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

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Multisensor statistical interval estimation fusion

Multisensor statistical interval estimation fusion

引用

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

作者： Zhu, YM Gan, Y Li, XR Sichuan Univ Dept Math Chengdu 610064 Sichuan Peoples R China

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.

关键词： interval estimation coverage probability convex linear fusion least mean square

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Active perception in a sensor fusion model

Active perception in a sensor fusion model

引用

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

作者： Biel, L Wide, P Univ Orebro Ctr Appl Autonomous Sensor Syst Orebro Sweden

ISBN: (纸本)0819444812

During the last decades the research in the sensor fusion area has mainly been focused on fusion methods and feature selection methods. A possible further development in this area is to incorporate a process referred to as active perception. This means that the system is able to manipulate the sensing mechanisms to create a focus on selected information in the surrounding environment. This process may also be able to handle the feature selection process with respect to which features to be used and/or the number of features to use. This paper presents a model that contains a decision system based on active perception integrated with previous sensor fusion algorithms. The human body has perhaps one of the most advanced perceptual processing systems. The human perception process can be divided into sensation (measurement collection) and perception (interpret the surroundings). During the sensation process a huge amount of data is collected from different sensors that reflect the environment. The information has to be interpreted in an effective way, i.e. in the fusion process. The interpretation together with a decision system to control the sensors to focus on important information will correspond to the (active) perception process. The model presented in this paper capitalizes on the properties presented by the biological counterpart to achieve more human-like processes for a sensor fusion. Finally, the paper presents the testing of the model in two examples. The applications used have a safety approach of fire indication, identification and decision-making. The goal is to enlarge a conventional fire alarm system to not only detect fire, but also to propose different actions for a human in a dangerous area for example.

关键词： sensors sensor fusion Data fusion Fuzzy systems Carbon monoxide Oxygen Systems modeling Environmental sensing Control systems Signal processing

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Multiple sources distributed information fusion based on multi-agent system

Multiple sources distributed information fusion based on mul...

引用

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

作者： Xia, ZX E China Shipbldg Inst Dept Comp Sci Zhenjiang 212003 Peoples R China

ISBN: (纸本)0819444812

In a multi-node distributed decision system under some conditions there are few or none permitted information exchange between the nodes, this makes the information fusion and final decision difficult. However if we treat this distributed system as a multi-agent system, and each node acts as an agent, it has some other node's historical experiences or knowledge for resolving problems and stored in additional case bases, so it can uses case based reasoning (CBR) and transposition reasoning to obtain the possible viewpoints or decisions of other nodes and then makes information fusion by itself This approach may reduce the subjectivism which is the weakness of pure transposition reasoning.

关键词： distributed decision system multi-agent case based reasoning transposition reasoning

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Bayesian approach to sensor fusion in a multi-sensor land mine detection system

Bayesian approach to sensor fusion in a multi-sensor land mi...

引用

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

作者： Erickson, D Kacelenga, R Palmer, D Gen Dynam Canada Ltd Calgary AB T2E 8P2 Canada

ISBN: (纸本)0819444812

In the present study, the investigation by General Dynamics Canada, formerly Computing Devices Canada, into Bayesian Inference shows improved sensor fusion of multiple scanning sensors in the detection of buried anti-tank (AT) mines. This algorithm uses statistical data taken from trials and constructs conditional probabilities for individual sensors in order to better discern landmines.

关键词： landmine detection Baye's rule Bayesian inference conditional probability minimum metal detector ground penetrating radar forward-looking infrared multi-sensor fusion

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Integrated spatio-temporal multiple sensor fusion system design

Integrated spatio-temporal multiple sensor fusion system des...

引用

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

作者： Chen, HW Olson, T Lockheed Martin Missiles & Fire Control Orlando Orlando FL 32819 USA

ISBN: (纸本)0819444812

In many missile and fire control applications, targets of interest may be acquired and tracked over some finite period of time with one or more sensors. This allows for the collection of sequential segments or frames of temporal information per sensor as well as across various sensors. By appropriately processing this information, target detection and classification performance can be considerably increased. Furthermore, we have developed new and different fusion strategies (additive and MINMAX fusion) in addition to the traditional strategies. Our test and analysis results show that temporal fusion can improve target classification as well as spatial fusion. In this work we have developed an optimal and novel design for an integrated spatio-temporal multi-sensor fusion system that combines inputs from different sensors as well as from the different time frames of each sensor.

关键词： sensors Signal to noise ratio sensor fusion Reliability Infrared sensors Missiles Statistical analysis Target detection Analytical research Fuzzy logic

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Neurophysiological-based signals analysis for level 5 user refinement for target localization

Neurophysiological-based signals analysis for level 5 user r...

