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

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PERFORMANCE AND LIMITATIONS OF DISTRIBUTED INFERENCE AND INFORMATION fusion IN WIRELESS sensor NETWORK applications

PERFORMANCE AND LIMITATIONS OF DISTRIBUTED INFERENCE AND INF...

引用

作者： Sherry, Richard Ray PennState University Libraries

学位级别：Doctor of Philosophy

Recent advances in sensor design and miniaturization have provided the opportunity for the creation of large distributed wireless sensor networks. There has been significant progress in combining sensing, processing, data storage and communications capabilities, in network self organization, and in optimizing communication architectures. In contrast to most other network applications, wireless sensor networks face a number of special challenges and constraints resulting from 1) lack of hardwired connections (no external power sources, low communications bandwidths, higher communication error rates), 2) small physical size (small onboard energy supply, small antennas/acoustic transducers, small low energy sensors) and 3) elevated sensor node failure rates. One of the key remaining challenges is in the area of inference and information fusion (aggregating/filtering/interpreting the sensor data into useful high level knowledge). Many authors have advocated the use of local distributed inference and fusion algorithms such as the iterative message-passing belief propagation algorithms employed on probabilistic graphical models (Bayesian Networks and Markov Random Fields). However, little research has been performed to assess the performance of these algorithms under the special constraints imposed by wireless sensor network applications. This dissertation reports on a study investigating issues associated with application of these algorithms to realistic wireless sensor networks configurations. This research has produced results delineating the performance and limitations including communications requirements, energy resource requirements and the impacts of different topologies and architectures such as hierarchical/non-hierarchical topologies, centralized or distributed processing, localized (in local node clusters) or full network models, and node cluster size.

关键词： wireless sensor networks information fusion data fusion

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Performance and limitations of distributed inference and information fusion in wireless sensor network applications

Performance and limitations of distributed inference and inf...

引用

作者： Sherry, Richard R. The Pennsylvania State University

学位级别：Ph.D.

Recent advances in sensor design and miniaturization have provided the opportunity for the creation of large distributed wireless sensor networks. There has been significant progress in combining sensing, processing, data storage and communications capabilities, in network self organization, and in optimizing communication architectures. In contrast to most other network applications, wireless sensor networks face a number of special challenges and constraints resulting from (1) lack of hardwired connections (no external power sources, low communications bandwidths, higher communication error rates), (2) small physical size (small onboard energy supply, small antennas/acoustic transducers, small low energy sensors) and (3) elevated sensor node failure rates. One of the key remaining challenges is in the area of inference and information fusion (aggregating/filtering/interpreting the sensor data into useful high level knowledge). Many authors have advocated the use of local distributed inference and fusion algorithms such as the iterative message-passing belief propagation algorithms employed on probabilistic graphical models (Bayesian Networks and Markov Random Fields). However, little research has been performed to assess the performance of these algorithms under the special constraints imposed by wireless sensor network applications. This dissertation reports on a study investigating issues associated with application of these algorithms to realistic wireless sensor networks configurations. This research has produced results delineating the performance and limitations including communications requirements, energy resource requirements and the impacts of different topologies and architectures such as hierarchical/non-hierarchical topologies, centralized or distributed processing, localized (in local node clusters) or full network models, and node cluster size.

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Optimal sensor dimension reduction in estimation fusion

Optimal sensor dimension reduction in estimation fusion

引用

conference on Multisensor, Multisource Information fusion

作者： Song, EB Zhu, YM Zhou, J Sichuan Univ Dept Math Chengdu 610064 Peoples R China

ISBN: (纸本)0819457981

When there exists the limitation of communication bandwidth between sensors and a fusion center, one needs to optimally pre-compress sensor outputs-sensor observations or estimates before sensors' transmission to obtain a constrained optimal estimation at the fusion center in terms of the linear minimum error variance criterion. This paper will give an analytic solution of the optimal linear dimensionality compression matrix for the single sensor case and analyze the existence of the optimal linear dimensionality compression matrix for the multisensor case, as well as how to implement a Gauss-Seidel algorithm to search for an optimal solution to linear dimensionality compression matrix.

