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Intelligent fusion processing in BMD applications

Intelligent fusion processing in BMD applications

引用

conference on sensor fusion - architectures, algorithms, and applications

作者： McCullough, C Byrd, K Bjork, C Grider, G Smith, B Morris, N Dasarathy, B U.S. Army Space and Strategic Defense Command (United States) Nichols Research Corp. (United States) Dynetics Inc. (United States)

ISBN: (纸本)081942482X

Intelligent processing techniques are applied to a Ballistic Missile Defense (BMD) application, focused on classifying the objects in a typical threat complex, using fused IR and Ladar sensors. These techniques indicate the potential to improve designation robustness against ''off-normal''/unexpected conditions, or when sensor data or classifier performance degrades. A Fused sensor Discrimination (FuSeD) simulation testbed was assembled for designation experiments, to evaluate test and simulation data, assess intelligent processor and classification algorithms, and evaluate sensor performance. Results were produced for a variety of neural net and other nonlinear classifiers, yielding high designation performance and low false alarm rates. Most classifiers yield a few percent in false alarm rate: rates are further improved when multiple techniques are applied via a Majority Based fusion technique. Example signatures, features, classifier descriptions, intelligent controller design, and architecture ate included. Work was performed for the Discriminating Interceptor Technology Program (DITP).

关键词： sensors LIDAR Intelligent sensors Neural networks Data fusion Doppler effect Computer simulations Detection and tracking algorithms Infrared sensors Infrared signatures

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The system parameter fusion principle and its application to fuzzy pattern recognition

The system parameter fusion principle and its application to...

引用

conference on Multisensor, Multisource Information fusion - architectures, algorithms and applications 2003

作者： Pu, QG Univ Sci & Technol Ctr Comp Suzhou 215011 Jiangsu Peoples R China

ISBN: (纸本)0819449598

Modern technology provides a great amount of information. In computer monitoring systems or computer control systems, especially real-time expert systems, in order to have the situation in hand, we need one or two parameters to express the quality and/or security of the whole system. This paper presents a principle for synthesizing measurements of multiple system parameters into a single parameter and its application to fuzzy pattern recognition.

关键词： sensor fusion fuzzy pattern recognition computer monitoring systems computer control systems realtime expert systems

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Decision fusion in sensor Networks for Spectrum Sensing based on Likelihood Ratio Tests

Decision Fusion in Sensor Networks for Spectrum Sensing base...

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conference on Advanced Signal Processing algorithms, architectures, and Implementantions XVIII

作者： Chung, Wei-Ho Yao, Kung Univ Calif Los Angeles Dept Elect Engn Los Angeles CA 90095 USA

ISBN: (纸本)9780819472946

sensor networks have been shown to be useful in diverse applications. One of the important applications is the collaborative detection based on multiple sensors to increase the detection performance. To exploit the spectrum vacancies in cognitive radios, we consider the collaborative spectrum sensing by sensor networks in the likelihood ratio test (LRT) frameworks. In the LRT, the sensors make individual decisions. These individual decisions are then transmitted to the fusion center to make the final decision, which provides better detection accuracy than the individual sensor decisions. We provide the lowered-bounded probability of detection (LBPD) criterion as an alternative criterion to the conventional Neyman-Pearson (NP) criterion. In the LBPD criterion, the detector pursues the minimization of the probability of false alarm while maintaining the probability of detection above the pre-defined value. In cognitive radios, the LBPD criterion limits the probabilities of channel conflicts to the primary users. Under the NP and LBPD criteria, we provide explicit algorithms to solve the LRT fusion rules, the probability of false alarm, and the probability of detection for the fusion center. The fusion rules generated by the algorithms are optimal under the specified criteria. In the spectrum sensing, the fading channels influence the detection accuracies. We investigate the single-sensor detection and collaborative detections of multiple sensors under various fading channels, and derive testing statistics of the LRT with known fading statistics.

