scholarly journals Effective Efficiency Advantage Assessment of Information Filter for Conventional Kalman Filter in GNSS Scenarios

Sensors ◽  
2019 ◽  
Vol 19 (18) ◽  
pp. 3858 ◽  
Author(s):  
Zheng ◽  
Wang ◽  
Wang
Keyword(s):  
Kalman Filter ◽  
Data Processing ◽  
Real Time ◽  
Computational Cost ◽  
Satellite System ◽  
Hardware Platform ◽  
Algorithm Efficiency ◽  
Information Filter ◽  
Global Navigation Satellite ◽  
Cv Model

The Global Navigation Satellite System (GNSS) is a widely used positioning technique. Computational efficiency is crucial to applications such as real-time GNSS positioning and GNSS network data processing. Many researchers have made great efforts to address this problem by means such as parameter elimination or satellite selection. However, parameter estimation is rarely discussed when analyzing GNSS algorithm efficiency. In addition, most studies on Kalman filter (KF) efficiency commonly have defects, such as neglecting application-specified optimization and limiting specific hardware platforms in the conclusion. The former reduces the practicality of the solution, because applications that need such analyses on filters are often optimized, and the latter reduces its generality because of differences between platforms. In this paper, the computational cost enhancement of replacing the conventional KF with the information filter (IF) is tested considering GNSS application-oriented optimization conditions and hardware platform differences. First, optimization conditions are abstracted from GNSS data-processing scenarios. Then, a thorough analysis is carried out on the computational cost of the filters, considering hardware–platform differences. Finally, a case of GNSS dynamic differencing positioning is studied. The simulation shows that the IF is slightly faster for precise point positioning and much faster for the code-based single-difference GNSS (SDGNSS) with the constant velocity (CV) model than the conventional KF, but is not a good substitute for the conventional KF in the other algorithms mentioned. The real test shows that the IF is about 50% faster than the conventional KF handling code-based SDGNSS with the CV model. Also, the information filter is theoretically equivalent to and can produce results that are consistent with the Kalman filter. Our conclusions can be used as a reference for GNSS applications that need high process speed or real-time capability.

Integrated Navigation Models of a Mobile Fodder-Pushing Robot Based on a Standardized Cow Husbandry Environment

2020 ◽  
Vol 63 (2) ◽  
pp. 221-230
Author(s):  
Shenghui Yang ◽  
Shenghao Liang ◽  
Yongjun Zheng ◽  
Yu Tan ◽  
Zhang Xiao ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Real Time ◽  
Time Course ◽  
Satellite System ◽  
Integrated Navigation ◽  
Multiple Sensors ◽  
Motion Models ◽  
Outdoor Environments ◽  
Global Navigation Satellite ◽  
Smart Mobile

HighlighIntegrated navigation models for a two-wheel robot were specifically developed for a semi-enclosed environment.A combination of Kalman filter and fuzzy control system was developed with mathematical models.Real-time pose estimate and adjustment of perturbances due to feeding cows and fodder resistance were achieved.Abstract. As part of welfare feeding, standardized feeding is commonly used for cows in confined operations. Due to the strict facility requirements, smart mobile robots have been specifically developed to address these semi-enclosed environments. Their navigation is based on electromagnetic sensors with magnetic tapes, which does not easily allow route changes and other abilities afforded by the newer integrated sensors and Global Navigation Satellite System (GNSS) guidance packages available on large agricultural machinery in outdoor environments. This article proposes a system of integrated navigation using multiple sensors, which was used for a two-wheel-drive robot operating in the standardized environment of a cow husbandry facility. The developed system combined incremental encoders, ultrasonic sensors, and a gyroscope to determine parameters such as course angle and covered distance. A fuzzy self-adaption Kalman filter was applied to integrate these parameters and estimate the robot pose, so that the robot could achieve real-time course adjustment during operation. Experimental trials indicated that the real-world route was highly consistent with the set route. Moreover, the cross-track error was =0.10 m at a travel velocity of 0.2 m s-1, indicating that perturbances due to feeding cows and fodder resistance had little interference on the movement of the robot, and the models were robust and accurate. This novel integrated sensing system with a fuzzy self-adaption Kalman filter and derived models was able to guide real-time robot operations in a modern cow husbandry environment without the need for magnetic tapes. Keywords: Kalman filter, Integrated navigation, Motion models, Pose estimate, Welfare feeding.

scholarly journals Compressed pseudo-SLAM: pseudorange-integrated compressed simultaneous localisation and mapping for unmanned aerial vehicle navigation

