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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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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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Extending the OneSAF testbed into a C41SR testbed

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SIMULATION-TRANSACTIONS OF THE SOCIETY FOR MODELING AND SIMULATION INTERNATIONAL 2004年第12期80卷 681-691页

作者： Giampapa, JA Sycara, K Owens, S Glinton, R Seo, YW Yu, B Grindle, CE Lewis, M Carnegie Mellon Univ Inst Robot Pittsburgh PA 15213 USA Univ Pittsburgh Sch Informat Sci Pittsburgh PA 15213 USA

This article describes how the modeling and simulation environment of the OneSAF Testbed Baseline (OTB) v1.0 has been extended to enable the testing of heterogeneous algorithms that are being designed for real-world C4ISR applications. This has been accomplished by building an architecture that extends functional and logical components of the OTB system in the following ways: the use of the OTB Compact Terrain Database for terrain analysis and preliminary threat assessment, the addition of the RETSINA-OTB Bridge for the real-time query and control of OTB entities, and the addition of new DIS-based sensor entities for interoperation with Command and Control algorithms, to name a few. This article illustrates how to make a few small but general extensions to a modeling and simulation system to create a larger testbed system with minimum impact on the native system and with great potential for the range of applications that can exploit it.

关键词： multi-level information fusion multi-agent systems terrain analysis RETSINA OTB

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Detection of chemical or biological artillery attacks using a seismic/acoustic sensor: preliminary results

Detection of chemical or biological artillery attacks using ...

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Conference on Multisensor, Multisource Information fusion

作者： Baker, v Walter, P Commun Syst E Camden NJ 08103 USA

ISBN: (纸本)0819453579

Chemical and biological weapons pose a serious threat to the United States armed forces. Early detection of a chemical or biological attack is critical to the safety of soldiers in the field. The Edgewood Chemical and Biological Center (ECBC) is conducting a study using currently fielded seismic and acoustic sensors to detect chemical and biological attacks. This paper presents some preliminary results.

关键词： Unattended Ground sensors chemical weapons biological weapons

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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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sensor fusion: architectures, algorithms, and applications v : 7-9 April 1999, Orlando, Florida / Belur v. Dasarathy, chair/editor;sponsored and published by SPIE--the International Society for Opti

Sensor fusion: architectures, algorithms, and applications V...

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2001年

作者： Belur v. Dasarathy chair/editor sponsored and published by SPIE--the International Society for Optical Engineering.

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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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Discrete event modeling and simulation: v-Lab® application to wireless sensor networks

Discrete event modeling and simulation: V-Lab&reg applicatio...

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2004 IEEE International Conference on Systems, Man and Cybernetics, SMC 2004

作者： Sridhar, Prasanna Jamshidi, Mo Department of Electrical Engineering University of New Mexico Albuquerque NM United States

The need for modeling and simulation (M&S) is seen in many diverse applications such as multi-agent systems, robotics, control systems, software engineering, complex adaptive systems, and homeland security. With the emerging applications of multi-agent systems, there is always a need for simulation to verify the results before the actual implementation. Multi-agent simulation provides a test bed for several soft computing algorithms like fuzzy logic, neural networks (NN), probabilistic reasoning (Stochastic Learning Automata, Reinforcement learning), and evolutionary algorithms (Genetic algorithms). fusion of soft computing methodology with existing simulation tools yields several advantages in simulating multi-agent systems. Such a fusion provides a novel and systematic way of handling time-dependent parameters in the simulation without altering the essential functionality and problem-solving capabilities of soft computing elements. The fusion here is the extension of the capabilities of simulation tools with intelligent tools from soft computing. This paper proposes a methodology for combining the agent-based architecture, discrete event system and the soft-computing methods in the simulation of multi-agent systems and defines a framework called virtual Laboratory (v-Lab®) for realizing such multi-agent system simulations. Detailed experimental results obtained from simulation of robotics agents and wireless sensor network is also discussed.

关键词： virtual reality

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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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Practical fusion of quantized measurements via particle filtering

Practical fusion of quantized measurements via particle filt...

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IEE Target Tracking 2004: algorithms and applications

作者： Yanhua Ruan P. Willett A. Marrs S. Marano F. Palmieri University of Connecticut USA Qinetiq Limited UK Universitià degli Studi di Salerno Italy Seconda Università degli Studi di Napoli Italy

Most treatments of decentralized estimation rely on some form of track fusion, in which local track estimates and their associated covariances are communicated. This implies a great deal of communication; and it was recently proposed that, by an intelligent direct quantization of measurements, the communication needs could be considerably cut. However, several issues were not discussed. The first of these, estimation with quantized measurements, would be a difficult task for dynamic estimation, but Markov-chain Monte-Carlo (MCMC), and specifically particle filtering techniques appear quite appropriate since the resulting system is, in essence, a nonlinear filter. For the second issue, out-of-sequence. arrival of measurements, a particle filter is again appropriate. We show results that indicate a compander/particle-filter combination is a natural fit, and, specifically, that quite good performance is achievable with only 2-3 bits per dimension per observation. The third issue is that intelligent quantization requires that both sensor and fuser share an understanding of the quantization rule, but in dynamic estimation, both quantizer and fuser are working with only partial information; the problem is worse if measurements arrive out of sequence. We therefore suggest architectures, and comment on their suitabilities for the task. A scheme based on /spl Delta/-modulation appears to be promising.

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