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International Conference on Information fusion

作者： ZHANG Xinghu Sharon TAN Sihong TOH Yew Hong DSO National Laboratories 20 Science Park Drive Singapore 118230 Republic of Singapore

ISBN: (纸本)9781509020126

Target positioning in 3D based on TDOA (time difference of arrival) measurements is a challenging problem. This paper will design a novel integrated closed-form (ICF) fusion algorithm by bringing in an ancillary-variable, which could be uniformly applicable to TDOA, AOA, as well as TDOA+AOA. This ICF fusion algorithm is stable and robust for any sensor network distribution and applicable for 3D position estimation with as few as two sensors with both TOA and DOA measurements. The effectiveness and accuracy of the algorithm for different kind of sensor distributions have been illustrated with a number of simulation examples.

关键词： fusion algorithm TOA TDOA AOA DOA ICF fusion algorithm

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Amnesic Multi-sensor fusion algorithm for Streaming Time Series

Amnesic Multi-sensor Fusion Algorithm for Streaming Time Ser...

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2007 8th International Conference on Electronic Measurement & Instruments（ICEMI’2007）

作者： Zhang Peng 1 Li Xueren 1 Zhang Jianye 2 Du Jun 1 1. Air force Engineering University Engineering College, Xi’an 050003 China (2. Department of Automatic Control, Northwestern Polytechnical University, Xi’an 710072 China)

Since more and more real time multi-sensor system generated continuous measurement values, a novel amnesic fusion algorithm is proposed. In the case of any prior knowledge is unknown, the algorithm takes use of the exponential function to build the support degree matrix, so each sensor’s weight coefficient of different time can be obtained. Based on the fact that in many domains recent information is more useful than older information, the user-specified piecewise constant amnesic function is defined and ensured the correctness of weight coefficient re-assignment and the reduction of computation and storage complexity. Three thermocouples with observation noise distribution unknown are used to detect the temperature of a constant temperature box to verify the effectiveness of this algorithm.

关键词： Multi-sensor fusion algorithm Amnesic function Support degree Streaming time series

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Attitude Estimation of MAV Based on fusion algorithm

Attitude Estimation of MAV Based on Fusion Algorithm

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2011 Third International Conference on Intelligent Human-Machine Systems and Cybernetics [第三届智能人机系统与控制论国际会议 IHMSC 2011]

作者： Min Xu Yanxuan Wu Zhengjie Wang Cheng Li Ningjun Fan School of Mechatronical Engineering Beijing Institute of Technology (BIT) Beijing China

A fusion algorithm for attitude estimation of MAV (Micro Aerial Vehicle) is presented. The algorithm use quaternion to represent rotation. Attitude quaternion errors and drift bias of gyros are selected to construct a Kalman filter state vector. The output of GPS is used to correct the accelerometer readings. The local earth magnetic and gravity are used to compute observation of Kalman filter by Levenberg-Marquardt algorithm .The algorithm can converge quickly to rotation attitude of small flight vehicle.

关键词： fusion algorithm Kalman filter Levenberg-Marquardt algorithm attitude estimation

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Fault diagnosis for discrete monitoring data based on fusion algorithm

Fault diagnosis for discrete monitoring data based on fusion...

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2015 IEEE 12th International Conference on Electronic Measurement & Instruments

作者： He Sijie Peng Yu Liu Datong Department of Automatic Test and Control Harbin Institute of Technology

Fault diagnosis has a significant role in enhancing the safety, reliability, and availability of complex systems. However, the problem of enormous condition monitoring data and multiple failure modes makes the diagnostics great challenge. The imbalance between normal and fault monitoring data will increase the false alarm rate and the false negative rate. On the other hand, discrete monitoring data such as events are frequent and critical to fault diagnosis of complex systems. In this work, we propose a fusion fault diagnostic method which combines Na?ve Bayes with Ada Boost ensemble algorithm. This integrated method is appropriate for discrete data and improves the adaptability for imbalanced condition monitoring data. Experimental results based on PHM 2013 dataset show that fault diagnosis performance using the fusion method can be ameliorated.

