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Information weighted consensus-based cooperative space object tracking to overcome malfunctioned sensors and noisy links

Information weighted consensus-based cooperative space objec...

引用

International conference on Information fusion

作者： Bin Jia Khanh D. Pham Erik Blasch Dan Shen Zhonghai Wang Xin Tian Genshe Chen Intelligent Fusion Technology Inc. Germantown MD Space Vehicles Directorate Air Force Research Lab NM Information Directorate Air Force Research Lab Rome NY Intelligent Fusion Technology Inc. Germantown MD USA

ISBN: (纸本)9781479974047

With the rapid development of sensor technology, multiple sensors are often available in many engineering applications, such as space object tracking. How to effectively use multiple sensor information is the key to achieving accurate space object state information. In this paper, the information weighted consensus (IWC) strategy is deployed to solve the cooperative sensor tracking problem. In addition, the information theoretic method and the repeated consensus, are used to detect a malfunctioned sensor and overcome the problem of noisy links in the cooperative tracking scenario. The proposed algorithms are demonstrated by a typical space object tracking problem using multiple sensors. The results indicate that: 1) The proposed algorithms can obtain stable estimation results when there is malfunctioned node in the network, 2) can mitigate the effect of noisy links, and 3) achieves close performance to the result with perfect communication links and known malfunctioned node. The results will facilitate the application of using the information weighted consensus algorithm for real multiple sensor space object tracking scenarios.

关键词： sensors Noise measurement Noise Estimation Object tracking Information filters Earth

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Access and resources reservation in 4G-VANETs for multimedia applications 13

Access and resources reservation in 4G-VANETs for multimedia...

引用

13th International conference on Ad-hoc Networks and Wireless, ADHOC-NOW 2014 accompanied by 2nd International Workshop on Emerging Technologies for Smart Devices, ETSD 2014, 2nd International Workshop on Marine sensors and Systems, MARSS 2014, Multimedia Wireless ad hoc Networks, MWaoN 2014, Security in Ad Hoc Networks, SecAN 2014, 2nd Smart sensor Protocols and algorithms, SSPA 2014 and 8th International Workshop on Wireless sensor, Actuator and Robot Networks, WiSARN 2014

作者： Garai, Mouna Mahjoub, Mariem Rekhis, Slim Boudriga, Noureddine Bettaz, Mohamed Communication Networks and Security Research Laboratory University of Carthage Tunis Tunisia Methods of Systems Design Laboratory National School of Computer Science Algiers Algeria

ISBN: (纸本)9783662463376

The development of Vehicular Ad-hoc Networks (VANET) has witnessed the release of various multimedia services and made it important to develop architectures and routing protocols capable of (a) handling the multimedia QoSs requirements and the real-time services’ constraints;(b) maximizing the network coverage;and (c) managing resources on the Road Side Units (RSUs), in order to guarantee the continuous delivery of real-time services. In this work, we provide a novel 4G-based VANET heterogeneous architecture, which integrates IEEE 802.11p and 3GPP LTE access networks, to provide access to multimedia services. A tree-based network access scheme is developed, providing a rapid connection and handover to highly mobility vehicles, and allowing to maximize at a large extent the network coverage beyond the area uncovered by RSUs (in the form of LTE eNodeBs). Techniques for the proactive resources provision on the RSUs, and the management of QoS-aware vertical and horizontal handovers, are developed. © Springer-Verlag Berlin Heidelberg 2015.

关键词： Vehicular ad hoc networks

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Effect of noise on wavelet transform based image fusion algorithms

Effect of noise on wavelet transform based image fusion algo...

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Global conference on Communication Technologies (GCCT)

作者： Senthilkumar Sadhasivam P. Gnanasivam Electronics and Communication Agni College of Technology Chennai India

Image fusion is used to integrate multiple images into a composite image, which contains complementary information from each of the source images. In defense applications, fusion is widely employed to obtain images pertaining to the object under surveillance and also for mapping terrain for navigation purposes. Surveillance imaging generally use two imaging sources, one an Infra Red (IR) camera and the other a conventional digital camera; and the images are usually captured under low-lighting and night time conditions. The imaging process is prone to sensor noise which degrades the fusion performance. This is because the noise is also considered as useful information by the fusion process, resulting in a corrupted fused output, rendering the image useless. We have formulated different fusion techniques based on the Discrete Wavelet Transform (DWT) and the Principal Component Analysis (PCA). In this paper, the efficiency of these fusion algorithms is evaluated under the presence of sensor noise. The Structural Similarity Index (SSIM), the Peak Signal to Noise Ratio (PSNR) and the Root Mean Square Error (RMSE) are used as metrics to evaluate the performance of the fusion schemes. Our experiments have shown that the DWT based fusion method that utilizes the energy of the wavelet coefficients for fusion produces good results under the noise constraints imposed.

