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Real time sensor validation and fusion for distributed autonomous sensors

Real time sensor validation and fusion for distributed auton...

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conference on Multisensor, Multisource Information fusion

作者： Yuan, XJ Li, XS Buckles, B Tulane Univ EECS Dept New Orleans LA 70118 USA

ISBN: (纸本)0819453579

Multi-sensor data fusion has found widespread applications in industrial and research sectors. The purpose of real time multi-sensor data fusion is to dynamically estimate an improved system model from a set of different data sources, i.e., sensors. This paper presented a systematic and unified real time sensor validation and fusion framework (RTSVFF) based on distributed autonomous sensors. The RTSVFF is an open architecture which consists of four layers - the transaction layer, the process fusion layer, the control layer, and the planning layer. This paradigm facilitates distribution of intelligence to the sensor level and sharing of information among sensors, controllers, and other devices in the system. The openness of the architecture also provides a platform to test different sensor validation and fusion algorithms and thus facilitates the selection of near optimal algorithms for specific sensor fusion application. In the version of the model presented in this paper, confidence weighted averaging is employed to address the dynamic system state issue noted above. The state is computed using an adaptive estimator and dynamic validation curve for numeric data fusion and a robust diagnostic map for decision level qualitative fusion. The framework is then applied to automatic monitoring of a gas-turbine engine, including a performance comparison of the proposed real-time sensor fusion algorithms and a traditional numerical weighted average.

关键词： real time sensor validation and fusion distributed sensor system design dynamic validation curve file based knowledge system confidence weighted averaging robust diagnostic maps

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Cognitive engineering in algorithm development for multisensor data fusion in military applications

Cognitive engineering in algorithm development for multisens...

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conference on Multisensor, Multisource Information fusion

作者： Kight, AC Narayanan, S Wright State Univ Dept Biomed Ind & Human Factors Engn Dayton OH 45435 USA

ISBN: (纸本)0819453579

In battlefield situations, human operators are bombarded with substantial amounts of information and expected to make near-instantaneous decisions. The large amounts of information, coupled with short decision times and the need to reduce the potential of making incorrect decisions, create the possibility for information overload. This problem is especially prominent in military applications involving imagery from multiple sensors. Computer-based algorithms for fusing pertinent sets of imagery have proven somewhat useful for alleviating this problem. However, little research has been done on designing multisensor data fusion systems using principles of cognitive engineering, which involves the consideration of human cognition during the design process. The design of a sensor fusion system using principles from cognitive engineering would create a more natural relationship between human and machine, and would thus be extremely effective in reducing operator error in military situations. This paper explores the need for integrating human reasoning and cognition in algorithm development for multisensor fusion applications.

关键词： Algorithm development Data fusion Defense technologies Cognition Image fusion Error analysis Image sensors sensor fusion sensors

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Simulation-based development of embedded sensor fusion applications

Simulation-based development of embedded sensor fusion appli...

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2nd IEEE International conference on Computational Cybernetics (ICCC 2004)

作者： Elmenreich, W Schlager, M Vienna Tech Univ A-1040 Vienna Austria

ISBN: (纸本)0780385888

This paper proposes a methodology for the design, testing, and fine-tuning of sensor fusion applications for distributed embedded sensor networks. The presented approach involves the following steps: (i) gathering data about the process environment, (ii) modeling of the process and the sensors to be used, (iii) selection of sensor fusion functions to process the sensor measurements, (iv) simulated closed-loop hardware-in-the-loop testing, (v) validation by open-loop testing in the real process, and, finally, (vi) application of the developed embedded sensor fusion application in the system. Particular steps may be repeated in a loop, if the result of a given step is not satisfactory. The main contribution of the approach is a separation of the modeling of process environment, sensors, and sensor processing. This allows for a strategic refinement of the model and supports the reuse and change of parts, e. g., in case of a sensor upgrade. The application of the approach is shown by a MATLAB/Simulink model that incorporates block diagrams describing process environment, sensor behavior, and sensor fusion algorithms.

