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检索条件"任意字段=Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2009"

共 283 条记录，以下是201-210 订阅

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Fuselets - An agent based architecture for fusion of heterogeneous information and data

Fuselets - An agent based architecture for fusion of heterog...

引用

Conference on multisensor, multisource information fusion

作者： Beyerer, Juergen Heizmann, Michael Sander, Jennifer Fraunhofer IITB Inst Informat & Datenverarbeitung Fraunhoferstr 1 D-76131 Karlsruhe Germany

ISBN: (纸本)0819462985

A new architecture for fusing information and data from heterogeneous sources is proposed. The approach takes criminalistics as a model. In analogy to the work of detectives, who investigate crimes, software agents are instantiated that pursue clues and try to consolidate or to dismiss hypotheses. Like their human pendants, they can, if questions beyond their competencies arise, consult expert agents. Within the context of a certain task, region, and time interval, specialized operations are applied to each relevant information source, e. g. IMINT, SIGINT, ACINT,..., HUMINT*, databases etc. in order to establish hit lists of first clues. Each clue is described by its pertinent facts, uncertainties, and dependencies in form of a local degree-of-belief (DoB) distribution dagger in a Bayesian sense. For each clue, an agent is instantiated which cooperates with other agents and experts. Expert agents support the use of different information sources. Consultation of experts capable of accessing certain information sources results in changes of the DoB of the pertinent clue. According to the significance of concentration of their DoB distribution, clues are abandoned or pursued further to formulate task specific hypotheses. Communication between the agents serves to find out whether different clues belong to the same cause and thus can be combined. At the end of the investigation process, the different hypotheses are evaluated by a jury and a final report is created that constitutes the fusion result. The approach proposed avoids calculating global DoB distributions by adopting a local Bayesian approximation and thus reduces the complexity of the problem essentially. Different information sources are transformed into DoB distributions using the maximum entropy paradigm and considering known facts as constraints. Nominal, ordinal, and cardinal quantities can be treated within this framework equally. The architecture is scalable by tailoring the number of agents according t

关键词： heterogeneous information sources Bayesian fusion agent technology criminalistics local Bayesian approach artificial intelligence man machine interaction representation of uncertainty

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Distributed sensor data compression algorithm

Distributed sensor data compression algorithm

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Conference on multisensor, multisource information fusion

作者： Ambrose, Barry Lin, Freddie Broadata Commun Inc 2545 W 237th St Torrance CA 90505 USA

ISBN: (纸本)0819462985

Theoretically it is possible for two sensors to reliably send data at rates smaller than the sum of the necessary data rates for sending the data independently, essentially taking advantage of the correlation of sensor readings to reduce the data rate. In 200 1, Caltech researchers Michelle Effros and Qian Zhao developed new techniques for data compression code design for correlated sensor data, which were published in a paper at the 2001 Data Compression Conference (DCC 2001). These techniques take advantage of correlations between two or more closely positioned sensors in a distributed sensor network. Given two signals, X and Y, the X signal is sent using standard data compression. The goal is to design a partition tree for the Y signal. The Y signal is sent using a code based on the partition tree. At the receiving end, if ambiguity arises when using the partition tree to decode the Y signal, the X signal is used to resolve the ambiguity. We have extended this work to increase the efficiency of the code search algorithms. Our results have shown that development of a highly integrated sensor network protocol that takes advantage of a correlation in sensor readings can result in 20-30% sensor data transport cost savings. In contrast, the best possible compression using state-of-the-art compression techniques that did not take into account the correlation of the incoming data signals achieved only 9-10% compression at most. This work was sponsored by MDA, but has very widespread applicability to ad hoc sensor networks, hyperspectral imaging sensors and vehicle health monitoring sensors for space applications.

关键词： information theory data compression sensor networks

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Pedestrian detection by Multi-spectral fusion

Pedestrian detection by Multi-spectral fusion

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Conference on multisensor, multisource information fusion

作者： Ma, Yunqian Wang, Zheng Bazakos, Mike Honeywell Labs 3660 Technol Dr Minneapolis MN 55418 USA Honeywell Technol Solut Lab Shanghai 201203 Peoples R China

ISBN: (纸本)0819462985

Security systems increasingly rely on the use of Automated Video Surveillance (AVS) technology. In particular the use of digital video renders itself to internet and local communications, remote monitoring, and to computer processing. AVS systems can perform many tedious and repetitive tasks currently performed by trained security personnel. AVS technology has already made some significant steps towards automating some basic security functions such as: motion detection, object tracking and event-based video recording. However, there are still many problems associated with just these automated functions, which need to be addressed further. Some examples of these problems are: the high "false alarm rate" and the "loss of track" under total or partial occlusion, when used under a wide range of operational parameters (day, night, sunshine, cloudy, foggy, range, viewing angle, clutter, etc.). Current surveillance systems work well only under a narrow range of operational parameters. Therefore, they need be hardened against a wide range of operational conditions. In this paper, we present a Multi-spectral fusion approach to perform accurate pedestrian segmentation under varying operational parameters. Our fusion method combines the "best" detection results from the visible images and the "best" from the thermal images. Commonly, the motion detection results in the visible images are easily affected by noise and shadows. The objects in the thermal image are relatively stable, but they may be missing some parts of the objects, because they thermally blend with the background. Our method makes use of the "best" object components and de-emphasize the "not best".

