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Integration of Multiple Adaptive algorithms for Parallel Decision fusion 50

Integration of Multiple Adaptive Algorithms for Parallel Dec...

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50th Annual conference on Information Science and Systems (CISS)

作者： Dong, Weigiang Kam, Moshe New Jersey Inst Technol Dept Elect & Comp Engn Newark NJ 07102 USA

ISBN: (纸本)9781467394574

The Chair-Varshney rule for parallel binary decision fusion requires knowledge of the a priori probabilities of the hypotheses and the performance of the sensors (probabilities of false alarm and missed detection). In most applications, this information is not available. Five methods were developed so far for estimating the unknown probabilities. However, none of them is the best under all circumstances. We present an algorithm that selects the best of these five methods. The algorithm estimates roughly the value of the a priori probabilities and the sensor performance from input data, and seeks support from a data base that provides archival data from the five methods at this operating point. In simulation, the algorithm performed on average better than each one of the five existing methods operating alone.

关键词： Distributed Detection Data fusion Decision fusion Adaptive Decision fusion Probability Estimation

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Robust Factor Graph Optimization - A Comparison for sensor fusion applications 21

Robust Factor Graph Optimization - A Comparison for Sensor F...

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21st IEEE International conference on Emerging Technologies and Factory Automation (ETFA)

作者： Pfeifer, Tim Weissig, Peter Lange, Sven Protzel, Peter TU Chemnitz Dept Elect Engn & Informat Technol Chemnitz Germany

ISBN: (纸本)9781509013142

While many applications of sensor fusion suffer from the occurrence of outliers, a broad range of outlier robust graph optimization techniques has been developed for simultaneous localization and mapping. In this paper we investigate the performance of some of the most advanced algorithms for a simulated wireless localization setting affected by non-Gaussian errors. With this first analysis we can show some of the advantages and disadvantages that are connected with the different concepts behind Max-Mixture, Generalized iSAM, Switchable Constraints and Dynamic Covariance Scaling.

关键词： Statistics

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Image sensor Data fusion Using Factorized Kalman Filter 1

Image Sensor Data Fusion Using Factorized Kalman Filter

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IEEE International conference on Recent Trends in Electronics, Information and Communication Technology (RTEICT)

作者： Roopa, H. R. Parimala, P. Raol, J. R. MSRIT Dept Telecommun Eng Bangalore Karnataka India MSRIT Bangalore Karnataka India

ISBN: (纸本)9781509007745

This paper presents image sensor data fusion strategy using factorized Kalman filter algorithm which has wide range of aerospace applications. This involves locating the target from the images obtained from the two sensors using Centroid tracking Factorized Kalman filter and then fusing the sensor data to get much better information of the target position and velocity. Factorized Kalman filter or UD filter (UDF) is used for predicting the upcoming position and other variables of the target. fusion is used to reduce the error that occurs due to clutters in image data taken from sensors. Performance of two fusion algorithms that is measurement or data level fusion and state vector fusion are carried out and good results are obtained regarding the position and velocity estimation of the target. Image sensor data fusion (ISDF) is realized using MATLAB tool. The sensor images are synthesized and added with different noise levels in order to represent sensor data obtained in the presence of different atmospheric clutter. Segmentation process and nearest neighbor technique is used to extract the target details from the sensor images.

关键词： Identity estimation Centroid tracking Automatic target recognition(ATR) Mean absolute errorr(MAE) Signal to noise ratio(SNR) Image sensor data fusion(ISDF) Kalman filter(KF) Centroid tracking UDF filter (CTUDFF) state vector fusion (SVF) Measurement Level fusion (MLF)

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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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An Efficient Architecture for Modeling Path Loss on Forest Canopy Using LiDAR and Wireless sensor Networks fusion

An Efficient Architecture for Modeling Path Loss on Forest C...

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European Wireless 2017;23th European Wireless conference

作者： Yunus Egi Carlos Otero Matthew Ridley Engin Eyceyurt

ISBN: (纸本)9781509038442

Wireless sensor Network (WSN) provide the means for efficient intelligence, surveillance, and reconnaissance (ISR) applications. However, deploying such networks in irregular terrains can be time-consuming, error-prone, and in most cases, result in unpredictable performance. For example, when WSN are deployed in forests or terrains with vegetation, measuring campaigns (using trial/error) are required to determine the path loss driving node positioning to ensure network connectivity. This paper proposes an architecture for planning optimal deployments of WSN. Specifically, it proposes the use of airborne Light Detection and Ranging (LiDAR), an Inertial Measurement Unit (IMU), a Global Positioning System (GPS), and a Stereo Camera (SC) to detect forest characteristics with real-time mapping which reduces the need for trial campaigns; thus, minimizing costs, time, and complexity. The proposed approach expands the state-of-the-art to optimize the performance of WSN upon deployment.

