检索结果-内蒙古大学图书馆

International Conference on Graphic and Image Processing (ICGIP)

作者： Wang Ming-fang Zhu Ming-e Yu Shao-jun Cent S Univ Forestry & Technol Sch Comp Sci & Technol Changsha 410004 Hunan Peoples R China

ISBN: (纸本)9780819489326

An improved multi-sensor data fusion algorithm based on Dempster-Shafer evidence theory and a criterion of the object evaluation are presented in this paper. The algorithm and the criterion investigate the monitor data of the indoor air that is the research object, and evaluate the quality grade of the indoor air. Experiment shows that the improved multi-sensor data fusion algorithm based on the Dempster-Shafer reasoning and the resulting evaluations are correct and solve the uncertainty problem which is produced in the multi-sensor information process.

关键词： improved Dempster-Shafer evidence reasoning data fusion algorithm multi-sensors

来源：评论

学校读者我要写书评

暂无评论

A Miniature Aerosol Sensor for Detecting Polydisperse Airborne Ultrafine Particles

引用

SENSORS 2017年第4期17卷 929-929页

作者： Zhang, Chao Wang, Dingqu Zhu, Rong Yang, Wenming Jiang, Peng Tsinghua Univ Dept Precis Instrument State Key Lab Precis Measurement Technol & Instru Beijing 100084 Peoples R China Tsinghua Univ Inst Nucl & New Energy Technol Beijing 100084 Peoples R China Univ Sci & Technol Beijing Sch Mech Engn Beijing 100083 Peoples R China

Counting and sizing of polydisperse airborne nanoparticles have attracted most attentions owing to increasing widespread presence of airborne engineered nanoparticles or ultrafine particles. Here we report a miniature aerosol sensor to detect particle size distribution of polydisperse ultrafine particles based on ion diffusion charging and electrical detection. The aerosol sensor comprises a couple of planar electrodes printed on two circuit boards assembled in parallel, where charging, precipitation and measurement sections are integrated into one chip, which can detect aerosol particle size in of 30-500 nm, number concentration in range of 5 x 10(2)-5 x 10(7) / cm(3). The average relative errors of the measured aerosol number concentration and the particle size are estimated to be 12.2% and 13.5% respectively. A novel measurement scheme is proposed to actualize a real-time detection of polydisperse particles by successively modulating the measurement voltage and deducing the particle size distribution through a smart data fusion algorithm. The effectiveness of the aerosol sensor is experimentally demonstrated via measurements of polystyrene latex (PSL) aerosol and nucleic acid aerosol, as well as sodium chloride aerosol particles.

关键词： aerosol sensor polydisperse ultrafine particle size distribution electrical detection data fusion algorithm

来源：评论

学校读者我要写书评

暂无评论

Accuracy Analysis for GNSS-based Urban Land Vehicle Localisation System

引用

IFAC-PapersOnLine 2016年第3期49卷 191-196页

作者： Toro, Federico Grasso Becker, Uwe Fuentes, Damian Eduardo Diaz Lu, Debiao Tao, Weijie Institute for Traffic Safety and Automation Engineering Technische Universität Braunschweig Germany iQST GmbH Institute for Quality Safety and Transportation Braunschweig Germany School of Electronic and Information Engineering Beijing Jiaotong University China

The future of Intelligent Transportation Systems (ITS) relies on a properly constructed Control Transportation System (CTS) based on a dynamically accurate localisation system. To ensure quality of the localisation system data-fusion algorithms are applied to enhance trueness and precision of the provided locations. But that quality is directly related to the accuracy of the Global Navigation Satellite System (GNSS) receiver. Nowadays Global Position System (GPS) is not the functional GNSS system over Asia. Even though the second generation of China's BeiDou Navigation Satellite System (BDS), also known as COMPASS, is still under construction on a global coverage, it provides service since the beginning of 2013 to the Asia-Pacific region. Focusing on urban scenarios applications, this paper analyses the accuracy of BDS receivers to provide location for localisation systems in urban scenarios, comparing it with GPS and the combination of both in a Multi-GNSS system, using a Differential GNSS (DGNSS) as a reference for the accuracy results. From the accuracy limits results further reliability analysis by means of trueness and precision for tangential and perpendicular coordinates in the dynamic frame of vehicles were proposed. The results show that a circular error probable (CEP) approach is not a realistic representation of the dynamic behaviour of the receivers. So the new Mahalanobis Ellipses Filter (MEF) approach was tested and proven to be a better dynamic accuracy representation for land vehicles, making it the best approach to describe accuracy requirements for BDS-based urban land vehicle localisation systems for safety-relevant ITS. © 2016

