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第43届中国控制会议

作者： Wenyi Xia Jun Yang Zhongyu Li Ziwen Wei School of Information Science and Engineering Wuhan University of Science and Technology

Due to the limited application of Global Positioning System(GPS) in many inaccessible areas,pedestrian dead reckoning(PDR) has become a hot research topic in the field of indoor *** at the problems of PDR algorithms,such as the accumulation of errors due to the interference of sensors in complex electromagnetic environments,this paper proposes an optimization algorithm for pedestrian dead reckoning based on Kalman *** algorithm first adopts the peak detection based on adaptive window to eliminate the interference of pseudo-peaks and pseudo-valleys,which can accurately find the number of pedestrian *** the step length model,which is a fusion of a linear model and a nonlinear model,is used to estimate the characteristic step length of ***,the magnetometer data and gyroscope data are fused by Kalman filter algorithm to reduce the heading estimation *** experimental results show that the PDR optimization algorithm proposed in this paper can effectively reduce the PDR cumulative error and improve the pedestrian positioning accuracy.

关键词： Kalman filter pedestrian dead reckoning Peak detection Step length estimation

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Dynamic Compensation for Environmental Magnetic Interference in pedestrian dead reckoning Using MEMS Sensors

Dynamic Compensation for Environmental Magnetic Interference...

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第40届中国控制会议

作者： Genlei Wang Senlin Zhang Meiqin Liu State Key Laboratory of Industrial Control Technology Zhejiang University College of Electrical Engineering Zhejiang University

When pedestrian positioning based on the global navigation satellite system is limited,inertial navigation based on the pedestrian dead reckoning（PDR） system using microelectromechanical system（MEMS） magnetic,angular rate,and gravity sensors is ***,the magnetometer in MEMS is sensitive to the environmental magnetic interference,which significantly affects the positioning accuracy of *** paper proposes a method for PDR based on zero-velocity-update（ZUPT） algorithm and extended Kalman filter（EKF） using MEMS sensors,which includes environmental magnetic interference detection and dynamic *** the zero-velocity interval of the ZUPT algorithm,mean filter and threshold decision are used to discriminate interference and estimate the parameters of magnetic interference based on the recursive least square *** the compensated magnetic field is used to calibrate the attitude and reduce the position error of the EKF-ZUPTbased PDR ***,the results of simulation and experiment indicate that the proposed method can effectively improve the anti-magnetic interference ability of PDR.

关键词： pedestrian dead reckoning magnetic interference dynamic compensation zero-velocity-update extended Kalman filter

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Strong Tracking Particle Filter Based on the Chi-Square Test for Indoor Positioning

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Computer Modeling in Engineering & Sciences 2023年第8期136卷 1441-1455页

作者： Lingwu Qian Jianxiang Li Qi Tang Mengfei Liu Bingjie Yuan Guoli Ji Department of Automation Xiamen UniversityXiamen361102China Xiamen Tobacco Industry Co. Ltd.Xiamen361022China

In recent years,a number of wireless indoor positioning(WIP),such as Bluetooth,Wi-Fi,and Ultra-Wideband(UWB)technologies,are ***,the indoor environment is complex and ***,pillars,and even pedestrians may block wireless signals and produce non-line-of-sight(NLOS)deviations,resulting in decreased positioning accuracy and the inability to provide people with real-time continuous indoor *** work proposed a strong tracking particle filter based on the chi-square test(SPFC)for indoor *** can fuse indoor wireless signals and the information of the inertial sensing unit(IMU)in the smartphone and detect the NLOS deviation through the chi-square test to avoid the influence of the NLOS deviation on the final positioning *** experiment results show that the proposed SPFC can reduce the positioning error by 15.1%and 12.3% compared with existing fusion positioning systems in the LOS and NLOS environment.

