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

作者： Fedosov, v. P. Lomakina, A. v. Legin, A. A. voronin, v. v. Southern Fed Univ Dept Fundamentals Radio Engn Taganrog Russia Don State Tech Univ Dept Radioelect Syst Rostov Na Donu Russia

ISBN: (纸本)9781510601130

In this paper the system of wireless transmission of data based on the use an adaptive algorithm for processing spatial-time signals using antenna arrays is presented. In the transmission of data in a multipath propagation of signals have been used such technologies as a MIMO (Multiple input-Multiple output) and OFDM (Orthogonal frequency division multiplexing) to solve the problem of increasing the maximum speed of data transfer and the low probability of errors. The adaptation process is based on the formation of the directional pattern equivalent to the amplitude antenna array in the signal arrival direction with the highest capacity on one of propagation paths in the channel. The simulation results showed that the use of an adaptive algorithm on the reception side can significantly reduce the probability of bit errors, thus to increase throughput in an underwater acoustic data channel.

关键词： antenna array (AA) MIMO OFDM adaptive algorithm underwater acoustic channel antenna directional pattern

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Heterogeneous Multi-view Information fusion: Review of 3-D Reconstruction Methods and a New Registration with Uncertainty Modeling

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IEEE ACCESS 2016年 4卷 8264-8285页

作者： Aliakbarpour, Hadi Prasath, v. B. Surya Palaniappan, Kannappan Seetharaman, Guna Dias, Jorge Univ Missouri Dept Comp Sci Computat Imaging & VisAnal Lab Columbia MO 65211 USA US Naval Res Lab Adv Comp Concepts Washington DC 20375 USA Univ Coimbra Inst Syst & Robot Fac Sci & Technol P-3000315 Coimbra Portugal Khalifa Univ Sci Technol & Res Inst Robot Abu Dhabi 127788 U Arab Emirates

We consider a multisensor network fusion framework for 3-D data registration using inertial planes, the underlying geometric relations, and transformation model uncertainties. We present a comprehensive review of 3-D reconstruction methods and registration techniques in terms of the underlying geometric relations and associated uncertainties in the registered images. The 3-D data registration and the scene reconstruction task using a set of multiview images are an essential goal of structure-from motion algorithms that still remains challenging for many applications, such as surveillance, human motion and behavior modeling, virtual-reality, smart-rooms, health-care, teleconferencing, games, human robot interaction, medical imaging, and scene understanding. We propose a framework to incorporate measurement uncertainties in the registered imagery, which is a critical issue to ensure the robustness of these applications but is often not addressed. In our test bed environment, a network of sensors is used where each physical node consists of a coupled camera and associated inertial sensor (IS)/inertial measurement unit. Each camera-IS node can be considered as a hybrid sensor or fusion-based virtual camera. The 3-D scene information is registered onto a set of virtual planes defined by the IS. The virtual registrations are based on using the homography calculated from 3-D orientation data provided by the IS. The uncertainty associated with each 3-D point projected onto the virtual planes is modeled using statistical geometry methods. Experimental results demonstrate the feasibility and effectiveness of the proposed approach for multiview reconstruction with sensor fusion.

关键词： Structure-from-motion image registration 3D reconstruction heterogeneous information fusion homography coupled sensors inertial measurement unit (IMU) sensor network geometric uncertainty virtual reality

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An asynchronous sensor bias estimation algorithm utilizing targets' positions only

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INFORMATION fusion 2016年 27卷 54-63页

作者： Yong, Xiaoju Fang, Yangwang Wu, Youli Yang, Pengfei Air Force Engn Univ Sch Aeronaut & Astronaut Engn Xian 710038 Shanxi Peoples R China