关键词： Estimation Field programmable gate arrays OFDM Modulation Filtration Clocks Signal processing algorithms

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Setting governor properties on ARM architectures in image processing applications 21

Setting governor properties on ARM architectures in image pr...

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21st IEEE International conference on Emerging Technologies and Factory Automation (ETFA)

作者： Silvestre-Blanes, Javier Univ Politecn Valencia UPV Inst Tecnol Informat ITI Plaza Ferrandiz & Carbonell S-N E-03801 Alcoy Spain

ISBN: (纸本)9781509013142

The huge growth in the smartphones market has led to the improvement in ARM architectures, so that today there are many devices based on them, with sufficient capacity to deal with certain image processing applications. These are used in VSN (Visual sensor Networks) and in other scenarios, where the energy used in the process is a parameter to be considered. In these scenarios, and with the HMP (Heterogeneous multiprocessing) architectures on which the current platforms are based, it is necessary to determine both the core as well as the working frequency in order to achieve the application's image processing objectives with the least possible energy consumption. In this type of system, the workload is oriented towards interactive applications, so the priorities are different to those of VSN type systems. Conventional regulation algorithms do not make appropriate use of the processor's frequency range, in relation to the load. This paper analyses the influence of the maximum frequency value on system performance and power consumption.

关键词： Image enhancement

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Collaborative Autonomous Sensing with Bayesians in the Loop 12

Collaborative Autonomous Sensing with Bayesians in the Loop

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conference on Unmanned/Unattended sensors and sensor Networks XII

作者： Ahmed, Nisar Univ Colorado Boulder Aerosp Engn Sci Boulder CO 80309 USA

ISBN: (数字)9781510603776 s

ISBN: (纸本)9781510603769;9781510603776

There is a strong push to develop intelligent unmanned autonomy that complements human reasoning for applications as diverse as wilderness search and rescue, military surveillance, and robotic space exploration. More than just replacing humans for 'dull, dirty and dangerous' work, autonomous agents are expected to cope with a whole host of uncertainties while working closely together with humans in new situations. The robotics revolution firmly established the primacy of Bayesian algorithms for tackling challenging perception, learning and decision-making problems. Since the next frontier of autonomy demands the ability to gather information across stretches of time and space that are beyond the reach of a single autonomous agent, the next generation of Bayesian algorithms must capitalize on opportunities to draw upon the sensing and perception abilities of humans-in/on-the-loop. This work summarizes our recent research toward harnessing 'human sensors' for information gathering tasks. The basic idea behind is to allow human end users (i.e. non-experts in robotics, statistics, machine learning, etc.) to directly 'talk to' the information fusion engine and perceptual processes aboard any autonomous agent. Our approach is grounded in rigorous Bayesian modeling and fusion of flexible semantic information derived from user-friendly interfaces, such as natural language chat and locative hand-drawn sketches. This naturally enables 'plug and play' human sensing with existing probabilistic algorithms for planning and perception, and has been successfully demonstrated with human-robot teams in target localization applications.

关键词： Human-machine systems collaborative sensing Bayesian methods machine learning sensor fusion estimation robotics

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Energy analysis of two-tiered clustered architectures for smart world applications

Energy analysis of two-tiered clustered architectures for sm...

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IEEE Region 10 Humanitarian Technology conference (R10-HTC)

作者： Rajvir Singh Rajnish Sharma C. Rama Krishna Renu Vig Dept. of ECE Chitkara University India Dept. of Computer Science National Institute of Technical Teachers Training and Research Chandigarh India Dept. of ECE University Institute of Engineering and Technology Chandigarh India

ISBN: (纸本)9781538621769;9781538621752

Use of two-tiered clustered architecture in deploying sensor networks for smart world applications is well-known in research community. No other single routing algorithm has spawned that many variations as the LEACH clustering algorithm. Till date researchers are interested in exploring the operation and performance of LEACH algorithm and its improved versions. Most of these works compare their performance with original/ adapted LECH algorithm by using aggregate measures such as network lifetime, stability and payload delivered by the sensor network. The methods used for improving the performance include generating optimum no. of clusters, ensuring uniform cluster distribution, and using an energy-aware clustering mechanism for CH selection. To understand the utility of these different methods to improve the basic LEACH algorithm, this work presents an improved clustered architecture (ICAR) that uses an energy-aware CH selection mechanism along with uniform cluster distribution in the networked area. The energy analysis presented in this work shows that as compared to other methods, using an energy aware cluster-head selection mechanism greatly improves the stability period of a two-tiered clustered architecture.

