Papers by Keyword: Data Fusion

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Authors: Qiang Xing, Wan Chun Chen, Bao Yin Ming
Abstract: In the modern warfare, the trajectory of flight vehicle was required to have the ability to be adjusted in specified shape to increasing the penetration force. This paper deals with the guidance law and data fusion system to impact a target in specified direction for precision guided munitions. A three-dimensional guidance law is designed by combining the optimal guidance law and terminal acceleration tuning methodology. A new configuration of Extended Kalman Filter (EKF) is employed to obtain the range and angle information from INS and infrared seeker to improve the survivability of guidance system in the circumstance with strong electromagnetic interference.
Authors: Jing Huang, Hai Hua Li, Rui Yang, Hai Yan Chen
Abstract: Data fusion is an important research issue in wireless sensor networks (WSN). The clustering based approach can reduce the interference among nodes, maintain the balance of energy consumption within WSNs, and therefore prolong the lifetime of WSNs. A clustering-based algorithm called LEACH-EC is presented in the paper. Aiming at solving the problems of the existing algorithms, the LEACH-EC takes the static clustering approach to reduce the energy consumption during clustering stage by first clustering sensors and then selecting the heads of respective clusters. When the heads of clusters send data to the base station, a proposed multi-hop strategy is adopted to further decrease the energy consumption of head sensors. Compared with the existing algorithms, the LEACH-EC has shown a good performance on both extending the lifetime of WSNs as well as reducing energy consumption of sensors.
Authors: Jun Fang Gao, Jian Long Shao
Abstract: Analyzing the two methods of file management and database management, and detailed introducing the method of saving binary-file under the background of LabVIEW and using LabSQL toolkits achieve techniques of accessing to database. Taking high rate data acquisition system for example and designing a data fusion management system based on LabVIEW which integrates file save and database management. Experimental results have shown that data fusion management system can efficiently settle the problems that a large number of acquisition data can high save and conveniently inquire in high rate data acquisition system.
Authors: Shi Jun Xu, Li Hong, Yong Hong Hu
Abstract: In this paper, the signal detection problem when distributed sensors are used a global decision is desired is considered. Local decisions from the sensors are fed to the data fusion center which then yields a global decision based on a fusion rule. Based on The data fusion theories of Bayesian criterion used for a distributed parallel structure, fusion rules at the fusion center、 the decision rules of sensors and the results of the computer simulation for two identical sensors, two different sensors and three identical sensors are presented. The results of the computer simulation show that the performance of the fusion system, compared with the sensor, has been improved. For the case there are three identical sensors in the fusion system, Bayesian risk is reduced by 26.5%, compared with the sensor.
Authors: Muhammad Ushaq, Fang Jian Cheng
Abstract: Strapdown Inertial navigation (SINS) is a highly reliable navigation system for short term applications. SINS functions continuously, less hardware failures, renders high speed navigation solutions ranging from 50 Hz to 1000 Hz and exhibits low short-term errors. It provides efficient attitude, angular rate, acceleration, velocity and position solutions. But, the accuracy of SINS solution vitiates with time as the sensor (gyros & accelerometers) errors are integrated through the navigation equations. Average navigation grade SINS are capable of providing effective stand-alone navigation for shorter duration (few minutes) applications Stand-alone SINS capable of providing solutions for applications exceeding 10 minutes duration, are generally highly expensive ($0.1M to $2.0M). To cope with this limitation, a cost effective solution is the integrated navigation system wherein the unboundedly growing errors of SINS are contained with the help of external non-inertial navigation aids like GPS, Celestial Navigation System (CNS), Odometer, Doppler radars etc. The efficient methodology for integrated or multi-sensory navigation is the Federated Kalman Filter (FKF) scheme. In FKF architecture, a reference SINS solution is integrated independently with each of the aiding navigation systems in a bank of local Kalman filters. There are a number of different ways in which the local filter outputs may be combined to produce an integrated navigation solution. The no-reset, fusion-reset, zero-reset, and cascaded versions of federated integration have been used by different researcher and navigators over the years. All different schemes of FKF have certain pros and cons. Fusion-reset method although nearly optimal is less fault tolerant while no-resent scheme renders highly fault tolerant solutions but with sub-optimal solutions and compromised precision. To enhance the fault tolerance ability of fusion-reset scheme of FKF, additional parameters called weighting factors are introduced to tune the contribution of each local filter in the final data fusion. The presented scheme has been found nearly optimal and expressively fault tolerant.