关键词： Fault diagnosis Na?ve Bayes AdaB oost discrete monitoring data fusion algorithm

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Preliminary study of multiple b-value diffusion-weighted images and T1 post enhancement magnetic resonance imaging images fusion with Laplacian Re-decomposition (LRD) medical fusion algorithm for glioma grading

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EUROPEAN JOURNAL OF RADIOLOGY OPEN 2021年 8卷 100378-100378页

作者： Khorasani, Amir Tavakoli, Mohamad Bagher Saboori, Masih Jalilian, Milad Isfahan Univ Med Sci Sch Med Dept Med Phys Esfahan *** Iran Isfahan Univ Med Sci Sch Med Dept Neurosurg Esfahan Iran

Background: Grade of brain tumor is thought to be the most significant and crucial component in treatment management. Recent development in medical imaging techniques have led to the introduce non-invasive methods for brain tumor grading such as different magnetic resonance imaging (MRI) protocols. Combination of different MRI protocols with fusion algorithms for tumor grading is used to increase diagnostic improvement. This paper investigated the efficiency of the Laplacian Re-decomposition (LRD) fusion algorithms for glioma grading. Procedures: In this study, 69 patients were examined with MRI. The T1 post enhancement (T1Gd) and diffusion weighted images (DWI) were obtained. To evaluated LRD performance for glioma grading, we compared the parameters of the receiver operating characteristic (ROC) curves. Findings: We found that the average Relative Signal Contrast (RSC) for high-grade gliomas is greater than RSCs for low-grade gliomas in T1Gd images and all fused images. No significant difference in RSCs of DWI images was observed between low-grade and high-grade gliomas. However, a significant RSCs difference was detected between grade III and IV in the T1Gd, b50, and all fussed images. Conclusions: This research suggests that T1Gd images are an appropriate imaging protocol for separating lowgrade and high-grade gliomas. According to the findings of this study, we may use the LRD fusion algorithm to increase the diagnostic value of T1Gd and DWI picture for grades III and IV glioma distinction. In conclusion, this article has emphasized the significance of the LRD fusion algorithm as a tool for differentiating grade III and IV gliomas.

关键词： fusion algorithm Glioma Grade Magnetic resonance imaging Laplacian Re-decomposition Diffusion-weighted images

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Research on an Improved Ant Colony algorithm fusion with Genetic algorithm for Route Planning 4

Research on an Improved Ant Colony Algorithm Fusion with Gen...

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4th IEEE Information Technology, Networking, Electronic and Automation Control Conference (ITNEC)

作者： Chen, Xiaoyan Dai, Yuhe Tianjin Univ Sci & Technol Coll Elect Informat & Automat Tianjin Peoples R China

ISBN: (纸本)9781728143903

This article focuses on an improved ant colony algorithm for solving the problem of route planning. An ant colony algorithm (ACO) fusion with genetic algorithm (GA) is proposed and verified by simulations. The genetic algorithm is used to calculate the initial pheromone according to the route nodes distribution. The output of GA is considered as prior information fed to ACO algorithm by selecting, crossing and variation evolution operations. Comparing with the ACO and GA routing algorithms individually under the condition of 10,20,40 nodes distribution within the region of interest based on MATLAB simulation, the fusion ACO-GA algorithm achieves the shortest route and fitness evolution results. Experimental tests have indicated that with the interior nodes of the interesting region increasing, the route distance obtained by the improved algorithm is shorter than GA and ACO algorithms both. Moreover, the proposed ant colony algorithm fusion with GA has fewer iterations to obtain the optimal solution, and the calculation time cost is decreased obviously.

关键词： route planning ant colony algorithm genetic algorithm fusion algorithm

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Quasi-consistent fusion navigation algorithm for DSS

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Science China(Information Sciences) 2018年第1期61卷 187-203页

作者： Qiya SU Yi HUANG Yanguang JIANG Haitao FANG Key Laboratory of Systems and Control Academy of Mathematics and Systems ScienceChinese Academy of Sciences School of Mathematical Sciences University of Chinese Academy of Sciences Beijing Institute of Control and Electronics Technology

A fusion navigation algorithm for the distributed satellites system(DSS) utilizing relative range measurements is proposed in this paper. Based on the quasi-consistent extended Kalman filter(QCEKF), an on-line evaluation of the navigation precision can be provided by the fusion navigation algorithm. In addition,the upper bound for the estimation error obtained from the fusion navigation algorithm is lower than those with any groups of measurements, which indicates that the fusion navigation algorithm can automatically choose the suitable redundant measurements to improve the navigation precision. The simulations show the feasibility and effectiveness of the proposed fusion navigation algorithm.

关键词： quasi-consistent extended Kalman filter(QCEKF) extended Kalman filter(EKF) fusion algorithm navigation distributed satellites system(DSS)

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A fusion Location algorithm Based on Federated Kalman Filtering

A Fusion Location Algorithm Based on Federated Kalman Filter...

