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Revisions to the JDL data fusion model

Revisions to the JDL data fusion model

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

作者： Steinberg, AN Bowman, CL White, FE ERIM Int Inc Arlington VA 22209 USA

ISBN: (纸本)0819431931

The Data fusion Model maintained by the Joint Directors of Laboratories (JDL) Data fusion Group is the most widely-used method for categorizing data fusion-related functions. This paper discusses the current effort to revise and expand this model to facilitate the cost-effective development, acquisition, integration and operation of multi-sensor/multi-source systems. Data fusion involves combining information - in the broadest sense - to estimate or predict the state of some aspect of the universe. These may be represented in terms of attributive and relational states. If the job is to estimate the state of a people (or any other sentient beings), it can be useful to include consideration of informational and perceptual stares in addition to the physical state. Developing cost-effective multi-source information systems requires a method for specifying data fusion processing and control functions, interfaces, and associated databases. The lack of common engineering standards for data fusion systems has been a major impediment to integration and re-use of available technology: current developments do nor lend themselves to objective evaluation, comparison or re-use. This paper reports on proposed revisions and expansions of the JDL Data fusion model to remedy some of these deficiencies. This involves broadening the functional model and related taxonomy beyond the original military focus, and integrating the Data fusion Tree Architecture model for system description, design and development.

关键词： Data fusion Data modeling Systems modeling Standards development Data processing sensors Algorithm development Data analysis Systems engineering Signal detection

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Neuro-Dynamic Programming for adaptive fusion complexity control

Neuro-Dynamic Programming for adaptive fusion complexity con...

引用

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

作者： Ross, KN Chaney, RD ALPHATECH Inc Burlington MA 01803 USA

ISBN: (纸本)0819431931

The prodigious amount of information provided by surveillance systems and other information sources has created unprecedented opportunities for achieving situation awareness. Because the mission's and user's needs are constantly evolving, fusion control strategics must adapt to these changing requirements. However, the optimal control problem with the desired adaptive control capabilities is enormously complex. Therefore, we solve the adaptive fusion control problem approximately using a methodology called Neuro-Dynamic Programming (NDP) that combines elements of dynamic programming, simulation-based reinforcement learning, and statistical inference techniques. This work demonstrates the promise of using NDP for adaptive fusion control by using it to allocate computational resources to Bayesian belief networks that use a variety of data types (e.g., SAR, MTI, ELINT, and terrain databases) to track and identify clusters of vehicles. We have significantly extended previous work by using NDP to adapt the fusion process itself in addition to deciding which clusters should get their inference updated. fusion within the Bayesian networks was adapted by using NDP to select the subset of available data to be used when updating the inference. We also extended previous work by using a dynamic scenario with moving vehicles for training and testing models.

关键词： adaptive fusion control Neuro-Dynamic Programming Bayesian networks reinforcement learning

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Multi-spectral image fusion for visual display

Multi-spectral image fusion for visual display

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

作者： Peli, T Peli, E Ellis, K Stahl, R Atlantic Aerosp Elect Corp Waltham MA 02154 USA

ISBN: (纸本)0819431931

This paper describes a contrast-based monochromatic fusion process. The fusion process is aimed for on board real time application and it is based on practical and computationally efficient image processing components. The process maximizes the information content in the combined image, while retaining visual clues that are essential for navigation/piloting tasks. The method is a multi scale fusion process that provides a combination of pixel selection from a single image and a weighing of the two/multiple images. The spectral region is divided into spatial sub bands of different scales and orientations, and within each scale a combination rule for the corresponding pixels taken from the two components is applied. Even when the combination rule is a binary selection the combined fused image may have a combination of pixel values taken from the two components at various scales since it is taken at each scale. The visual band input is given preference in low scale, large features fusion. This fusion process provides a fused image better tuned to the natural and intuitive human perception. This is necessary for pilotage and navigation under stressful conditions, while maintaining or enhancing the targeting detection and recognition performance of proven display fusion methodologies. The fusion concept was demonstrated against imagery from image intensifiers and forward looking infrared sensors currently used by the U.S. Navy for navigation and targeting. The approach is easily extendible to more than two bands.

