This paper presents results from an Adaptable Data fusion Testbed (ADFT) which has been constructed to analyze simulated or real data with the help of modular algorithms for each of the main fusion functions and image...
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This paper presents results from an Adaptable Data fusion Testbed (ADFT) which has been constructed to analyze simulated or real data with the help of modular algorithms for each of the main fusion functions and image interpretation algorithms. The results obtained from data fusion of information coming from an imaging Synthetic Aperture Radar (SAR) and non-imaging sensors (ESM, IFF, 2-D radar) on-board an airborne maritime surveillance platform are presented for two typical scenarios of Maritime Air Area Operations and Direct Fleet Support. An extensive set of realistic databases has been created that contains over 140 platforms, carrying over 170 emitters and representing targets from 24 countries. A truncated Dempster-Shafer evidential reasoning scheme is used that proves robust under countermeasures and deals efficiently with uncertain, incomplete or poor quality information. The evidential reasoning scheme can yield both single ID with an associated confidence level and more generic propositions of interest to the Commanding Officer. For nearly electromagnetically silent platforms, the Spot Adaptive mode of the SAR, which is appropriate for naval targets, is shown to be invaluable in providing long range features that are treated by a 4-step classifier to yield ship category, type and class. Our approach of reasoning over attributes provided by the imagery will allow the ADFT to process in the next phase (currently under way) both FLIR imagery and SAR imagery in different modes (RDP for naval targets, Strip Map and Spotlight Non-Adaptive for land targets).
This paper describes a work currently in progress whose aim is to design, develop and evaluate a Multi-Agent Framework for Data fusion (DFMAF). This is being done with the support of a battlefield surveillance demonst...
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ISBN:
(纸本)0819436771
This paper describes a work currently in progress whose aim is to design, develop and evaluate a Multi-Agent Framework for Data fusion (DFMAF). This is being done with the support of a battlefield surveillance demonstrator application, named TA-10 [3,6]. Through the following chapters, we will describe the benefits of using such a Framework for data fusion problems. Firstly, we will briefly present the multi-agent research domain. Then, we will go into further details to describe DFMAF, the multi-agent framework designed to help solving data fusion problems. The appropriateness of DFMAF to data fusion problems will also be pointed out. Next, the implementation and use of DFMAF in the support application will be detailed as well as the assessment procedure followed. Finally, we will conclude and expose the future work which will be done.
In this paper, we describe the progress we have achieved in developing a computationally efficient, grid-based Bayesian fusion tracking system. In our approach, the probability surface is represented by a collection o...
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ISBN:
(纸本)9780819490858
In this paper, we describe the progress we have achieved in developing a computationally efficient, grid-based Bayesian fusion tracking system. In our approach, the probability surface is represented by a collection of multidimensional polynomials, each computed adaptively on a grid of cells representing state space. Time evolution is performed using a hybrid particle/grid approach and knowledge of the grid structure, while sensor updates use a measurement-based sampling method with a Delaunay triangulation. We present an application of this system to the problem of tracking a submarine target using a field of active and passive sonar buoys.
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 c...
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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.
This proceedings contains 27 papers. These conferences provide a general discussion and dissemination for researchers and designers of recent advances in field of Multisensor, Multisource Information fusion: Architect...
ISBN:
(纸本)9780819490858
This proceedings contains 27 papers. These conferences provide a general discussion and dissemination for researchers and designers of recent advances in field of Multisensor, Multisource Information fusion: architectures, algorithms, and applications. Papers published were categorized under seven sessions, i.e. Session 1: Information fusion Approaches and algorithms with 4 papers;Session 2: Information fusion Approaches and algorithmsii with 3 papers;Session 3: Information fusion in Robotics with 6 papers;Session 4: Information fusion Approaches and algorithmsiiI (biometrics-related) with 3 papers;Session 5: Image fusion with 3 papers;Session 6: Information fusion Approaches and algorithms IV (human-in-the-loop) with 5 papers;Session 7: Information fusion Systems and Evaluation Measures with 2 papers. Besides, a paper was published as poster session. The key terms of the proceeding papers include sensorfusion;Intensity interferometry;Data Association;Intrusion protection;Network trace generators;Bayesian fusion;Layered sensing systems.
