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sensor management in an ASW data fusion system

Proceedings of SPIE - The International Society for Optical Engineering 1999年 3719卷 418-429页

作者： Penny, Dawn E. Defence Evaluation and Research Agency Worcestershire United Kingdom

The Multi-sensor fusion Management (MSFM) algorithm is extended to admit a richer variety of behavior. More realistic sensor characteristic models are used such as detection-plus-bearing sensors and false alarm probabilities commensurate with actual sonar sensor systems. The performance of the modified MSFM algorithm is illustrated on a realistic anti-submarine warfare (ASW) application.

关键词： sensor data fusion

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Virtual associative networks: a new paradigm for sensor fusion

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Proceedings of SPIE - The International Society for Optical Engineering 1999年 3719卷 43-50页

作者： Malhotra, Raj P. Yufik, Yan M. Air Force Research Lab Wright-Patterson Air Force Base United States

We discuss Virtual Associative Networks (VANs) and their relevance for addressing computationally prohibitive sensor fusion problems (with results in Dynamic sensor Management). To our knowledge, this discussion of VAN technology for sensor fusion is unique and our current result involving VANs for Dynamic sensor Management is the first of its kind. The following provides methodology, results, and extensions.

关键词： sensor data fusion

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Information fusion for onboard and offboard avionics

Information fusion for onboard and offboard avionics

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Conference on sensor fusion - architectures, algorithms, and applications ii

作者： Kurien, T Chao, A Gully, SW Wood, A ALPHATECH Inc Burlington MA 01803 USA

ISBN: (纸本)0819428256

This paper defines and demonstrates an all-source information fusion system for combining onboard and offboard data and maintain continuous track on targets. We provide an architecture containing an offboard data processor to extract data relevant to the attack aircraft mission, and a set of fusion modules for recursively associating sensor reports, tracking targets, and classifying targets. These modules are derived from a well-posed mathematical formulation which enables us to define precise interfaces among the fusion modules. This approach provides three benefits. First, it enables us to construct a fusion algorithm with close-to-optimal target tracking and classification performance. Second, it allows us to study new fusion algorithms by implementing alternate algorithms for each module. Third, it allows us to process data from any combination of sensors making the architecture applicable to a variety of attack aircraft and missions. We show that the proposed system can increase a pilot's situational awareness by providing him with a clearer battlefield picture consistent with attack aircraft mission objectives. Results for a simple but realistic air-to-ground scenario simulation demonstrate the benefits of fusing data from offboard and onboard sensors.

关键词： all source fusion Multiple Hypothesis Tracking (MHT) image gee-registration continuous tracking onboard-offboard fusion Kalman filtering

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To fuse or not to fuse: Fuser versus best classifier

To fuse or not to fuse: Fuser versus best classifier

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Conference on sensor fusion - architectures, algorithms, and applications ii

作者： Rao, NSV Oak Ridge Natl Lab Oak Ridge TN 37831 USA

ISBN: (纸本)0819428256

A sample from a class defined on a finite-dimensional Euclidean space and distributed according to an unknown distribution is given. We are given a set of classifiers each of which chooses a hypothesis with least misclassification error from a family of hypotheses. We address the question of choosing the classifier with the best performance guarantee versus combining the classifiers using a fuser. We first describe a fusion method based on isolation property such that the performance guarantee of the fused system is at least as good as the best of the classifiers. For a more restricted case of deterministic classes, we present a method based on error set estimation such that the performance guarantee of fusing all classifiers is at least as good as that of fusing any subset of classifiers.

关键词： classification finite sample analysis distributed detection fusion of classifiers

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Multi-sensor fusion for airport surface movement area surveillance and safety

Multi-sensor fusion for airport surface movement area survei...

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Conference on sensor fusion - architectures, algorithms, and applications VI

作者： Pendergast, SL CACI Technol Inc San Diego CA 92108 USA

ISBN: (纸本)0819444812

In this paper we describe the nature of the problem of surveillance of airport surface movement. We describe the characteristics, performance, and unique problems of various airport sensors available, and the need to develop a fusion system to provide an integrated surveillance picture. Parallel sensor fusion developments are described in terms of their applicability to the sensor fusion task in surface surveillance. Paradigms for sensor fusion, including alternative architectures, algorithms, and performance metrics will be described. Finally we describe system implementation and quantitative performance of sensor fusion applied to the surface surveillance problem at demonstrations in Atlanta Hartsfield International Airport (1998, ATL), Dallas Fort Worth International Airport (1999, 2000, DFW), and in-process and planned future developments in sensor fusion.

关键词： airport surveillance runway incursion safety ATIDS RIPS RIRP ASDE AMASS

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Quantisation for probability-level fusion on a bandwidth budget

Quantisation for probability-level fusion on a bandwidth bud...

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Conference on sensor fusion - architectures, algorithms, and applications ii

作者： Black, JV Bedworth, MD Def Evaluat & Res Agcy Malvern Malvern WR14 3PS Worcs England

ISBN: (纸本)0819428256

Results are established for a simulated data fusion architecture featuring a synthetic two-class Gaussian problem, with Bayesian recognisers. The recognisers output posterior probabilities for each class. The probabilities from two or more recognisers of identical error rate are quantised using the nearest-neighbour coding rule. The coded values are decoded at a fusion centre and fused. A decision is made from the fused probabilities. The performance of the architecture is examined experimentally using code values that are uniformly distributed and code values that are produced using the Linde-Buzo-Grey (LEG) algorithm. Results are produced for two to six sensors and two to 32 code values. These results are compared to fusing probabilities represented using 32 bit floating-point numbers. Using 32 uniform or LEG-produced code values, produces results that are at most only 1% worse than fusing the uncoded probabilities.

