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Colour-the-INSight: Combining a direct view rifle sight with fused intensified and thermal imagery

Proceedings of SPIE - The International Society for Optical Engineering 2012年 8407卷

作者： Hogervorst, M.A. Jansen, C. Toet, A. Bijl, P. Bakker, P. Hiddema, A.C. van Vliet, S.F. TNO Human Factors P.O. Box 23 3769 GZ Soesterberg Netherlands Thales Nederland B.V. Bestevaer 46 Huizen Netherlands PHOTONIS Netherlands B.V. P.O. Box 60 9300 AB Roden Netherlands Ministry of Defence Joint Soldier and Equipment Centre of Expertise Wuytierslaan 198 Amersfoort Netherlands

ISBN: (纸本)9780819490858

We present the design and evaluation of a new demonstrator rifle sight viewing system containing direct view, red aim point and fusion of an (uncooled, LWIR) thermal sensor with a digital image intensifier. Our goal is to create a system that performs well under a wide variety of (weather) conditions during daytime and nighttime and combines the advantages of the various sensor systems. A real-time colour image with salient hot targets is obtained from the night vision sensors by implementing the Colour-the-Night fusion method (Hogervorst & Toet, 2010) on the on-board processor. The prototype system was evaluated in a series of field trials with military observers performing detection and identification tasks. The tests showed that during daytime the addition of a thermal image to direct vision is advantageous, e.g. for the detection of hot targets. At nighttime, the fusion of thermal and image intensified imagery results in increased situational awareness and improved detection of (hot) targets. For identification of small (handheld) objects, the technology needs to be further refined. © 2012 SPIE.

关键词： Image fusion

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Cooperative and Self Organizing Paradigm for Wide Area Synchronized Monitoring of Smart Grids: performance analysis in real operating scenarios

Cooperative and Self Organizing Paradigm for Wide Area Synch...

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IEEE International Instrumentation and Measurement Technology Conference (I2MTC)

作者： Capriglione, Domenico Ferrigno, Luigi Paciello, Vincenzo Pietrosanto, Antonio Vaccaro, Alfredo Univ Cassino DIEI I-03043 Cassino Italy Univ Salerno DIIn Fisciano Italy Univ Sannio Dept Engn Benevento Italy

ISBN: (纸本)9781467363860

Synchronized Wide-Area Monitoring Systems (WAMS) are very important in the development and the use of power system-wide measurements to avoid large disturbances and reduce the probability of catastrophic events. Typically in WAMS the global absolute time reference for sensors synchronization is obtained by satellite-based timing signals processing. Since these signals are extremely vulnerable to radiofrequency interference, effective countermeasures aimed at increasing the resilience of synchronized WAMS to external and internal interferences need to be designed. To this aim several synchronization approaches are explored in literature. In particular, to avoid the large volume of raw data involved in typical client-server architectures, many researchers are analyzing the possibility offered by decentralized architecture based on consensus policies. In this scenario many consensus-based synchronization methods are proposed in literature but the attention has rarely been paid to the influence factors that characterize real environments and real smart grid applications as: (i) the presence of hardware characterized by finite processing time, and finite resolution of nodes involved in the consensus procedure;(ii) the effect of typical clock instability as drift, jitter and wander;(iii) the effect of latencies and limited bandwidths available on a radio system or when common commercial wireless communication are adopted. All the above-mentioned influence factors can be thought of as causes of uncertainties that could affect the overall performance. This paper proposes a study these influence factors both in simulated and real scenarios. The final aim is to find an uncertainty model to evaluate and forecast the reliability and the quality of the time synchronization procedure.

关键词： Smart grid Consensus sensor Network Time Synchronization data fusion measurement uncertainty

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On the Adaptivity of Unscented Particle Filter for GNSS/INS Tightly-Integrated Navigation Unit in Urban Environment

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IEEE ACCESS 2021年 9卷 144157-144170页

作者： Vouch, Oliviero Minetto, Alex Falco, Gianluca Dovis, Fabio Politecn Torino Dept Elect & Telecommun DET I-10129 Turin Italy LINKS Fdn Space & Nav Technol Area I-10138 Turin Italy

Tight integration algorithms fusing Global Navigation Satellite System (GNSS) and Inertial Navigation System (INS) have become popular in many high-accuracy positioning and navigation applications. Despite their reliability, common integration architectures can still run into accuracy drops under challenging navigation settings. The growing computational power of low-cost, embedded systems has allowed for the exploitation of several advanced Bayesian state estimation algorithms, such as the Particle Filter (PF) and its hybrid variants, e.g. Unscented Particle Filter (UPF). Although sophisticated, these architectures are not immune from multipath scattering and Non-Line-of-Sight (NLOS) signal receptions, which frequently corrupt satellite measurements and jeopardise GNSS/INS solutions. Hence, a certain level of modelling adaptivity should be granted to avoid severe drifts in the estimated states. Given these premises, the paper presents a novel Adaptive Unscented Particle Filter (AUPF) architecture leveraging two cascading stages to cope with disruptive, biased GNSS input observables in harsh conditions. A INS-based signal processing block is implemented upstream of a Redundant Measurement Noise Covariance Estimation (RMNCE) stage to strengthen the adaptation of observables' statistics and improve the state estimation. An experimental assessment is provided for the proposed robust AUPF that demonstrates a 10 % average reduction of the horizontal position error above the 75-th percentile. In addition, a comparative analysis both with previous adaptive architectures and a plain UPF is carried out to highlight the improved performance of the proposed methodology.

