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JDL level 5 fusion model "user refinement" issues and applications in group tracking

JDL level 5 fusion model "user refinement" issues and applic...

引用

conference on Signal Processing, sensor fusion, and Target Recognition XI

作者： Blasch, EP Plano, S Wright State Univ Dept Elect Engn Dayton OH 45435 USA

ISBN: (纸本)0819444790

The 1999 Joint Director of Labs (JDL) revised model incorporates five levels for fusion methodologies including level 0 for preprocessing, level I for object refinement, level 2 for situation refinement, level 3 for threat refinement, and level 4 for process refinement. The model was developed to define the fusion process. However, the model is only for automatic processing of a machine and does not account for human processing. Typically, a fusion architecture supports a user and thus, we propose a Level 5 "User refinement" to delineate the human from the machine in the process refinement. Typical "human in the loop" models do not deal with a machine fusion process, but only present the information to the human on a display. We seek to address issues for designing a fusion system which supports a user: trust, workload, attention and situation awareness. In this paper. we overview the need for a Level 5, the issues concerning the human for realizable fusion architectures, and examples where the human is instrumental in the fusion process such as group tracking.

关键词： information fusion group tracking identity workload attention situation awareness trust HMI HCI

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Support for reliability in self-organizing sensor networks

Support for reliability in self-organizing sensor networks

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5th International conference on Information fusion (fusion 2002)

作者： Lim, A Auburn Univ Dept Comp Sci & Engn Auburn AL 36849 USA

ISBN: (纸本)0972184422

As wireless sensor networks are becoming increasingly common, distributed embedded applications will exploit these sensor networks not only for information dissemination, but also for in-network processing and other distributed computation, such as sensor fusion, classification, and collaborative target tracking. However, sensor nodes are prone to failure, insufficient energy supply, high error rate, and mobility. Three main distributed services are important for maintaining reliability in distributed sensor network, in spite of these failures - distributed lookup services, composition service and dynamic adaptation service. In particular, the dynamic adaptation service collaborates with the distributed lookup service to monitor failures in the sensor nodes and manages the correct schedule of procedures for recovering from the failure. Developers may define their own detection algorithms for other changes, including available services in the sensor network, migration of sensor nodes, and changes in task and network requirements. The procedures for maintaining the level of reliability required for the application are specified by the application programmers. These distributed services execute over a diffusion network layer that alleviate some of the problems of mobility, disconnection, dynamic reconfiguration, and limited power.

关键词： reliability self-organizing sensor networks reconfigurable smart nodes distributed services adaptive sensor fusion

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Electro-optical and SAR image fusion for improvements on target feature estimation

Electro-optical and SAR image fusion for improvements on tar...

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5th International conference on applications of Photonic Technology (ICAPT 2002)

作者： Lampropoulos, GA Li, YF Secker, J Sévigny, L Beaudoin, A AUG Signals Ltd Toronto ON M4V 1K7 Canada

ISBN: (纸本)0819446122

In this paper, tradeoff studies on several pixel level fusion algorithms and on their performance evaluation criteria are presented. Electro-optical (EO) and Synthetic Aperture Radar (SAR) sensors are dissimilar and produce images with very low degree of correlation. These images are initially registered at subpixel level accuracy. The fusion is performed using the following pixel level fusion algorithms: Principal Component Analysis (PCA), Averaging (Ave), Laplacian Pyramid, Filter Subtract Decimate (FSD), Ratio Pyramid, Contrast Pyramid, Gradient Pyramid, Discrete Wavelet Transform (DWT), Shift Invariant DWT (SIDWT) with Haar, Morphological Pyramid, and the recent image fusion method developed by A.U.G. Signals Ltd. A MATLAB based dedicated image fusion toolbox, that includes several pixel level fusion, restoration and registration algorithms, has been recently developed by A.U.G. Signals. This toolbox is used for the tradeoff studies.

关键词： multi-sensor pixel level fusion feature extraction detection

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Tracking moving acoustic sources with a network of sensors

Tracking moving acoustic sources with a network of sensors

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conference on Unattended Ground sensor Technologies and applications IV

作者： Kozick, RJ Sadler, BM Bucknell Univ Dept Elect Engn Lewisburg PA 17837 USA

ISBN: (纸本)0819444936

This paper presents issues and algorithms for the problem of source tracking with a network of aeroacoustic sensors. We study fusion of data from sensors that are widely separated, and we give particular attention to the important issues of limited communication bandwidth between sensor nodes, effects of source motion, coherence loss between signals measured at different sensors, signal bandwidth, and noise. We compare the tracking performance of various schemes, including joint (coherent) processing of all sensor data, as well as data-reduction schemes that employ distributed computation and reduced communication bandwidth with a fusion center. The key result of our analysis is a quantification of the potential gain in source tracking accuracy that is achievable with greater communication bandwidth and joint processing of sensor data. We show that the potential gain in accuracy depends critically on the scenario, as determined by the source motion parameters, signal coherence between sensors, bandwidth of the source signals, and noise level. For scenarios that admit increased accuracy with joint processing, we present a bandwidth-efficient algorithm that involves beamforming at small-aperture sensor arrays combined with time-delay estimation between widely-spaced sensor arrays.