2021 ◽  
pp. 1-13
Author(s):  
Jonghyuk Kim ◽  
Jose Guivant ◽  
Martin L. Sollie ◽  
Torleiv H. Bryne ◽  
Tor Arne Johansen
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Computational Cost ◽  
Satellite System ◽  
Measurement Unit ◽  
Electronic Systems ◽  
Computationally Efficient ◽  
Global Correlation ◽  
Aerial Vehicle ◽  
Correlation Information ◽  
Global Navigation Satellite

Abstract This paper addresses the fusion of the pseudorange/pseudorange rate observations from the global navigation satellite system and the inertial–visual simultaneous localisation and mapping (SLAM) to achieve reliable navigation of unmanned aerial vehicles. This work extends the previous work on a simulation-based study [Kim et al. (2017). Compressed fusion of GNSS and inertial navigation with simultaneous localisation and mapping. IEEE Aerospace and Electronic Systems Magazine, 32(8), 22–36] to a real-flight dataset collected from a fixed-wing unmanned aerial vehicle platform. The dataset consists of measurements from visual landmarks, an inertial measurement unit, and pseudorange and pseudorange rates. We propose a novel all-source navigation filter, termed a compressed pseudo-SLAM, which can seamlessly integrate all available information in a computationally efficient way. In this framework, a local map is dynamically defined around the vehicle, updating the vehicle and local landmark states within the region. A global map includes the rest of the landmarks and is updated at a much lower rate by accumulating (or compressing) the local-to-global correlation information within the filter. It will show that the horizontal navigation error is effectively constrained with one satellite vehicle and one landmark observation. The computational cost will be analysed, demonstrating the efficiency of the method.

scholarly journals Methodology for the Correction of the Spatial Orientation Angles of the Unmanned Aerial Vehicle Using Real Time GNSS, a Shoreline Image and an Electronic Navigational Chart

Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2810
Author(s):  
Krzysztof Naus ◽  
Piotr Szymak ◽  
Paweł Piskur ◽  
Maciej Niedziela ◽  
Aleksander Nowak
Keyword(s):  
Real Time ◽  
Spatial Orientation ◽  
Orientation Angle ◽  
Satellite System ◽  
Angle Measurement ◽  
Angle Correction ◽  
Lidar Measurements ◽  
Aerial Vehicle ◽  
Marine Applications ◽  
Global Navigation Satellite

Undoubtedly, Low-Altitude Unmanned Aerial Vehicles (UAVs) are becoming more common in marine applications. Equipped with a Global Navigation Satellite System (GNSS) Real-Time Kinematic (RTK) receiver for highly accurate positioning, they perform camera and Light Detection and Ranging (LiDAR) measurements. Unfortunately, these measurements may still be subject to large errors-mainly due to the inaccuracy of measurement of the optical axis of the camera or LiDAR sensor. Usually, UAVs use a small and light Inertial Navigation System (INS) with an angle measurement error of up to 0.5∘ (RMSE). The methodology for spatial orientation angle correction presented in the article allows the reduction of this error even to the level of 0.01∘ (RMSE). It can be successfully used in coastal and port waters. To determine the corrections, only the Electronic Navigational Chart (ENC) and an image of the coastline are needed.

APLICAÇÃO DE GEOTECNOLOGIAS NA ANÁLISE DE VIABILIDADE TÉCNICA E ECONÔMICA DO PROJETO DE IMPLANTAÇÃO DO IFMA - CAMPUS ITAQUI-BACANGA.

2021 ◽  
Vol 14 (2) ◽  
pp. 105
Author(s):  
Maelckson Bruno Barros Gomes ◽  
André Luis Silva Santos
Keyword(s):  
Real Time ◽  
Global Navigation Satellite System ◽  
Satellite System ◽  
Navigation Satellite ◽  
Real Time Kinematic ◽  
Global Navigation ◽  
Global Navigation Satellite

<p class="04CorpodoTexto">Este artigo tem por objetivo aplicar geotecnologias para obtenção de informações planialtimétricas a fim de avaliar a viabilidade de implantação do campus Centro Histórico/Itaqui-Bacanga do IFMA. Considerando que para realização de levantamento por métodos tradicionais é recomendado que seja realizado o destocamento e a limpeza do terreno previamente, avaliou-se a realização do levantamento planialtimétrico a partir de um par de receptores <em>Global Navigation Satellite System</em> (GNSS) pelo método <em>Real Time Kinematic</em> (RTK) pós processado e também a partir da realização de levantamento fotogramétrico, utilizando aeronave remotamente pilotada (ARP), popularmente conhecida como drone. Esta análise permitiu demonstrar que o aerolevantamento com a ARP pode ser aplicado na concepção inicial de um projeto de engenharia, conforme classificação do Tribunal de Contas da União (TCU) para níveis de precisão, pois obteve-se uma diferença orçamentária de 19% entre os projetos elaborados a partir das duas geotecnologias.</p><div> </div>

scholarly journals Online Near real-time Mine Disaster Monitoring System Based on Geosensor Networks