关键词： Global positioning system Advanced vehicle control systems Communication satellites data fusion Intelligent systems Intelligent vehicle highway systems Radio navigation Reliability analysis Vehicles Beidou navigation satellite systems Circular error probable data fusion algorithm Global Navigation Satellite Systems Global position systems Intelligent transportation systems Localisation Systems Transportation system

来源：评论

学校读者我要写书评

暂无评论

UAV Attitude Estimation Using Nonlinear Filtering and Low-Cost Mems Sensors

引用

IFAC-PapersOnLine 2016年第21期49卷 521-528页

作者： Kada, B. Munawar, K. Shaikh, M.S. Hussaini, M.A. Al-Saggaf, U.M. Department of Aeronautical Engineering Faculty of Engineering King Abdul-Aziz University Jeddah21589 Saudi Arabia Department of Electrical and Computer Engineering Faculty of Engineering King Abdul-Aziz University Jeddah21589 Saudi Arabia

Integration of low-cost Micro-Electro-Mechanical Systems (MEMS) in the design of Inertial Navigation Systems (INS) for real-time guidance, navigation, and control of flying vehicles often results in low precision, poor accuracy, and degraded performance. Most of existing filtering and data fusion methods that have been applied to the problem of attitude estimation with use of low-cost MEMS-based INS fail in cases that have highly nonlinear process dynamics, nonlinear measurement models, and long-range navigation. This paper presents two nonlinear filtering algorithms for low-cost Unmanned Aerial Vehicles (UAVs) attitude and measurement biases estimation. An Unscented Kalman Filter (UKF) and a Minimum Energy Kalman Filter (MEKF) are designed using two different attitude parameterizations i.e. Euler Angle (EA) and Unit Quaternion (UQ). The two filters AE-UKF and UQ-MEKF use highly nonlinear process and measurements estimators, zero-mean Gaussian noises, and first-order Gauss-Markov biases models. Field experiments, adding systems, and data fusion algorithms are used to achieve real-time tracking and estimation. The results show that both AE-UKF and UQ-MEKF demonstrate high accuracy estimation and robustness for UAVs attitude as well as MEMS biases filtering. © 2016

关键词： Gaussian noise (electronic) Antennas Cost estimating data fusion Electromechanical filters Inertial navigation systems Kalman filters Machine design MEMS Nonlinear analysis Nonlinear filtering Real time systems Unmanned aerial vehicles (UAV) data fusion algorithm Guidance , navigation , and controls Inertial navigation systems (INS) Long range navigations Micro electromechanical system (MEMS) Nonlinear filtering algorithm Nonlinear measurement Unscented Kalman Filter

来源：评论

学校读者我要写书评

暂无评论

An innovative asynchronous, multi-rate, multi-sensor state vector fusion algorithm for air defence applications

引用

IFAC-PapersOnLine 2016年第1期49卷 337-342页

作者： Shivanand, G. Reddy, K Vamshi Krishna Prasad, D.B.N. Defence Research and Development Laboratory Hyderabad Telanagana India

This paper presents an innovative approach for data fusion of asynchronous, multi-rate, multi-sensor data in real time. This technique is based on state vector data fusion. For air defence applications, the target information from multi sensors is sent to a central control centre to create a complete threat scenario which would be used for taking appropriate decision. This target data needs to be sent in real time, hence there is a need for low bandwidth consuming data fusion algorithms but at the same time there should be minimal degradation in data accuracy. The optimal fusion algorithm requires the entire state covariance information matrix to be transmitted to the data fusion centre, however this requires huge bandwidth for transmission of data. To avoid this generally, only diagonal elements are transmitted at the cost of considerable degradation in performance. The authors present an innovative approach by considering the only covariance of position, velocity and acceleration but by neglecting the cross covariance terms among position, velocity and acceleration. The accuracy of this proposed algorithm is about 95% of that of optimal method but the reduction in bandwidth requirement is of the order of 60%. © 2016, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Sensor data fusion Bandwidth Covariance matrix data fusion Kalman filters Military rockets Bandwidth requirement Covariance information data fusion algorithm Innovative approaches Multi sensor data State vector fusion Target information Transmission of data

来源：评论

学校读者我要写书评

暂无评论

Thermal distortion real-time detection and correction of a high-power Laser beam-splitter mirror based on double Shack-Hartmann wavefront sensors 2

Thermal distortion real-time detection and correction of a h...

