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factor graph aided multiple hypothesis tracking

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Science China(Information Sciences) 2013年第10期56卷 284-289页

作者： WANG Huan SUN JinPing LU SongTao WEI ShaoMing School of Electronic and Information Engineering Beihang University Department of Electrical and Computer Engineering Iowa State University

Since closely moving targets exist extensively in the ground moving target tracking,the uncertainty of data association greatly increases making the measurement-to-track association more ***,traditional multiple hypothesis tracking(MHT)has high false tracking rate and track *** paper frst investigates the measurement based factor graph in data association,and gives the corresponding message passing ***,a factor graph aided multiple hypothesis tracking(FGA-MHT)method is proposed,which introduces factor graph based m-best hypothesis producing technique and exploits factor graph based probability refnement algorithm to reduce the uncertainty of measurement-to-track *** results demonstrate that FGA-MHT reduces times of track swap and increases the correct data association rate in closely moving target tracking.

关键词： multiple hypothesis tracking(MHT) data association factor graph message passing algorithm sum-product algorithm factor graph aided multiple hypothesis tracking(FGA-MHT

Generalized message passing detection of SCMA systems based on dynamic factor graph for better and flexible performance-complexity tradeoff

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Science China(Information Sciences) 2022年第5期65卷 242-249页

作者： Fangqi DONG Huijuan ZHENG Lei MA Sheng TONG State Key Laboratory of Integrated Services Networks Xidian University School of Electronic Engineering Xi'an University of Posts and Telecommunications

Multiuser detection based on the message passing algorithm(MPA) has been considered for sparse code multiple access(SCMA) systems. Recently, some complexity-reduced MPA detectors have been proposed, among which the MPA detector based on dynamic factor graph(DFG-MPA) has been shown to outperform other MPA detectors with comparable complexities. However, all these MPA detectors are somehow not very flexible in terms of performance-complexity tradeoff, i.e., the granularities of computational complexity reduction are relatively large. In this paper, a generalized scheme of DFG-MPA, termed as GDFG-MPA, is proposed to make a better and more flexible performance-complexity tradeoff. The proposed scheme features two aspects:(1) instead of banning a message update forever, a banned message update at some iteration is allowed to be updated at later iterations;(2) different numbers of message updates are banned from updating at different iterations. Optimization of GDFG-MPA can be made by allocating banned message updates among iterations. Numerical results have demonstrated that compared to DFG-MPA the proposed GDFG-MPA can achieve much better performance at the same computational complexity or achieve the same performance with much lower complexity. Moreover, the proposed GDFG-MPA is more flexible in tuning the performance and complexity tradeoff.

关键词： sparse code multiple access (SCMA) multiuser detection message passing algorithm (MPA) factor graph computational complexity

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Distributed cooperative localization based on Gaussian message passing on factor graph in wireless networks

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Science China(Information Sciences) 2015年第4期58卷 78-92页

作者： WU Nan LI Bin WANG Hua XING ChengWen KUANG JingMing School of Information and Electronics Beijing Institute of Technology

In conventional localization, agents may not be able to reach sufficient number of anchors to obtain unambiguous locations, especially in sparse networks. Cooperative localization is a promising solution in that harsh environment, which enables the agents to cooperate with each other by exchanging location information and performing range measurements. In this paper, a distributed cooperative localization method based on factor graph is proposed in wireless networks. Gaussian parametric messages are used to represent the messages passed on factor graph. However, because of the nonlinear observation model, no closed-form solutions can be obtained. To solve this problem, the Taylor expansion is used to approximate the nonlinear terms in message updating, which leads to the Gaussian message passing on factor graph. Accordingly, only two parameters of the Gaussian distribution have to be transmitted and the communication overhead for localization can be significantly reduced. The two proposed algorithms for the application with accurate and inaccurate anchors,respectively, are evaluated by Monte Carlo simulations and compared with the SPAWN and maximum likelihood(ML) estimator. The results show that the proposed algorithms can perform very close to SPAWN with much lower computational complexity, and it outperforms the ML estimator significantly.