A System for Systems (SoS) design is introduced for improving the overall performance, capabilities, operational robustness, and user confidence in Identification (ID) systems. The physio-associative temporal sensor i...
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A System for Systems (SoS) design is introduced for improving the overall performance, capabilities, operational robustness, and user confidence in Identification (ID) systems. The physio-associative temporal sensor integration algorithm (PATSIA) is used. The 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. These objectives are demonstrated by modeling similar processes from the eyes, ears, and somatosensory channels, through the thalamus, and to cortices as appropriate while using the hippocampus for short-term memory search and storage as necessary.
The work described in this paper focuses on cross band pixel selection as applied to pixel level multi-resolution image fusion. In addition, multi-resolution analysis and synthesis is realised via QMF sub-band decompo...
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The work described in this paper focuses on cross band pixel selection as applied to pixel level multi-resolution image fusion. In addition, multi-resolution analysis and synthesis is realised via QMF sub-band decomposition techniques. Thus cross-band pixel selection is considered with the aim of reducing the contrast and structural distortion image artefacts produced by existing wavelet based, pixel level, image fusion schemes. Preliminary subjective image fusion results demonstrate clearly the advantage which the proposed cross-band selection technique offers, when compared to conventional area based pixel selection.
In many instances, sensing tasks are best addressed with multiple sensing modalities. However, fusion of the outputs of disparate sensor systems presents a significant challenge to forming a cohesive sensing system. A...
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ISBN:
(纸本)9780819481740
In many instances, sensing tasks are best addressed with multiple sensing modalities. However, fusion of the outputs of disparate sensor systems presents a significant challenge to forming a cohesive sensing system. A discussion of strategies for fusion of disparate sensor data is presented and illustrated with examples of real time and retrospective data fusion for multisensor systems. The first example discussed is a real-time system for situational awareness and the detection of damage control events in ship compartments. The second example is a retrospective data fusion framework for a multisensor system for the detection of buried unexploded ordnance at former bomb and target ranges.
In this paper we present a methodology for fuzzy sensorfusion. We then apply this methodology to sensor data from a gas turbine power plant. The developed fusion algorithm tackles several problems: 1.) it aggregates ...
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ISBN:
(纸本)0819431931
In this paper we present a methodology for fuzzy sensorfusion. We then apply this methodology to sensor data from a gas turbine power plant. The developed fusion algorithm tackles several problems: 1.) it aggregates redundant (but uncertain) sensor information;this allows making decisions which sensors land to what degree) should be considered for propagation of sensor information. 2.) It filters out noise and sensor failure from measurements;this allows a system to operate despite temporary or permanent failure of one or more sensors. For the fusion, we use a combination of direct and functional redundancy. The fusion algorithm uses confidence values obtained for each sensor reading from validation curves and performs a weighted average fusion. With increasing distance from the predicted value, readings are discounted through a non-linear validation function. They are assigned a confidence value accordingly. The predicted value in the described algorithm is obtained through application of a fuzzy exponential weighted moving average time series predictor with adaptive coefficients. Experiments on real data from a gas turbine power plant show the robustness of the fusion algorithm which leads to smooth controller input values.
This paper reports on a tactile sensing system with only three sensing elements. The magnitude and position of the applied force is obtained by utilising triangulation approach combined with membrane stress, some info...
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ISBN:
(纸本)081942482X
This paper reports on a tactile sensing system with only three sensing elements. The magnitude and position of the applied force is obtained by utilising triangulation approach combined with membrane stress, some information about shape of the contact object is obtained. The sensor is designed to overcome the problems of cross-talk between sensing elements, complexity and fragility which is associated with some PVDF tactile sensors arranged in matrix form. The theoretical analysis of the sensor is made and compared with experimental results. The limitation of the sensor is also reported.
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