关键词： sensor data fusion

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A scalable, portable, object-oriented framework for parallel multi-sensor data-fusion applications in HPC systems

A scalable, portable, object-oriented framework for parallel...

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conference on Multisensor, Multisource Information fusion

作者： Gupta, P Prasad, G Univ Cent Florida Sch Comp Sci Orlando FL 32816 USA

ISBN: (纸本)0819453579

Multi-sensor Data fusion is synergistic integration of multiple data sets. Data fusion includes processes for aligning, associating and combining data and information in estimating and predicting the state of objects, their relationships, and characterizing situations and their significance. The combination of complex data sets and the need for real-time data storage and retrieval compounds the data fusion problem. The systematic development and use of data fusion techniques are particularly critical in applications requiring massive, diverse, ambiguous, and time-critical data. Such conditions are characteristic of new emerging requirements;e.g., network-centric and information-centric warfare, low intensity conflicts such as special operations, counter narcotics, antiterrorism, information operations and CALOW (Conventional Arms, Limited Objectives Warfare), economic and political intelligence. In this paper, Aximetric presents a novel, scalable, object-oriented, metamodel framework for parallel, cluster-based data-fusion engine on High Performance Computing (HPC) Systems. The data-clustering algorithms provide a fast, scalable technique to sift through massive, complex data sets coming through multiple streams in real-time. The load-balancing algorithm provides the capability to evenly distribute the workload among processors on-the-fly and achieve real-time scalability. The proposed data-fusion engine exploits unique data-structures for fast storage, retrieval and interactive visualization of the multiple data streams.

关键词： sensor fusion HPC systems meta-modefing object-oriented simulation data fusion

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An information system for target recognition

An information system for target recognition

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conference on Multisensor, Multisource Information fusion

作者： Horney, T Ahlberg, J Grönwall, C Folkesson, M Silvervarg, K Fransson, J Klasén, L Jungert, E Lantz, F Ulvklo, M Swedish Def Res Agcy FOI Dept Data & Informat Fus Div Command & Control Syst SE-58111 Linkoping Sweden

ISBN: (纸本)0819453579

We present an approach to a general decision support system. The aim is to cover the complete process for automatic target recognition, from sensor data to the user interface. The approach is based on a query-based information system, and include tasks like feature extraction from sensor data, data association, data fusion and situation analysis. Currently, we are working with data from laser radar, infrared cameras, and visual cameras, studying target recognition from cooperating sensors on one or several platforms. The sensors are typically airborne and at low altitude. The processing of sensor data is performed in two steps. First, several attributes are estimated from the (unknown but detected) target. The attributes include orientation, size, speed, temperature etc. These estimates are used to select the models of interest in the matching step, where the target is matched with a number of target models, returning a likelihood value for each model. Several methods and sensor data types are used in both steps. The user communicates with the system via a visual user interface, where, for instance, the user can mark an area on a map and ask for hostile vehicles in the chosen area. The user input is converted to a query in SigmaQL, a query language developed for this type of applications, and an ontological system decides which algorithms should be invoked and which sensor data should be used. The output from the sensors is fused by a fusion module and answers are given back to the user. The user does not need to have any detailed technical knowledge about the sensors (or which sensors that are available), and new sensors and algorithms can easily be plugged into the system.

关键词： automatic target recognition multisensor fusion query languages

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A mathematical framework for the optimization of rejection and ROC thresholds in the fusion of correlated sensor data

A mathematical framework for the optimization of rejection a...