关键词： sensor networks cognitive radio lower-bounded probability of detection criterion Neyman-Pearson criterion decision fusion

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A Metamaterial-Inspired Combined Inductive-Capacitive sensor

A Metamaterial-Inspired Combined Inductive-Capacitive Sensor

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conference on Multisensor, Multisource Information fusion - architectures, algorithms, and applications

作者： Long, Jiang Wang, Bingnan Mitsubishi Elect Res Labs Cambridge MA 02139 USA

ISBN: (纸本)9781628410587

This paper reports a metamaterial inspired combined inductive-capacitive sensing method for detecting and distinguishing metallic and non-metallic objects. Metallic and non-metallic objects can be distinguished by measuring both of their inductive and capacitive responses based on the fact that they respond differently to inductive and capacitive sensing. The proposed method is inspired by metamaterial structures. Both inductive and capacitive sensing are simultaneously realized when the sensor is operating at off-resonant frequencies. The proposed method is demonstrated with typical printed circuit board (PCB) technology. The designed sensor can distinguish the metallic and dielectric objects with a sensing range about 10 mm, showing a competitive performance compared with commercially available proximity sensors.

关键词： proximity sensor metamaterials combined sensing

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Performance evaluation on contour extraction using Hough transform and RANSAC for multi-sensor data fusion applications in industrial food inspection

Performance evaluation on contour extraction using Hough tra...

引用

20th IEEE conference on Signal Processing - algorithms, architectures, Arrangements, and applications (SPA)

作者： Kroeger, M. Sauer-Greff, W. Urbansky, R. Lorang, M. Siegrist, M. Univ Kaiserslautern Chair Commun Engeneering Kaiserslautern Germany WIPOTEC GmbH Kaiserslautern Germany

ISBN: (纸本)9788362065271

For multi-sensor data fusion applications the accurate alignment of different sensor data is essential for the proper combination of matching features. In food inspection system the boxing often is in a rectangular shape. This knowledge can be used to rectify the image data, an important step in the alignment stage. In case of low contrast between boxing and background, the detected contour may differ significantly from the actual values. In this paper the performance of the Hough transform and the RANdom SAmple Consensus (RANSAC)-algorithm are evaluated relating to the correct extraction of the boxing contour out of contour data distorted by position errors of the outer shape. The evaluation results indicate the superiority of the RANSAC algorithm with respect to scalability, robustness and execution time.

关键词： Hough transforms

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Application of sensor fusion and signal classification techniques in a distributed machinery condition monitoring system

Application of sensor fusion and signal classification techn...

引用

sensor fusion: architectures, algorithms, and applications iv

作者： Reichard, Karl M. Van Dyke, Mike Maynard, Ken Pennsylvania State Univ State College United States

A new paradigm for machinery maintenance is emerging as preventive maintenance strategies are being replaced by condition-based maintenance. In condition-based maintenance, machinery is repaired or serviced only when an intelligent monitoring system indicates that the system cannot fulfill mission requirements. The implementation of such systems requires a combination of sensor data fusion, feature extraction, classification, and prediction algorithms. In addition, new system architectures are being developed to facilitate the reduction of wide bandwidth sensor data to concise predictions of ability of the system to complete its current mission or future missions. This paper describes the system architecture, data fusion, and classification algorithms employed in a distributed, wireless bearing and gear health monitoring system. The role and integration of prognostic algorithms - required to predict future system health - are also discussed. Examples are provided which illustrate the application of the system architecture and algorithms to data collected on a machinery diagnostics test bed at the Applied Research Laboratory at The Pennsylvania State University.

关键词： sensor data fusion

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sensor management in an ASW data fusion system

Sensor management in an ASW data fusion system

引用

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

作者： Penny, DE Def Evaluat & Res Agcy Malvern WR14 3PS Worcs England

ISBN: (纸本)0819431931

The Multi-sensor fusion Management (MSFM) algorithm positions multiple, detection-only, passive sensors in a two-dimensional plane to optimise the fused probability of detection using a simple decision fusion method, previously the MSFM algorithm was evaluated on two synthetic problem domains comprising of both static and moving targets(1). In the original formulation the probability distribution of the target location was modelled using a non-parametric approach. The logarithm of the fused detection probability was used as a criterion function for the optimisation of the sensor positions. This optimisation used a straightforward gradient ascent approach, which occasionally found local optima. Following the placement optimisation the sensors were deployed and the individual sensor detections combined using a logical OR fusion rule. The target location distribution could then be updated using the method of sampling, importance re-sampling (SIR). In the current work the algorithm is extended to admit a richer variety of behaviour. More realistic sensor characteristic models are used which include detection-plus-bearing sensors and false alarm probabilities commensurate with actual sonar sensor systems. In this paper the performance of the updated MSFM algorithm is illustrated on a realistic anti-submarine warfare (ASW) application(2) in which the placement of the sensors is carried out incrementally, allowing for the optimisation of both the location and the number of sensors to be deployed.