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2016 4th International Conference on Machinery,Materials and Computing Technology(ICMMCT 2016)

作者： LV Long-hui JIN Hong-xia Henan Quality Engineering Vocational College

The paper designed a WLAN system with RFID systems joint locating algorithm based on Federated Kalman Filtering. For the problem in indoor mobile node single positioning system, such as insufficient positioning accuracy, longer positioning time and not ideal algorithm complexity, it was proposed that the federated filtering techniques was applied in the location system, and was combined with data from WLAN and RFID to realize all accuracy improved. In the system, sub-filter use unscented Kalman filter algorithm independent measurement updates and time update, and the subsystem information is fused with the main filter based on no feedback mode. It was proved from the result that the calculation improved was of feasibility, which reduced unscented Kalman filter calculation, decreased maximum deviation and minimum deviation and improved the positioning accuracy.

关键词： Federal Kalman Filter WLAN System RFID System Location algorithm fusion algorithm

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On Fusing Wireless Fingerprints with Pedestrian Dead Reckoning to Improve Indoor Localization Accuracy

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SENSORS 2025年第5期25卷 1294-1294页

作者： Fernando, Gimo C. Qi, Tinghao Ndimbo, Edmund V. Abraha, Assefa Tesfay Wang, Bang Huazhong Univ Sci & Technol Sch Informat Elect & Commun Wuhan 430074 Peoples R China Mekelle Univ Mekelle Inst Technol Mekelle 7000 Ethiopia Huazhong Univ Sci & Technol Hubei Key Lab Smart Internet Technol Wuhan 430074 Peoples R China

Accurate indoor positioning remains a critical challenge due to the limitations of single-source systems, such as signal instability and environmental obstructions. This study introduces a multi-source fusion positioning algorithm that integrates inertial sensors and signal fingerprints to address these issues. Using a weighted fusion method, the algorithm employs pedestrian dead reckoning (PDR) for trajectory tracking and combines its outputs with wireless signal fingerprints. Experimental evaluations conducted on diverse trajectories reveal significant improvements in accuracy, achieving a 35.3% enhancement over wireless-only systems and a 71.4% improvement compared to standalone PDR. The proposed method effectively balances computational efficiency and accuracy, demonstrating robustness in complex and dynamic indoor environments. These findings establish the algorithm's potential for practical applications in navigation, robotics, and Industry 4.0, where precise indoor localization is essential.

关键词： indoor positioning fusion algorithm inertial sensors signal fingerprints pedestrian dead reckoning multi-source data fusion

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Research on Fire Detection of Cotton Picker Based on Improved algorithm

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SENSORS 2025年第2期25卷 564-564页

作者： Shi, Zhai Wu, Fangwei Han, Changjie Song, Dongdong Xinjiang Agr Univ Coll Mech & Elect Engn Urumqi 830052 Peoples R China

According to the physical characteristics of cotton and the work characteristics of cotton pickers in the field, during the picking process, there is a risk of cotton combustion. The cotton picker working environment is complex, cotton ignition can be hidden, and fire is difficult to detect. Therefore, in this study, we designed an improved algorithm for multi-sensor data fusion;built a cotton picker fire detection system by using infrared temperature sensors, CO sensors, and the upper computer;and proposed a BP neural network model based on improved mutation operator hybrid gray wolf optimizer and particle swarm optimization (MGWO-PSO) algorithm based on the BP neural network model. This algorithm includes the introduction of a mutation operator in the gray wolf algorithm to improve the search ability of the algorithm, and, at the same time, we introduce the PSO algorithm idea. The improved fusion algorithm is used as a learning algorithm to optimize the BP neural network, and the optimized network is used to process and predict the data collected from temperature and gas sensors, which effectively improves the accuracy of fire prediction. The sensor measurements were compared with the actual values to verify the effectiveness of the GWO-PSO-optimized BP neural network model. Once experimentally verified, the improved GWO-PSO algorithm achieves a correlation coefficient R of 0.96929, a prediction accuracy rate of 96.10%, and a prediction error rate of only 3.9%, while the system monitors an accurate early warning rate of 96.07%, and the false alarm and omission rates are both less than 5%. This study can detect cotton picker fires in real time and provide timely warnings, which provides a new method for the accurate detection of fires during the field operation of cotton pickers.

关键词： fusion algorithm neural network cotton pickers fire detection system

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