关键词： Global navigation satellite system Navigation Measurement uncertainty Noise measurement Adaptation models Satellites Position measurement Bayes methods sensor fusion inertial navigation satellite navigation systems particle filters adaptive estimation position accuracy

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Multi-camera networks : principles and applications /

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2009年

作者： Hamid Aghajan Andrea Cavallaro [editors].

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Resource-Efficient sensor fusion via System-Wide Dynamic Gated Neural Networks

Resource-Efficient Sensor Fusion via System-Wide Dynamic Gat...

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IEEE Communications Society Conference on sensor and Ad Hoc Communications and Networks (SECON)

作者： C. Singhal Y. Wu F. Malandrino S. Ladron de Guevara Contreras M. Levorato C. F. Chiasserini INRIA France UC Irvine USA CNR-IEIIT Italy CNIT Italy Politecnico di Torino Italy Chalmers University of Technology Sweden

ISBN: (数字)9798331519186

ISBN: (纸本)9798331519193

Mobile systems will have to support multiple AI-based applications, each leveraging heterogeneous data sources through DNN architectures collaboratively executed within the network. To minimize the cost of the AI inference task subject to requirements on latency, quality, and - crucially - reliability of the inference process, it is vital to optimize (i) the set of sensors/data sources and (ii) the DNN architecture, (iii) the network nodes executing sections of the DNN, and (iv) the resources to use. To this end, we leverage dynamic gated neural networks with branches, and propose a novel algorithmic strategy called Quantile-constrained Inference (QIC), based upon quantile-Constrained policy optimization. QIC makes joint, high-quality, swift decisions on all the above aspects of the system, with the aim to minimize inference energy cost. We remark that this is the first contribution connecting gated dynamic DNNs with infrastructure-level decision making. We evaluate QIC using a dynamic gated DNN with stems and branches for optimal sensor fusion and inference, trained on the RADIATE dataset offering Radar, LiDAR, and Camera data, and real-world wireless measurements. Our results confirm that QIC matches the optimum and outperforms its alternatives by over 80%.

关键词： Wireless communication Wireless sensor networks Costs Soft sensors Heuristic algorithms Neural networks Logic gates sensor fusion Dynamic scheduling Time measurement

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Advanced sensing issues for UAS collision avoidance 12

Advanced sensing issues for UAS collision avoidance

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Proceedings of the 2nd International Conference on Application and Theory of Automation in Command and Control Systems

作者： Anna Elena Tirri Giancarmine Fasano Domenico Accardo Antonio Moccia Ettore De Lellis Università degli Studi di Napoli "Federico II" Napoli Italy Centro Italiano Ricerche Aerospaziali (CIRA) Capua (CE) Italy

ISBN: (纸本)9782917490204

This paper presents the results of up to date investigations in the field of Obstacle Tracking System for Sense and Avoid applications of Unmanned Aerial Systems. In particular it highlights the most recent trends in this field, such as the adoption of Advanced Multi sensor Data fusion techniques in order to increase the awareness on the information of a collision threat and the adoption of lightweight onboard system architectures that can meet the requirements for installation onboard small Unmanned Aerial Systems. As a result of the experience with flight testing for a prototypical Sense and Avoid System developed within the framework of a project of the Italian Aerospace Research Centre, some advanced solutions have been proposed to solve the above reported issues. In particular, the adoption of Particle Filtering for realizing Multi-sensor Data fusion has been considered in order to get reliable and accurate estimates of the collision threat, such increasing flight awareness. A customized version of the Particle Filter has been developed and tested by exploiting data acquired during flight tests. Moreover, a specific study has been carried out considering the issues for the realization of an adequate Sense and Avoid system for small Unmanned Aerial System. An integrated configuration that includes ADS-B and Electro Optical sensor has been identified as the most effective solutions standing Sense and Avoid requirements. This solution requires that a great effort is put on software both in terms of data fusion algorithms and real time image processing. The results of this study are described at the end of the paper.

关键词： unmanned aerial systems collision avoidance sense and avoid airborne obstacle tracking unmanned aerial vehicles simulation

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Human cognitive and perceptual factors in JDL level 4 hard / soft data fusion

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Proceedings of SPIE - The International Society for Optical Engineering 2012年 8407卷

作者： Rimland, Jeffrey C. Hall, David L. Graham, Jacob L. Pennsylvania State University College of Information Sciences and Technology 101 IST Building University Park PA 16802-6822 United States

