Hybrid pedestrian positioning system using wearable inertial sensors and ultrasonic ranging

Pedestrian positioning system(PPS)using wearable inertial sensors has wide applications towards various emerging fields such as smart healthcare,emergency rescue,soldier positioning,etc.The performance of traditional PPS is limited by the cumulative error of inertial sensors,complex motion modes of pedestrians,and the low robustness of the multi-sensor collaboration structure.This paper presents a hybrid pedestrian positioning system using the combination of wearable inertial sensors and ultrasonic ranging(H-PPS).A robust two nodes integration structure is developed to adaptively combine the motion data acquired from the single waist-mounted and foot-mounted node,and enhanced by a novel ellipsoid constraint model.In addition,a deep-learning-based walking speed estimator is proposed by considering all the motion features provided by different nodes,which effectively reduces the cumulative error originating from inertial sensors.Finally,a comprehensive data and model dual-driven model is presented to effectively combine the motion data provided by different sensor nodes and walking speed estimator,and multi-level constraints are extracted to further improve the performance of the overall system.Experimental results indicate that the proposed H-PPS significantly improves the performance of the single PPS and outperforms existing algorithms in accuracy index under complex indoor scenarios.

Positioning-control Based on Trapezoidal Velocity Curve for High-precision Basis Weight Control Valve

Traditionally, basis weight control valve is driven by a constant frequency pulse signal. Therefore, it is difficult for the valve to match the control precision of basis weight. Dynamic simulation research using Matlab/Simulink indicates that there is much more overshoot and fluctuating during the valve-positioning process. In order to improve the valve-positioning precision, the control method of trapezoidal velocity curve was studied. The simulation result showed that the positioning steady-state error was less than 0.0056%, whereas the peak error was less than 0.016% by using trapezoidal velocity curve at 10 positioning steps. A valve-positioning precision experimental device for the stepper motor of basis weight control valve was developed. The experiment results showed that the error ratio of 1/10000 positioning steps was 4% by using trapezoidal velocity curve. Furthermore, the error ratio of 10/10000 positioning steps was 0.5%. It proved that the valve-positioning precision of trapezoidal velocity curve was much higher than that of the constant frequency pulse signal control strategy. The new control method of trapezoidal velocity curve can satisfy the precision requirement of 10000 steps.

The Quality Assessment of Non-Integer-Hour Data in GPS Broadcast Ephemerides and Its Impact on the Accuracy of Real- Time Kinematic Positioning Over the South China Sea

Abnormal effects in GPS broadcast ephemerides can have a significant effect on real-time navigation and positioning solutions that use the orbit and clock error data provided by GPS broadcast ephemerides.This paper describes three types of non-integerhour navigation data in GPS broadcast ephemeris data.Compared with GPST integer hour data,we find that there are two types of data blocks for non-integer-hour navigation containing gross errors with different levels of precision,which is reflected in the user range accuracy(URA)of the broadcast ephemeris.These gross errors can cause large deviations when using the GPS broadcast ephemeris for orbit calculation and lead to a decrease in the kinematic positioning accuracy.An improved weighting method which is based on the consistency relationship between the URA value and the orbital precision is proposed to improve the positioning accuracy by controlling the effect of gross errors in the broadcast ephemerides.The correction algorithm proposed in this paper was applied to real-time kinematic positioning with shipborne GPS data over the South China Sea.The results showed that the proposed positioning algorithm can effectively reduce the effects of gross errors in the broadcast ephemeris,and significantly improve the accuracy of the navigation and positioning.

An ERA5 tropospheric parameters-augmented approach for improving GNSS precise point positioning

