A Joint Dual-Frequency GNSS/SINS Deep-Coupled Navigation System for Polar Navigation

The strategic position of the polar area and its rich natural resources are becoming increasingly important, while the northeast and northwest passages through the Arctic are receiving much attention as glaciers continue to melt. The global navigation satellite system (GNSS) can provide real-time observation data for the polar areas, but may suffer low elevation problems of satellites, signals with poor carrier-power-to-noise-density ratio (C/N0), ionospheric scintillations, and dynamic requirements. In order to improve the navigation performance in polar areas, a deep-coupled navigation system with dual-frequency GNSS and a grid strapdown inertial navigation system (SINS) is proposed in the paper. The coverage and visibility of the GNSS constellation in polar areas are briefly reviewed firstly. Then, the joint dual-frequency vector tracking architecture of GNSS is designed with the aid of grid SINS information, which can optimize the tracking band, sharing tracking information to aid weak signal channels with strong signal channels and meet the dynamic requirement to improve the accuracy and robustness of the system. Besides this, the ionosphere-free combination of global positioning system (GPS) L1 C/A and L2 signals is used in the proposed system to further reduce ionospheric influence. Finally, the performance of the system is tested using a hardware simulator and semiphysical experiments. Experimental results indicate that the proposed system can obtain a better navigation accuracy and robust performance in polar areas.

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Fault Detection and Exclusion Method for a Deeply Integrated BDS/INS System

Sensors ◽

10.3390/s20071844 ◽

2020 ◽

Vol 20 (7) ◽

pp. 1844

Author(s):

Junren Sun ◽

Zun Niu ◽

Bocheng Zhu

Keyword(s):

Fault Detection ◽

Navigation System ◽

Satellite System ◽

Navigation Satellite ◽

Vector Tracking ◽

Tightly Coupled ◽

Tracking Loops ◽

Deep Integration ◽

Navigation Service ◽

Global Navigation Satellite

The Inertial Navigation System (INS) is often fused with the Global Navigation Satellite System (GNSS) to provide more robust and superior navigation service, especially in degraded signal environments. Compared with loosely and tightly coupled architectures, the Deep Integration (DI) architecture has better tracking and positioning performance. Information is shared among channels, and the assistant information from INS helps to reduce the dynamic stress of tracking loops. However, this vector tracking architecture may result in easy propagation of errors among tracking channels. To solve this problem, a Fault Detection and Exclusion (FDE) method for the deeply integrated BeiDou Navigation Satellite System (BDS)/INS navigation system is proposed in this paper. This method utilizes pre-filters’ outputs and integration filter’s estimations to form test statistics. These statistics can help to detect and exclude both step errors and Slowly Growing Errors (SGEs) correctly. The monitoring capability of the method was verified by a simulation which was based on a software receiver. The simulation results show that the proposed FDE method works effectively. Additionally, the method is convenient to be implemented in real-time applications because of its simplicity.

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Observability Analysis and Navigation Filter Optimization of High-Orbit Satellite Navigation System Based on GNSS

Applied Sciences ◽

10.3390/app10217513 ◽

2020 ◽

Vol 10 (21) ◽

pp. 7513

Author(s):

Yaqi Xiao ◽

Xuanying Zhou ◽

Jiongqi Wang ◽

Zhangming He ◽

Haiyin Zhou

Keyword(s):

Navigation System ◽

Estimation Error ◽

Satellite System ◽

Filter Method ◽

Observation Data ◽

Satellite Navigation System ◽

Observability Analysis ◽

Spatial Geometry ◽

High Orbit ◽

Global Navigation Satellite

Global Navigation Satellite System (GNSS) can be applied for the navigation of the high-orbit satellites. The system observability will change due to the changes in the visible satellite numbers and the spatial geometry between the navigation satellites and the users in the navigation system. The influence of the observability changing is not considered in the traditional navigation filter algorithm. In this paper, an optimized navigation filter method based on observability analysis is proposed. Firstly, a novel criterion for the relative observable degree is proposed for each observation component by making use of observation data from previous and posterior time simultaneously. Secondly, according to the relationship between observability and navigation filter accuracy, a novel optimized navigation filter method is constructed by introducing an adjusting factor based on the relative observable degree. Through the comparative simulations with the traditional Extended Kalman Filter (EKF), the optimized navigation filter method can reduce the estimation error of position and velocity by about 36% and 44% respectively. Therefore, the superiority of the proposed filter optimization algorithm is verified.