关键词： NLOS strong tracking filter particle filter CST pedestrian dead reckoning indoor positioning

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An Indoor Localization Approach Based on Fingerprint and Time-Difference of Arrival Fusion

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Journal of Beijing Institute of Technology 2022年第6期31卷 570-583页

作者： Haoyu Yang Yuanshuo Wang Dongchen Li Tiancheng Li the Key Laboratory of Information Fusion Technology(Ministry of Education) School of AutomationNorthwest-ern Polytechnical UniversityXi’an 710072China CSSC Systems Engineering Research Institute Beijing 100094China

In this paper,an effective target locating approach based on the fingerprint fusion posi-tioning(FFP)method is proposed which integrates the time-difference of arrival(TDOA)and the received signal strength according to the statistical variance of target position in the stationary 3D *** FFP method fuses the pedestrian dead reckoning(PDR)estimation to solve the moving target localization *** also introduce auxiliary parameters to estimate the target motion ***,we can locate the static pedestrians and track the the moving *** the case study,eight access stationary points are placed on a bookshelf and hypermarket;one target node is moving inside hypermarkets in 2D and 3D scenarios or stationary on the *** compare the performance of our proposed method with existing localization algorithms such as k-nearest neighbor,weighted k-nearest neighbor,pure TDOA and fingerprinting combining Bayesian frameworks including the extended Kalman filter,unscented Kalman filter and particle fil-ter(PF).The proposed approach outperforms obviously the counterpart methodologies in terms of the root mean square error and the cumulative distribution function of localization errors,espe-cially in the 3D *** results corroborate the effectiveness of our proposed approach.

关键词： 3D indoor localization fingerprint fusion positioning time-difference of arrival pedestrian dead reckoning received signal strength

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A UWB/IMU Complementary Indoor pedestrian Positioning Method Based on Pose Recognition

A UWB/IMU Complementary Indoor Pedestrian Positioning Method...

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第43届中国控制会议

作者： Qiang Zhang Chunjie Gu Qi Shi Xinqi Fang Department of Automation School of Electronic Information and Electrical EngineeringShanghai Jiao Tong University East China Branch of State Grid Corporation of China

Indoor positioning is critical for the safe and efficient operation of *** complexity and the high requirements for positioning accuracy of the internal environment in the substation make the choice of indoor positioning technology a significant ***-wideband(UWB) positioning is widely favored due to its high accuracy and strong resistance to interference,but it is susceptible to non-line-of-sight(NLOS) propagation of *** contrast,inertial positioning does not rely on external environmental factors and relies solely on acceleration and angular velocity data obtained by inertial sensors to calculate positioning ***,due to sensor defects,inertial positioning can lead to error accumulation and an inability to maintain long-term positioning *** address these challenges,we propose a UWB/IMU complementary indoor pedestrian positioning method based on pose *** main concept of this method is to use a combination of one primary and one secondary channel in parallel,with the advantages of each being *** UWB positioning results are determined using the weighted least squares(WLS) algorithm,while the inertial positioning results are obtained using the pedestrian dead reckoning(PDR) *** combination of UWB and IMU positioning results through complementary methods leverages the strengths of both technologies to mitigate their individual weaknesses,resulting in a better positioning effect than a single positioning *** effectiveness of the proposed algorithm is verified through experimental results conducted in an actual scene.

关键词： UWB Positioning IMU Positioning pedestrian dead reckoning Pose Recognition Data Fusion

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Smartphone heading correction method based on LSTM Neural Network

Smartphone heading correction method based on LSTM Neural Ne...

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第十三届中国卫星导航年会

作者： Yan Huang Qinghua Zeng Qiyao Lei Zhijun Chen Kecheng Sun College of Automation Engineering Nanjing University of Aeronautics ＆ Astronautics

The error of heading estimation is the main factor that affects the accuracy of the navigation and positioning of the smartphone based on the pedestrian dead reckoning. In this paper, aiming at the heading error caused by gyroscope drift in smartphone pedestrian heading estimation, a smartphone heading error compensation model based on Long Short-Term Memory network（LSTM） is proposed. Due to the low precision of inertial devices in smartphones, the direct integration will lead to cumulative errors that the neural network can correct. Considering that the calculation method of inertial navigation is dead reckoning, the data time of the preceding and following moments is related. And LSTM performs better in the long sequence than the ordinary neural network, so this paper uses a dynamic capture system to get high-precision attitude information. The LSTM actual value of the neural network training establishes the direction error correction model of smartphones. By comparing the proposed algorithm with traditional quaternion heading estimation methods, the error correction model presented in this paper can effectively suppress the influence of gyroscope drift. The result is better,which can meet the basic needs of pedestrian navigation and positioning.

关键词： pedestrian dead reckoning Heading correction Smartphone Netural network

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