Precise Point Positioning(PPP) technology has developed into a potent instrument for geodetic positioning, ionospheric modeling, tropospheric atmospheric parameter detection, and seismic monitoring.As atmospheric reanalysis data products’ accuracy and spatiotemporal resolution have improved recently, it has become important to apply these products to obtain high-accuracy tropospheric delay parameters, like zenith tropospheric delay(ZTD) and tropospheric horizontal gradient. These tropospheric delay parameters can be applied to PPP to reduce the convergence time and to increase the accuracy in the vertical direction of the position. The European Centre for Medium-Range Weather Forecasts Reanalysis 5(ERA5) atmospheric reanalysis data is the latest product with a high spatiotemporal resolution released by the European Center for Medium-Range Weather Forecasts(ECMWF). Only a few researches have evaluated the application of ERA5 data to Global Navigation Satellite System(GNSS)PPP. Therefore, this study compared and validated the ZTD products derived from ERA5 data using ZTD values provided by 290 global International GNSS Service(IGS) stations for 2016-2017. The results indicated a stable performance for ZTD, with annual average bias and RMS values of 0.23 cm and 1.09 cm,respectively. Further, GNSS observations for one week in each of the four seasons(spring: DOY 92-98;summer: DOY 199-205;autumn: DOY 275-281;and winter: DOY 22-28) from 34 multi-GNSS experiments(MGEX) stations distributed globally in 2016 were considered to evaluate the performance of ERA5-derived tropospheric delay products in GNSS PPP. The performance of ERA5-enhanced PPP was compared with that of the two standard GNSS PPP schemes(without estimated tropospheric horizontal gradient and with estimated tropospheric horizontal gradient). The results demonstrated that ERA5-enhanced GNSS PPP showed no significant improvement in the convergence times in both the Eastern(E) and Northern(N) directions, while the average convergence time over four weeks in the vertical(U)direction improved by 53.3% and 52.7%, respectively(in the case of pngm station). The average convergence times for each week in the U direction of the northern and southern hemisphere stations indicated a decrease of 16.3%, 12.6%, 9.6%, and 9.1%, and 16.9%, 9.6%, 8.9%, and 14.5%, respectively.Regarding positioning accuracy, ERA5-enhanced PPP showed an improvement of 13.3% and 16.2% over the two standard PPP schemes in the U direction, respectively. No significant improvement in the positioning performance was observed in both the E and N directions. Thus, this study demonstrated the potential application of the ERA5 tropospheric parameters-augmented approach to Beidou navigation and positioning.

Application of Lightning Monitoring and Positioning Data in Investigation and Identification of Lightning Disaster in Inner Mongolia

The lightning current magnitude and other characteristics are important basic data of the lightning disaster investigation and identification. The characteristics of lightning monitoring and positioning system in Inner Mongolia were introduced and studied in the lightning accident analysis based on the lightning monitoring and positioning data of the lightning stroke accidents. The positioning error of lightning monitoring and positioning system was analyzed. The results showed that lightning current intensity and the position precision were very important data in the lightning disaster investigation. Finally, a variety of meteorological data should be applied in the lightning disaster investigation and identification.

Multi-channel & high-precision data acquisition devi ce for aerospace

This paper describes the detailed desi gn of data acquisition device with multi-channel and high-precision for aerosp ace.Based on detailed analysis of the advantages and disadvantages of tw o common acquisition circuits,the design factors of acquisition device focus o n accuracy,sampling rate,hardware overhead and design space.The me chanical structure of the system is divided into different card layers according to different functions and the structure has the characteristics of high reliability,conveni ence to install and scalability.To ens ure reliable operation mode,the interface uses the optocoupler isolated from th e e xternal circuit.The transmission of signal is decided by the current in the cur rent loop that consists of optocouplers between acquisition device and t est bench.In multi-channel switching circuit,by establ ishing analog multiplexer model,the selection principles of circuit modes are given.

Data Logic Structure and Key Technologies on Intelligent High-precision Map

Taking autonomous driving and driverless as the research object,we discuss and define intelligent high-precision map.Intelligent high-precision map is considered as a key link of future travel,a carrier of real-time perception of traffic resources in the entire space-time range,and the criterion for the operation and control of the whole process of the vehicle.As a new form of map,it has distinctive features in terms of cartography theory and application requirements compared with traditional navigation electronic maps.Thus,it is necessary to analyze and discuss its key features and problems to promote the development of research and application of intelligent high-precision map.Accordingly,we propose an information transmission model based on the cartography theory and combine the wheeled robot’s control flow in practical application.Next,we put forward the data logic structure of intelligent high-precision map,and analyze its application in autonomous driving.Then,we summarize the computing mode of“Crowdsourcing+Edge-Cloud Collaborative Computing”,and carry out key technical analysis on how to improve the quality of crowdsourced data.We also analyze the effective application scenarios of intelligent high-precision map in the future.Finally,we present some thoughts and suggestions for the future development of this field.