关键词： multisensor estimation fusion linear compression minimum variance estimation

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Product-based multiresolution image fusion

Product-based multiresolution image fusion

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conference on Multisensor, Multisource Information fusion

作者： Ostrem, T Kozaitis, SP Florida Inst Technol Dept Elect & Comp Engn Melbourne FL 32901 USA

ISBN: (纸本)0819457981

We combined images from different sensors that were enhanced by multiscale products of the wavelet coefficients. Using the wavelet transform, we used a multiresolution analysis to form products of coefficients across scales. Then, a fusion rule was applied to the product images to determine how the original images could be combined. Using this approach, we were able to decrease the sensitivity of the fusion process to noise.

关键词： multiresolution image processing sensor fusion wavelet transform

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A controllable sensor management algorithm capable of learning

A controllable sensor management algorithm capable of learni...

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conference on Multisensor, Multisource Information fusion

作者： Osadciw, L Veeramacheneni, K Syracuse Univ Syracuse NY 13244 USA

ISBN: (纸本)0819457981

sensor management technology progress is challenged by the geographic space it spans, the heterogeneity of the sensors, and the real-time timeframes within which plans controlling the assets are executed. This paper presents a new sensor management paradigm and demonstrates its application in a sensor management algorithm designed for a biometric access control system. This approach consists of an artificial intelligence (AI) algorithm focused on uncertainty measures, which makes the high level decisions to reduce uncertainties and interfaces with the user, integrated cohesively with a bottom up evolutionary algorithm, which optimizes the sensor network's operation as deter-mined by the AI algorithm. The sensor management algorithm presented is composed of a Bayesian network, the AI algorithm component, and a swarm optimization algorithm, the evolutionary algorithm. Thus, the algorithm can change its own performance goals in real-time and will modify its own decisions based on observed measures within the sensor network. The definition of the measures as well as the Bayesian network determine the robustness of the algorithm and its utility in reacting dynamically to changes in the global system.

关键词： sensor networks sensor management data fusion swarm algorithms Bayesian networks

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Multispectral sensor fusion using the projection-slice theorem

Multispectral sensor fusion using the projection-slice theor...

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conference on Multisensor, Multisource Information fusion

作者： Riasati, VR Ro, S Sci Applicat Int Corp San Diego CA 92121 USA

ISBN: (纸本)0819457981

In this paper we discuss the utilization of the Projection-Slice Theorem, PST, to reduce a data set that display each multiple spectral band representation of an image and to extract variant features from those representation. Noise is removed from each of the one-dimensional projections of the images via PST and a wavelet transform thresholding process. The extracted features emphasize differences in spectral information from the same image and are combined through synthesis via the inverse PST. This sensor fusion method facilitates the design of filters to recognize an image with characteristics similar to the relevant features from each of the bands that have been incorporated in a combined multispectral/fused image. We present our method of feature extraction, wavelet noise removal, and data synthesis.

关键词： projection-slice theorem wavelet transforms data fusion multispectral components

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Current research on wavelet-based image fusion algorithms

Current research on wavelet-based image fusion algorithms

引用

conference on Multisensor, Multisource Information fusion

作者： Li, HH Guo, L Liu, H Northwestern Polytech Univ Coll Automat Xian 710072 Peoples R China

ISBN: (纸本)0819457981

Wavelet transform is efficiently applied to the area of image fusion because it's properties such as multiresolution analysis, accurate reconstruction and similarity to people's vision understanding. On the basis of reviewing the former research, the fusion results may be better than those with previous common fusion algorithms in many applications. This paper describes the principle and method of wavelet-based image fusion and analyzes it's current research and future trend from the two respects: the modality of wavelet transform and fusion rules.

