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检索条件"任意字段=Sensor Fusion: Architectures, Algorithms and Applications V"

共 786 条记录，以下是451-460 订阅

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A new class of Heuristic Polynomial Time algorithms to solve the Multidimensional Assignment Problem

A new class of Heuristic Polynomial Time Algorithms to solve...

引用

International Conference on Information fusion

作者： F. Perea H. W. De Waard AWS Department Thales Naval Nederland B.V. Netherlands

ISBN: (纸本)1424409535

The multidimensional assignment problem (MAP) is a combinatorial optimization problem arising in many applications, for instance in multi-target multi-sensor tracking problems. It is well-known that the MAP is NP-hard. The objective of a MAP is to match d-tuples of objects in such a way that the solution with the optimum total cost is found. In this paper a new class of approximation algorithms to solve the MAP is presented, named K-SGTS, and its effectiveness in multi-target multi-sensor tracking situations is shown. Its computational complexity is proven to be polynomial. Experimental results on the accuracy and speed of K-SGTS are provided in the last section of the paper

关键词： Polynomials Heuristic algorithms Multidimensional systems Radar tracking Position measurement Target tracking State estimation Covariance matrix Clutter Radar measurements

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Development of a MATLAB Based Target Tracking Simulation Environment

Development of a MATLAB Based Target Tracking Simulation Env...

引用

IEEE Signal Processing and Communications applications (SIU)

作者： Aslan Saranli Baykal İLTAREN TÜBİTAK-UEKAE Ankara Turkey TÜBİTAK-UEKAE İLTAREN Ankara Elektrik ve Elektronik Müihendisliği Bölümü O.D.T.Ü Ankara Turkey Elektrik ve Elektronik Mühendisliği Bölümü O.D.T.Ü Ankara

A simulation environment for tracking of maneuvering targets in clutter is developed in MATLAB. The simulation environment allows to generate 2-dimensional surveillance radar measurements and to run various target tracking algorithms on these measurements. As a first simulation example, IMM-NNJPDA algorithm, which incorporates NNJPDA data association and IMM filter structure, is implemented and the performance of this algorithm is investigated in an example scenario. By this simulator, in the future, it is aimed that statistical test and evaluation of different radar sensors, scenarios, target tracking methods and data fusion architectures will be performed

关键词： MATLAB Target tracking Radar tracking Clutter Surveillance Radar measurements Filters Testing sensor fusion Performance evaluation

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Multiple-Hypothesis Trilateration and Tracking with Distributed Radars

Multiple-Hypothesis Trilateration and Tracking with Distribu...

引用

International Conference on Information fusion

作者： Jelle van Kleef Jeroen Bergmans Leon Kester Frans Groen TNO D&V TNO D & V Netherlands Informatics Institute University of Amsterdam Netherlands

ISBN: (纸本)1424409535

A novel algorithm to associate and trilaterate detections from multiple distributed radars is presented. The algorithm provides for flexible track state representations. The coordinate system of a track is switched from the measurement coordinates (range-Doppler) to cartesian coordinates when a detection from another sensor is associated to the track. In the case of multiple targets and false alarms we run into the complication of multiple association possibilities. These can be resolved by using a multi-hypothesis algorithm. In general, correctly formed tracks will have more likely associations. Therefore, hypotheses describing these tracks will be favored. Simulations with one or two targets and different false alarm rates show the need to preserve multiple hypotheses of the world state. Tracking performance for various false alarms rates is evaluated

关键词： Radar tracking Radar detection Target tracking Coordinate measuring machines Robustness Equations sensor systems Informatics Change detection algorithms Radar applications

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Objectively Optimised Multisensor Image fusion

Objectively Optimised Multisensor Image Fusion

引用

International Conference on Information fusion

作者： v. Petrovic T. Cootes Imaging Science Biomedical Engineering University of Manchester Institute of Science and Technology Manchester UK

ISBN: (纸本)1424409535

A plethora of image fusion algorithms have been proposed recently, yet what are optimal fusion parameters that should be used for any multi-sensor dataset cannot be defined a priori. They could be learned by evaluating all available fusion strategies on large, representative datasets, but this is not practical and provides no guarantee that fusion performance will remain optimal should real input conditions differ from sample data. This paper proposes and examines the viability of a powerful framework for objectively optimal image fusion that explicitly optimises fusion performance for any set of input conditions. The idea is to integrate proven concepts used in objective image fusion evaluation metrics to optimally adapt the fusion process to the input conditions. Specific focus is on fusion for display, which has a broad appeal in a wide range of fusion applications as only metrics shown to be subjectively relevant are considered. The results show that the proposed framework achieves a considerable improvement in both the level and robustness of fusion performance for a wide array of multi-sensor images

关键词： Image fusion Discrete wavelet transforms Displays Robustness Multiresolution analysis Biomedical imaging Biomedical engineering Image reconstruction Laplace equations Image segmentation

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On handling dependent evidence and multiple faults in knowledge fusion for engine health management

On handling dependent evidence and multiple faults in knowle...