关键词： image fusion contrast visual model night pilotage

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Automated image registration using the projective transformation model and block matching feature point pair selection

Automated image registration using the projective transforma...

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

作者： Schultz, RR Alford, MG Univ N Dakota Dept Elect Engn Grand Forks ND 58202 USA

ISBN: (纸本)0819431931

A subpixel-resolution image registration algorithm based on the nonlinear projective transformation model is proposed to account for camera translation, rotation, zoom, pan, and tilt. Typically, parameter estimation techniques for rigid-body transformations require the user to manually select feature point pairs between the images undergoing registration. In this research, the block matching algorithm is used to automatically select correlated feature point pairs between two images;these features are then used to calculate an iterative least squares estimate of the nonlinear projective transformation parameters. Since block matching is only capable of estimating accurate displacement vectors in image regions containing a large number of edges, inaccurate feature point pairs are statistically eliminated prior to computing the least squares parameter estimate. Convergence of the registration algorithm is generally achieved in several iterations. Simulations show that the algorithm estimates accurate integer- and subpixel-resolution registration parameters for similar sensor data sets such as intensity image sequence fi ames, as well as for dissimilar sensor images such as multimodality slices from the Visible Human Project. Through subpixel-resolution registration, integrating the registered pixels fi om a short sequence of low-resolution video fi-ames generates a high-resolution video still. Experimental results are also shown in utilizing dissimilar data registration followed by vector quantization to segment tissues from multimodality Visible Human Project image slices.

关键词： block matching image registration projective transformation sensor fusion super-resolution enhancement

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Development of emergent processing loops as a system of systems concept

Development of emergent processing loops as a system of syst...

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

作者： Gainey, J Blasch, E USAF Res Lab Sensors Directorate Wright Patterson AFB OH 45433 USA

ISBN: (纸本)0819431931

This paper describes an engineering approach toward implementing the current neuroscientific understanding of how the primate brain fuses, or integrates, "'information" in the decision-making process. We describe a System of Systems (SoS) design far improving the overall performance, capabilities, operational robustness, and user confidence in Identification (ID) systems and show how it could be applied to biometrics security. We use the physio-associative temporal sensor integration algorithm (PATSIA) which is motivated by observed functions and interactions of the thalamus, hippocampus, and cortical structures in the brain. PATSIA utilizes signal theory mathematics to model how the human efficiently perceives and uses information from the environment. The hybrid architecture implements a possible SoS-level description of the Joint Directors of US Laboratories (JDL) for fusion Working Group's functional description involving 5 levels of fusion (i.e., Preprocessing, kinematic, situation, threat, and process refinement) and their associated definitions. This SoS architecture proposes dynamic sensor and knowledge-source integration by implementing multiple Emergent Processing Loops (EPL) for Predicting, feature Extracting, Matching, and Searching both static and dynamic databases like MSTAR's PEMS loops. Biologically, this effort demonstrates these objectives by modeling similar processes from the eyes, ears. and somatosensory channels, through the thalamus, and to the cortices as appropriate while using the hippocampus for short-term memory search and storage as necessary. The particular approach demonstrated incorporates commercially available speaker verification (simulating 1D audio/signal inputs) and face recognition (simulating 2D video/image inputs) software and hardware to collect data and extract features to the PATSIA. The PATSIA maximizes the confidence levels for target identification or verification in dynamic situations using a belief filter. The proof o

关键词： sensor data fusion

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Temporal fusion a basic for neural plasticity in the visual pathways

Temporal fusion a basic for neural plasticity in the visual ...