关键词： wireless networks cooperative localization factor graph Gaussian message passing

Modified attitude factor graph fusion method for unmanned helicopter under atmospheric disturbance

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Chinese Journal of Aeronautics 2022年第6期35卷 285-297页

作者： Kecheng SUN Qinghua ZENG Jianye LIU Wenqi QIU Jinhen SHI Navigation Research Center Nanjing University of Aeronautics&AstronauticsNanjing 211106China Key Laboratory of the MIIT Advanced Aircraft Navigation Control and Health ManagementNanjing 211106China Jiangsu University Collaborative Innovation Center for Satellite Communication and Navigation Nanjing 211106China

The Unmanned Aerial Helicopter(UAH)has attracted increasing attention in the military and civil areas with the unique flight *** significant impact on the attitude measurement performance of UAHs by the strong airflow disturbance is an essential factor threatening flight *** improve the attitude measurement performance of UAHs under atmospheric disturbance,an attitude fusion method over the factor graph is applied and provides the plug-and-play *** on the relationship between position,velocity and attitude,a new attitude correction algorithm for the Modified Attitude factor graph Fusion(MAFGF)navigation method is designed and constructed through the fused position and velocity ***,results of simulation and experiment are given to show the effectiveness of the proposed method.

关键词： Attitude correction factor graph Integrated navigation Strong airflow environment Unmanned aerial helicopter

Personnel Localization Method in Transformer Substation Based on factor graph

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Journal of Computer and Communications 2023年第8期11卷 96-106页

作者： Haifei Yang Yuntao Zhou Huaijun Li Baojun Wu Fuchao Liu Status Grid Shanxi Yangquan Power Supply Company Yangquan China School of Automation Beijing Information Science & Technology University Beijing China

A SINS/GNSS location method based on factor diagram is proposed to meet the requirement of accurate location of substation construction personnel. In this paper, the inertial autonomous positioning, carrier motion information acquisition and satellite positioning technologies are integrated. The factor graph method is adopted to abstract the measurement information received by inertial navigation and satellite into factor nodes, and the state information into variable nodes, so as to construct the SINS/GNSS construction personnel positioning fusion factor graph model. The Gauss-Newton iterative method is used to implement the recursive updating of variable nodes, and the optimal estimate of the location information of the construction personnel is calculated, which realized the high precision location of the construction personnel. The factor graph method is verified by pedestrian navigation data. The results show that the factor graph method can continuously and stably output high-precision positioning results, and realize non-equidistant fusion of SINS and GNSS. The positioning accuracy is better than Kalman filter algorithm, and the horizontal positioning accuracy is less than 1 m. Therefore, the factor graph method proposed can provide accurate location information for substation construction personnel.

关键词： Personnel Positioning factor graph SINS/GNSS Gauss-Newton Iteration Information Fusion

Multi-Sensor Fusion Technology in Inertial Navigation System Using factor graph

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Multi-Sensor Fusion Technology in Inertial Navigation System...

factor-graph-based iterative channel estimation and signal detection algorithm over time-varying frequency-selective fading channels

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作者： Cheng Chen Xiaoli Zhang Xiafu Peng Xiaoqiang Hu School of Aerospace Engineering Xiamen University

This paper presents a novel algorithm that is able to satisfy the demands of multi-sensor fusion. It uses a probabilistic model based on factor graph, which provides a better understanding of navigation solution on non-linear optimization. This architecture which achieves plug-and-play can receive multi-rate, asynchronous measurements. The incoming measurements from various sensors are added to the factor graph as nodes and form an entire graph structure. We design a total-state estimator including velocity and poses of the vehicle. To reduce the angular error because of gyroscope drift, a novel quaternion-based on attitude estimator with magnetic, angular rate and gravity（MARG） sensor arrays are used to ensure the accuracy of attitude heading reference system（AHRS）. The attitude estimator provides a better reference value for the inertial navigation system in time. The simulation results show that the approach not only provides a solution of high accuracy and reliability, but also meets the need of various condition using the multi-sensor fusion.