引用

IEEE Conference on Aerospace

作者： v. Guralnik D. Mylaraswamy H. voges Honeywell Aerospace Research Laboratories Minneapolis MN USA

Diagnostic architectures that fuse outputs from multiple algorithms are described as knowledge fusion or evidence aggregation. Knowledge fusion using a statistical framework such as Dempster-Shafer (D-S) has been used in the context of engine health management. Fundamental assumptions made by this approach include the notion of independent evidence and single fault. In most real world systems, these assumptions are rarely satisfied. Relaxing the single fault assumption in D-S based knowledge fusion involves working with a hyper-power set of the frame of discernment. Computational complexity limits the practical use of such extension. In this paper, we introduce the notion of mutually exclusive diagnostic subsets. In our approach, elements of the frame of discernment are subsets of faults that cannot be mistaken for each other, rather than failure modes. These subsets are derived using a systematic analysis of connectivity and causal relationship between various components within the system. Specifically, we employ a special form of reachability analysis to derive such subsets. The theory of D-S can be extended to handle dependent evidence for simple and separable belief functions. However, in the real world the conclusions of diagnostic algorithms might not take the form of simple or separable belief functions. In this paper, we present a formal definition of algorithm dependency based on three metrics: the underlying technique an algorithm is using, the sensors it is using, and the feature of the sensor that the algorithm is using. With this formal definition, we partition evidence into highly dependent, weakly dependent and independent evidence. We present examples from a Honeywell auxiliary power unit to illustrate our modified D-S method of evidence aggregation

关键词： Engines Knowledge management Partitioning algorithms Technology management Laboratories Fuses Manufacturing Monitoring Computer architecture Large-scale systems

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Real-time acoustic monitoring using wireless sensor motes

Real-time acoustic monitoring using wireless sensor motes

引用

IEEE International Symposium on Circuits and Systems (ISCAS)

作者： v. Berisha Homin Kwon A. Spanias Department of Electrical Engineering Arizona State University Tempe AZ USA

Wireless sensor networks (WSN) have recently gained popularity in distributed monitoring and surveillance applications. The objective of these devices is to extract pertinent information under several constrains such as low computational capabilities, limited arithmetic precision, and the need to conserve power. One of the most revealing environmental cues is audio. In this paper, we propose a voice activity detector and a simple gender classifier for use in a distributed acoustic sensing system. This algorithm makes use of low-complexity audio features and a pre-trained regression tree to classify incoming speech by gender. The algorithm is implemented real-time on the Crossbow sensor motes and a series of results are given that characterize the algorithm performance and complexity. Challenges in this real-time implementation include designing the algorithm and software architecture such that the signal processing is appropriately distributed between the sensor mote and the base station. At the base station, a data fusion algorithm considers a linear combination of individual mote decisions to form a final decision

关键词： Monitoring Wireless sensor networks Acoustic sensors Signal processing algorithms sensor phenomena and characterization Base stations Acoustic devices Surveillance Data mining Arithmetic

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Resource Allocation and Cross Layer Control in Wireless Networks

引用

2006年

作者： Leonidas Georgiadis Michael Neely Leandros Tassiulas

ISBN: (数字)9781933019697

ISBN: (纸本)9781933019260

Information flow in a telecommunication network is accomplished through the interaction of mechanisms at various design layers with the end goal of supporting the information exchange needs of the applications. In wireless networks in particular, the different layers interact in a nontrivial manner in order to support information transfer. Resource Allocation and Cross Layer Control in Wireless Networks presents abstract models that capture the cross layer interaction from the physical to transport layer in wireless network architectures including cellular, ad-hoc and sensor networks as well as hybrid wireless-wireline. The model allows for arbitrary network topologies as well as traffic forwarding modes, including datagrams and virtual circuits. Furthermore the time varying nature of a wireless network, due either to fading channels or to changing connectivity due to mobility, is adequately captured in this model to allow for state dependent network control policies. Quantitative performance measures that capture the quality of service requirements in these systems depending on the supported applications are discussed, including throughput maximization, energy consumption minimization, rate utility function maximization as well as general performance functionals. Cross-layer control algorithms with optimal or suboptimal performance with respect to the above measures are presented and analyzed. A detailed exposition of the related analysis and design techniques is provided. The emphasis in the presentation is on describing the models and the algorithms with application examples that illustrate the range of possible applications. Representative cases are analyzed in full detail to illustrate the applicability of the analysis techniques, while in other cases the results are described without proofs and references to the literature are provided.