关键词： aeroacoustic sensor arrays source localization and tracking imperfect spatial coherence decentralized signal processing data compression and fusion

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Query routing optimization in sensor communication networks

Query routing optimization in sensor communication networks

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41st IEEE conference on Decision and Control

作者： Jiang, GF Cybenko, G Dartmouth Coll Inst Secur Technol Studies Hanover NH 03755 USA

ISBN: (纸本)0780375165

Interest in large-scale sensor networks for both civilian and military applications is burgeoning. The deployment of such networks will require new approaches in resource discovery, query processing and data routing. This paper presents a framework and some analytic results for query satisfaction and: data routing in networks consisting of clients, sensors and data filtering/fusion servers. In this model, multiple. clients pose queries that are satisfied by processing a set of sensor data streams through a set of filters or fuselets. Fuselets are lightweight data fusion algorithms that can be deployed in a network environment. The queries can have common subexpressions (sub-queries) that should be reused by multiple clients if possible and appropriate. Moreover, effective routing of data streams from sensors to clients requires routing the streams through network nodes that can implement the required filtering/fusion operations. We formulate these problems quantitatively and propose a dynamic programming based solution using sensor-fuselet location and performance tables. The framework is preliminary in that many details and variations are abstracted or ignored. However, at the end of the paper we discuss several directions that can be explored to make these preliminary results more relevant to real scenarios.

关键词： Control system synthesis

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Multiple sensor image registration, image fusion and dimension reduction of Earth science imagery

Multiple sensor image registration, image fusion and dimensi...

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5th International conference on Information fusion, fusion 2002

作者： Moigne, Jacqueline Le Cole-Rhodes, Arlene Eastman, Roger El-Ghazawi, Tarek Johnson, Kisha Kaewpijit, Sinthop Laporte, Nadine Morisette, Jeffrey Netanyahu, Nathan S. Stone, Harold S. Zavorin, Ilya NASA Gcddard Space Flight Center Applied Information Science Branch Greenbelt MD 20771 United States

ISBN: (纸本)0972184414

The goal of our project is to develop and evaluate image analysis methodologies for use on the ground or on-board spacecraft particularly spacecraft constellations. Our focus is on developing methods to perform automatic registration and fusion of multisensor data representing multiple spatial, spectral and temporal resolutions, as well as dimension reduction of hyperspectral data. Feature extraction methods such as wavelet decomposition, edge detection and mutual information are combined with feature matching methods such as cross-correlation, optimization, and statistically robust techniques to perform image registration. The approach to image fusion is application-based and involves wavelet decomposition, dimension reduction, and classification methods. Dimension reduction is approached through novel methods based on principal component analysis and wavelet decomposition, and implemented on Beowulf-type parallel architectures. Registration algorithms are tested and compared on several multi-sensor datasets, including one of the EOS Core Sites, the Konza Prairie in Kansas, utilizing four different sensors: IKONOS, Landsat-7/ETM+, MODIS, and SeaWIFS. fusion methods are tested using Landsat, MODIS and SAR or JERS data. Dimension reduction is demonstrated on A VIRIS hyperspectral data. © 2002 Int. Soc. of Information fusion.

关键词： Remote sensing

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Networked sensor communications for the objective force

Networked sensor communications for the objective force

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conference on Unattended Ground sensor Technologies and applications IV

作者： Nemeroff, JL Garcia, L DiPierro, S Hamilton, BA USA CECOM RDEC Space & Terr Commun Directorate Ft Monmouth NJ USA

ISBN: (纸本)0819444936

The US Army's Future Combat Systems (FCS) and Objective Force will rely heavily on the use of unattended sensor net-works to detect, locate and identify enemy targets in order to survive with less armor protection on the future battlefield. Successful implementation of these critical communication net-works will require the collection of the sensor data, processing and collating it with available intelligence, then transporting it in a format conducive to make quick and accurate command decisions based on the latest tactical situational awareness. The networked communications must support both static deployed and mobile ground and air robotic sensors with secure, stealthy, andjam resistant links for sensor fusion and command and control. It is envisioned for broadest application that sensor networks can be deployed in a two-tiered architecture. The architecture includes a lower sensor sub-layer consisting of mixes of acoustic, magnetic and seismic detectors and an upper sub-layer consisting of infrared or visual imagers. The upper sub-layer can be cued by the lower sub-layer and provides a gateway link to the higher echelon tactical maneuver layer networks such as the Tactical Internet. The sensor deployments, networking constraints and reach back distances to Command and Control (C2) nodes will be mission scenario specific, however, the architecture will also apply to tactical unattended sensor, munition and robotic applications. Technologies from the Army Research Laboratory, Defense Advance Research Projects Agency (DARPA), and commercial will be leveraged for this effort.