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Triple-Frequency GPS Un-Differenced and Uncombined PPP Ambiguity Resolution Using Observable-Specific Satellite Signal Biases

Remote Sensing ◽

10.3390/rs12142310 ◽

2020 ◽

Vol 12 (14) ◽

pp. 2310 ◽

Cited By ~ 1

Author(s):

Gen Liu ◽

Fei Guo ◽

Jian Wang ◽

Mingyi Du ◽

Lizhong Qu

Keyword(s):

Ambiguity Resolution ◽

Bias Correction ◽

Correction Method ◽

Satellite System ◽

Space Vehicles ◽

Observation Data ◽

Dual Frequency ◽

Triple Frequency ◽

Original Observation ◽

Global Navigation Satellite

The new generations of global navigation satellite system (GNSS) space vehicles can transmit three or more frequency signals. Multi-frequency observations bring a significant improvement to precise point positioning ambiguity resolution (PPP AR). However, the multi-frequency satellite code and phase biases need to be properly handled before conducting PPP AR. The traditional satellite bias correction methods, for example, the commonly used differential code biases (DCB), are limited to the dual-frequency ionosphere-free (IF) case and become more and more difficult to extend to multi-GNSS and multi-frequency cases. In this contribution, we propose the observable-specific signal bias (OSB) correction method for un-differenced and uncombined (UDUC) PPP AR. The OSB correction method, which includes observable-specific satellite code and phase bias correction, can directly apply kinds of OSBs to GNSS original observation data, thus, it is more appropriate for multi-GNSS and multi-frequency cases. In order to verify the performance of multi-frequency UDUC-PPP AR based on the OSB correction method, triple-frequency GPS observation data provided by 142 Multi-GNSS Experiment (MGEX) stations were used to estimate observable-specific satellite phase biases at the PPP service end and some of them were also used to conduct AR at the PPP user end. The experiment results showed: the averaged time-to-first-fix (TTFF) of triple-frequency GPS kinematic UDUC-PPP AR with observable-specific satellite code bias (SCB) corrections could reach about 22 min with about 29% improvement, compared with that without observable-specific SCB corrections; TTFF of triple-frequency static UDUC-PPP AR with observable-specific phase-specific time-variant inter-frequency clock bias (IFCB) corrections took about 15.6 min with about 64.3% improvement, compared with that without observable-specific IFCB corrections.

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Estimation of fractional cycle bias for GPS/BDS-2/Galileo based on international GNSS monitoring and assessment system observations using the uncombined PPP model

Satellite Navigation ◽

10.1186/s43020-021-00039-x ◽

2021 ◽

Vol 2 (1) ◽

Author(s):

Jin Wang ◽

Qin Zhang ◽

Guanwen Huang

Keyword(s):