2016 ◽  
Vol 12 (03) ◽  
pp. 64
Author(s):  
Haifeng Hu
Keyword(s):  
Real Time ◽  
Monitoring System ◽  
Satellite System ◽  
Open Pit ◽  
Observation Data ◽  
Complex Data ◽  
Disaster Monitoring ◽  
Process Observation ◽  
Global Navigation Satellite ◽  
Safety And Stability

Abstract—An online automatic disaster monitoring system can reduce or prevent geological mine disasters to protect life and property. Global Navigation Satellite System receivers and the GeoRobot are two kinds of in-situ geosensors widely used for monitoring ground movements near mines. A combined monitoring solution is presented that integrates the advantages of both. In addition, a geosensor network system to be used for geological mine disaster monitoring is described. A complete online automatic mine disaster monitoring system including data transmission, data management, and complex data analysis is outlined. This paper proposes a novel overall architecture for mine disaster monitoring. This architecture can seamlessly integrate sensors for long-term, remote, and near real-time monitoring. In the architecture, three layers are used to collect, manage and process observation data. To demonstrate the applicability of the method, a system encompassing this architecture has been deployed to monitor the safety and stability of a slope at an open-pit mine in Inner Mongolia.

scholarly journals Opportunistic In-Flight INS Alignment Using LEO Satellites and a Rotatory IMU Platform

Aerospace ◽  
2021 ◽  
Vol 8 (10) ◽  
pp. 280
Author(s):  
Farzan Farhangian ◽  
Hamza Benzerrouk ◽  
Rene Landry
Keyword(s):  
Kalman Filter ◽  
State Space Model ◽  
Flight Test ◽  
Satellite System ◽  
Low Earth Orbit ◽  
Measurement Unit ◽  
Starting Point ◽  
Leo Satellites ◽  
Positioning Method ◽  
Global Navigation Satellite

With the emergence of numerous low Earth orbit (LEO) satellite constellations such as Iridium-Next, Globalstar, Orbcomm, Starlink, and OneWeb, the idea of considering their downlink signals as a source of pseudorange and pseudorange rate measurements has become incredibly attractive to the community. LEO satellites could be a reliable alternative for environments or situations in which the global navigation satellite system (GNSS) is blocked or inaccessible. In this article, we present a novel in-flight alignment method for a strapdown inertial navigation system (SINS) using Doppler shift measurements obtained from single or multi-constellation LEO satellites and a rotation technique applied on the inertial measurement unit (IMU). Firstly, a regular Doppler positioning algorithm based on the extended Kalman filter (EKF) calculates states of the receiver. This system is considered as a slave block. In parallel, a master INS estimates the position, velocity, and attitude of the system. Secondly, the linearized state space model of the INS errors is formulated. The alignment model accounts for obtaining the errors of the INS by a Kalman filter. The measurements of this system are the difference in the outputs from the master and slave systems. Thirdly, as the observability rank of the system is not sufficient for estimating all the parameters, a discrete dual-axis IMU rotation sequence was simulated. By increasing the observability rank of the system, all the states were estimated. Two experiments were performed with different overhead satellites and numbers of constellations: one for a ground vehicle and another for a small flight vehicle. Finally, the results showed a significant improvement compared to stand-alone INS and the regular Doppler positioning method. The error of the ground test reached around 26 m. This error for the flight test was demonstrated in different time intervals from the starting point of the trajectory. The proposed method showed a 180% accuracy improvement compared to the Doppler positioning method for up to 4.5 min after blocking the GNSS.

Leveraging Intelligent Compaction and Thermal Profiling Technologies to Improve Asphalt Pavement Construction Quality: A Case Study

2018 ◽  
Vol 2672 (26) ◽  
pp. 48-56 ◽  
Author(s):  
George K. Chang ◽  
Kiran Mohanraj ◽  
William A. Stone ◽  
Daniel J. Oesch ◽  
Victor (Lee) Gallivan
Keyword(s):  
Real Time ◽  
Satellite System ◽  
Material Transfer ◽  
Intelligent Compaction ◽  
Two Factors ◽  
Thermal Profiling ◽  
Compaction Control ◽  
Pavement Construction ◽  
Global Navigation Satellite