关键词： sensors Unattended ground sensors sensor networks Network architectures Telecommunications Fluorescence correlation spectroscopy Magnetic sensors Image processing Situational awareness sensors Unattended sensors

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Neural networks estimation of truck static weights by fusing weight-in-motion data

Neural networks estimation of truck static weights by fusing...

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5th International conference on Information fusion (fusion 2002)

作者： Mangeas, M Glaser, S Dolcemascolo, V LCPC INRETS LIVIC F-78000 Versailles France

ISBN: (纸本)0972184414

This paper presents a complete neural networks approach developed to improve the accuracy of multiple-sensor Weigh-In-Motion system. This system consists in fusing the dynamical measurements of individual sensors installed in the road, into one improved estimate of static gross or axle weight. This task is complex due to the difficulty to inverse the model that describes the dynamical vehicle-pavement interactions. The sensors are also difficult to calibrate and remain sensitive to the environmental conditions. We chose to model the data with neural networks named 'general feedforward neural networks'. This class of neural nets includes in particular the famous Multilayer Perceptron model used in many applications. In order to increase the accuracy and the generalization capacity of this neural model, we also use an automatic method of model selection based on genetic algorithms. Simulated traffic data, computed with a realistic model based on vehicle-pavement interaction, indicated that a neural network can produce results with a higher degree of accuracy than the simple linear regression method. Moreover, our results show that the fusion of several sensors significantly improved the estimation of the static weight, much more in the frame of non linear modeling than in. the frame of linear one. In our simulation, the optimal number of sensors to fuse stands around 7.

关键词： multisensor fusion neural networks genetic algorithms nonlinear estimation real world application

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Filter construction for topological track association and sensor registration

Filter construction for topological track association and se...

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conference on algorithms and Systems for Optical Information Processing VI

作者： Stanek, CJ Javidi, B Skorokhod, A Yanni, P ANZUS San Diego CA 92131 USA

ISBN: (纸本)0819445568

Correlation engines have been evolving since the implementation of radar. Here, correlation refers to association, which in this context is track-to-track association. In modem sensor fusion architectures, correlation and sensor registration are required to produce common, continuous, and unambiguous tracks of all objects in the surveillance area [1]. The objective is to provide a unified picture of the theatre or area of interest to battlefield decision makers. This unified picture has many names, but is most commonly referred to as a Single Integrated Picture (SIP). A related process, known as sensor registration or gridlock filtering (gridlocking), refers to the reduction in navigation errors and sensor misalignment errors so that one sensor's track data can be accurately transformed into another sensor's coordinate system. As platforms gain multiple sensors, the correlation and gridlocking of tracks become significantly more difficult. Current correlation technology revolves around likelihood ratio theory and the assignment algorithm to resolve association ambiguities. While a Bayes classifier is the best classifier, all classifiers potentially lead to classification errors. The performance, with respect to misclassification, is usually expressed via the operating characteristic curve. When the observed feature vector has a high dimension, finding the class densities can be difficult. Even if these densities are available, we should remember that no classifier can perform perfectly when the class distributions overlap. sensor registration is typically accomplished with some type of least-squares algorithm, such as the Kalman filtering technique, which attempts to locate the best bias error vector estimate from a set of associated/fused track pairs. In this paper, we examine the track association and sensor registration problem in terms of several correlation classifiers, the most famous of these being the matched filter. Thus, we seek some unification between th

关键词： correlation gridlock topology Bayesian image-based likelihood ratio optical constellation

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Super-fusion: A super-resolution method based on fusion

Super-fusion: A super-resolution method based on fusion

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作者： Zhao, W. Sawhncy, H. Hansen, M. Samarasekera, S. Sarnoff Corporation Princeton NJ 08540

Reconstruction-based super-resolution algorithms require very accurate alignment and good choice of filters to be effective. Often these requirements are hard to satisfy, for example, when we adopt optical flow as the motion model. In addition, the condition of having enough sub-samples may vary from pixel to pixel. In this paper, we propose an alternative super-resolution method based on image fusion (called super-fusion hereafter). Image fusion has been proven to be effective in many applications. Extending image fusion to super-resolve images, we show that super-fusion is a faster alternative that imposes less requirements and is more stable than traditional super-resolution methods. © 2002 IEEE.

关键词： sensor data fusion

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