Wi-Fi Positioning Dataset with Multiusers and Multidevices Considering Spatio-Temporal Variations

Precise information on indoor positioning provides a foundation for position-related customer services.Despite the emergence of several indoor positioning technologies such as ultrawideband,infrared,radio frequency identification,Bluetooth beacons,pedestrian dead reckoning,and magnetic field,Wi-Fi is one of the most widely used technologies.Predominantly,Wi-Fi fingerprinting is the most popular method and has been researched over the past two decades.Wi-Fi positioning faces three core problems:device heterogeneity,robustness to signal changes caused by human mobility,and device attitude,i.e.,varying orientations.The existing methods do not cover these aspects owing to the unavailability of publicly available datasets.This study introduces a dataset that includes the Wi-Fi received signal strength(RSS)gathered using four different devices,namely Samsung Galaxy S8,S9,A8,LG G6,and LG G7,operated by three surveyors,including a female and two males.In addition,three orientations of the smartphones are used for the data collection and include multiple buildings with a multifloor environment.Various levels of human mobility have been considered in dynamic environments.To analyze the time-related impact on Wi-Fi RSS,data over 3 years have been considered.

Fingerprint Database Updating Using Crowdsourcing in Indoor Bluetooth Positioning System

Fingerprint⁃based Bluetooth positioning is a popular indoor positioning technology.However,the change of indoor environment and Bluetooth anchor locations has significant impact on signal distribution,which will result in the decline of positioning accuracy.The widespread extension of Bluetooth positioning is limited by the need of manual effort to collect the fingerprints with position labels for fingerprint database construction and updating.To address this problem,this paper presents an adaptive fingerprint database updating approach.First,the crowdsourced data including the Bluetooth Received Signal Strength(RSS)sequences and the speed and heading of the pedestrian were recorded.Second,the recorded crowdsourced data were fused by the Kalman Filtering(KF),and then fed into the trajectory validity analysis model with the purpose of assigning the unlabeled RSS data with position labels to generate candidate fingerprints.Third,after enough candidate fingerprints were obtained at each Reference Point(RP),the Density⁃based Spatial Clustering of Applications with Noise(DBSCAN)approach was conducted on both the original and the candidate fingerprints to filter out the fingerprints which had been identified as the noise,and then the mean of fingerprints in the cluster with the largest data volume was selected as the updated fingerprint of the corresponding RP.Finally,the extensive experimental results show that with the increase of the number of candidate fingerprints and update iterations,the fingerprint⁃based Bluetooth positioning accuracy can be effectively improved.

基于改进ISODATA聚类的Wi-Fi室内定位算法

为解决传统聚类算法在Wi-Fi室内定位中易陷入局部最优影响定位精度的问题,提出一种改进迭代自组织数据分析聚类Wi-Fi室内定位算法。离线阶段通过计算指纹数据库中各点欧氏距离标准差,优化初始参数阈值,动态选择聚类中心,减少定位误差;在线阶段将自适应加权K近邻与聚类算法结合,避免固定K值对定位结果影响,有效提高定位精度;将改进算法用于工程实例进行验证。结果表明,提出的算法在定位精度1 m范围内时概率为63.33%,定位精度2 m范围内时概率为90.00%,验证了该算法的有效性。

Underwater Terrain Positioning Method Based on Least Squares Estimation for AUV

To achieve accurate positioning of autonomous underwater vehicles, an appropriate underwater terrain database storage format for underwater terrain-matching positioning is established using multi-beam data as underwater terrainmatching data. An underwater terrain interpolation error compensation method based on fractional Brownian motion is proposed for defects of normal terrain interpolation, and an underwater terrain-matching positioning method based on least squares estimation（LSE） is proposed for correlation analysis of topographic features. The Fisher method is introduced as a secondary criterion for pseudo localization appearing in a topographic features flat area, effectively reducing the impact of pseudo positioning points on matching accuracy and improving the positioning accuracy of terrain flat areas. Simulation experiments based on electronic chart and multi-beam sea trial data show that drift errors of an inertial navigation system can be corrected effectively using the proposed method. The positioning accuracy and practicality are high, satisfying the requirement of underwater accurate positioning.

Effects of Uncertainties in the Position and Orientation of Both the Transmitter and Receivers on Marine Controlled-Source Electromagnetic Data

Simulation and interpretation of marine controlled-source electromagnetic(CSEM) data often approximate the transmitter source as an ideal horizontal electric dipole(HED) and assume that the receivers are located on a flat seabed.Actually,however,the transmitter dipole source will be rotated,tilted and deviated from the survey profile due to ocean currents.And free-fall receivers may be also rotated to some arbitrary horizontal orientation and located on sloping seafloor.In this paper,we investigate the effects of uncertainties in the transmitter tilt,transmitter rotation and transmitter deviation from the survey profile as well as in the receiver's location and orientation on marine CSEM data.The model study shows that the uncertainties of all position and orientation parameters of both the transmitter and receivers can propagate into observed data uncertainties,but to a different extent.In interpreting marine data,field data uncertainties caused by the position and orientation uncertainties of both the transmitter and receivers need to be taken into account.

