BeiDou-3 Global Positioning System Officially Initiates Construction

China’s Bei Dou-3 global positioning system has been officially initiated construction with four global networking satel ites to be launched by the end of this year,according to the announcement at the Sixth China Annual Meeting of Satellite Navigation and Location Services in Shenzhen on September 16 and the First Satellite Application International Exposition held.

Relativistic Effects in the Global Positioning System

The Global Positioning System (GPS) uses accurate atomic clocks in satellites and on the ground to provide world-wide position and time determination. These clocks have gravitational and motional frequency shifts which are so large that, without properly accounting for relativistic effects, the system would not work. As a practical matter, therefore, many individuals who use the GPS need to understand how relativistic effects accounted for in the system. This paper discusses relativistic effects arising from both special relativity and general relativity, and how these effects are incorporated in GPS operations. Two introductory sections on kinematics in special and general relativity, respectively, are followed by a section which describes how relativistic effects should be accounted for. The concept of synchroization in the Earth-Centered Inertial frame is discussed in detail. Numerical and experimental examples are given, showing the sizes of the various effects. The treatment of special and general relativity is sufficiently complete that a person should be able to follow the development without much reference to external material, except that a few standard results have been quoted from textbooks without derivation.

Modeling of Selective Availability for Global Positioning System

To degrade location accuracy for unauthorized GPS users, US government applied Selective Availability (SA) to Global Positioning System (GPS). In this paper we discuss an anti-SAapproach to improve location accuracy which is very important in landing position, and then we derived the SA error by eliminating almost all other errors including ionospheric and tropospheric timedelays and clock errors both in satellites and in receiver, etc. By means of the system identificationtheory, an SA errorl all SA error model with the second-order Gauss-Maukov stochastic process wasderived and simulated. With the selected parameters of the stochastic process) the simulation resultsshow that there is the excellent agreement between the simulated SA error model and that of reallyapplied in GPS system.

Vehicle Ego-Localization Based on Streetscape Image Database Under Blind Area of Global Positioning System

Vehicle positioning is critical for inter-vehicle communication, navigation, vehicle monitoring and tracking. They are regarded as the core technology ensuring safety in everyday-driving. This paper proposes an enhanced vehicle ego-localization method based on streetscape image database. It is most useful in the global positioning system(GPS) blind area. Firstly, a database is built by collecting streetscape images, extracting dominant color feature and detecting speeded up robust feature(SURF) points. Secondly, an image that the vehicle shoots at one point is analyzed to find a matching image in the database by dynamic programming(DP)matching. According to the image similarity, several images with higher probabilities are selected to realize coarse positioning. Finally, different weights are set to the coordinates of the shooting location with the maximum similarity and its 8 neighborhoods according to the number of matching points, and then interpolating calculation is applied to complete accurate positioning. Experimental results show that the accuracy of this study is less than 1.5 m and its running time is about 3.6 s. These are basically in line with the practical need. The described system has an advantage of low cost, high reliability and strong resistance to signal interference, so it has a better practical value as compared with visual odometry(VO) and radio frequency identification(RFID) based approach for vehicle positioning in the case of GPS not working.

Locating Global System for Mobile Communication(GSM)Base Stations Using Geographic Information System(GIS)

The global system for mobile communication(GSM)is planned to meet the needs of the whole subscribers.The number of subscribers increased as the population increased due to the acceptance of GSM services by the subscribers.Thus,there should be a way to monitor base stations that will meet the increasing demand of subscribers in any area as a population surge will lead to more subscriptions.This will allow GSM network operators to serve their subscribers better and ease network congestion.This work presents a review of mobile evolution from the first generation to the fifth generation.A review of global positioning system(GPS)technology and its applications to geographic information systems(GIS)was done.The coordinates of these base stations were taken using a GPS device.These base station coordinates were then exported to QGIS for the design of the map.Thereafter,the output map was then integrated into the website.The discussions on the results followed and some useful suggestions given will go a long way to help the operators of GSM in Nigeria and in general.If the propositions given are adhered to,it will go a long way to help the operators reduce congestion on their network and thereby increase the satisfaction of the subscribers.

