Sensor fusion

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Sensor fusion is the combining of sensory data or data derived from sensory data from disparate sources such that the resulting information is in some sense better than would be possible when these sources were used individually. (Wikipedia.org)






Conferences related to Sensor fusion

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2020 59th IEEE Conference on Decision and Control (CDC)

The CDC is the premier conference dedicated to the advancement of the theory and practice of systems and control. The CDC annually brings together an international community of researchers and practitioners in the field of automatic control to discuss new research results, perspectives on future developments, and innovative applications relevant to decision making, automatic control, and related areas.


2020 IEEE International Conference on Robotics and Automation (ICRA)

The International Conference on Robotics and Automation (ICRA) is the IEEE Robotics and Automation Society’s biggest conference and one of the leading international forums for robotics researchers to present their work.


2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

The 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2020) will be held in Metro Toronto Convention Centre (MTCC), Toronto, Ontario, Canada. SMC 2020 is the flagship conference of the IEEE Systems, Man, and Cybernetics Society. It provides an international forum for researchers and practitioners to report most recent innovations and developments, summarize state-of-the-art, and exchange ideas and advances in all aspects of systems science and engineering, human machine systems, and cybernetics. Advances in these fields have increasing importance in the creation of intelligent environments involving technologies interacting with humans to provide an enriching experience and thereby improve quality of life. Papers related to the conference theme are solicited, including theories, methodologies, and emerging applications. Contributions to theory and practice, including but not limited to the following technical areas, are invited.


2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)

The Conference focuses on all aspects of instrumentation and measurement science andtechnology research development and applications. The list of program topics includes but isnot limited to: Measurement Science & Education, Measurement Systems, Measurement DataAcquisition, Measurements of Physical Quantities, and Measurement Applications.


GLOBECOM 2020 - 2020 IEEE Global Communications Conference

IEEE Global Communications Conference (GLOBECOM) is one of the IEEE Communications Society’s two flagship conferences dedicated to driving innovation in nearly every aspect of communications. Each year, more than 2,900 scientific researchers and their management submit proposals for program sessions to be held at the annual conference. After extensive peer review, the best of the proposals are selected for the conference program, which includes technical papers, tutorials, workshops and industry sessions designed specifically to advance technologies, systems and infrastructure that are continuing to reshape the world and provide all users with access to an unprecedented spectrum of high-speed, seamless and cost-effective global telecommunications services.


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Periodicals related to Sensor fusion

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Aerospace and Electronic Systems Magazine, IEEE

The IEEE Aerospace and Electronic Systems Magazine publishes articles concerned with the various aspects of systems for space, air, ocean, or ground environments.


Applied Superconductivity, IEEE Transactions on

Contains articles on the applications and other relevant technology. Electronic applications include analog and digital circuits employing thin films and active devices such as Josephson junctions. Power applications include magnet design as well asmotors, generators, and power transmission


Automatic Control, IEEE Transactions on

The theory, design and application of Control Systems. It shall encompass components, and the integration of these components, as are necessary for the construction of such systems. The word `systems' as used herein shall be interpreted to include physical, biological, organizational and other entities and combinations thereof, which can be represented through a mathematical symbolism. The Field of Interest: shall ...


Biomedical Engineering, IEEE Transactions on

Broad coverage of concepts and methods of the physical and engineering sciences applied in biology and medicine, ranging from formalized mathematical theory through experimental science and technological development to practical clinical applications.


Communications Letters, IEEE

Covers topics in the scope of IEEE Transactions on Communications but in the form of very brief publication (maximum of 6column lengths, including all diagrams and tables.)


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Most published Xplore authors for Sensor fusion

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Xplore Articles related to Sensor fusion

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Session MA6: MIMO radar and sensor fusion

2008 42nd Asilomar Conference on Signals, Systems and Computers, 2008

None


Sensor Fusion Methodology for Vehicle Detection

IEEE Intelligent Transportation Systems Magazine, 2017

A novel sensor fusion methodology is presented, which provides intelligent vehicles with augmented environment information and knowledge, enabled by vision-based system, laser sensor and global positioning system. The presented approach achieves safer roads by data fusion techniques, especially in single- lane carriage-ways where casualties are higher than in other road classes, and focuses on the interplay between vehicle drivers and ...