Intelligent compaction (IC) is an emerging technology with rollers equipped with global navigation satellite system (GNSS), an accelerometer-based measurement system, and an onboard color-coded display for real-time monitoring and compaction control. Paver-mounted thermal profiling (PMTP) is used to monitor asphalt surface temperatures behind a paver with a thermal scanner, and to track paver speeds, stops, and stop durations. Leveraging both IC and PMTP technologies allows for paving and compaction controls in real time, and for executing appropriate adjustments as needed. A case study is used to demonstrate the advantage of using both IC and PMTP over conventional operations. Postconstruction asphalt coring and tests, as well as pavement profile surveys were conducted to provide asphalt density data and pavement smoothness acceptance data for comparison and correlation analysis with IC and PMTP data. The data from 2 days of operations, one without the Material Transfer Vehicle (MTV) and another with the MTV, were analyzed and compared to illustrate the benefits of using IC, PMTP, and MTV for producing quality pavement products. Durability and smoothness are two key construction qualities for agencies and users of hot mix asphalt (HMA) pavements. These two factors also affect the long-term structural and functional pavement performance.

scholarly journals Real-Time Precise Point Positioning Using Orbit and Clock Corrections as Quasi-Observations for Improved Detection of Faults

2018 ◽  
Vol 71 (4) ◽  
pp. 769-787 ◽  
Author(s):  
Ahmed El-Mowafy
Keyword(s):  
Real Time ◽  
Precise Point Positioning ◽  
Exclusion Process ◽  
Satellite Orbit ◽  
Satellite System ◽  
Navigation Satellite ◽  
System Service ◽  
Point Positioning ◽  
Predicted Values ◽  
Global Navigation Satellite

Real-time Precise Point Positioning (PPP) relies on the use of accurate satellite orbit and clock corrections. If these corrections contain large errors or faults, either from the system or by meaconing, they will adversely affect positioning. Therefore, such faults have to be detected and excluded. In traditional PPP, measurements that have faulty corrections are typically excluded as they are merged together. In this contribution, a new PPP model that encompasses the orbit and clock corrections as quasi-observations is presented such that they undergo the fault detection and exclusion process separate from the observations. This enables the use of measurements that have faulty corrections along with predicted values of these corrections in place of the excluded ones. Moreover, the proposed approach allows for inclusion of the complete stochastic information of the corrections. To facilitate modelling of the orbit and clock corrections as quasi-observations, International Global Navigation Satellite System Service (IGS) real-time corrections were characterised over a six-month period. The proposed method is validated and its benefits are demonstrated at two sites using three days of data.

scholarly journals Multi-GNSS Combined Precise Point Positioning Using Additional Observations with Opposite Weight for Real-Time Quality Control

2019 ◽  
Vol 11 (3) ◽  
pp. 311 ◽  
Author(s):  
Wenju Fu ◽  
Guanwen Huang ◽  
Yuanxi Zhang ◽  
Qin Zhang ◽  
Bobin Cui ◽  
...  
Keyword(s):  
Quality Control ◽  
Real Time ◽  
Precise Point Positioning ◽  
Satellite System ◽  
Convergence Time ◽  
Navigation Satellite ◽  
Positioning Accuracy ◽  
Global Navigation ◽  
Point Positioning ◽  
Global Navigation Satellite

The emergence of multiple global navigation satellite systems (multi-GNSS), including global positioning system (GPS), global navigation satellite system (GLONASS), Beidou navigation satellite system (BDS), and Galileo, brings not only great opportunities for real-time precise point positioning (PPP), but also challenges in quality control because of inevitable data anomalies. This research aims at achieving the real-time quality control of the multi-GNSS combined PPP using additional observations with opposite weight. A robust multiple-system combined PPP estimation is developed to simultaneously process observations from all the four GNSS systems as well as single, dual, or triple systems. The experiment indicates that the proposed quality control can effectively eliminate the influence of outliers on the single GPS and the multiple-system combined PPP. The analysis on the positioning accuracy and the convergence time of the proposed robust PPP is conducted based on one week’s data from 32 globally distributed stations. The positioning root mean square (RMS) error of the quad-system combined PPP is 1.2 cm, 1.0 cm, and 3.0 cm in the east, north, and upward components, respectively, with the improvements of 62.5%, 63.0%, and 55.2% compared to those of single GPS. The average convergence time of the quad-system combined PPP in the horizontal and vertical components is 12.8 min and 12.2 min, respectively, while it is 26.5 min and 23.7 min when only using single-GPS PPP. The positioning performance of the GPS, GLONASS, and BDS (GRC) combination and the GPS, GLONASS, and Galileo (GRE) combination is comparable to the GPS, GLONASS, BDS and Galileo (GRCE) combination and it is better than that of the GPS, BDS, and Galileo (GCE) combination. Compared to GPS, the improvements of the positioning accuracy of the GPS and GLONASS (GR) combination, the GPS and Galileo (GE) combination, the GPS and BDS (GC) combination in the east component are 53.1%, 43.8%, and 40.6%, respectively, while they are 55.6%, 48.1%, and 40.7% in the north component, and 47.8%, 40.3%, and 34.3% in the upward component.

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