Bias estimation is a critical problem in multi-sensor tracking systems, and most existing research has focused on the bias estimation of synchronous sensors;however, in practical applications, sensor measurements are usually asynchronous. The primary contribution of this paper is that a novel algorithm using B-spline interpolation time registration to achieve asynchronous sensor bias estimation is proposed. First, measurements are transformed into synchronous data using the B-spline interpolation time registration method. The time registration results are expressed as weighted results of the measurements. Second, a pseudo measurement equation is created based on the synchronous data. Compared with the pseudo measurements of other algorithms that use weighting coefficients, which are calculated by the target's state, including the target's velocity and time of arrival (TOA), a pseudo measurement that only depends on the target's position can be derived. Thus, the problem of asynchronous sensor bias estimation, particularly with manoeuvring targets, can be solved effectively by the proposed algorithm. Finally, the effectiveness of the proposed algorithm is verified by simulations with the target performing s-shaped manoeuvres. Monte Carlo simulation results indicate that the Cramer-Rao lower bound (CRLB) is achievable;thus, the proposed algorithm is statistically efficient. (C) 2015 Elsevier B.v. All rights reserved.

关键词： Bias estimation Data fusion Manoeuvring targets Spatial registration Asynchronous sensors

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Sampling Jitter mitigation in latency-critical state-estimation applications using particle filters

Sampling Jitter mitigation in latency-critical state-estimat...

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SICE International Symposium on Control Systems (ISCS)

作者： viktorio S. El Hakim Marco J.G. Bekooij Department of Embedded Software and Signal Processing NXP Semiconductors Eindhoven The Netherlands Department of Computer Architectures for Embedded Systems University of Twente Enschede The Netherlands

ISBN: (纸本)9781509056149

State estimation algorithms, such as the Kalman filter, are applied for conditioning and sensor fusion in digital control loops. It is desirable that these algorithms can be executed on embedded multiprocessor systems. However this results in large worst-case execution times with a consequence that a large sampling period must selected, which degrades the estimation and control performance. In this paper, we propose a free-running state-estimation approach in which the next sample is taken as soon as the current iteration completes. The approach utilizes the particle filter algorithm to mitigate the effects of sampling jitter, introduced by the variation in the execution times of tasks. As a result of the reduced interval between subsequent sampling moments the estimation accuracy is improved. The delay introduced by the estimator in a control loop is reduced by enabling execution of the prediction step in parallel with other control tasks. We compare simulation results obtained for our approach with a Kalman filter based approach, by estimating the state of a DC motor. These results show that our approach minimizes the estimation error, as a result of sampling jitter, by up to a factor of 10. Additionally we show that the approach does not require precise knowledge of the distribution of the execution times of the tasks.

关键词： Jitter Schedules Delays State estimation Signal processing algorithms

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Real Time Cooperative Localization for Autonomous vehicles 19

Real Time Cooperative Localization for Autonomous Vehicles

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19th IEEE International Conference on Intelligent Transportation Systems (ITSC)

作者： Bounini, Farid Gingras, Denis Pollart, Herve Gruyer, Dominique LIV Univ Sherbrooke Sherbrooke PQ Canada OPAL RT Technol Inc Montreal PQ Canada IFSTTAR LIVIC Nantes France

ISBN: (纸本)9781509018895

This paper describes a new strategy for real-time cooperative localization of autonomous vehicles. The strategy aims to improve the vehicles localization accuracy and reduce the impact of computing time of multi-sensor data fusion algorithms and vehicle-to-vehicle communication on parallel architectures. The method aims to solve localization issues in a cluster of autonomous vehicles, equipped with low-cost navigation systems in an unknown environment. It stands on multiple forms of the Kalman filter derivatives to estimate the vehicles' nonlinear model vector state, named local fusion node. The vehicles exchange their local state estimate and Covariance Intersection algorithm for merging the local vehicles' state estimate in the second node (named global data fusion node). This strategy simultaneously exploits the proprioceptive and sensors -a Global Positioning System, and a vehicle-to-vehicle transmitter and receiver-and an exteroceptive sensor, range finder, to sense their surroundings for more accurate and reliable collaborative localization.