关键词： sensor fusion resource allocation anti-submarine warfare (ASW)

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Feature level sensor fusion

Feature level sensor fusion

引用

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

作者： Peli, T Young, M Knox, R Ellis, K Bennett, F Atlantic Aerosp Elect Corp Waltham MA 02154 USA

ISBN: (纸本)0819431931

This paper describes two practical fusion techniques (hybrid fusion and cued fusion) for automatic target cueing that combine features derived from each sensor data at the object-level. In the hybrid fusion method each of the input sensor data is prescreened (i.e. Automatic Target Cueing (ATC) is performed) before the fusion stage. The cued fusion method assumes that one of the sensors is designated as a primary sensor, and thus ATC is only applied to its input data. If one of the sensors exhibits a higher Pd and/or a lower false alarm rate, it can be selected as the primary sensor, However, if the ground coverage can be segmented to regions in which one of the sensors is known to exhibit better performance, then the cued fusion can be applied locally/adaptively by switching the choice of a primary sensor. Otherwise, the cued fusion is applied both ways (each sensor as primary) and the outputs of each cued mode are combined. Both fusion approaches use a back-end discrimination stage that is applied to a combined feature vector to reduce false alarms. The two fusion processes were applied to spectral and radar sensor data and were shown to provide substantial False alarm reduction. The approaches are easily extendable to more than two sensors.

关键词： sensors Image fusion Data fusion Synthetic aperture radar Target detection Feature extraction sensor fusion Image processing Infrared sensors Target recognition

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Proceedings of SPIE: Multisensor, Multisource Information fusion: architectures, algorithms, and applications 2003

Proceedings of SPIE: Multisensor, Multisource Information Fu...

引用

Multisensor. Multisource Information fusion: architectures, algorithms, and applications 2003

This Volume 5099 of the conference proceedings contains 45 papers. Topics discussed include classification and decision fusion, image level fusion, approximate reasoning methodologies, estimation and tracking, fusion methodologies, evolving concepts and methodologies, architectures and related topics, industrial, medical and speech applications, defense applications, sensor/resource management and related topics.

关键词： sensor data fusion

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Biologically-based sensor fusion for medical imaging

Biologically-based sensor fusion for medical imaging

引用

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

作者： Aguilar, M Garrett, AL Jacksonville State Univ Knowledge Syst Lab Jacksonville AL 36265 USA

ISBN: (纸本)0819440809

We present an architecture for the fusion of multiple medical image modalities that enhances the original imagery and combines the complementary information of the various modalities. The design principles follow the organization of the color vision system in humans and primates. Mainly, the design of within-modality enhancement and between-modality combination for fusion is based on the neural connectivity of retina and visual cortex. The architecture is based on a system developed and deployed for night vision applications while the first author was at MIT Lincoln Laboratory [1, 2]. Results of fusing various modalities are presented, including: a) fusion of T1-weighted and T2-weighted MRI images, b) fusion of PD, T1-weighted, and T2-weighted, and c) fusion of SPECT and MRI/CT. The results will demonstrate the ability to fuse such disparate imaging modalities with regards to information content and complementarities. These results will show how both brightness and color contrast are used in the resulting color fused images to convey information to the user. In addition, we will demonstrate the ability to preserve the high spatial resolution of modalities such as MRI even when combined with poor resolution images such as from SPECT scans. We conclude by motivating the use of the fusion method to derive more powerful image features to be used in segmentation and pattern recognition.

关键词： image fusion sensor fusion medical image processing automated diagnosis diagnostic aids

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