关键词： wavelet transform image fusion multi-band wavelet wavelet package

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Multiple objective optimization for active sensor management

Multiple objective optimization for active sensor management

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conference on Multisensor, Multisource Information fusion

作者： Page, SF Dolia, AN Harris, CJ White, NM Univ Southampton Sch Elect & Comp Sci Southampton SO9 5NH Hants England

ISBN: (纸本)0819457981

The performance of a multi-sensor data fusion system is inherently constrained by the configuration of the given sensor suite. Intelligent or adaptive control of sensor resources has been shown to offer improved fusion performance in many applications. Common approaches to sensor management select sensor observation tasks that are optimal in terms of a measure of information. However, optimising for information alone is inherently sub-optimal as it does not take account of any other system requirements such as stealth or sensor power conservation. We discuss the issues relating to developing a suite of performance metrics for optimising multi-sensor systems and propose some candidate metrics. In addition it may not always be necessary to maximize information gain, in some cases small increases in information gain may take place at the cost of large sensor resource requirements. Additionally, the problems of sensor tasking and placement are usually treated separately, leading to a lack of coherency between sensor management frameworks. We propose a novel approach based on a high level decentralized information-theoretic sensor management architecture that unifies the processes of sensor tasking and sensor placement into a single framework. sensors are controlled using a minimax multiple objective optimisation approach in order to address probability of target detection, sensor power consumption, and sensor survivability whilst maintaining a target estimation covariance threshold. We demonstrate the potential of the approach through simulation of a multi-sensor, target tracking scenario and compare the results with a single objective information based approach.

关键词： sensor management resource allocation information filter multi-objective optimization target tracking

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MASM: A market architecture for sensor management in distributed sensor networks

MASM: A market architecture for sensor management in distrib...

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conference on Multisensor, Multisource Information fusion

作者： Viswanath, A Mullen, T Hall, D Garga, A Penn State Univ Sch Informat Sci & Technol University Pk PA 16802 USA

ISBN: (纸本)0819457981

Rapid developments in sensor technology and its applications have energized research efforts towards devising a firm theoretical foundation for sensor management. Ubiquitous sensing, wide bandwidth communications and distributed processing provide both opportunities and challenges for sensor and process control and optimization. Traditional optimization techniques do not have the ability to simultaneously consider the wildly non-commensurate measures involved in sensor management in a single optimization routine. Market-oriented programming provides a valuable and principled paradigm to designing systems to solve this dynamic and distributed resource allocation problem. We have modeled the sensor management scenario as a competitive market, wherein the sensor manager holds a combinatorial auction to sell the various items produced by the sensors and the communication channels. However, standard auction mechanisms have been found not to be directly applicable to the sensor management domain. For this purpose, we have developed a specialized market architecture MASM (Market architecture for sensor Management). In MASM, the mission manager is responsible for deciding task allocations to the consumers and their corresponding budgets and the sensor manager is responsible for resource allocation to the various consumers. In addition to having a modified combinatorial winner determination algorithm, MASM has specialized sensor network modules that address commensurability issues between consumers and producers in the sensor network domain. A preliminary multi-sensor, multi-target simulation environment has been implemented to test the performance of the proposed system. MASM outperformed the information theoretic sensor manager in meeting the mission objectives in the simulation experiments.

关键词： sensor management market-oriented programming combinatorial auctions genetic algorithms information theory

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sensor fusion for coastal waters surveillance

Sensor fusion for coastal waters surveillance

引用

conference on Multisensor, Multisource Information fusion

作者： Doshi, B Benmohamed, L Chimento, P Wang, IJ Johns Hopkins Univ Appl Phys Lab Laurel MD 20723 USA

ISBN: (纸本)0819457981

We describe a large sensor field whose mission is to protect coastal waters by detecting objects like submarines. The system is buoy-based and distributed over a littoral area. The opportunities for detection are short and intermittent and the signal to noise ratio is low. The topology of the field changes with time due to currents, wind, tides and storms. The field has a number of gateway nodes that have the capability to transmit off-field through a satellite, a ship or a plane. We propose an approach to fusion that includes on-buoy processing, cooperative processing with nearest neighbors and the potential for off-field processing. Each stage of processing tries both to minimize false positive events and to maximize the probability of detection when an object is present. It also tries to minimize power used in order to prolong the life of the field. We analyze the optimal placement of gateway nodes in the field to minimize power consumption and maximize reliability and probability of successful off-field transmission. We analyze the duty cycles of the sensor and gateway nodes to optimize lifetime. We also analyze the traffic that the field will be expected to handle in order to support network control and coordination, distributed fusion, off-field communication (including queries and responses, and reporting of detection events), forwarding of traffic through individual sensor nodes toward gateways or for fusion.

关键词： distributed sensor field sensor networks coastal surveillance

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