Authors: Ming Yu Liu, Chi Fai Cheung, Ming Jun Ren, Ching Hsiang Cheng, Ling Bao Kong, Wing Bun Lee
Abstract: Multiscale surfaces enriched with different scales of features are becoming widely used in many fields such as MEMS and optics industries. Due to the complexity of the multiple scale geometries, a single sensor or a single measurement can hardly obtain the holistic information of these surfaces. Multiple measurement method can solve this problem while it will introduce a lot of challenges for multiscale data fusion for the measurement results. This paper presents a framework of a data fusion algorithm for precision measurement of multiscale surfaces. The method makes use of iterative closest point based method to precisely register the datasets obtained in multiple measurements, and a Gaussian zero-order regression filter is used to separate the geometric features in different scales. Hence, the datasets are fused based on an edge intensity data fusion algorithm within the same wavelength. Finally, the fused datasets of different wavelengths were merged and replaced to the corresponding area in the large scale measurement to form a new surface with holistic multiscale information. The effectiveness of the proposed method has been verified on a v-grooved surface through a series of simulation experiments
Authors: Yi Lv
Abstract: According to the features and needs of collecting the data of temperature and humidity of current industrial environment, and the multi-places and multi-sensors data fusion as well, this paper proposes a fuzzy logic-based approach for the multi-places and multi-sensors data fusion. Firstly, this paper introduces the hardware construction of monitor system of temperature and humidity. Then, based on fuzzy set theory, the paper describes the model of fuzzy synthetic evaluation, and then proposes a novel algorithm for choosing the weights assignment proposals. Finally, a multi-places and multi-sensors data fusion approach, which is based on fuzzy synthetic evaluation, is presented. An example is also used for demonstrating the proposed approach. The results of system implementation identify that the approach can remove the influence of incorrect data on evaluating the temperature and humidity of current environment, and the data fusion result is objective and correct as well.
Authors: Zheng Ying
Abstract: To estimate the pose of large aircraft component in pose adjustment quickly and accurately, a real-time estimation method based on Unscented Kalman filter (UKF) is proposed. Firstly, in the process of the aircraft component adjustment, a rough value of aircraft component’s pose is acquired by using forward kinematic model and the displacement of positioners on real time. Then, position of a measuring point fixed on aircraft component is obtained by a laser tracker. At last, UKF is employed to integrate the previous rough value and the measuring point position for evaluating the accurate pose of aircraft component. Numerical simulation results show that the presented method is achieved easily, calculated fast and high accurate.
Authors: Rong Rui Fang, Sheng Hu Xue, Zi Hong Ye, Xiao Ping Yu
Abstract: Method based on multi-sensor detection and data fusion technology is proposed for the temperature of real-time quantitative PCR reaction samples .The principle of Grubbs is used to eliminate the careless mistake data. Particularly, the fusion method based on weighted mean value and estimation in batches is used to process the sampled data, which gives error of indication. And then we can revise indication values.
Authors: Wei Gong
Abstract: The abilities of summarization, learning and self-fitting and inner-parallel computing make artificial neural networks suitable for intrusion detection. On the other hand, data fusion based IDS has been used to solve the problem of distorting rate and failing-to-report rate and improve its performance. However, multi-sensor input-data makes the IDS lose its efficiency. The research of neural network based data fusion IDS tries to combine the strong process ability of neural network with the advantages of data fusion IDS. A neural network is designed to realize the data fusion and intrusion analysis and Pruning algorithm of neural networks is used for filtering information from multi-sensors. In the process of intrusion analysis pruning algorithm of neural networks is used for filtering information from multi-sensors so as to increase its performance and save the bandwidth of networks.
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