scholarly journals Stability Analysis of Position Datum for Real-Time GPS/BDS/INS Positioning in a Platform System with Multiple Moving Devices

2021 ◽  
Vol 13 (23) ◽  
pp. 4764
Author(s):  
Weiming Tang ◽  
Yangyang Li ◽  
Chenlong Deng ◽  
Xuan Zou ◽  
Yawei Wang ◽  
...  
Keyword(s):  
Real Time ◽  
Attitude Determination ◽  
Rapid Development ◽  
Single Point ◽  
Satellite System ◽  
Stable Position ◽  
Vehicle Trajectories ◽  
Time Position ◽  
Set Up ◽  
Platform System

The rapid development of unmanned aerial vehicles (UAVs) in recent years has promoted their application in various fields, such as precise agriculture, formation flight, etc. In these applications, the accurate and reliable real-time position and attitude determination between each moving device in the same platform system are the key issue for safe and effective cooperative works. In traditional ways, static reference stations should be set up near the platform to keep the stable position datum of the platform system. In this paper, we abandoned the static stations and expected to achieve stable position datums with the platform system itself. To achieve this goal, we proposed an improved method based on both the Global Positioning System (GPS)/Beidou Navigation Satellite System (BDS) data and the inertial navigation system (INS) data to obtain precise positions of the moving devices. The time-differenced carrier phase (TDCP) was used to get the position variations and update the positions over time, and then, the INS data was integrated to further improve the accuracy and reliability of the updated positions; thus, this method is denoted as the TDCP/INS method. To evaluate the performance of this method and compare it with the traditional single-point positioning (SPP) method and the Kalman filtered SPP (KFSPP) method, a field vehicle experiment was conducted, and the position results achieved from these three methods were compared with those from the tightly combined real-time kinematic positioning (RTK)/INS method, where centimeter-level accuracy was obtained and regarded as the reference. The quantitative analysis where the position variations were evaluated and the qualitative analysis where the vehicle trajectories in three typical urban driving scenarios were discussed were both made for the three methods. The numerical results showed that the accuracy of the position variations from the SPP, KSPP, and TDCP methods was at the meter level, while that from the TDCP/INS method improved to the centimeter level, and the accuracies were 1.9 cm, 2.9 cm, and 3.1 cm in the east, north, and upward directions. The trajectory results also demonstrated a perfect consistency of the driving positions between the TDCP/INS method and the reference. As a contrast, the trajectories from the SPP and KFSPP methods had frequent jumps or sways when the vehicle drove along a large, curved road, turned at a crossroad, and passed under an urban viaduct.

scholarly journals Establishment of a Real-Time Local Tropospheric Fusion Model

2019 ◽  
Vol 11 (11) ◽  
pp. 1321 ◽  
Author(s):  
Yibin Yao ◽  
Xingyu Xu ◽  
Chaoqian Xu ◽  
Wenjie Peng ◽  
Yangyang Wan
Keyword(s):  
Real Time ◽  
Meteorological Data ◽  
Rapid Development ◽  
Water Vapor Pressure ◽  
Auxiliary Information ◽  
Satellite System ◽  
Tropospheric Delay ◽  
Navigation Systems ◽  
Delay Model ◽  
Fusion Model

The tropospheric delay is one major error source affecting the precise positioning provided by the global navigation satellite system (GNSS). This error occurs because the GNSS signals are refracted while travelling through the troposphere layer. Nowadays, various types of model can produce the tropospheric delay. Among them, the globally distributed GNSS permanent stations can resolve the tropospheric delay with the highest accuracy and the best continuity. Meteorological models, such as the Saastamoinen model, provide formulae to calculate temperature, pressure, water vapor pressure and subsequently the tropospheric delay. Some grid-based empirical tropospheric delay models directly provide tropospheric parameters at a global scale and in real time without any auxiliary information. However, the spatial resolution of the GNSS tropospheric delay is not sufficient, and the accuracy of the meteorological and empirical models is relatively poor. With the rapid development of satellite navigation systems around the globe, the demand for real-time high-precision GNSS positioning services has been growing dramatically, requiring real-time and high-accuracy troposphere models as a critical prerequisite. Therefore, this paper proposes a multi-source real-time local tropospheric delay model that uses polynomial fitting of ground-based GNSS observations, meteorological data, and empirical GPT2w models. The results show that the accuracy in the zenith tropospheric delay (ZTD) of the proposed tropospheric delay model has been verified with a RMS (root mean square) of 1.48 cm in active troposphere conditions, and 1.45 cm in stable troposphere conditions, which is significantly better than the conventional tropospheric GPT2w and Saastamoinen models.

scholarly journals Performance Evaluation of Real-Time Precise Point Positioning with Both BDS-3 and BDS-2 Observations

Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6027
Author(s):  
Lin Pan ◽  
Xuanping Li ◽  
Wenkun Yu ◽  
Wujiao Dai ◽  
Cuilin Kuang ◽  
...  
Keyword(s):  
Real Time ◽  
Precise Point Positioning ◽  
Rapid Development ◽  
Satellite System ◽  
Convergence Time ◽  
Static Mode ◽  
The Real ◽  
Point Positioning ◽  
Time Critical

For time-critical precise applications, one popular technology is the real-time precise point positioning (PPP). In recent years, there has been a rapid development in the BeiDou Navigation Satellite System (BDS), and the constellation of global BDS (BDS-3) has been fully deployed. In addition to the regional BDS (BDS-2) constellation, the real-time stream CLK93 has started to support the BDS-3 constellation, indicating that the real-time PPP processing involving BDS-3 observations is feasible. In this study, the global positioning performance of real-time PPP with BDS-3/BDS-2 observations is initially evaluated using the datasets from 147 stations. In the east, north and upward directions, positioning accuracy of 1.8, 1.2 and 2.5 cm in the static mode, and of 6.7, 5.1 and 10.4 cm in the kinematic mode can be achieved for the BDS-3/BDS-2 real-time PPP, respectively, while the corresponding convergence time with a threshold of 10 cm is 32.9, 23.7 and 32.8 min, and 66.9, 42.9 and 69.1 min in the two modes in the three directions, respectively. To complete this, the availability of BDS-3/BDS-2 constellations, the quality of BDS-3/BDS-2 real-time precise satellite products, and the BDS-3/BDS-2 post-processed PPP solutions are also analyzed. For comparison, the results for the GPS are also presented.

scholarly journals A Stream Processing System for Multisource Heterogeneous Sensor Data

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Liang Hu ◽  
Rui Sun ◽  
Feng Wang ◽  
Xiuhong Fei ◽  
Kuo Zhao
Keyword(s):  
Data Integration ◽  
Data Processing ◽  
Real Time ◽  
Rapid Development ◽  
Streaming Data ◽  
Sensor Data ◽  
Low Latency ◽  
Time System ◽  
Real Time System ◽  
Set Up

With the rapid development of the Internet of Things (IoT), a variety of sensor data are generated around everyone’s life. New research perspective regarding the streaming sensor data processing of the IoT has been raised as a hot research topic that is precisely the theme of this paper. Our study serves to provide guidance regarding the practical aspects of the IoT. Such guidance is rarely mentioned in the current research in which the focus has been more on theory and less on issues describing how to set up a practical system. In our study, we employ numerous open source projects to establish a distributed real time system to process streaming data of the IoT. Two urgent issues have been solved in our study that are (1) multisource heterogeneous sensor data integration and (2) processing streaming sensor data in real time manner with low latency. Furthermore, we set up a real time system to process streaming heterogeneous sensor data from multiple sources with low latency. Our tests are performed using field test data derived from environmental monitoring sensor data collected from indoor environment for system validation. The results show that our proposed system is valid and efficient for multisource heterogeneous sensor data integration and streaming data processing in real time manner.

scholarly journals IONORING: Real-Time Monitoring of the Total Electron Content over Italy

2021 ◽  
Vol 13 (16) ◽  
pp. 3290
Author(s):  
Claudio Cesaroni ◽  
Luca Spogli ◽  
Giorgiana De Franceschi
Keyword(s):  
Real Time ◽  
Total Electron Content ◽  
Geomagnetic Storms ◽  
Single Point ◽  
Satellite System ◽  
Electron Content ◽  
Real Time Monitoring ◽  
International Gnss Service ◽  
Total Electron ◽  
Global Navigation Satellite

IONORING (IONOspheric RING) is a tool capable to provide the real-time monitoring and modeling of the ionospheric Total Electron Content (TEC) over Italy, in the latitudinal and longitudinal ranges of 35°N-48°N and 5°E-20°E, respectively. IONORING exploits the Global Navigation Satellite System (GNSS) data acquired by the RING (Rete Integrata Nazionale GNSS) network, managed by the Istituto Nazionale di Geofisica e Vulcanologia (INGV). The system provides TEC real-time maps with a very fine spatial resolution (0.1° latitude x 0.1° longitude), with a refresh time of 10 min and a typical latency below the minute. The TEC estimated at the ionospheric piercing points from about 40 RING stations, equally distributed over the Italian territory, are interpolated using locally (weighted) regression scatter plot smoothing (LOWESS). The validation is performed by comparing the IONORING TEC maps (in real-time) with independent products: i) the Global Ionospheric Maps (GIM) - final product- provided by the International GNSS Service (IGS), and ii) the European TEC maps from the Royal Observatory of Belgium. The validation results are satisfactory in terms of Root Mean Square Error (RMSE) between 2 and 3 TECu for both comparisons. The potential of IONORING in depicting the TEC daily and seasonal variations is analyzed over 3 years, from May 2017 to April 2020, as well as its capability to account for the effect of the disturbed geospace on the ionosphere at mid-latitudes. The IONORING response to the X9.3 flare event of September 2017 highlights a sudden TEC increase over Italy of about 20%, with a small, expected dependence on the latitude, i.e., on the distance from the subsolar point. Subsequent large regional TEC various were observed in response to related follow-on geomagnetic storms. This storm is also used as a case event to demonstrate the potential of IONORING in improving the accuracy of the GNSS Single Point Positioning. By processing data in kinematic mode and by using the Klobuchar as the model to provide the ionospheric correction, the resulting Horizontal Positioning Error is 4.3 m, lowering to, 3.84 m when GIM maps are used. If IONORING maps are used as the reference ionosphere, the error is as low as 2.5 m. Real-times application and services in which IONORING is currently integrated are also described in the conclusive remarks.

