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检索条件"任意字段=Conference on Sensor Fusion - Architectures, Algorithms, and Applications VI"

共 306 条记录，以下是91-100 订阅

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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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Joint fusion and detection of mines using hyperspectral and SAR data

Joint fusion and detection of mines using hyperspectral and ...

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conference on Image Processing - algorithms and Systems vi

作者： Nasrabadi, Nasser M. Army Res Lab Adelphi MD 20783 USA

ISBN: (纸本)9780819469847

This paper describes a new nonlinear joint fusion and anomaly detection technique for mine detection applications using two different types of sensor data (synthetic aperture radar (SAR) and Hyperspectral sensor (HS) data). A well-known anomaly detector so called the RX algorithm is first extended to perform fusion and detection simultaneously at the pixel level by appropriately concatenating the information from the two sensors. This approach is then extended to its nonlinear version. The nonlinear fusion-detection approach is based on the statistical kernel learning theory which explicitly exploits the higher order dependencies (nonlinear relationships) between the two sensor data through an appropriate kernel. Experimental results for detecting anomalies (mines) in hyperspectral imagery are presented for linear and nonlinear joint fusion and detection for a co-registered SAR and HS imagery. The result show that the nonlinear techniques outperform linear versions.

关键词： sensor fusion anomaly detection hyperspectral mine detection joint fusion and detection

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Data and sensor fusion for bistatic applications

Data and sensor fusion for bistatic applications

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conference on Multisensor, Multisource Information fusion

作者： Lee, Anne L. Walden Univ Minneapolis MN 55401 USA

ISBN: (纸本)9780819471659

Detection and tracking of sophisticated targets involving increased resolution and the utility of synthetic aperture transmitter windows require new and innovative approaches to active sensor technologies. The bistatic technique to target tracking is extended to form a multistatic radar system using multiple and separate transmitters and receivers that are designated sparsely located in a region. The fusion of the received data through the utility of a non-linear Kalman filter technique is discussed to predict track through observations from the multistatic system. Target positions and velocities are estimated and the error is shown to converge to zero. The Munkre algorithm is utilized for data and track association to improve error minimization.

关键词： Munkre algorithm resolution active sensors data fusion tracking non-linear Kalman filtering radar

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Advances in image registration and fusion

Advances in image registration and fusion

引用

conference on Multisensor, Multisource Information fusion

作者： Steer, Chris Rogers, Jeremy Smith, Moira Heather, Jamie Bernhardt, Mark Hickman, Duncan Waterfall Solut Ltd Surrey GU2 9JX England

ISBN: (纸本)9780819471659

Many image fusion systems involving passive sensors require the accurate registration of the sensor data prior to performing fusion. Since depth information is not readily available in such systems, all registration algorithms are intrinsically approximations based upon various assumption about the depth field. Although often overlooked, many registration algorithms can break down in certain situations and this may adversely affect the image fusion performance. In this paper, we discuss a framework for quantifying the accuracy and robustness of image registration algorithms which allows a more precise understanding of their shortcomings. In addition, some novel algorithms have been investigated that overcome some of these limitations. A second aspect of this work has considered the treatment of images from multiple sensors whose angular and spatial separation is large and where conventional registration algorithms break down (typically greater than a few degrees of separation). A range of novel approaches is reported which exploit the use of parallax to estimate depth information and reconstruct a geometrical model of the scene. The imagery can then be combined with this geometrical model to render a variety of useful representations of the data. These techniques (which we term Volume Registration) show great promise as a means of gathering and presenting 3D and 4D scene information for both military and civilian applications.

关键词： model generation registration fusion

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A field demonstration of multi-INT surveillance and data fusion

A field demonstration of multi-INT surveillance and data fus...

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conference on Multisensor, Multisource Information fusion

作者： Na, Arthur Havens, Steve Argon ST (United States)

ISBN: (纸本)9780819471659

Collecting data in any domain is often only the first step in creating intelligence. This is the beginning of a process which includes fusing that data with other data sources to create something more than the individual data elements. This has been historically difficult because collection sensors are optimized for their respective conventional domains. We have developed a multi-sensor system combining an electro-optical camera and infi-ared camera, using a revolutionary data handling and manipulating process to fuse multiple types of data to create inteffigence. To address the data fusion needs of such a system, we have developed an internationally recognized, open data fusion language called Transducer Markup Language (TML). TML was used in conjunction with the multi-sensor system to describe data from the EO and IR cameras and support sensors all within a self-contained mobile delivery system during mifitary exercises in July 2007. The TML data was collected and disseminated to multiple users within a Service Oriented Architecture (SOA), after which it was Ruther distributed using Cursor-On-Target (COT) messages over a second network. This demonstrated both data fusion of multiple sensor data sources and integration into existing data distribution infrastructures. Key innovations of this demonstration included the use of multiple sensors including EO & IR cameras and a single sensor data exchange language to capture and describe sensor output.

关键词： sensor fusion Transducer Markup Language sensor network SOA sensor actuator data exchange standard common data model common sensor model sensor ontology

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Experimental Characterization of Synchronization Protocols for Wireless Networks

Experimental Characterization of Synchronization Protocols f...

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IEEE International conference on virtual Environments, Human-Computer Interfaces and Measurement Systems

作者： De Santo, M. Ferrigno, L. Paciello, V. Pietrosanto, A. Univ Salerno DIIIE I-84084 Fisciano SA Italy

ISBN: (纸本)9781424419272

Nowadays more and more measurement applications where sensor nodes cooperate to realize a data fusion process are entrusted to Wireless sensor Networks (WSN). Data fusion to be accurate requires that nodes be referred to a common clock and among themselves. In this scenario node synchronization got a crucial research topic and even sophisticated synchronization algorithms can be easily found in literature. Not a few others show to be especially designed for low cost, low memory and low power architectures. Their performance is usually evaluated either through analytical considerations or in simulation environments, but in some cases where ad hoc radio systems have been adopted. This paper makes a first step toward an experimental characterization of synchronization protocols that hold into account also influence factors which arise when commercial wireless communication busses as WiFi, BlueTooth (BT), ZigBee are adopted.