Session: distributed information processing

1988 IEEE International Symposium on Information Theory., 1988

The following topics are dealt with: distributed detection in Gaussian noise; correlated observations; distributed filtering with random sampling and delay; networking delay and channel errors; optimal partitioning of observation; and decentralised hypothesis testing.<<ETX>>


Design of quantizers for decentralized estimation systems

IEEE Transactions on Communications, 1993

The authors consider parameter estimation in decentralized systems with distributed processors. They restrict the local processors to be quantizers and consider the optimal design of the systems to minimize the estimation error. They present necessary conditions for the optimal system based on the Bayes distortion functions and Fisher's information. The numerical results compare the resulting quantizers obtained by different distortion ...


Data fusion in multi sensor platforms for wide-area perception

2006 IEEE Intelligent Vehicles Symposium, 2006

There is a strong belief that the improvement of preventive safety applications and the extension of their operative range are achieved by the deployment of multiple sensors with wide fields of view (FOV). The paper contributes to the solution of the problem and introduces distributed sensor data fusion architectures and algorithms for an efficient deployment of multiple sensors that give ...


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Educational Resources on Sensor fusion

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IEEE.tv Videos

Skillful Manipulation Based on High-Speed Sensory-Motor Fusion
Disruptive Internet of Things course, Part 2 - IEEE Smart Tech Workshop
Disruptive Internet of Things course, Part 4 - IEEE Smart Tech Workshop
Disruptive Internet of Things course, Part 3 - IEEE Smart Tech Workshop
Disruptive Internet of Things course, Part 1 - IEEE Smart Tech Workshop
Fusion here, there and almost everywhere in computer vision - driving new advances in fuzzy integrals
A 4x4x4 mm³ Fully Integrated Sensor-to-Sensor Radio - Li-Xuan Chuo - RFIC 2019 Showcase
Programming Human Ethics: Cui Bono? - IEEE AI & Ethics Summit 2016
Robotics History: Narratives and Networks Oral Histories: Gary Bradsky
Cooperative Localization in Sensor Networks
Generation of Models for Wireless Sensor Network Assessment
Technology for Health Summit 2017 - Panel II: Managing the data deluge linked to connected technology in health
Kurt Petersen: 2019 IEEE Medal of Honor Recipient
Industrial Standards and IoT Use Cases - Talk Three: IECON 2018
Multiple Sensor Fault Detection and Isolation in Complex Distributed Dynamical Systems
Performance, Environment, Actuators, Sensors (PEAS)
Compressive Sensing Tutorial: A Game Changing Technology for Energy Efficient IoT Sensor Networks: WF-IoT 2016
Fog Computing Manageability and Orchestration: How To Fuse Cloud, Network, and Fog - Marcelo Yannuzzi, Fog World Congress 2017
George Oikonomou’s Paper: Traffic Forensics for IPv6-Based Wireless Sensor Networks and the IoT: WF-IoT 2016
3D Printing for Sensor Platform Integration - Benjamin Ingis - IEEE EMBS at NIH, 2019

IEEE-USA E-Books

  • Session MA6: MIMO radar and sensor fusion

    None

  • Sensor Fusion Methodology for Vehicle Detection

    A novel sensor fusion methodology is presented, which provides intelligent vehicles with augmented environment information and knowledge, enabled by vision-based system, laser sensor and global positioning system. The presented approach achieves safer roads by data fusion techniques, especially in single- lane carriage-ways where casualties are higher than in other road classes, and focuses on the interplay between vehicle drivers and intelligent vehicles. The system is based on the reliability of laser scanner for obstacle detection, the use of camera based identification techniques and advanced tracking and data association algorithms i.e. Unscented Kalman Filter and Joint Probabilistic Data Association. The achieved results foster the implementation of the sensor fusion methodology in forthcoming Intelligent Transportation Systems.

