• International Journal of Control, Automation, and Systems
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• v.4 no.2
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• pp.165-171
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• 2006

This paper proposes a data fusion algorithm of nonlinear multi sensor dynamic systems of synchronous sampling based on filtering step by step. Firstly, the object state variable at the next time index can be predicted by the previous global information with the systems, then the predicted estimation can be updated in turn by use of the extended Kalman filter when all of the observations aiming at the target state variable arrive. Finally a fusion estimation of the object state variable is obtained based on the system global information. Synchronously, we formulate the new algorithm and compare its performances with those of the traditional nonlinear centralized and distributed data fusion algorithms by the indexes that include the computational complexity, data communicational burden, time delay and estimation accuracy, etc.. These compared results indicate that the performance from the new algorithm is superior to the performances from the two traditional nonlinear data fusion algorithms.

• 한국데이터정보과학회:학술대회논문집
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• 2006.11a
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• pp.21-27
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• 2006

Data fusion is generally defined as the use of techniques that combine data from multiple sources and gather that information in order to achieve inferences. Data fusion is also called data combination or data matching. Data fusion is divided in five branch types which are exact matching, judgemental matching, probability matching, statistical matching, and data linking. Currently, Gyeongnam province is executing the social survey every year with the provincials. But, they have the limit of the analysis as execute the different survey to 3 year cycles. In this paper, we study to data fusion of environmental survey data using sas macro. We can use data fusion outputs in environmental preservation and environmental improvement.

• Journal of Advanced Navigation Technology
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• v.19 no.5
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• pp.345-353
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• 2015

In this paper, we proposed an information fusion method for enhancement of automatic dependent surveillance - broadcast (ADS-B) system which is one of the next generation navigation system. Although ADS-B provides better performance than traditional radar, ADS-B still has error due to dependence of global navigation satellite system (GNSS) information. In this paper, we improved the ADS-B performance using information fusion of multilateration (MLAT) and wide area multilateration (WAM). Information fusion provides accurate data compared to original data. Mostly, information fusion methods use Kalman filter or IMM(interacting multiple model) filter as a subfilter. However, we used Robust IMM filter as a subfilter to improve the aircraft tracking performance. Also, we use actual ADS-B data not virtual data to increase reliability of our information fusion method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.2
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• pp.528-544
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• 2015

Base Station Cooperation (BSC) has been a promising technique for combating the Inter-Cell Interference (ICI) by exchanging information through a high-speed optical fiber back-haul to increase the diversity gain. In this paper, we propose a novel pilot symbol assisted data fusion scheme for distributed Uplink BSC (UBSC) based on Differential Evolution (DE) algorithm. Furthermore, the proposed scheme exploits the pre-defined pilot symbols as the sample of transmitted symbols to constitute a sub-optimal Weight Calculation (WC) model. To circumvent the non-linear programming problem of the proposed sub-optimal model, DE algorithm is employed for searching the proper fusion weights. Compared with the existing equal weights based soft combining scheme, the proposed scheme can adaptively adjust the fusion weights according to the accuracy of cooperative information, which remains the relatively low computational complexity and back-haul traffic. Performance analysis and simulation results show that, the proposed scheme can significantly improve the system performance with the pilot settings of the existing standards.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1001-1004
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• 1993

The Multisensor Fusion Problem (MFP) deals with the methodologies involved in effectively combining together homogeneous or non-homegeneous information obtained from multiple redundant or disparate sensors in order to perform a task more accurately, efficiently, and reliably. The inherent uncertainties in the sensory information are represented using Fuzzy Numbers, -numbers, and the Uncertainty-Reductive Fusion Technique (URFT) is introduced to combine the multiple sensory information into one consensus -number. The MFP is formulated from the Information Theory perspective where sensors are viewed as information sources with a fixed output alphabet and systems are modeled as a network of information processing and processing and propagating channels. The performance of the URFT is compared with other fusion techniques in solving the 3-Sensor Problem.

• The Transactions of the Korea Information Processing Society
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• v.6 no.10
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• pp.2728-2739
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• 1999

This paper proposes an effective fusion algorithm for retrieval results from heterogeneous information sources in federated digital libraries. The algorithm determines the population of documents retrieved from involved information sources for a given query and evaluates the degree of relevance between the query and the population. The evaluated results are used as relevance distribution information for collection fusion. The main informations used for the fusion are relevance distribution among collections, the population size N, and ranking information of relevant documents in their origin. We also present th performance evaluation of the algorithm by developing the prototype of a meta-searcher.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.2D
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• pp.305-309
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• 2009

The object of image fusion is to integrate information from multiple images as the same scene. In the satellite image fusion, many image fusion methods have been proposed for combining a high resolution panchromatic(PAN) image with low resolution multispectral(MS) images and it is very important to preserve both the spatial detail and the spectral information of fusion result. The image fusion method using wavelet transform shows good result compared with other fusion methods in preserving spectral information. This study proposes a modified a'trous algorithm based wavelet image fusion method using IKONOS image. Based on the result of experiment using IKONOS image, we confirmed that proposed method was more effective in preserving spatial detail and spectral information than existing fusion methods using a'trous algorithm.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10a
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• pp.19-20
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• 2007

• Journal of Korean Library and Information Science Society
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• v.45 no.3
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• pp.5-36
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• 2014

The Web is rich with various sources of information that go beyond the contents of documents, such as hyperlinks and manually classified directories of Web documents such as Yahoo. This research extends past fusion IR studies, which have repeatedly shown that combining multiple sources of evidence (i.e. fusion) can improve retrieval performance, by investigating the effects of combining three distinct retrieval approaches for Web IR: the text-based approach that leverages document texts, the link-based approach that leverages hyperlinks, and the classification-based approach that leverages Yahoo categories. Retrieval results of text-, link-, and classification-based methods were combined using variations of the linear combination formula to produce fusion results, which were compared to individual retrieval results using traditional retrieval evaluation metrics. Fusion results were also examined to ascertain the significance of overlap (i.e. the number of systems that retrieve a document) in fusion. The analysis of results suggests that the solution spaces of text-, link-, and classification-based retrieval methods are diverse enough for fusion to be beneficial while revealing important characteristics of the fusion environment, such as effects of system parameters and relationship between overlap, document ranking and relevance.

• Journal of The Korean Association of Information Education
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• v.19 no.1
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• pp.139-148
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• 2015

The purpose of image fusion is to combine the relevant information from a set of images into a single image, where the resultant fused image will be more informative and complete than any of the input images. Image fusion techniques can improve the quality and increase the application of these data important applications of the fusion of images include medical imaging, remote sensing, and robotics. In this paper, we suggest a new method to generate a fusion image using the close relation of image features obtained through maximum entropy threshold and mutual information. This method represents a good image registration in case of using a blurring image than other image fusion methods.