关键词： Multi-sensor fusion factor graph asynchronous navigation plug-and-play

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Journal of Beijing Institute of Technology 2015年第4期24卷 494-500页

作者：赵宏杰武楠王华李智信匡镜明 School of Information and Electronics Beijing Institute of Technology

The problem of soft-input so,output （ SISO ） detection for time-varying frequency-selec- tive fading channels is considered. Based on a suitably-designed factor graph and the sum-product al- gorithm, a low-complexity iterative message passing scheme is proposed for joint channel estima- tion, equalization and decoding. Two kinds of schedules （parallel and serial） are adopted in message updates to produce two algorithms with different latency. The computational complexity per iteration of the proposed algorithms grows only linearly with the channel length, which is a significantly de- crease compared to the optimal maximum a posteriori （MAP） detection with the exponential com- plexity. Computer simulations demonstrate the effectiveness of the proposed schemes in terms of bit error rate performance.

关键词： factor graph message passing frequency-selective fading channel soft-input soft-out-put (SISO) detection turbo equalization

Low-complexity factor-graph-based MAP detector for filter bank multicarrier systems

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Journal of Communications and Information Networks 2016年第3期1卷 10-22页

作者： CUI Fangyu ZHAO Minjian CAI Yunlong CHAMPAGNE Benoit College of Information Science and Electronic Engineering Zhejiang UniversityHangzhou 310027China Department of Electrical and Computer Engineering McGill UniversityMontreal H3A0E9Canada

FBMC(Filter Bank Multicarrier)modulation is considered one of the waveform candidates in fifth generation wireless communication technology because of its several improved features compared to conventional orthogonal frequency division multiplexing schemes.A soft-input-soft-output factor-graph-based maximum-a-posterior detector is applied to FBMC *** detector achieves better performance than simple linear equalizers such as minimum mean square error and zero forcing in coded systems while exhibiting only a linear growth in complexity with the number of simultaneous interfering ***,the proposed detector can be easily extended to cases where FBMC modulation is combined with multiple-input-multiple-output *** complexity of the detector is analyzed and the simulation results demonstrated its superior performance.

关键词： FBMC MIMO factor graph turbo detection MAP

Achieving Differential Privacy of Genomic Data Releasing via Belief Propagation

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Tsinghua Science and Technology 2018年第4期23卷 389-395页

作者： Zaobo He Yingshu Li Ji Li Kaiyang Li Qing Cai Yi Liang Department of Computer Science Georgia State University Atlanta GA 30303 USA School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu 611731 China

Privacy preserving data releasing is an important problem for reconciling data openness with individual privacy. The state-of-the-art approach for privacy preserving data release is differential privacy, which offers powerful privacy guarantee without confining assumptions about the background knowledge about attackers. For genomic data with huge-dimensional attributes, however, current approaches based on differential privacy are not effective to handle. Specifically, amount of noise is required to be injected to genomic data with tens of million of SNPs （Single Nucleotide Polymorphisms）, which would significantly degrade the utility of released data. To address this problem, this paper proposes a differential privacy guaranteed genomic data releasing method. Through executing belief propagation on factor graph, our method can factorize the distribution of sensitive genomic data into a set of local distributions. After injecting differential-privacy noise to these local distributions, synthetic sensitive data can be obtained by sampling on noise distribution. Synthetic sensitive data and factor graph can be further used to construct approximate distribution of non-sensitive data. Finally, non-sensitive genomic data is sampled from the approximate distribution to construct a synthetic genomic dataset.

关键词： differential privacy SNP/trait associations belief propagation factor graph data releasing