scholarly journals Real-Time Detection of Orbital Maneuvers Using Epoch-Differenced Carrier Phase Observations and Broadcast Ephemeris Data: A Case Study of the BDS Dataset

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4584 ◽  
Author(s):  
Rui Tu ◽  
Rui Zhang ◽  
Lihong Fan ◽  
Junqiang Han ◽  
Pengfei Zhang ◽  
...  
Keyword(s):  
Real Time ◽  
Carrier Phase ◽  
Single Point ◽  
Satellite System ◽  
Velocity Estimation ◽  
Navigation Satellite ◽  
Orbital Maneuvers ◽  
Broadcast Ephemeris ◽  
Real Time Detection ◽  
Global Navigation Satellite

The orbital maneuvers of the global navigation satellite system (GNSSs) have a significant influence on the performance of the precise positioning, navigation, and timing (PNT) services. Because the Chinese BeiDou Navigation Satellite System (BDS) has three types of satellites in the geostationary orbit (GEO), inclined geosynchronous orbit (IGSO), and medium earth orbit (MEO) maneuvers occur more frequently. Thus, it is essential to determine an effective approach for the detection of orbital maneuvers. This study proposes a method for the detection of orbital maneuvers using epoch-differenced carrier phase observations and broadcast ephemeris data. When using the epoch-differenced velocity estimation as a basic data solution model, the time discrimination and satellite identification factors are defined and used for the real-time detection of the beginning and the pseudorandom noise code (PRN) of satellites. The datasets from four GNSS stations (WUH1, BJF1, POHN, CUT0) from the year 2016 were collected and analyzed. The validations showed that the beginning, the PRN of the orbital maneuver of the satellite can be precisely detected in real time for all GEO, IGSO, and MEO satellites, and the detected results also showed good consistency, with the beginning time at a difference of 1–2 min across different stations. The proposed approach was observed to be more sensitive, and the detected beginning time was about 30 min earlier than the single point positioning approach when the high-precision carrier phase observation was used. Thus, orbital maneuvering can be accurately detected by the proposed method. It not only improves the utilization of the collected data but also improves the performance of PNT services.

scholarly journals Research and Analysis of Sports Training Real-Time Monitoring System Based on Mobile Artificial Intelligence Terminal

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Biao Ma ◽  
Shangqi Nie ◽  
Minghui Ji ◽  
Jeho Song ◽  
Wei Wang
Keyword(s):  
Artificial Intelligence ◽  
Real Time ◽  
Monitoring System ◽  
Rapid Development ◽  
Position Information ◽  
Security Monitoring ◽  
Training Plan ◽  
Time Position ◽  
Individual Sports ◽  
Training State

With the rapid development of artificial intelligence, related technologies and applications come into being, and industries based on artificial intelligence are booming, among which image recognition and target tracking technologies are widely used in various fields, especially in the fields of security monitoring and augmented reality. In this paper, combined with the characteristics of athletes, based on mobile artificial intelligence terminal technology, the C/S mode of athlete training process monitoring system is developed and designed, which uses GPS to obtain the real-time position information of athletes and provide real-time guidance for athletes. In order to reveal the changing rules of various indexes of athletes in training state, the author makes synchronous tracking analysis from the aspects of individual sports function characteristics of athletes, training plan arrangement of coaches, brain function state, routine physiological and biochemical indexes, nutrition regulation, and injury conditions.