Applying Global Positioning System Real-Time Kinematic Technology to Collection and Analysis of Rowing Information

To obtain higher accuracy of information concerning boat motion, the use of global positioning system (GPS) real-time kinematic (RTK) technology was investigated. Through RTK technology, a measurement precision of the ±1 cm range can be achieved. The research equipment included a GPS receiver and a personal digital assistant as a data control and processing unit. Real-time GPS data was captured and processed to acquire various parameters, including the boat track, velocity curve, stroke rate, and stroke distance. Using this data, the quantitative information related to rowing training can be achieved. The results are helpful for analyzing the biomechanical parameters of rowing techniques and for evaluating training efficiency.

Absolute and relative sea-level rise in the New York City area by measurements from tide gauges and satellite global positioning system

The absolute and relative rates of rise of the sea level are computed for the New York City area by coupling global positioning system records of the position of fixed domes nearby tide gauges,with the tide gauges’records.Two tide gauges are considered,one long-term trend,more reliable,The Battery,in lower Manhattan,and one shorter,less reliable,Sandy Hook,in New Jersey.The relative rates of rise of the sea level are+2.851 and+4.076 mm/yr.The subsidence rates are-2.151 and-3.076 mm/yr.The absolute rates of rise of the sea level are+0.7 and+1.0 mm/yr.The relative sea-level acceleration,reliable only in The Battery,is about+0.008 mm/yr².This acceleration is about the same as the world average long-term trend tide gauge,as well as the average long-term trend tide gauge of the East Coast of North America.The absolute rate of rise of the sea level by 2050 in the lower Manhattan area will be likely less than 30 mm,and the absolute rate of rise of the sea level by 2100 likely less than 80 mm.The relative rate of rise of the sea level by 2050 in the Manhattan area will be likely 85 mm,and the relative rate of rise of the sea level by 2100 likely 228 mm,because of the overwhelming subsidence contribution.

Remote positioning system based on GPS/GPRS

Considering the need of target positioning,a remote positioning system is designed based on global positioning system(GPS)and general packet radio service(GPRS);The data collection terminal is based on microcontroller unit(MCU)PIC24FV301.It uses GPRS network to create wireless link and transmits GPS source information which is collected by LEA-5H board to monitor center on the Internet.The monitor center obtains the target information through processing and analysis of the calculated data.Actual operation results indicate that the designed system has excellent performance and achieves the goal of the remote location.

Analysis of Geo Positioning System Using RF &DA

Indoor positioning systems (IPSs) have been intended to provide position information of persons and devices. Higher user percentage of handheld devices such as tablets or mobile phones had led to the development of a number of indoor positioning systems. In this research a work on a real time portable RFID indoor positioning device such as on smartphone will be performed. The personal networks will be designed to meet the users’ needs and interconnect users’ devices equipped with different communications technologies in various places to form one network for better result. Radio frequency identification (RFID) with directional antenna has proved its potential for locating objects in indoor environment. Hence, the proposed device idea will be used to exploit various unknown locations in an indoor environment such as college campus;this interpretation will rely on Wireless LAN, Received Signal Strength values from Access Points (AP) in specific mentioned arenas;these APs will be monitored constantly by RFID with directional antenna (DA) and handheld devices. For obtaining the better results from existing devices, algorithms of Range Estimation are proposed, which can be used on various handheld devices for locating indoor objects.

