• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.97-98
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• 2006

Fusion of decisions from multiple distributed sensor nodes is studied in this work. Based on the canonical parallel fusion model, we derive the optimal likelihood ratio based fusion rule with the assumptions of the generalized Gaussian noise model and the arbitrary fading channel. This optimal fusion rule, however, requires the complete knowledge of the channels and the detection performance of local sensor nodes. To mitigate these requirements and to provide near optimum performance, we derive suboptimum fusion rules by using high and low signal-to-noise ratio (SNR) approximations to the optimal fusion rule. Performance evaluation is conducted through simulations.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.12
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• pp.1230-1242
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• 2007

This paper describes an IIR/FIR fusion filter for a nonlinear system, and analyzes the stability of the fusion filter. The fusion filter is applied to INS/GPS integrated system, and the performance is verified by simulation and experiment. In the fusion filter, an IIR-type filter (SPKF) and FIR-type filter (MRHKF filter) are processed independently, then the two filters are merged using the mixing probability calculated using the residuals and residual covariance information of the two filters. The merits of the SPKF and the MRHKF filter are embossed and the demerits of the filters are diminished via the filter fusion. Consequently, the proposed fusion filter has robustness against to model uncertainty, temporary disturbing noise, large initial estimation error, etc. The stability of the fusion filter is verified by showing the closeness of the states of the two sub filters in the mixing/redistribution process and the upper bound of the error covariance matrices. This fusion filter is applied into INS/GPS integrated system, and important factors for filter processing are presented. The performance of the INS/GPS integrated system designed using the fusion filter is verified by simulation under various error environments and is confirmed by experiment.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.1
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• pp.63-69
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• 2004

In this paper, we propose a general framework for sensor data fusion applied to control systems. Since many kinds of disturbances are introduced to a control system, it is necessary to rely on multisensor data fusion to improve control performance in spite of the disturbances. Multisensor data fusion for a control system is considered a sequence of making decisions for a combination of sensor data to make a proper control input in uncertain conditions of disturbance effects on sensors. The proposed method is applied to a typical control system of a flexible link system in which reduction of oscillation is obtained using a photo sensor at the tip of the link. But the control performance depends heavily on the environmental light conditions. To overcome the light disturbance difficulties, an accelerometer is used in addition to the existing photo sensor. Improvement of control performance is possible by utilizing multisensor data fusion for various output responses to show the feasibility of the proposed method in this paper.

• Journal of Korean Society for Quality Management
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• v.49 no.1
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• pp.1-15
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• 2021

Purpose: The purpose of this study was to propose a sensor fusion algorithm that integrates vehicle motion sensor(VMS) into the hybrid navigation system. Methods: How to evaluate the navigation performance was comparison test with the hybrid navigation system and the sensor fusion method. Results: The results of this study are as follows. It was found that the effects of the sensor fusion method and α value estimation were significant. Applying these greatly improves the navigation performance. Conclusion: For improving the reliability of navigation system, the sensor fusion method shows that the proposed method improves the navigation performance in a combat vehicle.

• Nuclear Engineering and Technology
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• v.51 no.4
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• pp.1142-1153
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• 2019

This paper presents the effect of fusion procedure on the fusion performance of the thermal butt fusion in the safety class III buried HDPE piping per various tests performed, including high speed tensile impact, free bend, blunt notched tensile, notched creep, and PENT tests. The suitability of fusion joints and qualification procedures was evaluated by comparing test results from the base material and buttfusion joints. From the notched tensile test result, it was found that the fused joints have much lower toughness than the base material. It was also identified that the notched tensile test is more desirable than the high speed tensile impact and free bend tests presented in the ASME Code Case N-755-3 as a fusion qualification test method. In addition, with regard to the single low-pressure fusion joint performances, the procedure given by the ISO 21307 was determined to be better that the one specified in the Code Case N-755-3.