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

作者： Blasch, EP Wright State Univ Dayton OH 45435 USA

ISBN: (纸本)0819444812

The human brain fuses information from a variety of modalities to locate, track, and identify targets. Vision-based tracking, which uses a 2D signal, is able to accurately identify and locate objects, however it requires more processing time than 1-D auditory systems. Auditory systems can locate and identify objects based on interaural time difference (ITD) and interaural intensity difference (IID) fusion. In order to investigate the advantages of a neurophysiology-based fusion model, we seek to localize a target from a 1-D signals analysis conducted over repeated measurements where a user is allowed move sensors. Similar to the human fusing auditory information from the ears, we seek to fuse information over time and space from two sensors monitoring a single target. Through spatiotemporal fusion from the 1-D analysis, we show how ITD and IID fusion functions support a Level 5 User Refinement task.

关键词： information fusion auditory system ITD IID tracking identification ATR

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Robust speech separation using visually constructed speech signals

Robust speech separation using visually constructed speech s...

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

作者： Aarabi, P Khameneh, NH Univ Toronto Dept Elect & Comp Engn Toronto ON M5M 3G4 Canada

ISBN: (纸本)0819444812

A technique to virtually recreate speech signals entirely from the visual lip motions of a speaker is proposed. By using six geometric parameters of the lips obtained from the Tulips1 database, a virtual speech signal is recreated by using a 3.6s audiovisual training segment as a basis for the recreation. It is shown that the virtual speech signal has an envelope that is directly related to the envelope of the original acoustic signal. This visual signal envelope reconstruction is then used as a basis for robust speech separation where all the visual parameters of the different speakers are available. It is shown that, unlike previous signal separation techniques, which required an ideal mixture of independent signals, the mixture coefficients can be very accurately estimated using the proposed technique in even non-ideal situations.

关键词： audiovisual information fusion blind speech separation independent component analysis audiovisual signal separation robust speech recognition

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An unified approach to the fusion of imperfect data?

An unified approach to the fusion of imperfect data?

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

作者： Florea, MC Jousselme, AL Grenier, D Bossé, É Univ Laval Dept Genie Elect LRTS Ste Foy PQ G1K 7P4 Canada

ISBN: (纸本)0819444812

For several years, researchers have explored the unification of the theories enabling the fusion of imperfect data and have finally considered two frameworks: the random sets and the conditional events algebra. Traditionally, the information is modeled and fused in one of the known theories: bayesian, fuzzy sets, possibilistic, evidential, or rough sets... Previous work has shown what kind of imperfect data these theories can best deal with. So, depending on the quality of the available information (uncertain, vague, imprecise,...), one particular theory seems to be the preferred choice for fusion. However, in a typical application, the variety of sources provides different kinds of imperfect data. The classical approach is then to model and fuse the incoming data in a single theory being previously chosen. In this paper, we first introduce the various kinds of imperfect data and then the theories that can be used to cope with the imperfection. We also present the existing relationships between them and detail the most important properties for each theory. We finally propose the random sets theory as a possible framework for unification, and thus show how the individual theories can fit in this framework.

关键词： imperfect data data fusion random sets

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Fuser design for thick film pH sensor electrodes using empirical data

Fuser design for thick film pH sensor electrodes using empir...

引用

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

作者： Wellington, SJ Atkinson, JK Sion, RP Southampton Inst Sch Comp & Digital Commun Southampton SO14 0RD Hants England

ISBN: (纸本)0819444812

An array of thick film pH sensor electrodes has been fused using two separate fuser designs: the feedforward neural network and Nadaraya-Watson kernel estimator. In both cases the fuser is based on empirical data rather than analytical sensor models. Complementary sensor responses have been obtained by fabricating sensors using different metal oxides. This approach provides some immunity to interference caused by the ionic composition of the solution being sensed. The Nadaraya-Watson estimator is shown to provide a useful alternative to the feedforward neural network for multisensor fusion where sensor distributions are unknown. Indicative test results are provided for the measurement of pH in printing ink. The results confirm that the fused results are more accurate than those obtained using the single best sensor, or simple fusion schemes such as averaging or majority voting.

关键词： pH electrode thick film sensor multisensor fusion Nadaraya-Watson artificial neural network

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Distributed air-to-ground targeting

Distributed air-to-ground targeting

引用

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

作者： Ralph, JF Smith, MI Bernhardt, M West, CE Angell, CR Sims, SW Univ Liverpool Dept Elect Engn & Elect Liverpool L69 3GJ Merseyside England

ISBN: (纸本)0819444812

This paper examines the requirement for accurate estimates of the statistical correlations between measurements in a distributed air-to-ground targeting system. The study uses results from a distributed multi-platform targeting simulation based on a level-1 data fusion system to assess the extent to which correlated measurements can degrade system performance, and the degree to which these effects need to be included to obtain a required level of accuracy. The data fusion environment described in the paper incorporates a range of target tracking and data association algorithms, including several variants of the standard Kalman filter, probabilistic association techniques and Reid's multiple hypothesis tracker. A variety of decentralized architectures are supported, allowing comparison with the performance of equivalent centralized systems. In the analysis, consideration is given to constraints on the computational complexities of the fusion system, and the availability of estimates of the measurement correlations and platform-dependent biases. Particular emphasis is placed on the localisation accuracy achieved by different algorithmic approaches and the robustness of the system to errors in the estimated covariance matrices.

关键词： targeting object localisation data fusion

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