关键词： Clustering algorithms Stability analysis Mathematical model Computer architecture Algorithm design and analysis Energy consumption Matlab

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Visualization to support Identification, Exploitation and fusion of Data and Information delivered from Heterogeneous Sources in ISR

Visualization to support Identification, Exploitation and Fu...

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

作者： Jamboti, Kavyashree Van de Camp, Florian Kuwertz, Achim Haferkorn, Daniel Eck, Ralf Grasemann, Gunther Fraunhofer IOSB Fraunhofer Str 1 D-76131 Karlsruhe Germany

ISBN: (纸本)9781510601130

In ISR (Intelligence, Surveillance and Reconnaissance), heterogeneous sources deliver data and information having spatial and temporal attributes. Real time and non-real time data created for various purposes, present in different formats has to be exploited and fused. The Coalition Shared Data (CSD) concept makes the interoperable sharing of ISR data and information possible. The concept itself and a technical approach for it were developed within the multinational projects CAESAR, MAJIIC and MAJIIC 2 and tested in coalition exercises. The interfaces of software systems providing access to CSD data must allow the user to intuitively use the system and form a substantial part with regard to user acceptance. We describe different systems and approaches we designed and developed to access CSD data that can locate and present the data to the user based on his specific demands. Visualization forms an important part of these systems which share the common challenge of representing data and information with spatial and temporal attributes. The visualization of data and information has to be designed in a manner that supports efficient access, discovery and optionally additional processing (such as filtering and sorting). Given the large amount of data and information that may be available, visualization taking into account their quality and inherent uncertainty is an additional challenge. This publication provides an overview of the systems and approaches we developed to present CSD data and identifies challenges common to these systems. To tackle these challenges, we present new research results regarding visualization of data and information with temporal and spatial attributes.

关键词： ISR visualization spatio-temporal data CSD clustering filtering heat maps

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Underwater Threat Detection and Tracking using Multiple sensors and Advanced Processing 50

Underwater Threat Detection and Tracking using Multiple Sens...

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IEEE International Carnahan conference on Security Technology (ICCST)

作者： Meecham, Andy Acker, Tim Northern Def Ind Inc Alexandria VA 22314 USA BioSonics Inc Seattle WA USA

ISBN: (纸本)9781509010721

The vulnerability of military installations and critical infrastructure sites from underwater threats is now well accepted and, in order to combat these security weaknesses, there has been growing interest in - and adoption of - sonar technology. Greater availability of Autonomous/Unmanned Underwater Vehicles (A/UUVs) to both adversary nations and terrorists/saboteurs is also a cause of increasing concern. The small size and low acoustic target strength/signature of these vehicles presents significant challenges for sonar systems. The well-known challenges of the underwater environment, particularly in a harbor or port setting, can lead to a Nuisance Alarm Rate (NAR) that is higher than that of traditional security sensors (e.g. CCTV). This, in turn, can lead to a lack of confidence from end users and a possibility that real' alerts are incorrectly dismissed. In the past this has been addressed by increasing the capability of individual sensors, leading to ever-increasing sensor complexity, however, the relationship between sensor performance and complexity/cost is highly non-linear. Even with the most complex and capable sensors, the fundamental limit to performance is often limited by acoustics, not sensor capability. In this paper we describe an alternative approach to reducing NAR and improving detection of difficult targets (e.g. UUVs), through intelligent combination and fusion of outputs from multiple sensors and data/signal processing algorithms. We describe the statistical basis for this approach, as well as techniques, methodologies and architectures for implementation. We describe the approach taken in our prototype algorithms/system, as well as quantitative and qualitative results from testing in a real-world environment. These results show a significant reduction in NAR and increase in classification/alert range. Finally, we describe current focus areas for algorithmic and system development in both the short and medium term, as well as future extension

关键词： sonar maritime security UUV data fusion

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