Estimation Method ◽

Satellite Orbit ◽

Satellite System ◽

Assessment System ◽

Navigation Satellite ◽

Dual Frequency ◽

Fractional Cycle Bias ◽

The Stability ◽

High Consistency ◽

Global Navigation Satellite

AbstractThe Fractional Cycle Bias (FCB) product is crucial for the Ambiguity Resolution (AR) in Precise Point Positioning (PPP). Different from the traditional method using the ionospheric-free ambiguity which is formed by the Wide Lane (WL) and Narrow Lane (NL) combinations, the uncombined PPP model is flexible and effective to generate the FCB products. This study presents the FCB estimation method based on the multi-Global Navigation Satellite System (GNSS) precise satellite orbit and clock corrections from the international GNSS Monitoring and Assessment System (iGMAS) observations using the uncombined PPP model. The dual-frequency raw ambiguities are combined by the integer coefficients (4,− 3) and (1,− 1) to directly estimate the FCBs. The details of FCB estimation are described with the Global Positioning System (GPS), BeiDou-2 Navigation Satellite System (BDS-2) and Galileo Navigation Satellite System (Galileo). For the estimated FCBs, the Root Mean Squares (RMSs) of the posterior residuals are smaller than 0.1 cycles, which indicates a high consistency for the float ambiguities. The stability of the WL FCBs series is better than 0.02 cycles for the three GNSS systems, while the STandard Deviation (STD) of the NL FCBs for BDS-2 is larger than 0.139 cycles. The combined FCBs have better stability than the raw series. With the multi-GNSS FCB products, the PPP AR for GPS/BDS-2/Galileo is demonstrated using the raw observations. For hourly static positioning results, the performance of the PPP AR with the three-system observations is improved by 42.6%, but only 13.1% for kinematic positioning results. The results indicate that precise and reliable positioning can be achieved with the PPP AR of GPS/BDS-2/Galileo, supported by multi-GNSS satellite orbit, clock, and FCB products based on iGMAS.

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Conditioning and PPP processing of smartphone GNSS measurements in realistic environments

Satellite Navigation ◽

10.1186/s43020-021-00042-2 ◽

2021 ◽

Vol 2 (1) ◽

Author(s):

Ganga Shinghal ◽

Sunil Bisnath

Keyword(s):

Single Point ◽

A Priori ◽

Density Ratio ◽

Satellite System ◽

Quality Parameters ◽

Urban Environments ◽

Dual Frequency ◽

Missing Measurements ◽

Data Gaps ◽

Point Positioning

AbstractSmartphones typically compute position using duty-cycled Global Navigation Satellite System (GNSS) L1 code measurements and Single Point Positioning (SPP) processing with the aid of cellular and other measurements. This internal positioning solution has an accuracy of several tens to hundreds of meters in realistic environments (handheld, vehicle dashboard, suburban, urban forested, etc.). With the advent of multi-constellation, dual-frequency GNSS chips in smartphones, along with the ability to extract raw code and carrier-phase measurements, it is possible to use Precise Point Positioning (PPP) to improve positioning without any additional equipment. This research analyses GNSS measurement quality parameters from a Xiaomi MI 8 dual-frequency smartphone in varied, realistic environments. In such environments, the system suffers from frequent phase loss-of-lock leading to data gaps. The smartphone measurements have low and irregular carrier-to-noise (C/N0) density ratio and high multipath, which leads to poor or no positioning solution. These problems are addressed by implementing a prediction technique for data gaps and a C/N0-based stochastic model for assigning realistic a priori weights to the observables in the PPP processing engine. Using these conditioning techniques, there is a 64% decrease in the horizontal positioning Root Mean Square (RMS) error and 100% positioning solution availability in sub-urban environments tested. The horizontal and 3D RMS were 20 cm and 30 cm respectively in a static open-sky environment and the horizontal RMS for the realistic kinematic scenario was 7 m with the phone on the dashboard of the car, using the SwiftNav Piksi Real-Time Kinematic (RTK) solution as reference. The PPP solution, computed using the YorkU PPP engine, also had a 5–10% percentage point more availability than the RTK solution, computed using RTKLIB software, since missing measurements in the logged file cause epoch rejection and a non-continuous solution, a problem which is solved by prediction for the PPP solution. The internal unaided positioning solution of the phone obtained from the logged NMEA (The National Marine Electronics Association) file was computed using point positioning with the aid of measurements from internal sensors. The PPP solution was 80% more accurate than the internal solution which had periodic drifts due to non-continuous computation of solution.

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Modeling and Performance Evaluation of Precise Positioning and Time-Frequency Transfer with Galileo Five-Frequency Observations

Remote Sensing ◽

10.3390/rs13152972 ◽

2021 ◽

Vol 13 (15) ◽

pp. 2972

Author(s):

Wei Xu ◽

Wen-Bin Shen ◽

Cheng-Hui Cai ◽

Li-Hong Li ◽

Lei Wang ◽

...

