Wireless sensor networks have potential to monitor environments for both military and civil applications. Due to inhospitable conditions these sensors are not always deployed uniformly ion the area of interest. Since ...
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Wireless sensor networks have potential to monitor environments for both military and civil applications. Due to inhospitable conditions these sensors are not always deployed uniformly ion the area of interest. Since sensors are generally constrained in on-board energy supply, efficient management of the network is crucial to extend the life of the sensors. sensors' energy cannot support long haul communication to reach a remote command site and thus requires many levels of hops or a gateway to forward the data on behalf of the sensor. In this paper, we propose an algorithm to network these sensors in to well define clusters with less energy-constrained gateway nodes acting as cluster-heads, and balance load among these gateways. Simulation results show how our approach can balance the load and improve the lifetime of the system.
The proceedings contains 31 papers from the conference on sensorfusion: architectures, algorithms, and applications VI. Topics discussed include: adaptive sequential Bayesian classification using Page's test;onto...
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The proceedings contains 31 papers from the conference on sensorfusion: architectures, algorithms, and applications VI. Topics discussed include: adaptive sequential Bayesian classification using Page's test;ontology-based multiagent approach to data fusion;unified approach to the fusion of imperfect data;fusion approach to stereo vision uncertainity;robust fusion with reliabilities weights;distributed air-to-ground targeting;and fuser design for thick film pH sensor electrodes using emperical data.
In this paper we describe the nature of the problem of surveillance of airport surface movement. We describe the characteristics, performance, and unique problems of various airport sensors available, and the need to ...
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ISBN:
(纸本)0819444812
In this paper we describe the nature of the problem of surveillance of airport surface movement. We describe the characteristics, performance, and unique problems of various airport sensors available, and the need to develop a fusion system to provide an integrated surveillance picture. Parallel sensorfusion developments are described in terms of their applicability to the sensorfusion task in surface surveillance. Paradigms for sensorfusion, including alternative architectures, algorithms, and performance metrics will be described. Finally we describe system implementation and quantitative performance of sensorfusion applied to the surface surveillance problem at demonstrations in Atlanta Hartsfield International Airport (1998, ATL), Dallas Fort Worth International Airport (1999, 2000, DFW), and in-process and planned future developments in sensorfusion.
作者：
Braun, JJMIT
Lincoln Lab Lexington MA 02420 USA
This paper presents an approach to multisensor data fusion based on the use of Support Vector Machines (SVM). The approach is investigated using simulated generic sensor data, representative of data imperfections that...
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ISBN:
(纸本)0819444812
This paper presents an approach to multisensor data fusion based on the use of Support Vector Machines (SVM). The approach is investigated using simulated generic sensor data, representative of data imperfections that may be encountered in multisensorfusionapplications. In particular the issue of data incompleteness is addressed and a method exploiting vicinity of training points is proposed for incompleteness correction. The paper also investigates applicability of vicinal kernels in SVM-based sensor data fusion.
Data fusion architecture can be categorized into data-level fusion, feature-level fusion and decision-level fusion by its characteristics. In this paper, we provide a new target identification fusion technology in whi...
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ISBN:
(纸本)0819444812
Data fusion architecture can be categorized into data-level fusion, feature-level fusion and decision-level fusion by its characteristics. In this paper, we provide a new target identification fusion technology in which we adopt not only feature-level fusion approach but also decision-level fusion approach in order to consider even sensors' uncertain reports and improve fusion performance. In feature-level fusion stage, we applied fuzzy set theory and Bayesian theory based on the sensor data, such as sensor parameter and detected target information. In decision-level fusion stage, we applied advanced Bayesian theory to decide final target identification. Experimental results with various kinds of sensor data have verified the robustness of our algorithms comparing with conventional feature-level, decision-level fusion algorithms.
In this paper, a series of knowledge fusion operators are motivated and analyzed. They are defined in a semantic way, although syntactical facets of knowledge are taken into account. More precisely, they rely on a ran...
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ISBN:
(纸本)0819444812
In this paper, a series of knowledge fusion operators are motivated and analyzed. They are defined in a semantic way, although syntactical facets of knowledge are taken into account. More precisely, they rely on a rank-ordering of interpretations that is based on the number of formulas that the interpretations falsify. It is briefly discussed how these operators could be refined, by taking into account various distribution policies of the falsified information among the knowledge sources, syntactical properties of formulas to be fused and forms of integrity constraints preference among literals.
Modern technology provides a great amount of information. In computer monitoring systems or computer control systems, especially real-time expert systems, in order to have the situation in hand, we need one or two par...
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ISBN:
(纸本)0819444812
Modern technology provides a great amount of information. In computer monitoring systems or computer control systems, especially real-time expert systems, in order to have the situation in hand, we need one or two parameters to express the quality and/or security of the whole system. This paper presents a principle for synthesizing measurements of multiple system parameters into a single parameter. This principle has been successfully applied in the monitoring of an ultra-energy efficient house in Canada and other applications.
This paper deals with multisensor statistical interval interval estimation fusion, that is, data fusion from multiple statistical interval estimators for the purpose of estimation of a parameter theta. A multisensor c...
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ISBN:
(纸本)0819444812
This paper deals with multisensor statistical interval interval estimation fusion, that is, data fusion from multiple statistical interval estimators for the purpose of estimation of a parameter theta. A multisensor convex linear statistic fusion model for optimal interval estimation fusion is established. A Gaussian-Seidel iteration algorithm for searching for the fusion weights is proposed. In particular, we suggest convex combination minimum variance fusion that reduces huge computation of fusion weights and yields near optimal estimate performance generally, and moreover, may achieve exactly optimal performance for some specific distributions of obsevation data. Numerical examples are provided and give additional support to the above results.
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