Rapid Fault Analysis by Deep Learning-Based PMU for Smart Grid System

Smart Grids(SG)is a power system development concept that has received significant attention nationally.SG signifies real-time data for specific communication requirements.The best capabilities for monitoring and controlling the grid are essential to system stability.One of the most critical needs for smart-grid execution is fast,precise,and economically synchronized measurements,which are made feasible by Phasor Measurement Units(PMU).PMUs can pro-vide synchronized measurements and measure voltages as well as current phasors dynamically.PMUs utilize GPS time-stamping at Coordinated Universal Time(UTC)to capture electric phasors with great accuracy and precision.This research tends to Deep Learning(DL)advances to design a Residual Network(ResNet)model that can accurately identify and classify defects in grid-connected systems.As part of fault detection and probe,the proposed strategy uses a ResNet-50 tech-nique to evaluate real-time measurement data from geographically scattered PMUs.As a result of its excellent signal classification efficiency and ability to extract high-quality signal features,its fault diagnosis performance is excellent.Our results demonstrate that the proposed method is effective in detecting and classifying faults at sufficient time.The proposed approaches classify the fault type with a precision of 98.5%and an accuracy of 99.1%.The long-short-term memory(LSTM),Convolutional Neural Network(CNN),and CNN-LSTM algo-rithms are applied to compare the networks.Real-world data tends to evaluate these networks.

Cycle slip detection approach based on time-relative positioning theory

An efficient cycle slip detection method is proposed for high precision positioning and navigation results with global positioning system （GPS）,which is based on the assumption of a high sampling interval, measurement errors are so small that they can be ignored in the temporal single difference observables. And ambiguities are ordinarily equal to zero,but could be the number of cycles that have ＂slipped＂ if loss-of-lock has occurred.Therefore,cycle slips are estimated as parameters of time-relative positioning observation equations.Because the temporal single difference observables are taken at different epochs and different stations with a single GPS receiver,if time-relative positioning observation equations are linearized as that of conventional relative positioning,the design matrix will be rank defective.To obtain a stable linearization scheme,time-relative positioning observation equations are further analyzed,and the concept of virtual measurement is applied.A sample of data collected on a vehicle test shows that a cycle slip detection approach based on time-relative positioning theory can detect slips at the value of one cycle.The results also indicate if two satellites are so near to each other that they have the same equivalent to satellite-receiver geometry,cycle slip detection will be difficult and may get wrong results.Cycle slips of different satellites also affect detection by satellite-receiver geometry.

Slip rate and interseismic coupling along the Moxi-Shimian segment of the Xianshuihe fault, Eastern Qinghai-Xizang Plateau

On September 5,2022,the Luding M6.8 earthquake occurred in the Moxi-Shimian segment of the Xianshuihe fault,coinciding with the historical ruptured zone of the 1786 Moxi earthquake.Its seis-mogenic environment provides a foundation for comprehending the mechanism of the earthquake and its future hazard.In the Moxi-Shimian segment,we establish a series of near-field Global Navigation Satellite Systems(GNsS)stations to enhance the spatial resolution of observational data for the inversion of the interseismic kinematic parameters.In this study,with an elastic screw dislocation model con-strained by GNsS observations,the slip rate of the Moxi-Shimian segment is estimated to be 10.9±1.0 mm/yr,while the locking depth is 15.7±6.2 km.Additionally,we utilize a block-dislocation model to invert the interseismic fault coupling along the Kangding-Moxi-Shimian segment.The result indicates a gradual deepening of the locking depth along the section from Kangding to Shimian.The coseismic rupture of the 2022 event occurred within the high coupling regions in the Kangding-Moxi-Shimian segment,which indicates that the rupture kinematics in this event might be controlled by the interseismic deformation.The seismic moment accumulated within the ruptured zone of the Luding earthquake since 1786 ranges in[1.42-3.40]×10^(19) N-m,which is significantly greater than the seismic moment released during the 2022 event.As a result,we infer that the Luding earthquake released only a portion of the accumulated energy within the original rupture zone since 1786,indicating that the 2022 event has not caused a complete rupture in the Moxi-Shimian segment.Consequently,there remains a substantial seismic hazard in this area.

