)9781424415014

In this paper, we present algorithms for in-situ calibration of sensor networks for distributed detection in the parallel fusion architecture. The wireless sensors act as local detectors and transmit preliminary detection results to an access point or fusion center for decision combining. In order to implement an optimal fusion center, both the performance parameters of each local detector (i.e., its probability of false alarm and probability of miss) as well as the wireless channel conditions must be known. However, in real-world applications these statistics may be unknown or vary in time. In our approach, the fusion center receives a collection of labeled samples from the sensor nodes after deployment of the network and calibrates the impact of individual sensors on the final detection result. In the case that local sensor decisions are independent, we employ maximum likelihood parameter estimation techniques, whereas in the case of arbitrarily correlated sensor Outputs, we use the method of kernel smoothing. The obtained fusion rules are both asymptotically optimal and show good performance for finite sample sizes.

关键词： sensor nodes

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Protocols for traffic safety using wireless sensor network

Protocols for traffic safety using wireless sensor network

引用

7th International conference on algorithms and architectures for Parallel Processing

作者： Lai, Yi Zheng, Yuan Cao, Jiannong Hong Kong Polytech Univ Internet & Mobile Comp Lab Dept Comp Kowloon Hong Kong Peoples R China

ISBN: (纸本)9783540729044

Wireless sensor Networks (WSNs) have attracted wide interests from both academic and industrial communities due to their diversity of applications. In this paper, we describe the design and implementation of energy-efficient protocols that can be used to improve traffic safety using WSN. Based on these protocols, we implement an intelligent traffic management system. Low-cost wireless sensor nodes are deployed on the roadbed and work collaboratively to detect potential collisions on the road. Experiments have been performed on this system and the results demonstrate the effectiveness of our protocols.

关键词： wireless sensor networks (WSNs) intelligent transportation pervasive computing

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