• Korean Journal of Remote Sensing
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• v.36 no.5_1
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• pp.807-821
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• 2020

The objective of this study is to evaluate the applicability of representative spatio-temporal fusion models developed for the fusion of mid- and low-resolution satellite images in order to construct a set of time-series high-resolution images for crop monitoring. Particularly, the effects of the characteristics of input image pairs on the prediction performance are investigated by considering the principle of spatio-temporal fusion. An experiment on the fusion of multi-temporal Sentinel-2 and RapidEye images in agricultural fields was conducted to evaluate the prediction performance. Three representative fusion models, including Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM), SParse-representation-based SpatioTemporal reflectance Fusion Model (SPSTFM), and Flexible Spatiotemporal DAta Fusion (FSDAF), were applied to this comparative experiment. The three spatio-temporal fusion models exhibited different prediction performance in terms of prediction errors and spatial similarity. However, regardless of the model types, the correlation between coarse resolution images acquired on the pair dates and the prediction date was more significant than the difference between the pair dates and the prediction date to improve the prediction performance. In addition, using vegetation index as input for spatio-temporal fusion showed better prediction performance by alleviating error propagation problems, compared with using fused reflectance values in the calculation of vegetation index. These experimental results can be used as basic information for both the selection of optimal image pairs and input types, and the development of an advanced model in spatio-temporal fusion for crop monitoring.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.1
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• pp.5-24
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• 2010

Data fusion is an attractive technology because it allows various trade-offs related to performance metrics, e.g., energy, latency, accuracy, fault-tolerance and security in wireless sensor networks (WSNs). Under a complicated environment, each sensor node must be equipped with more than one type of sensor module to monitor multi-targets, so that the complexity for the fusion process is increased due to the existence of various physical attributes. In this paper, we first investigate the process and performance of multi-attribute fusion in data gathering of WSNs, and then propose a self-adaptive threshold method to balance the different change rates of each attributive data. Furthermore, we present a method to measure the energy-conservation efficiency of multi-attribute fusion. Based on our proposed methods, we design a novel energy equilibrium routing method for WSNs, viz., multi-attribute fusion tree (MAFT). Simulation results demonstrate that MAFT achieves very good performance in terms of the network lifetime.

• Journal of Information Processing Systems
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• v.10 no.4
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• pp.555-567
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• 2014

Biometric performance improvement is a challenging task. In this paper, a hierarchical strategy fusion based on multimodal biometric system is presented. This strategy relies on a combination of several biometric traits using a multi-level biometric fusion hierarchy. The multi-level biometric fusion includes a pre-classification fusion with optimal feature selection and a post-classification fusion that is based on the similarity of the maximum of matching scores. The proposed solution enhances biometric recognition performances based on suitable feature selection and reduction, such as principal component analysis (PCA) and linear discriminant analysis (LDA), as much as not all of the feature vectors components support the performance improvement degree.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2253-2272
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• 2018

We propose a deep learning method for multi-focus image fusion. Unlike most existing pixel-level fusion methods, either in spatial domain or in transform domain, our method directly learns an end-to-end fully convolutional two-stream network. The framework maps a pair of different focus images to a clean version, with a chain of convolutional layers, fusion layer and deconvolutional layers. Our deep fusion model has advantages of efficiency and robustness, yet demonstrates state-of-art fusion quality. We explore different parameter settings to achieve trade-offs between performance and speed. Moreover, the experiment results on our training dataset show that our network can achieve good performance with subjective visual perception and objective assessment metrics.

• Nuclear Engineering and Technology
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• v.55 no.9
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• pp.3342-3351
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• 2023

High-density polyethylene (HDPE) pipelines in nuclear power plants (NPPs) have to meet high requirements for seismic performance. HDPE pipes have been proved to have good seismic performance, but joints are the weak links in the pipelines, and pipeline failures usually initiate from the defects inside the joints. Limited data are available on the seismic performance of butt-fusion joints of HDPE pipelines in NPPs, especially in terms of defects changes inside the joints after earthquakes. In this paper, full-scale shaking table tests were performed on a test section of suspended HDPE pipelines in an NPP, which included straight pipes, elbows, and 10 butt-fusion joints. During the tests, the seismic load-induced strain of the joints was analyzed by strain gauges, and it was much smaller than the internal pressure and self-weight-induced strain. Before and after the shaking table tests, phased array ultrasonic testing (PA-UT) was conducted to detect defects inside the joints. The locations, numbers, and dimensions of the defects were analyzed. It was found that defects were more likely to occur in elbows joints. No new defect was observed after the shaking table tests, and the defects showed no significant growth, indicating the satisfactory seismic performance of the butt-fusion joints.