引用

Conference on High-Power, High-Energy, and High-Intensity Laser Technology II

作者： Ning, Yu Sun, Quan Wang, Hongyan Wu, Wuming Du, Shaojun Xu, Xiaojun Natl Univ Def Technol Coll Optoelect Sci & Engn Changsha 410073 Hunan Peoples R China

ISBN: (纸本)9781628416343

In a high-power laser system, a beam splitter refers to the mirror which locates at the cross point of the path of high-power beam and the weak light section. Because of the thermo-optic effect and elasto-optic effect, a beam splitter deforms under intense laser radiation. This deformation adds extra phase on the incident waves and deliveries inaccurate information to the wavefront sensor. Consequently, the output laser focuses at finite distance and gets divergent when arrives at the target. To settle the above problem, this paper presents a new method for real-time correction of the thermal distortion of beam splitter, based on algorithm of the data fusion of two Shack-Hartmann wavefront sensors (SH-WFS). Different from the traditional AO system, which contains a wavefront sensor, a corrector and a servo controller, two extra Shack-Hartmann wavefront detectors are adopted in our AO system, to detect the transmitted and reflected aberrations of beam splitter mirror. And these aberrations are real-timely delivered to the wavefront sensor. Based on coordinate conversion and data fusion algorithm, it makes the wavefront sensor of AO can "see" the aberrations of splitter mirror by itself. Thus, the servo system controls the corrector to compensate these aberrations correctly. In this paper, the theoretical model of data fusion algorithm is carried out. A closed-loop AO system, which consists of a typical AO system and two extra Shack-Hartmann wavefront detectors, is set up to validate the data fusion algorithm. Experimental results show that, the distortion of a CaF2 beam splitter can be real-time corrected when the AO closed-loop control is on. The beam quality factor of output laser decreases from 4 to 1.7 times of diffraction limit.

关键词： adaptive optics beam splitter mirror thermal distortion double Shack-Hartmann wavefront sensors data fusion algorithm

来源：评论

学校读者我要写书评

暂无评论

The Environmental Information Monitoring Network Set up based on Service Discovery Mechanism

The Environmental Information Monitoring Network Set up base...

引用

3rd International Conference on Energy, Environment and Sustainable Development (EESD 2013)

作者： Li Zhaoming Yang Xu Changchun Vocat Inst Technol Network Ctr Changchun 130022 Peoples R China

ISBN: (纸本)9783037859728

The wireless sensor network is widely used in the largely data measure. The research on the energy consumption is the key point in it's practical application recently for the wireless sensor network has the problem of energy restrain. Considering the wireless sensor network applies in the information monitoring system on environmental has the inadequate of the limited energy of nodes and the irregular network energy consumption, this paper analyses the basic structure of the environmental sensor network, and proposes the service discovery mechanism based on the catalogue model. This system can reduces the system's energy consumption, and is able to achieve the purpose of increasing the reliability and security of the sensor network, reducing the data redundancy degree and extending the lifetime of the network according to the experimental simulation.

关键词： wireless sensor network service discovery mechanism improved GAF algorithm data fusion algorithm

来源：评论

学校读者我要写书评

暂无评论

Cooperative Combining of Cumulants-Based Modulation Classification in CR Networks 33

Cooperative Combining of Cumulants-Based Modulation Classifi...

引用

33rd Annual IEEE Military Communications Conference on Affordable Mission Success - Meeting the Challenge (MILCOM)

作者： Abdelbar, Mahi Tranter, Bill Bose, Tamal Virginia Tech Wireless VT Bradley Dept Elect & Comp Engn Blacksburg VA 24061 USA Univ Arizona Dept Elect & Comp Engn Tucson AZ 85721 USA