关键词： Discrete wavelet transforms Image fusion Principal component analysis Cameras Approximation methods

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Integrated Multi-sensor fusion for Mapping and Localization in Outdoor Environments for Mobile Robots

Integrated Multi-sensor Fusion for Mapping and Localization ...

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

作者： Emter, Thomas Petereit, Janko Fraunhofer Inst Optron Syst Technol & Image Explo Karlsruhe Germany

ISBN: (纸本)9781628410587

An integrated multi-sensor fusion framework for localization and mapping for autonomous navigation in unstructured outdoor environments based on extended Kalman filters (EKF) is presented. The sensors for localization include an inertial measurement unit, a GPS, a fiber optic gyroscope, and wheel odometry. Additionally a 3D LIDAR is used for simultaneous localization and mapping (SLAM). A 3D map is built while concurrently a localization in a so far established 2D map is estimated with the current scan of the LIDAR. Despite of longer run-time of the SLAM algorithm compared to the EKF update, a high update rate is still guaranteed by sophisticatedly joining and synchronizing two parallel localization estimators.

关键词： multi-sensor fusion extended Kalman filter particle filter SLAM autonomous mobile robot asynchronous fusion 3D LIDAR mapping

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An Evaluation of Background Subtraction algorithms on Fused Infrared-Visible Video Streams

An Evaluation of Background Subtraction Algorithms on Fused ...

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Proceedings of the Digital Image Computing: Technqiues and applications (DICTA)

作者： Stefan Becker Norbert Scherer-Negenborn Pooja Thakkar Wolfgang Hubner Michael Arens Fraunhofer Institute for Optronics System Technologies and Image Exploitation (IOSB) Gutleuthausstr Ettlinzen Germanv

ISBN: (纸本)9781467367967

The detection of motion is an essential preprocessing step in many vision based systems. While showing good performance in the visible or the infrared spectrum, some of the state-of-the-art background subtraction methods are quite sensitive to a change in the spectral range. In this paper, the robustness of various background subtraction algorithms is not only compared between visible and infrared video streams, but in addition to the robustness that can be achieved by fusing visible and infrared video streams. Thereby, we show the effects of several fusion methods on a large set of background subtraction algorithms. By analyzing quantitative results, we identify approaches which can benefit from fused sensor signals. Towards this end, we further analyze the effectiveness of 14 fusion strategies. The evaluation is done on the public available OSU Color-Thermal Database reflecting a typical outdoor surveillance scenario.

关键词： Image fusion Streaming media TV Principal component analysis Transforms Robustness Gaussian mixture model

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Fast and efficient signals recovery for deterministic compressive sensing: applications to biosignals

Fast and efficient signals recovery for deterministic compre...

引用

conference on Design and architectures for Signal and Image Processing

作者： Andrianiaina Ravelomanantsoa Hassan Rabah Amar Rouane Institut Jean Lamour (IJL) UMR7198 Université de Lorraine Vandoeuvre-Les-Nancy France

Compressed sensing is a technique that is suitable for compressing and recovering signals having sparse representations in certain bases. Compressed sensing has been widely used to optimize the measurement process of power and bandwidth constrained systems like wireless body sensor network. The central issues with compressed sensing are mainly the construction of measurement matrices and the development of efficient recovery algorithms. In this paper, we proposed a simple and fast recovery algorithm which performed a thresholding in the discrete cosine transform domain. We validated it by recovering electrocardiogram and electromyogram signals taken from the Phyiobank database. The simulation and experimental results have shown that the proposed recovery algorithm was 25 and 12 times faster than orthogonal matching pursuit and stagewise orthogonal matching pursuit, respectively. In addition, depending on the compression ratio, the signal-to-noise ratio of recovered signals were improved up to 2 dB.