IAE-adaptive Kalman filter for INS/GPS integrated navigation system

A marine INS/GPS adaptive navigation system is presented. GPS with two antenna providing vessel＇ s altitude is selected as the auxiliary system fusing with INS to improve the performance of the hybrid system. The Kalman filter is the most frequently used algorithm in the integrated navigation system, which is capable of estimating INS errors online based on the measured errors between INS and GPS. The standard Kalman filter （SKF） assumes that the statistics of the noise on each sensor are given. As long as the noise distributions do not change, the Kalman filter will give the optimal estimation. However GPS receiver will be disturbed easily and thus temporally changing measurement noise will join into the outputs of GPS, which will lead to performance degradation of the Kalman filter. Many researchers introduce fuzzy logic control method into innovation-based adaptive estimation adaptive Kalman filtering （IAE-AKF） algorithm, and accordingly propose various adaptive Kalman filters. However how to design the fuzzy logic controller is a very complicated problem still without a convincing solution. A novel IAE-AKF is proposed herein, which is based on the maximum likelihood criterion for the proper computation of the filter innovation covariance and hence of the filter gain. The approach is direct and simple without having to establish fuzzy inference rules. After having deduced the proposed IAEAKF algorithm theoretically in detail, the approach is tested by the simulation based on the system error model of the developed INS/GPS integrated marine navigation system. Simulation results show that the adaptive Kalman filter outperforms the SKF with higher accuracy, robustness and less computation. It is demonstra- ted that this proposed approach is a valid solution for the unknown changing measurement noise exited in the Kalman filter.

The measurement of time spent outdoors in child myopia research： a systematic review

The purpose of this article is to summarize the methods most commonly used to measure time spent outdoors and provide a comprehensive review of time and activity recording methods with the aim of encouraging the development of new methods. PubMed, Embase and the Cochrane Library were searched from Jan. 1st, 1990 to Aug. 31th, 2017. Studies including the following specific terms： “outdoor”, “outside”, “outdoor activity”, “outside activity”, “outdoor time”, “outside time”, and “outdoor AND measurement of time spent outdoors” were considered for this review. In total, three kinds of outdoor time measurements were discussed. Questionnaires have the longest history and are the most thoroughly revised instruments for assessing time spent outdoors, but recall bias is their most substantial drawback. Global positioning system （GPS） tracking can distinguish between indoor and outdoor locations, but its utility is limited due to several factors such as subject compatibility. Light exposure measurement devices are newly emerging, but all of these devices require good subject cooperation. Further efforts and exploration are needed to develop better methods and new tools to record exposure to the outdoors in real time. Moreover, inventing a new device by combining two or more types of devices mentioned above and using the latest technology of en ergy supplementation and autoswitching may make the best use of the advantages and bypass the disadvantages of each tool.

Study on Federated Architecture for GPS/INS/TRN Integrated Navigation System

Based on the information fusion theory, a kind of integrated navigation system integration for cruise missile is presented in this paper. Besides, the way with which the system is integrated and the related data fusion technique are discussed. Information-fusion-based hybrid navigation system integration can fully utilize information provided by all kinds of navigation sensor subsystem and can improve the precision of the system effectively. Simultaneously, the reconstructing ability ensures the system of great reliability.

Analysis of unmanned aerial vehicle navigation and height control system based on GPS

According to the characteristic of global positioning system（GPS） reflection signals,a GPS delay mapping receiver system scheme is put forward,which not only satisfies the unmanned aerial vehicle（UAV） guidance localization but also realizes height measurement.A code delay algorithm is put forward,which processes the direct and land reflected signal and outputs the navigation data and specular point.The GPS terrain reflected echo signal mathematical equation is inferred.The reflecting signal area,when the GPS signal passes the land,is analyzed.The height survey model reflected land surface characteristic is established.A simulation system which carries guidance localization of the UAV and the height measuring control through the GPS direct signal and the land reflected signal is designed,taken the GPS satellite as the illumination source,the receiver is put on the UAV.Then the UAV guidance signal,the GPS reflection signal and receiver＇s parallel processing are realized.The parallel processing reduces UAV＇s payload and raises system＇s operating efficiency.The simulation results confirms the validity of the model and also provides the basis for the UAV＇s optimization design.