关键词： wireless sensor network, synchronization, trigger, measurement

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Comparing discrimination and CFA for selecting tracking features

Comparing discrimination and CFA for selecting tracking feat...

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conference on Multisensor, Multisource Information fusion

作者： Lyons, Damian M. Hsu, D. Frank Fordham Univ Dept Comp & Informat Sci Robot & Comp Vis Lab Bronx NY 10458 USA

ISBN: (纸本)9780819471659

The ability of a tracker to isolate the foreground target from the background of an image is crucially dependent on the set of features selected for tracking. Collins & Liu [2] propose an on-line, adaptive approach to selecting the set of features based on the insight that the set of features that best discriminate between target and background classes is the best set to use for tracking. In previous work [10], we have proposed an approach based on Combinatorial fusion Analysis for selecting features for Real-Time tracking. We discuss the relative merits of the two methods and motivate their combination to produce an improved tracking system. We show several results from a difficult tracking sequence with human targets to demonstrate the effectiveness of the combined system.

关键词： target tracking sensor fusion information fusion video tracking surveillance

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Dynamic resource management for adaptive distributed information fusion in large volume surveillance

Dynamic resource management for adaptive distributed informa...

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conference on Multisensor, Multisource Information fusion

作者： Farahbod, Roozbeh Glasser, Uwe Welm, Hans Simon Fraser Univ Software Technol Lab Burnaby BC V5A 1S6 Canada MDA Corp Res & Dev Richmond BC Canada

ISBN: (纸本)9780819471659

We propose a highly adaptive and auto-configurable, multi-layer network architecture for distributed information fusion to address large volume surveillance challenges, assuming a multitude of different sensor types on multiple mobile platforms for intelligence, surveillance and reconnaissance. Our focus is on network enabled operations to efficiently manage and improve employment of a set of mobile resources, their information fusion engines and networking capabilities under dynamically changing and essentially unpredictable conditions. A high-level model of the proposed architecture is formally described in abstract functional and operational terms based on the Abstract State Machine formalism. This description of the underlying design concepts provides a concise and precise blueprint for reasoning about key system attributes at an intuitive level of understanding.

关键词： distributed systems sensor networks dynamically configurable systems resource management network architecture abstract state machines formal specification high level design

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Automatic extraction of corresponding-points for image registration

Automatic extraction of corresponding-points for image regis...

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conference on Multisensor, Multisource Information fusion

作者： Jung, Jik-Han Choi, Won-Chul Park, Dong-Jo Park, Chang-Han Lee, Jae-Ik Korea Adv Inst Sci & Technol Sch EECS 373-1 Guseong Dong Taejon 305701 South Korea Samsung Thales Co Ltd Gyeonggi South Korea

ISBN: (纸本)9780819471659

Recently, multi-sensor image fusion systems and related applications have been widely investigated. In an image fusion system, robust and accurate multi-modal image registration is essential. In the conventional method, the image registration process starts with manually-pointed corresponding pairs in both sensored images. Using these corresponding pairs, a transform matrix is initialized and refined through an optimization process. In this paper, we propose a new automatic extraction method for such corresponding pairs. The Harris comer detector is employed to extract feature points in both EO/IR images individually. Patches around the detected feature points are matched with a probabilistic criterion, mutual information (MI), which is a preferred measure for image registration due to its robust and accurate performance. Simulation results show that the proposed scheme has a low time complexity and extracts corresponding pairs well.

关键词： image fusion image registration mutual information automatic extraction

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A heterogeneous sensor network simulation system with integrated terrain data for real-time target detection in 3D space

A heterogeneous sensor network simulation system with integr...

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conference on Multisensor, Multisource Information fusion

作者： Lin, Hong Tanner, Steve Rushing, John Graves, Sara Criswell, Evans Univ Alabama Informat Technol & Syst Ctr Huntsville AL 35899 USA

ISBN: (纸本)9780819471659

Large scale sensor networks composed of many low-cost small sensors networked together with a small number of high fidelity position sensors can provide a robust, fast and accurate air defense and warning system. The team has been developing simulations of such large networks, and is now adding terrain data in an effort to provide more realistic analysis of the approach. This work, a heterogeneous sensor network simulation system with integrated terrain data for real-time target detection in a three-dimensional environment is presented. The sensor network can be composed of large numbers of low fidelity binary and bearing-only sensors, and small numbers of high fidelity position sensors, such as radars. The binary and bearing-only sensors are randomly distributed over a large geographic region;while the position sensors are distributed evenly. The elevations of the sensors are determined through the use of DTED Level 0 dataset. The targets are located through fusing measurement information from all types of sensors modeled by the simulation. The network simulation utilizes the same search-based optimization algorithm as in our previous two-dimensional sensor network simulation with some significant modifications. The fusion algorithm is parallelized using spatial decomposition approach: the entire surveillance area is divided into small regions and each region is assigned to one compute node. Each node processes sensor measurements and terrain data only for the assigned sub region. A master process combines the information from all the compute nodes to get the overall network state. The simulation results have indicated that the distributed fusion algorithm is efficient enough so that an optimal solution can be reached before the arrival of the next sensor data with a reasonable time interval, and real-time target detection can be achieved. The simulation was performed on a Linux cluster with communication between nodes facilitated by the Message Passing Interface (

关键词： heterogeneous sensor network data fusion terrain data real-time target detection three-dimensional space

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