ISBN: (纸本)9780819490858

Utilization of human participants as "soft sensors" is becoming increasingly important for gathering information related to a wide range of phenomena including natural and man-made disasters, environmental changes over time, crime prevention, and other roles of the "citizen scientist." The ubiquity of advanced mobile devices is facilitating the role of humans as "hybrid sensor platforms", allowing them to gather data (e.g. video, still images, GPS coordinates), annotate it based on their intuitive human understanding, and upload it using existing infrastructure and social networks. However, this new paradigm presents many challenges related to source characterization, effective tasking, and utilization of massive quantities of physical sensor, human-based, and hybrid hard/soft data in a manner that facilitates decision making instead of simply amplifying information overload. In the Joint Directors of Laboratories (JDL) data fusion process model, "level 4" fusion is a meta-process that attempts to improve performance of the entire fusion system through effective source utilization. While there are well-defined approaches for tasking and categorizing physical sensors, these methods fall short when attempting to effectively utilize a hybrid group of physical sensors and human observers. While physical sensor characterization can rely on statistical models of performance (e.g. accuracy, reliability, specificity, etc.) under given conditions, "soft" sensors add the additional challenges of characterizing human performance, tasking without inducing bias, and effectively balancing strengths and weaknesses of both human and physical sensors. This paper addresses the challenges of the evolving human-centric fusion paradigm and presents cognitive, perceptual, and other human factors that help to understand, categorize, and augment the roles and capabilities of humans as observers in hybrid systems. © 2012 SPIE.

关键词： Data fusion

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Soft body sensor networks: architectures and applications

Soft body sensor networks: Architectures and Applications

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IEEE International Conference on Networking, Sensing and Control

作者： Wentao Dong Xiao Cheng Daojin Yao School of Electrical and Automation Engineering East China Jiaotong University Nanchang China Rail Transportation Technology Innovation Center East China Jiaotong University Nanchang China

ISBN: (数字)9781728168555

ISBN: (纸本)9781728168562

Body sensor networks (BSNs) are designed to collect, process, and transmit the biological data from different parts of human body from wearable electronics with limited resources. Conventional BSN node is also designed and fabricated by the rigid sensors, printed circuit board (PCB), and integrated chip (IC), which are not compatible with the soft human skin. The concepts of soft body sensor networks (SBSNs) are given in the manuscript based on wireless sensor networks and flexible electronics. SBSN node is composed of soft sensors, flexible data modulation and process unit and flexible wireless communication unit, and all the components of SBSN node are designed to be bended and be compatible with soft skin surface by flexible electronic. The architecture of SBSNs are built with several layers: soft sensors, data collection, wireless communication, body could, data fusion algorithm and monitoring interface for further online healthy monitoring. Multisensory decision fusion algorithm has been presented with biometric and medical monitoring applications which is subsequently analyzed for medical diagnosis. Emotion recognitions are realized to predict healthy state based on SBSNs using the intelligent data fusion algorithms.

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From Vision to Realtime Motion Control for the RoboCup Domain

From Vision to Realtime Motion Control for the RoboCup Domai...

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IEEE Conference on Control Technology and applications (CCTA)

作者： Dennis Bruijnen Wouter Aangenent Jeroen van Helvoort Rene van de Molengraft Faculty of Mechanical Engineering Technische Universiteit Eindhoven The Netherlands

In this paper, an overview is given of how the path from vision to motion has been developed in the TechUnited team. The vision module includes: (i) color calibration using a union of convex hulls to select an area in the 3D-colorspace, (ii) automatic calibration of the mapping from the camera image to the field via a genetic algorithm, (iii) self localization based on field lines. The output of the vision module is used by the motion module which includes: (i) vision and encoder sensor fusion by monitoring the drift caused by odometry, (ii) generating a motion path complying with the robot's limitations to prevent wheel slippage, (iii) collocated motion control. In contrast to closing the loop on vision, our approach uses wheel encoders as the basis for motion control, which has several advantages such as less delay due to a higher sampling frequency. Vision is only used to compensate for slow drift caused by slip in the wheel-surface contact.

关键词： Motion control Calibration Wheels Motion planning Cameras Genetic algorithms sensor fusion Monitoring fusion power generation Mobile robots

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Studying the complexities in distributed object tracking systems

Studying the complexities in distributed object tracking sys...

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IEEE International Conference on Systems, Man and Cybernetics

作者： J. Llinas Industrial Engineering Depment Center for Multisource Information Fusion University of Buffallo Buffalo NY USA

Tracking of moving objects based on multisensor input is a topic that has received considerable attention, and has been the subject of many papers. As Web-type capabilities have emerged, along with ever-improving wireless communications capabilities, coupled with the needs of various applications to include "network-centric warfare" on the part of the military, research on distributed multi-object, multi-sensor tracking has received some attention in recent years. However, the study of these distributed problems at the complete-architecture level, accounting for (among yet other factors) organizational information-sharing protocols, dynamic network topologies, mixes of stationary and moving sensors, complex object dynamics, equipment failure modes, node-specific tracking algorithms and data fusion algorithms, does not seem to have been addressed in any "holistic" way. This paper addresses these issues and describes an integrated testbed being developed at the University at Buffalo's Center for Multisource Information fusion for the empirical study of these complex architectures involving, in essence, the interconnection of multiple systems.

关键词： Target tracking Modems sensor fusion Network topology Algorithm design and analysis Industrial engineering sensor systems Wireless communication Military communication Protocols

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