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

作者： Navabi, H IPM Inst Studies Thoret Phys & Math ISRF Tehran Iran

ISBN: (纸本)0819431931

Vision is an excellent example of the rich interplay between computational and biological approaches to the understanding of complex information processing tasks. Studies of biological solutions to the computational problems of vision, such as contrast masking, movement detection, orientation selectivity has created many controversies in visual neuroscience. Recent neurobiological findings suggest an experimental paradigm that gives emphasis to strategies, which rely on the combined activities of cells or cell assembly for information transforms. This new perspective explains an integrated synaptic facilitation that is contingent upon the emergent spatial and temporal properties of cell activities. The paper briefly presents a novel biologically inspired adaptive architecture that can serve for analysis of cell response dynamics to encode analog (gray scale) visual sensory data under varying conditions. The key will be the active representation of visual objects temporal characteristics, i.e., the exposures (or presentation) time and the syntactic structure to achieve invariance for the fundamental problems of scene segmentation and figure-ground separation. The basic neural mechanism is that of plastic relationship between and within participating cells or cellular groups with known receptive field organizations. Our system behavior is tested with numerous parametric psychophysical data, and the selected simulation samples predict: Only the active integration (or fusion) from multiple exposure to the sequence of sensory visual information can yield a reliable encode to extract salient features of visual objects, in partially unknown and possibly changing environments.

关键词： cell assembly active representation plasticity figure_ground separation receptive field organization

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Distributed event driven architectures for evolutionary sensor fusion

Distributed event driven architectures for evolutionary sens...

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

作者： Lake, RT Dynam Control Syst Inc Delta BC Canada

ISBN: (纸本)0819428256

The next decade will require the development of complex sensor systems that integrate data from a large number of sensor elements. Such systems will play important roles in a wide variety of industrial and defense systems, as the fusion of multiple sources of information is crucial to sensor operation in noisy environments, and in complex decision making. The arrival of ubiquitous processing elements is one requirement for the development of such systems;however, the ability to connect and integrate these elements at the logical level is the more limiting aspect of their development. Furthermore, it is unlikely that such systems can be developed in a single linear process. It is much more probable that such systems will need to be evolved over time, perhaps a substantial period of time, and as result the ability to logically interconnect heterogeneous elements in an evolutionary manner will be of great importance. This paper outlines some approaches to this problem based on the distributed object-computing model as introduced in the OMG CORBA. It is our belief that this technology is maturing to the point that it could form the foundations for a sensor architecture that would support the evolutionary development of complex sensor networks.

关键词： distributed objects sensor networks embedded CORBA event-driven evolution

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A maximum likelihood approach for multisensor data fusion applications

A maximum likelihood approach for multisensor data fusion ap...

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

作者： Zhou, YF Leung, H Telexis Corp Canada Ottawa ON K1V 7P2 Canada

ISBN: (纸本)0819428256

In this paper, we proposed a maximum likelihood fusion approach for multisensor fusion applications. The proposed approach was based on a parametric modeling of the noise covariance and formulated in the transformed noise subspace. It could solve the fusion problems when the sensor noises are correlated and the scaling coefficients unknown. The approach could also deal with nonstationary signals. We showed that in the optimization process, the computation of the noise parameters and the scaling coefficients were separable leading to a reduced optimization dimensionality and computational complexity. Computer simulations were used to demonstrate the effectiveness of the proposed fusion approach.

关键词： maximum likelihood minimum variance least squares data fusion multisensor tracking nonstationarity unknown noise sensory information statistical consistency

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fusion of LWIR sensor data by Bayesian methods

Fusion of LWIR sensor data by Bayesian methods

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

作者： Inguva, R Garrison, G EW Enterprises Inc Dba Sci & Technol Consultants Huntsville AL 35805 USA

ISBN: (纸本)0819428256

Using Bayesian statistical methods a formulation is setup for fusing multi band data from LWIR sensors. This formulation is illustrated with applications to synthetic data consisting of 100 signatures in the wavelength bands 6-10 mu m, 11-16 mu m and 17-21 mu m. Following the works of Jaynes, and Bretthorst, a Bayesian formulation is given for detrending the time seriesdata for the emissive area, followed by estimations of frequencies and their amplitudes. This formulation is illustrated with analysis of the synthetic data.

关键词： sensors Data modeling sensor fusion Long wavelength infrared Data fusion Infrared sensors Statistical analysis Data analysis Signal to noise ratio Statistical methods

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Proceedings of SPIE: sensor fusion: architectures, algorithms, and applications II

Proceedings of SPIE: Sensor Fusion: Architectures, Algorithm...

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sensor fusion: architectures, algorithms and applications II

This Volume 3376 of the conference proceedings contains 22 papers. Topics discussed include sensor fusion, sensor fusion architectures, feature and decision level fusion, data and image level fusion and sensor fusion ... 详细信息

关键词： sensor data fusion

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