A three-dimensional positioning method based on three satellites

A three-dimensional positioning method for global positioning system(GPS)receivers based on three satellites was proposed.In the method,the measurement equation used for positioning calculation was expanded by means of two measures.In this case,the measurement equation could be solved,and the function of positioning calculation could be performed.The detailed steps of the method and how to evaluate the positioning precision of the method were given,respectively.The positioning performance of the method was demonstrated through some experiments.It is shown that the method can provide the three-dimensional positioning information under the condition that there are only three useful satellites.

Driving Style Recognition System Using Smartphone Sensors Based on Fuzzy Logic

Every 24 seconds,someone dies on the road due to road accidents and it is the 8th leading cause of death and the first among children aged 15–29 years.1.35 million people globally die every year due to road traffic crashes.An additional 20–50 million suffer from non-fatal injuries,often resulting in longterm disabilities.This costs around 3%of Gross Domestic Product to most countries,and it is a considerable economic loss.The governments have taken various measures such as better road infrastructures and strict enforcement of motor-vehicle laws to reduce these accidents.However,there is still no remarkable reduction in the number of accidents.To ensure driver safety and achieve vision of zero accidents,there is a great need to monitor drivers’driving styles.Most of the existing driving behavior monitoring solutions are based on expensive hardware sensors.As most people are using smartphones in the modern era,a system based on mobile application is proposed,which can reduce the cost for developing intelligent transport systems(ITS)to a large extent.In this paper,we utilize the accelerometer sensor data and the global positioning system(GPS)sensor deployed in smartphones to recognize driving and speeding events.A driving style recognition system based on fuzzy logic is designed to classify different driving styles and control reckless driving by taking the longitudinal/lateral acceleration and speed as input parameters.Thus,the proposed system uses fuzzy logic rather than taking the crisp values of the sensors.Results indicate that the proposed system can classify reckless driving based on fuzzy logic and,therefore,reduce the number of accidents.

A GPS/BDS dual-mode positioning algorithm for a train based on CIPSO_EKF

When using global positioning system/BeiDou navigation satellite(GPS/BDS)dual-mode navigation system to locate a train,Kalman filter that is used to calculate train position has to be adjusted according to the features of the dual-mode observation.Due to multipath effect,positioning accuracy of present Kalman filter algorithm is really low.To solve this problem,a chaotic immune-vaccine particle swarm optimization_extended Kalman filter(CIPSO_EKF)algorithm is proposed to improve the output accuracy of the Kalman filter.By chaotic mapping and immunization,the particle swarm algorithm is first optimized,and then the optimized particle swarm algorithm is used to optimize the observation error covariance matrix.The optimal parameters are provided to the EKF,which can effectively reduce the impact of the observation value oscillation caused by multipath effect on positioning accuracy.At the same time,the train positioning results of EKF and CIPSO_EKF algorithms are compared.The eastward position errors and velocity errors show that CIPSO_EKF algorithm has faster convergence speed and higher real-time performance,which can effectively suppress interference and improve positioning accuracy.

Hybrid Kalman and unscented Kalman filters for INS/GPS integrated system considering constant lever arm effect

In inertial navigation system(INS) and global positioning system(GPS) integrated system, GPS antennas are usually not located at the same location as the inertial measurement unit(IMU) of the INS, so the lever arm effect exists, which makes the observation equation highly nonlinear. The INS/GPS integration with constant lever arm effect is studied. The position relation of IMU and GPS's antenna is represented in the earth centered earth fixed frame, while the velocity relation of these two systems is represented in local horizontal frame. Due to the small integration time interval of INS, i.e. 0.1 s in this work, the nonlinearity in the INS error equation is trivial, so the linear INS error model is constructed and addressed by Kalman filter's prediction step. On the other hand, the high nonlinearity in the observation equation due to lever arm effect is addressed by unscented Kalman filter's update step to attain higher accuracy and better applicability. Simulation is designed and the performance of the hybrid filter is validated.