关键词： Discrete cosine transforms Atmospheric measurements Particle measurements Sparse matrices Signal processing algorithms Matching pursuit algorithms

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Data fusion for unsupervised video object detection, tracking and geo-positioning

Data fusion for unsupervised video object detection, trackin...

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International conference on Information fusion

作者： Denis Kolev Garik Markarian Dmitry Kangin R & D Department Rinicom Ltd. Lancaster Lancashire UK Data Science Group Lancaster University UK

In this work we describe a system and propose a novel algorithm for moving object detection and tracking based on video feed. Apart of many well-known algorithms, it performs detection in unsupervised style, using velocity criteria for the objects detection. The algorithm utilises data from a single camera and Inertial Measurement Unit (IMU) sensors and performs fusion of video and sensory data captured from the UAV. The algorithm includes object tracking and detection, augmented by object geographical co-ordinates estimation. The algorithm can be generalised for any particular video sensor and is not restricted to any specific applications. For object tracking, Bayesian filter scheme combined with approximate inference is utilised. Object localisation in real-world co-ordinates is based on the tracking results and IMU sensor measurements.

关键词： Decision support systems

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Financialized methods for market-based multi-sensor fusion

Financialized methods for market-based multi-sensor fusion

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IEEE/RSJ International conference on Intelligent Robots and Systems

作者： J. Abernethy M. Johnson-Roberson Department of Electrical Engineering & Computer Science University of Michigan Ann Arbor MI USA Department of Naval Architecture & Marine Engineering University of Michigan Ann Arbor MI USA

Autonomous systems rely on an increasing number of input sensors of various modalities, and the problem of sensor fusion has received attention for many years. Autonomous system architectures are becoming more complex with time, and the number and placement of sensors will be modified regularly, sensors will fail for many reasons, information will arrive asynchronously, and the system will need to adjust to rapidly changing environments. To address these issues we propose a new paradigm for fusing information from multiple sources that draws from the rich of field pertaining to financial markets, particularly recent research on prediction market design. Among the many benefits of this financialized approach is that, both in theory and in practice, markets are well-equipped to robustly synthesize information from diverse sources in a decentralized fashion. Our framework poses sensor processing algorithms as profit-seeking market participants, data is incorporated via financial transactions, and the joint estimation is represented as a price equilibrium. We use pedestrian detection as a motivating application. Pedestrian detection is a well studied field and essential to autonomous driving. Real world fusion results are presented on RGB and LIDAR data from the KITTI Vision Benchmark Suite. We demonstrate we can achieve comparable performance to state-of-the-art hand designed fusion techniques using the proposed approach.

关键词： sensor fusion Contracts sensor systems Bayes methods Robot kinematics

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On Data fusion for Orientation Sensing in WBASNs Using Smart Phones

On Data Fusion for Orientation Sensing in WBASNs Using Smart...

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International conference on Advanced Information Networking and applications (AINA)

作者： Danish Mahmood Nadeem Javaid Muhammad Imran Zahoor Ali Khan Umar Qasim Mohammed Alnuem CS Dept COMSATS Institute of Information Technology Islamabad Pakistan CAST COMSATS Institute of Information Technology Islamabad Pakistan College of CIS King Saud University Ryadh Saudi Arabia CIS Higher Colleges of Technology Fujairah Campus UAE University of Alberta Alberta Canada

Orientation sensing is not a new concept. It is being used since ages however, with emergence of new technologies such as Wireless Body Area sensor Networks (WBASNs), it gives new challenges. Commencement of smart phones that have built in orientation sensors are replacing expensive and complex Inertial Measurement Units (IMUs) designed for a specific purpose. Orientation sensing in WBASN have numerous applications. In e-health applications, rehabilitation investigation of backbone injuries can be measured by continues readings of posture. For that, gyroscopes and accelerometers are key sensors that play vital role. For machines such as robots and air crafts, such data fusion is in practice. However, considering human body movements yet there is a need to find an accurate fusion algorithm that meets all demands with low complexity. In this work, we discussed and compared two algorithms considering Wireless Body Area sensor fusion (WBASF) i.e. Kalman and Complementary data fusion techniques. According to our findings, Kalman Filter may have given very good results regarding machines however, Complementary filter proved itself better in performance, complexity and required computational power in WBASNs.

关键词： conferences

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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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