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conference on Multisensor, Multisource Information fusion

作者： Laine, TI Bauer, KW USAF Inst Technol Dept Operat Sci Wright Patterson AFB OH 45433 USA

ISBN: (纸本)0819453579

In pattern recognition applications, significant costs can be associated with various decision options and a minimum acceptable level of confidence is often required. Combat target identification is one example where the incorrect labeling of Targets and Non-targets incurs substantial costs: yet, these costs may be difficult to quantify. One way to increase decision confidence is through fusion of data from multiple sources or from multiple looks through time. Numerous methods have been published to determine optimal rules for the fusion of decision labels or to determine the Bayes' optimal decision if prior and posterior probabilities along with decision costs can be accurately estimated. This paper introduces a mathematical framework to optimize multiple decision thresholds subject to a decision maker's preferences. when a continuous measure of class membership is available. Decision variables may include rejection thresholds to specify non-declaration regions and ROC thresholds to explore viable trite positive and false positive Target classification rates, where the feasible space can be partially visualized by a 3D ROC surface. This methodology yields an optimal class declaration rule subject to decision maker preferences without using explicit costs associated with each type of decision. Some properties of this optimization framework are shown for Gaussian distributions representing Target and Non-target classes with various prior probabilities and correlation levels between simulated multiple sensor looks.

关键词： combat identification (CID) fusion receiver operating characteristic (ROC). 3-D ROC surface automatic taraet recosinition (ATR) performance rejection

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Multi-sensor, multi-source information fusion: architecture, algorithms, and applications - a panoramic overview

Multi-sensor, multi-source information fusion: architecture,...

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International conference on Computational Cybernetics (ICCC)

作者： B.V. Dasarathy Huntsville AL USA

This plenary presentation offers a panoramic overview of the field of multi-sensor, and/or multi-source information fusion from three complementary perspectives, namely, architectures, algorithms, and applications. This overview is developed through addressing the questions of 'what', 'why', 'when', and last but not least 'how' of information fusion and illustrating the answers with appropriate algorithmic and applicative examples

关键词： Feature extraction Iron Taxonomy Data processing Data mining Biosensors sensor fusion Security Bibliographies

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Simulation-based development of embedded sensor fusion applications

Simulation-based development of embedded sensor fusion appli...

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International conference on Computational Cybernetics (ICCC)

作者： W. Elmenreich M. Schlager University of Technology Vienna Vienna Austria

关键词： sensor fusion sensor systems Intelligent sensors Design methodology sensor systems and applications System testing Intelligent actuators Data processing sensor phenomena and characterization Partitioning algorithms

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Impact of expanding the multiplicity of information sources on fusion system architecture and fusion logic options

Impact of expanding the multiplicity of information sources ...

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conference on Multisensor, Multisource Information fusion - architectures, algorithms and applications 2003

作者： Dasarathy, BV

ISBN: (纸本)0819449598

Various fusion system architectures postulated and studied previously for environments with two and three data sources are further explored in this study to bring out the expanding scope for delineating the architecture options for multiple data source environments. A spectrum of single and multi-stage fusion architecture options are defined. The potential for such expansion of choices is illustrated using the scenario with four data sources as an example. Potential problem environments corresponding to this range of two to four data sources are identified. Various fusion logic strategies that can be brought to bear for the analysis of these fusion architecture options, when these fusion architectures are employed for Decisions In - Decision Out (DEI-DEO) fusion, are also discussed.

关键词： sensor fusion decision fusion fusion strategies multi-sensor suites

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A simple test-bed for real-time sensor-to-shooter applications of decentralised data fusion

A simple test-bed for real-time sensor-to-shooter applicatio...

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conference on Multisensor, Multisource Information fusion - architectures, algorithms and applications 2003

作者： Binns, L Cooke, A Fryers, S Greenway, P Mullin, D Nicholson, D Valachis, D BAE Syst Adv Technol Ctr Bristol BS34 7QW Avon England

ISBN: (纸本)0819449598

In this paper we describe a simple physical test-bed, developed to allow practical experimentation in the use of Decentralised Data fusion (DDF) in sensor-to-shooter applications. Running DDF over an ad hoc network of distributed sensors produces target location information. This is used to guide a Leica laser-tracker system to designate currently tracked targets. We outline how the system is robust to network and/or node failure. Moreover, we discuss the system properties that lead to it being completely "plug-and-play", as, like the distributed sensor nodes, the "shooter" does not require knowledge of the overall network topology and can connect at any point.

关键词： data fusion network centric warfare ad-hoc networks sensor-to-shooter

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