关键词： pedestrian detection sensor fusion surveillance level set

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Intent inference for attack aircraft through fusion

Intent inference for attack aircraft through fusion

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Conference on multisensor, multisource information fusion

作者： Ng, Gee Wah Ng, Khin Hua Yang, Rong Foo, Pek Hui DSO Natl Labs Adv Anal & Fus Lab 20 Sci Pk Dr Singapore 118230 Singapore Natl Univ Singapore Dept Computat Sci Singapore 117543 Singapore

ISBN: (纸本)0819462985

Intent inference is about analyzing the actions and activities of an adversarial force or target of interest to reach a conclusion (prediction) on its purpose. In this paper, we report one of our research works on intent inference to deter-mine the likelihood of an attack aircraft being tracked by a military surveillance system delivering its weapon. Effective intent inference will greatly enhance the defense capability of a military force in taking preemptive action against potential adversaries. It serves as early warning and assists the commander in his decision making. For an air defense system, the ability to accurately infer the likelihood of a weapon delivery by an attack aircraft is critical. It is also important for an intent inference system to be able to provide timely inference. We propose a solution based on the analysis of flight profiles for offset pop-up delivery. Simulation tests are carried out on flight profiles generated using different combinations of delivery parameters. In each simulation test, the state vectors of the tracked aircraft are updated via the application of the Interacting Multiple Model filter. Relevant variables of the filtered track (flight trajectory) are used as inputs to a Mamdani-type fuzzy inference system. The output produced by the fuzzy inference system is the inferred possibility of the tracked aircraft carrying out a pop-up delivery. We present experimental results to support our claim that the proposed solution is indeed feasible and also provides timely inference that will assist in the decision making cycle.

关键词： fusion intent inference flight profile fuzzy logic cognitive

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Data fusion cm a distributed heterogeneous sensor network

Data fusion cm a distributed heterogeneous sensor network

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multisensor, multisource information fusion: architectures, algorithms, and applications 2006

作者： Lamborn, Peter Williams, Pamela J. Mississippi State University 302 B Park Circle Place Starkville MS 39759 United States Sandia National Laboratories MS9159 P.O. Box 969 Livermore CA 94551-0969 United States

ISBN: (纸本)0819462985

Alarm-based sensor systems are being explored as a tool to expand perimeter security for facilities and force protection. However, the collection of increased sensor data has resulted in an insufficient solution that includes faulty data points. Data analysis is needed to reduce nuisance and false alarms, which will improve officials' decision making and confidence levels in the system's alarms. Moreover, operational costs can be allayed and losses mitigated if authorities are alerted only when a real threat is detected. In the current system, heuristics such as persistence of alarm and type of sensor that detected an event are used to guide officials' responses. We hypothesize that fusing data from heterogeneous sensors in the sensor field can provide more complete situational awareness than looking at individual sensor data. We propose a two stage approach to reduce false alarms. First, we use self organizing maps to cluster sensors based on global positioning coordinates and then train classifiers on the within cluster data to obtain a local view of the event. Next, we train a classifier on the local results to compute a global solution. We investigate the use of machine learning techniques, such as k-nearest neighbor, neural networks, and support vector machines to improve alarm accuracy. On simulated sensor data, the proposed approach identifies false alarms with greater accuracy than a weighted voting algorithm.

关键词： Sensor data fusion

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Current research on wavelet-based image fusion algorithms

Current research on wavelet-based image fusion algorithms

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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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A performance metric for belief fusion techniques

A performance metric for belief fusion techniques

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Conference on multisensor, multisource information fusion

作者： Friesel, MA Lockheed Martin Maritime Syst & Sensors Command & Control Syst Engn Moorestown NJ 08057 USA

ISBN: (纸本)0819457981

In this paper it is illustrated how Bayes equations and frequency data may use as a measure of performance for belief fusion algorithms. A review of Bayes equations for single and multiple sources is provided. A simple performance measure is then calculated and applied to some belief fusion examples from the literature. Their performance measures are qualitatively similar, but the quantitative differences among these techniques appear to be arbitrary.

关键词： belief theory datafusion performance characterization Bayes Dempster-Shafer combat identification

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information fusion and uncertainty management for biological multisensor systems

Information fusion and uncertainty management for biological...

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Conference on multisensor, multisource information fusion

作者： Braun, JJ Glina, Y Stein, DW Skomoroch, PN Fox, EB MIT Lincoln Lab Lexington MA 02420 USA

ISBN: (纸本)0819457981

This paper investigates methods of decision-making from uncertain and disparate data. The need for such methods arises in those sensing application areas in which multiple and diverse sensing modalities are available, but the information provided can be imprecise or only indirectly related to the effects to be discerned. Biological sensing for biodefense is an important instance of such applications. information fusion in that context is the focus of a research program now underway at MIT Lincoln Laboratory. The paper outlines a multi-level, multi-classifier recognition architecture developed within this program, and discusses its components. information source uncertainty is quantified and exploited for improving the quality of data that constitute the input to the classification processes. Several methods of sensor uncertainty exploitation at the feature-level are proposed and their efficacy is investigated. Other aspects of the program are discussed as well. While the primary focus of the paper is on biodefense, the applicability of concepts and techniques presented here extends to other multisensor fusion application domains.

关键词： information fusion multisensor data fusion machine learning biological sensors biodefense

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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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Optimal sensor dimension reduction in estimation fusion

Optimal sensor dimension reduction in estimation fusion

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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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