  • Session: distributed information processing

    The following topics are dealt with: distributed detection in Gaussian noise; correlated observations; distributed filtering with random sampling and delay; networking delay and channel errors; optimal partitioning of observation; and decentralised hypothesis testing.<<ETX>>

  • Design of quantizers for decentralized estimation systems

    The authors consider parameter estimation in decentralized systems with distributed processors. They restrict the local processors to be quantizers and consider the optimal design of the systems to minimize the estimation error. They present necessary conditions for the optimal system based on the Bayes distortion functions and Fisher's information. The numerical results compare the resulting quantizers obtained by different distortion criteria.<<ETX>>

  • Data fusion in multi sensor platforms for wide-area perception

    There is a strong belief that the improvement of preventive safety applications and the extension of their operative range are achieved by the deployment of multiple sensors with wide fields of view (FOV). The paper contributes to the solution of the problem and introduces distributed sensor data fusion architectures and algorithms for an efficient deployment of multiple sensors that give redundant or complementary information for the moving objects. The proposed fusion architecture is based on a modular approach allowing exchangeability and benchmarking using the output of individual trackers, whereas the fusion algorithm gives a solution to the track management problem and the coverage of wide perception areas. The test case is LATERAL SAFE sensor configuration, which monitors the rear and lateral areas of the vehicle. Results show that with the given approach the system is able to maintain the ID of all objects in transition (an object enters a sensor's FOV) and blind areas (no sensor coverage)

  • Bias estimation of DGPS multi-path data for localization of mobile robot

    In this paper, a localization method is provided estimating bias error due to multi-path phenomenon of DGPS sensor. In order to recognize the position of mobile robot, it is necessary data structure to integrate information from sensor data. To take full advantage of two sensor data, an integration mechanism is provided and implemented. It is provided bias detection and bias estimation for multi-path phenomenon of DGPS sensor in the surrounding of buildings. A performance evaluation is shown through an outdoor experiment data with Yamabico mobile robot.

  • How dense should a sensor network be for detection applications?

    A binary decentralized detection problem is studied in which a collection of wireless sensor nodes provides relevant information about their environment to a fusion center. The observations at the nodes are samples of a finite state Markov process under each hypothesis. The nodes transmit their data to a fusion center over a multiple access channel. Upon reception of the information, the fusion center selects one of the two possible hypotheses. It is assumed that the sensor system is constrained by the capacity of the multiple access channel over which the sensor nodes are transmitting. Thus, as the node density increases, the sensor observations get more correlated, and, furthermore, fewer bits can be transmitted by each sensor node. A framework is presented in this paper for deriving design guidelines relating sensor density to system performance under a total communication constraint. The framework is based on large deviation theory applied to the asymptotic regime where the number of sensor nodes is large. This framework is applied to a specific example to compare the gains offered by having a higher node density with the benefits of getting detailed information from each sensor.

  • Using resource-bonded sensing in telerobotics

    Investigates the use of resource-bounded sensing to increase the performance of telerobotic systems. By examining the role of sensing in telerobotics, the authors isolate several desirable sensing functions to be performed. They then review the state of the art in sensor data fusion and point out some of the limitations of current technology, particularly for use in unstructured environments. Methods more suitable for unstructured environments require information about the goals of the operator. They also describe what information the operator must supply, and how it may be entered into the system.<<ETX>>

  • Adaptive signaling schemes for detection in wireless sensor networks

    A binary decentralized detection problem in which sensor nodes provide partial information about their environment to a fusion center is studied. The nodes have access to conditionally independent observations and transmit a summary of their own data over wireless channels. Upon reception of the information, the fusion center attempts to accurately reconstruct the state of nature. The communication link between each node and the fusion center is modeled as a fading channel corrupted by additive noise. Channel state information is available at the fusion center and at the sensor nodes. Large deviation theory is used to show that having identical sensor nodes is asymptotically optimal. Algorithms in which each sensor node selects a signaling/coding schemes based on the quality of its channel are studied.

  • SAR/IR sensor image fusion and real-time implementation

    This paper presents a real time SAR/IR fusion system for automatic target recognition (ATR) applications. The system contains three major components: preprocessing, registration and fusion. The registration algorithm is based on Zheng-Chellappa's (see IEEE Transactions on Image Processing, no.7, p.311, 1993) APFBR work. The fusion algorithm employs a biologically inspired merging rule to carry out SAR/IR fusion at the pixel level. In the fused images, features from individual sensor images are not only preserved but also enhanced. The fused images are more suitable for visual perception and ATR operations. The system has been implemented on a SIMD parallel processor to achieve real-time performance. It has been extensively tested on real SAR/IR data.



Standards related to Sensor fusion

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No standards are currently tagged "Sensor fusion"