Keyword(s):

Three Dimensional ◽

Satellite Orbit ◽

Average Frequency ◽

Satellite System ◽

Observation Data ◽

Navigation Satellite ◽

Dual Frequency ◽

Time Frequency ◽

Combination Model ◽

Frequency Transfer

The present Global Navigation Satellite System (GNSS) can provide at least double-frequency observations, and especially the Galileo Navigation Satellite System (Galileo) can provide five-frequency observations for all constellation satellites. In this contribution, precision point positioning (PPP) models with Galileo E1, E5a, E5b, E5 and E6 frequency observations are established, including a dual-frequency (DF) ionospheric-free (IF) combination model, triple-frequency (TF) IF combination model, quad-frequency (QF) IF combination model, four five-frequency (FF) IF com-bination models and an FF uncombined (UC) model. The observation data of five stations for seven days are selected from the multi-GNSS experiment (MGEX) network, forming four time-frequency links ranging from 454.6 km to 5991.2 km. The positioning and time-frequency transfer performances of Galileo multi-frequency PPP are compared and evaluated using GBM (which denotes precise satellite orbit and clock bias products provided by Geo Forschung Zentrum (GFZ)), WUM (which denotes precise satellite orbit and clock bias products provided by Wuhan University (WHU)) and GRG (which denotes precise satellite orbit and clock bias products provided by the Centre National d’Etudes Spatiales (CNES)) precise products. The results show that the performances of the DF, TF, QF and FF PPP models are basically the same, the frequency stabilities of most links can reach sub10−16 level at 120,000 s, and the average three-dimensional (3D) root mean square (RMS) of position and average frequency stability (120,000 s) can reach 1.82 cm and 1.18 × 10−15, respectively. The differences of 3D RMS among all models are within 0.17 cm, and the differences in frequency stabilities (in 120,000 s) among all models are within 0.08 × 10−15. Using the GRG precise product, the solution performance is slightly better than that of the GBM or WUM precise product, the average 3D RMS values obtained using the WUM and GRG precise products are 1.85 cm and 1.77 cm, respectively, and the average frequency stabilities at 120,000 s can reach 1.13 × 10−15 and 1.06 × 10−15, respectively.

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Implementation of a Dual-Frequency GLONASS and GPS L1 C/A Software Receiver

Journal of Navigation ◽

10.1017/s0373463309990476 ◽

2010 ◽

Vol 63 (2) ◽

pp. 269-287 ◽

Cited By ~ 4

Author(s):

S. Abbasian Nik ◽

M. G. Petovello

Keyword(s):

Global Navigation Satellite System ◽

Critical Role ◽

Satellite System ◽

Navigation Satellite ◽

Dual Frequency ◽

Software Receiver ◽

The Public ◽

Global Navigation ◽

Global Navigation Satellite

These days, Global Navigation Satellite System (GNSS) technology plays a critical role in positioning and navigation applications. Use of GNSS is becoming more of a need to the public. Therefore, much effort is needed to make the civilian part of the system more accurate, reliable and available, especially for the safety-of-life purposes. With the recent revitalization of Russian Global Navigation Satellite System (GLONASS), with a constellation of 20 satellites in August 2009 and the promise of 24 satellites by 2010, it is worthwhile concentrating on the GLONASS system as a method of GPS augmentation to achieve more reliable and accurate navigation solutions.

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

International Journal of Online Engineering (iJOE) ◽

10.3991/ijoe.v12i03.5450 ◽

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.

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Assessing the quality of ionospheric models through GNSS positioning error: methodology and results

GPS Solutions ◽

10.1007/s10291-019-0918-z ◽

2019 ◽

Vol 24 (1) ◽

Cited By ~ 6

Author(s):

Adrià Rovira-Garcia ◽

Deimos Ibáñez-Segura ◽

Raul Orús-Perez ◽

José Miguel Juan ◽

Jaume Sanz ◽

...