关键词： wireless networks foundations control layer allocation cross resource

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PERFORMANCE AND LIMITATIONS OF DISTRIBUTED INFERENCE AND INFORMATION fusion IN WIRELESS sensor NETWORK applications

PERFORMANCE AND LIMITATIONS OF DISTRIBUTED INFERENCE AND INF...

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作者： Sherry, Richard Ray PennState University Libraries

学位级别：Doctor of Philosophy

Recent advances in sensor design and miniaturization have provided the opportunity for the creation of large distributed wireless sensor networks. There has been significant progress in combining sensing, processing, data storage and communications capabilities, in network self organization, and in optimizing communication architectures. In contrast to most other network applications, wireless sensor networks face a number of special challenges and constraints resulting from 1) lack of hardwired connections (no external power sources, low communications bandwidths, higher communication error rates), 2) small physical size (small onboard energy supply, small antennas/acoustic transducers, small low energy sensors) and 3) elevated sensor node failure rates. One of the key remaining challenges is in the area of inference and information fusion (aggregating/filtering/interpreting the sensor data into useful high level knowledge). Many authors have advocated the use of local distributed inference and fusion algorithms such as the iterative message-passing belief propagation algorithms employed on probabilistic graphical models (Bayesian Networks and Markov Random Fields). However, little research has been performed to assess the performance of these algorithms under the special constraints imposed by wireless sensor network applications. This dissertation reports on a study investigating issues associated with application of these algorithms to realistic wireless sensor networks configurations. This research has produced results delineating the performance and limitations including communications requirements, energy resource requirements and the impacts of different topologies and architectures such as hierarchical/non-hierarchical topologies, centralized or distributed processing, localized (in local node clusters) or full network models, and node cluster size.

关键词： wireless sensor networks information fusion data fusion

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Performance and limitations of distributed inference and information fusion in wireless sensor network applications

Performance and limitations of distributed inference and inf...

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作者： Sherry, Richard R. The Pennsylvania State University

学位级别：Ph.D.

Recent advances in sensor design and miniaturization have provided the opportunity for the creation of large distributed wireless sensor networks. There has been significant progress in combining sensing, processing, data storage and communications capabilities, in network self organization, and in optimizing communication architectures. In contrast to most other network applications, wireless sensor networks face a number of special challenges and constraints resulting from (1) lack of hardwired connections (no external power sources, low communications bandwidths, higher communication error rates), (2) small physical size (small onboard energy supply, small antennas/acoustic transducers, small low energy sensors) and (3) elevated sensor node failure rates. One of the key remaining challenges is in the area of inference and information fusion (aggregating/filtering/interpreting the sensor data into useful high level knowledge). Many authors have advocated the use of local distributed inference and fusion algorithms such as the iterative message-passing belief propagation algorithms employed on probabilistic graphical models (Bayesian Networks and Markov Random Fields). However, little research has been performed to assess the performance of these algorithms under the special constraints imposed by wireless sensor network applications. This dissertation reports on a study investigating issues associated with application of these algorithms to realistic wireless sensor networks configurations. This research has produced results delineating the performance and limitations including communications requirements, energy resource requirements and the impacts of different topologies and architectures such as hierarchical/non-hierarchical topologies, centralized or distributed processing, localized (in local node clusters) or full network models, and node cluster size.

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Proceedings of SPIE: Multisensor, Multisource Information fusion: architectures, algorithms, and applications 2005

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

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Multisensor, Multisource Information fusion: Architecture, algorithms, and applications 2005

The proceedings contain 35 papers from the conference on Multisensor, Multisource Information fusion: architectures, algorithms, and applications 2005. Topics discussed include: reduced data projection slice image fusion using principal component analysis;real-time implementation of image alignment and fusion;image fusion with the hybrid evolutionary algorithm and response analysis;a perceptual quality metric for image fusion based on regional information;multispectral sensor fusion using the projection-slice theorem;a situation awareness model applied to multiple domains;hybrid framework for fusion 2+ in multi-multi air engagement;and product-based multiresolution image fusion.

关键词： sensor data fusion

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