DEVELOPMENT OF MULTIPLEX REAL-TIME PCR ASSAY FOR SIX PATHOGENS: RAPID TOOL FOR DIAGNOSIS OF BACTERIAL MENINGITIS

2019 ◽  
pp. 60-66
Author(s):  
Viet Quynh Tram Ngo ◽  
Thi Ti Na Nguyen ◽  
Hoang Bach Nguyen ◽  
Thi Tuyet Ngoc Tran ◽  
Thi Nam Lien Nguyen ◽  
...  
Keyword(s):  
Bacterial Meningitis ◽  
Real Time ◽  
Real Time Pcr ◽  
Diagnostic Methods ◽  
Type B ◽  
E Coli ◽  
Pcr Assays ◽  
Set Up ◽  
Etiological Agents ◽  
Suis Serotype

Introduction: Bacterial meningitis is an acute central nervous infection with high mortality or permanent neurological sequelae if remained undiagnosed. However, traditional diagnostic methods for bacterial meningitis pose challenge in prompt and precise identification of causative agents. Aims: The present study will therefore aim to set up in-house PCR assays for diagnosis of six pathogens causing the disease including H. influenzae type b, S. pneumoniae, N. meningitidis, S. suis serotype 2, E. coli and S. aureus. Methods: inhouse PCR assays for detecting six above-mentioned bacteria were optimized after specific pairs of primers and probes collected from the reliable literature resources and then were performed for cerebrospinal fluid (CSF) samples from patients with suspected meningitis in Hue Hospitals. Results: The set of four PCR assays was developed including a multiplex real-time PCR for S. suis serotype 2, H. influenzae type b and N. meningitides; three monoplex real-time PCRs for E. coli, S. aureus and S. pneumoniae. Application of the in-house PCRs for 116 CSF samples, the results indicated that 48 (39.7%) cases were positive with S. suis serotype 2; one case was positive with H. influenzae type b; 4 cases were positive with E. coli; pneumococcal meningitis were 19 (16.4%) cases, meningitis with S. aureus and N. meningitidis were not observed in any CSF samples in this study. Conclusion: our in-house real-time PCR assays are rapid, sensitive and specific tools for routine diagnosis to detect six mentioned above meningitis etiological agents. Key words: Bacterial meningitis, etiological agents, multiplex real-time PCR

scholarly journals Current Trends in Random Walks on Random Lattices

Mathematics ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 1148
Author(s):  
Jewgeni H. Dshalalow ◽  
Ryan T. White
Keyword(s):  
Random Walk ◽  
Random Walks ◽  
Real Time ◽  
Real Space ◽  
Historical Background ◽  
Escape Time ◽  
The Real ◽  
Current Trends ◽  
One Step ◽  
Time Position

In a classical random walk model, a walker moves through a deterministic d-dimensional integer lattice in one step at a time, without drifting in any direction. In a more advanced setting, a walker randomly moves over a randomly configured (non equidistant) lattice jumping a random number of steps. In some further variants, there is a limited access walker’s moves. That is, the walker’s movements are not available in real time. Instead, the observations are limited to some random epochs resulting in a delayed information about the real-time position of the walker, its escape time, and location outside a bounded subset of the real space. In this case we target the virtual first passage (or escape) time. Thus, unlike standard random walk problems, rather than crossing the boundary, we deal with the walker’s escape location arbitrarily distant from the boundary. In this paper, we give a short historical background on random walk, discuss various directions in the development of random walk theory, and survey most of our results obtained in the last 25–30 years, including the very recent ones dated 2020–21. Among different applications of such random walks, we discuss stock markets, stochastic networks, games, and queueing.

scholarly journals Implementation of a deep learning model for automated classification of Aedes aegypti (Linnaeus) and Aedes albopictus (Skuse) in real time

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Song-Quan Ong ◽  
Hamdan Ahmad ◽  
Gomesh Nair ◽  
Pradeep Isawasan ◽  
Abdul Hafiz Ab Majid
Keyword(s):  
Deep Learning ◽  
Aedes Aegypti ◽  
Real Time ◽  
Aedes Albopictus ◽  
Automated Classification ◽  
Expert Performance ◽  
Deep Convolutional Neural Networks ◽  
Significant Difference ◽  
Set Up

AbstractClassification of Aedes aegypti (Linnaeus) and Aedes albopictus (Skuse) by humans remains challenging. We proposed a highly accessible method to develop a deep learning (DL) model and implement the model for mosquito image classification by using hardware that could regulate the development process. In particular, we constructed a dataset with 4120 images of Aedes mosquitoes that were older than 12 days old and had common morphological features that disappeared, and we illustrated how to set up supervised deep convolutional neural networks (DCNNs) with hyperparameter adjustment. The model application was first conducted by deploying the model externally in real time on three different generations of mosquitoes, and the accuracy was compared with human expert performance. Our results showed that both the learning rate and epochs significantly affected the accuracy, and the best-performing hyperparameters achieved an accuracy of more than 98% at classifying mosquitoes, which showed no significant difference from human-level performance. We demonstrated the feasibility of the method to construct a model with the DCNN when deployed externally on mosquitoes in real time.

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