BP-LMS-based BDS-3 power system positioning method

The BeiDou-3 navigation satellite system(BDS-3)provides a full-domain high-precision positioning service for the power system to ensure safe and stable operation.However,BDS-3 power system positioning faces certain challenges,such as complex electromagnetic interference and incomplete error elimination.Herein,a back propagation neural network-improved least mean square(BP-LMS)adaptive filtering method is proposed for the BDS-3 full-domain and high-precision power system positioning,which utilizes the loss function to update the weight of the BP hidden layer,computes the pseudo compensation range,and eliminates the impact of electromagnetic interference to enhance the accuracy of power system positioning.Simulation results confirm the superior performance of BP-LMS in positioning accuracy and error elimination.Compared with LMS and normalized least mean square(NLMS),the filtering error of the proposed BP-LMS adaptive filtering method is decreased by 57.14%and 51.38%,respectively.

Understanding occupancy pattern and improving building energy efficiency through Wi-Fi based indoor positioning

Detailed visualisation and data analysis of occupancy patterns including spatial distribution and temporal variations are of great importance to delivering energy efficient and productive buildings. An experimental study comprising 24-h monitoring over 30 full days was conducted in a university library building.Occupancy profiles have been monitored and analysis has been carried out. Central to this monitoring study is the Wi-Fi based indoor positioning system based on the measured Wi-Fi devices' number and locations and data mining methods. Distinct from traditional occupancy and energy studies,more detailed informationrelated to the indoor positions and number of occupants has offered a better understanding of building user behaviour. The implication of the occupancy patterns for energy( e. g. lighting and other building services) efficiency is assessed,assisted with data from lighting sensors where needed. It is found occupancy patterns change dramatically with time. Also,the energy waste patterns have been identified through the method of data association rule mining. If the identified energy waste is removed,the total energy consumption can be reduced by 26. 1%. The indoor positioning information also has implications for optimizing space use,opening hours as well as staff deployment. The work could be extended to more rooms with diverse functions,other seasons and other types of non-domestic buildings for a more comprehensive understanding of building user behaviour and energy efficiency.

Cross-ocean GPS long distance rapid static positioning methods

The method of cross-ocean GPS long distance rapid static positioning has become one of the main technical means of GPS static positioning away from the mainland. The key technology had been analyzed in-cluding data preprocessing and quality control, long distance integer ambiguity resolution and static Kalman filter parameter estimation. Effective data processing method of cross-ocean GPS long baseline rapid static positioning had been proposed. Through the analysis of practical examples of coastal and ocean, the feasibility of cross-ocean GPS long distance rapid static positioning based on the method is testified and verified. The results show that the accuracy of one-hour single baseline static positioning for the 500 - 600 km distance can be better than 10cm in the three-dimensional coordinates ocean environment. , which can suffice static positioning accuracy in the special

China's Trade Data Shows Positive Signs

China＇s foreign trade operation situation According to the statistics collected by Customs, in January-October 2017, China＇s total import and export value reached RMB 22.52 trillion, with an increase of 15.9% year on year.

Modeling and Prediction of Inter-System Bias for GPS/BDS-2/BDS-3 Combined Precision Point Positioning