ISBN: (纸本)9781479967704

Automatic Modulation Classification (AMC) is a key enabling technology in Cognitive Radio (CR) Networks. The ability of CR transceivers to detect and classify unknown wireless signals has various applications in civilian and military domains. Performance of AMC degrades severely under low Signal-to-Noise Ratio (SNR) and variable channel conditions. Cooperative classification has been presented as a means to overcome the detrimental channel effects by combining the results from physically scattered CR nodes. In this work, Maximum Likelihood (ML) combining of classification features is presented as a data fusion algorithm that provides better classification accuracy compared to hard decision combining algorithms without high network overhead. The performance of a cumulants-based modulation classifier under Additive White Gaussian Noise (AWGN) is analyzed. The enhancement in classification performance when applying ML combining of more than one classifier is presented. Theoretical analysis as well as various simulations are presented for ML combining of CR nodes with equal SNR. In addition, analysis is extended to the case where CR nodes have different SNRs. Theory and simulations show that applying ML combining will result in a better classification accuracy, even when one of the nodes has a much lower SNR.

关键词： AWGN classification cognitive radio cooperative communication higher order statistics maximum likelihood estimation modulation additive white Gaussian noise automatic modulation classification classification features cognitive radio network cooperative classification cooperative combining cumulants based modulation classification data fusion algorithm maximum likelihood combining Accuracy algorithm design and analysis Manganese Maximum likelihood estimation Phase shift keying Signal to noise ratio

来源：评论

学校读者我要写书评

暂无评论

A Merging algorithm for Regional Snow Mapping over Eastern Canada from AVHRR and SSM/I data

引用

REMOTE SENSING 2013年第11期5卷 5463-5487页

作者： Chokmani, Karem Bernier, Monique Royer, Alain Inst Natl Rech Sci Ctr Eau Terre Environm Quebec City PQ G1K 9A9 Canada Univ Sherbrooke Dept Geomat Appl Sherbrooke PQ J1K 2R1 Canada

We present an algorithm for regional snow mapping that combines snow maps derived from Advanced Very High Resolution Radiometer (AVHRR) and Special Sensor Microwave/Imager (SSM/I) data. This merging algorithm combines AVHRR's moderate spatial resolution with SSM/I's ability to penetrate clouds and, thus, benefits from the advantages of the two sensors while minimizing their limitations. First, each of the two detection algorithms were upgraded before developing the methodology to merge the snow mapping results obtained using both algorithms. The merging methodology is based on a membership function calculated over a temporal running window of +/- 4 days from the actual date. The studied algorithms were developed and tested over Eastern Canada for the period from 1988 to 1999. The snow mapping algorithm focused on the spring melt season (1 April to 31 May). The snow maps were validated using snow depth observations from meteorological stations. The overall accuracy of the merging algorithm is about 86%, which is between that of the new versions of the two individual algorithms: AVHRR (90%) and SSM/I (83%). Furthermore, the algorithm was able to locate the end date of the snowmelt season with reasonable accuracy (bias = 0 days;SD = 11 days). Comparison of mapping results with high spatial resolution snow cover from Landsat imagery demonstrates the feasibility of clear-sky snow mapping with relatively good accuracy despite some underestimation of snow extent inherited from the AVHRR algorithm. It was found that the detection limit of the algorithm is 80% snow cover within a 1 x 1 km pixel.

关键词： snow cover regional-scale snow mapping multisensory snow product optical and microwave satellite data AVHRR SSM/I data fusion algorithm

来源：评论

学校读者我要写书评

暂无评论

An on-line measuring fusion model of lumber moisture content based on data fusion algorithm

An on-line measuring fusion model of lumber moisture content...

引用

5th International Conference on Wavelet Analysis and Pattern Recognition

作者： Li, Jian Sun, Li-Ping Liu, De-Sheng NE Forestry Univ Coll Mech & Elect Harbin 150040 Peoples R China

ISBN: (纸本)9781424410651

Lumber moisture content is a key parameter for regulating and controlling wood drying process. Its precision directly affects the drying quality, cost and drying time. In this paper a fusion model capable of on-line measuring lumber moisture content is presented. Models for predicting lumber moisture content are established using both back-propagation neural networks (BPNN) and dynamical recurrent Mural networks (DRNN). Furthermore, the two models are integrated by arithmetic average and recursive estimation algorithm. The simulation result, which is worked out by experimental data, shows that fusion model have a higher predictive precision than any one of BP Mural network's and DRNN's, therefore, this method is proved to be feasible.

关键词： lumber moisture content data fusion algorithm neural network fusion model

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：