关键词： Data fusion extended Kalman filter covariance intersection ADAS Transportation System autonomous vehicles v2v communication cooperative localization

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WIRELESS POWERED COMMUNICATION NETWORKS: architectures, PROTOCOL DESIGNS, AND STANDARDIZATION

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IEEE WIRELESS COMMUNICATIONS 2016年第2期23卷 8-9页

作者： Niyato, Dusit Kim, Dong In Han, Zhu Maso, Marco Nanyang Technol Univ Sch Comp Engn Singapore 639798 Singapore Simon Fraser Univ Sch Engn Sci Burnaby BC V5A 1S6 Canada Sungkyunkwan Univ Suwon South Korea Coll Informat & Commun Engn Shenzhen Peoples R China R&D Engineer JDSU Germantown MD USA Univ Maryland College Pk MD USA Boise State Univ Boise ID 83725 USA Univ Houston Dept Elect & Comp Engn Houston TX 77004 USA Univ Houston Dept Comp Sci Houston TX 77004 USA Singapore Univ Technol & Design Singapore Singapore Huawei France Res Center Math & Algorithm Sci Lab Paris France

The recent advent of wireless energy transfer and harvesting (ETH) technologies has caused an upsurge of research activities directed to the design of novel ETH-based network architectures, protocols, and algorithms. Wireless ETH techniques not only improve the convenience of energy replenishment of electronic devices by obviating the need for physical charging or replacement of a battery, but also become an efficient and economical way to supply energy to a large number of nodes. This controllable one-to-many ETH capability is particularly attractive for many scenarios. For instance, an interesting target scenario for the many ETH-based applications are sensor/actuator networks or, more generally, the so-called Internet of Things (IoT). In this multifarious context, a new networking paradigm, called wireless powered communication networking (WPCN), has been introduced. An ever increasing research interest in this area has been observed in the last few years due to the growing market penetration of both consumer and low-power electronics. The literature on this subject is heterogeneous and characterized by many diverse research directions. This Feature Topic aims at harmonizing the results of these efforts and providing a first comprehensive definition of WPCN, in order to blaze the trail for new tailored designs, novel technical solutions, and clear standardization directions.

关键词： Special issues and sections Communication networks Energy transfer Energy harvesting Energy exchange Wireless sensor networks Network architecture Protocols

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Trajectory Optimisation for Avionics-Based GNSS Integrity Augmentation System 35

Trajectory Optimisation for Avionics-Based GNSS Integrity Au...

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35th IEEE/AIAA Digital Avionics Systems Conference (DASC)

作者： Sabatini, Roberto Moore, Terry Hill, Chris Gardi, Alessandro Ramasamy, Subramanian Gilgien, Michael RMIT Univ Sch Engn Melbourne Vic 3000 Australia Univ Nottingham Nottingham Geospatial Inst Nottingham NG7 2TU England Cranfield Univ Dept Aerosp Engn Cranfield MK43 0AL Beds England

ISBN: (纸本)9781509025237

In this paper, trajectory optimisation algorithms developed specifically for the Global Navigation satellite System (GNSS) Avionics-Based Integrity Augmentation (ABIA) system are presented. The ABIA system is designed to increase the levels of integrity and accuracy (as well as continuity in multi-sensor data fusion architectures) of GNSS in a variety of mission-and safety-critical aviation applications. The trajectory optimisation algorithms can be employed both for flight planning as well as real-time optimisation of manned and unmanned aircraft for all flight phases. Three and six Degrees-of-Freedom (3-DoF/6-DoF) aircraft dynamics models are adopted to generate a number of feasible flight trajectories that also satisfy the GNSS constraints. A detailed simulation case study is presented to evaluate the performance of trajectory optimisation algorithms for GNSS integrity augmentation using an AIRBUS A320 3-DoF aircraft dynamics model. Results confirm that the employed trajectory optimisation algorithms are capable of supporting high-integrity tasks when GNSS is used as the primary source of navigation data.

关键词： Avionics Based Integrity Augmentation Trajectory Optimisation Caution and Wanirng Flags GNSS Integrity Mission-and Safety-Critical GNSS applications

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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...