Keyword(s):

Satellite System ◽

Ionospheric Delay ◽

Single Frequency ◽

Positioning Error ◽

Dual Frequency ◽

Error Sources ◽

Ionospheric Models ◽

Evaluation Metric ◽

Global Navigation Satellite

Abstract Single-frequency users of the global navigation satellite system (GNSS) must correct for the ionospheric delay. These corrections are available from global ionospheric models (GIMs). Therefore, the accuracy of the GIM is important because the unmodeled or incorrectly part of ionospheric delay contributes to the positioning error of GNSS-based positioning. However, the positioning error of receivers located at known coordinates can be used to infer the accuracy of GIMs in a simple manner. This is why assessment of GIMs by means of the position domain is often used as an alternative to assessments in the ionospheric delay domain. The latter method requires accurate reference ionospheric values obtained from a network solution and complex geodetic modeling. However, evaluations using the positioning error method present several difficulties, as evidenced in recent works, that can lead to inconsistent results compared to the tests using the ionospheric delay domain. We analyze the reasons why such inconsistencies occur, applying both methodologies. We have computed the position of 34 permanent stations for the entire year of 2014 within the last Solar Maximum. The positioning tests have been done using code pseudoranges and carrier-phase leveled (CCL) measurements. We identify the error sources that make it difficult to distinguish the part of the positioning error that is attributable to the ionospheric correction: the measurement noise, pseudorange multipath, evaluation metric, and outliers. Once these error sources are considered, we obtain equivalent results to those found in the ionospheric delay domain assessments. Accurate GIMs can provide single-frequency navigation positioning at the decimeter level using CCL measurements and better positions than those obtained using the dual-frequency ionospheric-free combination of pseudoranges. Finally, some recommendations are provided for further studies of ionospheric models using the position domain method.

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Kinematic PPP Using Mixed GPS/Glonass Single-Frequency Observations

Artificial Satellites ◽

10.2478/arsa-2019-0008 ◽

2019 ◽

Vol 54 (3) ◽

pp. 97-112

Author(s):

Mostafa Hamed ◽

Ashraf Abdallah ◽

Ashraf Farah

Keyword(s):

Low Cost ◽

Satellite System ◽

Single Frequency ◽

Future Research ◽

Frequency Data ◽

Dual Frequency ◽

Trajectory Data ◽

Average Improvement ◽

Kinematic Ppp ◽

Global Navigation Satellite

Abstract Nowadays, Precise Point Positioning (PPP) is a very popular technique for Global Navigation Satellite System (GNSS) positioning. The advantage of PPP is its low cost as well as no distance limitation when compared with the differential technique. Single-frequency receivers have the advantage of cost effectiveness when compared with the expensive dual-frequency receivers, but the ionosphere error makes a difficulty to be completely mitigated. This research aims to assess the effect of using observations from both GPS and GLONASS constellations in comparison with GPS only for kinematic purposes using single-frequency observations. Six days of the year 2018 with single-frequency data for the Ethiopian IGS station named “ADIS” were processed epoch by epoch for 24 hours once with GPS-only observations and another with GPS/GLONASS observations. In addition to “ADIS” station, a kinematic track in the New Aswan City, Aswan, Egypt, has been observed using Leica GS15, geodetic type, dual-frequency, GPS/GLONASS GNSS receiver and single-frequency data have been processed. Net_Diff software was used for processing all the data. The results have been compared with a reference solution. Adding GLONASS satellites significantly improved the satellite number and Position Dilution Of Precision (PDOP) value and accordingly improved the accuracy of positioning. In the case of “ADIS” data, the 3D Root Mean Square Error (RMSE) ranged between 0.273 and 0.816 m for GPS only and improved to a range from 0.256 to 0.550 m for GPS/GLONASS for the 6 processed days. An average improvement ratio of 24%, 29%, 30%, and 29% in the east, north, height, and 3D position components, respectively, was achieved. For the kinematic trajectory, the 3D position RMSE improved from 0.733 m for GPS only to 0.638 m for GPS/GLONASS. The improvement ratios were 7%, 5%, 28%, and 13% in the east, north, height, and 3D position components, respectively, for the kinematic trajectory data. This opens the way to add observations from the other two constellations (Galileo and BeiDou) for more accuracy in future research.

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