关键词： data fusion quantisation architecture

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sensor fusion with application to Electronic Warfare

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Proceedings of SPIE - The International Society for Optical Engineering 1999年 3719卷 114-125页

作者： Zanzalari, Robert M. Van Alstine, Edward AMSEL-RD-NV-S/CCD Fort Monmouth United States

Situational Awareness is one of the keys to realizing the full potential of a weapons platform. It encompasses mission planning and rehearsal, the optimum use of offensive and defensive resources, and post mission analysis. In this report, the Situation Awareness process is described as it relates to the integration of Electronic Warfare (EW) with targeting and intelligence and information warfare systems. Discussion is focused on the sensor fusion, Situation Assessment, and Response Management Strategies.

关键词： sensor data fusion

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Intelligent processing techniques for sensor fusion

Intelligent processing techniques for sensor fusion

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Conference on sensor fusion - architectures, algorithms, and applications ii

作者： Byrd, K Smith, B Allen, D Morris, N Bjork, C Deal-Giblin, K Nichols Res Corp Huntsville AL 35815 USA

ISBN: (纸本)0819428256

Intelligent processing techniques which can effectively combine sensor data from disparate sensors by selecting and using only the most beneficial individual sensor data is a critical element of exoatmospheric interceptor systems. A major goal of these algorithms is to provide robust discrimination against stressing threats in poor a priori conditions, and to incorporate adaptive approaches in off-nominal conditions. This paper summarizes the intelligent processing algorithms being developed, implemented and tested to intelligently fuse data from passive infrared and active LADAR sensors at the measurement, feature and decision level. These intelligent algorithms employ dynamic selection of individual sensor features and the weighting of multiple classifier decisions to optimize performance in good a priori conditions and robustness in poor a priori conditions. Features can be dynamically selected based on an estimate of the feature confidence which is determined from feature quality and weighting terms derived from the quality of sensor data and expected phenomenology. Multiple classifiers are employed which use both fuzzy logic and knowledge based approaches to fuse the sensor data and to provide a target lethality estimate. Target designation decisions can be made by fusing weighted individual classifier decisions whose output contains an estimate of the confidence of the data and the discrimination decisions. The confidence in the data and decisions can be used in real time to dynamically select different sensor feature data or to request additional sensor data on specific objects that have not been confidently identified as being lethal or non-lethal, The algorithms are implemented in C within a graphic user interface framework. Dynamic memory allocation and the sequential implementation of the feature algorithms are employed. The baseline set of fused sensor discrimination algorithms with intelligent processing are described in this paper. Example results from

关键词： sensor fusion intelligent processing discrimination feature extraction infrared laser radar fuzzy logic

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Morphological filters and wavelet based image fusion for concealed weapons detection

Morphological filters and wavelet based image fusion for con...

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Conference on sensor fusion - architectures, algorithms, and applications ii

作者： Ramac, LC Uner, MK Varshney, PK Alford, M Ferris, D Syracuse Univ Dept Elect Engn & Comp Sci Syracuse NY 13244 USA

ISBN: (纸本)0819428256

When viewing a scene for an object recognition task, one imaging sensor may not provide all the information needed for recognition. One way to obtain more information is to use multiple sensors. These sensors should provide images that contain complementary information about the same scene. After preprocessing the source images, we use image fusion to combine the information from the different sensors. The images to be fused may have some details such as shadows, wrinkles, imaging artifacts, etc., that are not needed in the final fused image. One application of morphological filters is to remove objects of a given size range from the image. Therefore, we use morphological filters in conjunction with wavelets to improve the recognition performance after fusion. After morphological filtering, wavelets are used to construct multiresolution representations of the source images. Once the source images are decomposed, the details are combined to form a composite decomposed image. This method allows details at different levels to be combined independently so that important information is maintained in the final composite image. We are developing image fusion algorithms for concealed weapon detection (CWD) applications. fusion is useful in situations where the sensor types have different properties, e.g., IR and MMW sensors. Fusing these types of images results in composite images which contain more complete information for CWD applications such as detection of concealed weapons on a person, In this paper we present our most recent results in this area.

关键词： image fusion mathematical morphology wavelets

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Feature and data level fusion of infrared and visual images

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Proceedings of SPIE - The International Society for Optical Engineering 1999年 3719卷 312-318页

作者： Ulug, M.E. McCullough, Claire L. Intelligent Neurons Deerfield Beach United States

In both military and civilian applications, increasing interest is being shown in fusing infrared and vision images for improved situational awareness. In previous work, the authors have developed a fusion method for combining the thermal and vision images into a single image emphasizing the most salient features of the surrounding environment. This approach is based on the assumption that although the thermal and vision data are uncorrelated, they are complementary and can be fused using a suitable disjunctive function. This paper, as a continuation of that work, will describe the development of an information based real-time data level fusion method. In addition, applicability of the algorithms that we developed for data level fusion to feature level techniques (e.g., shapes, lines, and edges) will be investigated.

关键词： sensor data fusion

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