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IEEE Signal Processing algorithms, architectures, Arrangements, and applications Conference

作者： M. Kroger W. Sauer-Greff R. Urbansky M. Lorang M. Siegrist Chair for Communications Engeneering University of Kaiserslautern WIPOTEC GmbH

ISBN: (纸本)9781509026616

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 transform Food inspection Edge detection boxing multi-sensor data fusion sensor Data Performance Evaluation location error contour image data execution time

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Special Issue on Cloud Computing for IoT

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IEEE INTERNET OF THINGS JOURNAL 2016年第3期3卷 254-256页

作者： Lin, Chuang Ramakrishnan, K. K. Liu, Jiangchuan Ngai, Edith Tsinghua Univ Dept Comp Sci & Technol Beijing 100084 Peoples R China Univ Calif Riverside Dept Comp Sci & Engn Riverside CA 92521 USA Simon Fraser Univ Sch Comp Sci Burnaby BC V5A 1S6 Canada Uppsala Univ Dept Informat Technol Uppsala Sweden

In recent years, there has been a growing interest in the ability of embedded devices, sensors, and actuators to communicate, and create a ubiquitous cyber-physical world. The growth of the notion of the Internet of Things (IoT) and the rapid development of technologies such as short range mobile communication and improved energy-efficiency is expected to create a pervasive connection of “things.” This will inevitably result in the generation of enormous amount of data, which have to be stored, processed, and accessed. Cloud computing has long been recognized as a paradigm for big data storage and analytics. The combination of cloud computing and IoT can enable ubiquitous sensing services and powerful processing of sensing data streams beyond the capability of individual things, thus stimulating innovations in both fields. For example, cloud platforms allow the sensing data to be stored and used intelligently for smart monitoring and actuation with the smart devices. Novel data fusion algorithms, machine learning methods, and artificial intelligence techniques can be implemented and run centralized or distributed on the cloud to achieve automated decision making. These will boost the development of new applications, such as smart cities, grids, and transportation systems. New challenges, however, arise when IoT meets cloud—there is an urgent need for novel network architectures that seamlessly integrate them, and protocols that facilitate big data streaming from IoT to the cloud. QoS and QoE, as well as data security, privacy, and reliability, are critical concerns during the integration.

关键词： Special issues and sections Cloud computing Embedded systems sensors Data analysis Actuators Energy efficiency Cyber-physical systems

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A Source-Attractor Approach to Network Detection of Radiation Sources

A Source-Attractor Approach to Network Detection of Radiatio...

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IEEE International Conference on Multisensor fusion and Integration for Intelligent Systems (MFI)

作者： Wu, Chase Q. Berry, Mark L. Grieme, Kayla M. Sen, Satyabrata Rao, Nageswara S. v. Brooks, Richard R. Cordone, Guthrie New Jersey Inst Technol Dept Comp Sci Newark NJ 07102 USA Oak Ridge Natl Lab Comp Sci & Math Div Oak Ridge TN 37831 USA Clemson Univ Dept Elect & Comp Engn Clemson SC 29634 USA

ISBN: (纸本)9781467397087

Radiation source detection using a network of detectors is an active field of research for homeland security and defense applications. We propose Source-attractor Radiation Detection (SRD) method to aggregate measurements from a network of detectors for radiation source detection. SRD method models a potential radiation source as a "magnet"-like attractor that pulls in pre-computed virtual points from the detector locations. A detection decision is made if a sufficient level of attraction, quantified by the increase in the clustering of the shifted virtual points, is observed. Compared with traditional methods, SRD has the following advantages: i) it does not require an accurate estimate of the source location from limited and noise-corrupted sensor readings, unlike the localization-based methods, and ii) its virtual point shifting and clustering calculation involve simple arithmetic operations based on the number of detectors, avoiding the high computational complexity of grid-based likelihood estimation methods. We evaluate its detection performance using canonical datasets from Domestic Nuclear Detection Office's (DNDO) Intelligence Radiation sensors Systems (IRSS) tests. SRD achieves both lower false alarm rate and false negative rate compared to three existing algorithms for network source detection.

关键词： Radiation detection object localization sensor networks

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