The combination of Precision Point Positioning(PPP)with Multi-Global Navigation Satellite System(MultiGNSS),called MGPPP,can improve the positioning precision and shorten the convergence time more effectively than the combination of PPP with only the BeiDou Navigation Satellite System(BDS).However,the Inter-System Bias(ISB)measurement of Multi-GNSS,including the time system offset,the coordinate system difference,and the inter-system hardware delay bias,must be considered for Multi-GNSS data fusion processing.The detected ISB can be well modeled and predicted by using a quadratic model(QM),an autoregressive integrated moving average model(ARIMA),as well as the sliding window strategy(SW).In this study,the experimental results indicate that there is no apparent difference in the ISB between BDS-2 and BDS-3 observations if B1I/B3I signals are used.However,an obvious difference in ISB can be found between BDS-2 and BDS-3 observations if B1I/B3I and B1C/B2a signals are used.Meanwhile,the precision of the Predicted ISB(PISB)on the next day of all stations is about 0.1−0.6 ns.Besides,to effectively utilize the PISB,a new strategy for predicting the PISB for MGPPP is proposed.In the proposed strategy,the PISB is used by adding two virtual observation equations,and an adaptive factor is adopted to balance the contribution of the Observed ISB(OISB)and the PISB to the final estimations of ISB.To validate the effectiveness of the proposed method,some experimental schemes are designed and tested under different satellite availability conditions.The results indicate that in open sky environment,the selective utilization of the PISB achieves almost the same positioning precision of MGPPP as the direct utilization of the PISB,but the convergence time of MGPPP is reduced by 7.1%at most in the north(N),east(E),and up(U)components.In the blocked sky environment,the selective utilization of the PISB contributes to more significant improvement of the positioning precision and convergence time than that in the open sky environment.Compared with the direct utilization of the PISB,the selective utilization of the PISB improves the positioning precision and convergence time by 6.7%and 12.7%at most in the N,E,and U components,respectively.

Backward Support Computation Method for Positive and Negative Frequent Itemset Mining

Association rules mining is a major data mining field that leads to discovery of associations and correlations among items in today’s big data environment. The conventional association rule mining focuses mainly on positive itemsets generated from frequently occurring itemsets (PFIS). However, there has been a significant study focused on infrequent itemsets with utilization of negative association rules to mine interesting frequent itemsets (NFIS) from transactions. In this work, we propose an efficient backward calculating negative frequent itemset algorithm namely EBC-NFIS for computing backward supports that can extract both positive and negative frequent itemsets synchronously from dataset. EBC-NFIS algorithm is based on popular e-NFIS algorithm that computes supports of negative itemsets from the supports of positive itemsets. The proposed algorithm makes use of previously computed supports from memory to minimize the computation time. In addition, association rules, i.e. positive and negative association rules (PNARs) are generated from discovered frequent itemsets using EBC-NFIS algorithm. The efficiency of the proposed algorithm is verified by several experiments and comparing results with e-NFIS algorithm. The experimental results confirm that the proposed algorithm successfully discovers NFIS and PNARs and runs significantly faster than conventional e-NFIS algorithm.

Status of UnDifferenced and Uncombined GNSS Data Processing Activities in China

With the continued development of multiple Global Navigation Satellite Systems(GNSS)and the emergence of various frequencies,UnDifferenced and UnCombined(UDUC)data processing has become an increasingly attractive option.In this contribution,we provide an overview of the current status of UDUC GNSS data processing activities in China.These activities encompass the formulation of Precise Point Positioning(PPP)models and PPP-Real-Time Kinematic(PPP-RTK)models for processing single-station and multi-station GNSS data,respectively.Regarding single-station data processing,we discuss the advancements in PPP models,particularly the extension from a single system to multiple systems,and from dual frequencies to single and multiple frequencies.Additionally,we introduce the modified PPP model,which accounts for the time variation of receiver code biases,a departure from the conventional PPP model that typically assumes these biases to be time-constant.In the realm of multi-station PPP-RTK data processing,we introduce the ionosphere-weighted PPP-RTK model,which enhances the model strength by considering the spatial correlation of ionospheric delays.We also review the phase-only PPP-RTK model,designed to mitigate the impact of unmodelled code-related errors.Furthermore,we explore GLONASS PPP-RTK,achieved through the application of the integer-estimable model.For large-scale network data processing,we introduce the all-in-view PPP-RTK model,which alleviates the strict common-view requirement at all receivers.Moreover,we present the decentralized PPP-RTK data processing strategy,designed to improve computational efficiency.Overall,this work highlights the various advancements in UDUC GNSS data processing,providing insights into the state-of-the-art techniques employed in China to achieve precise GNSS applications.

数据产权刑法保护模式的构建

数据产权是一种具有财产权属性的新型权利,该权利与虚拟财产权和知识产权具有明显差异。数据产权属于刑法保护的公法益范畴,其应归属于市场经济秩序法益之中。现行刑法有关财产犯罪、知识产权犯罪和数据犯罪的规定均无法实现对数据产权的全面保护。刑法对数据产权的保护应以促进数据流通为主要目标,且应当覆盖数据处理的各流程阶段。对侵犯数据产权行为进行刑法规制时,应对“未经同意”获取数据行为审慎入罪。应增设妨害数据流通管理秩序罪,对“情节严重的”妨害数据流通管理秩序行为予以刑法规制。