Global Navigation Satellite System Module Research Articles

Developing an Algorithm to Improve Positioning Accuracy of Low-Cost Global Navigation Satellite System Modules

Global Navigation Satellite System (GNSS) technology is the most widely used technique for obtaining positioning and navigation information for various applications. However, GNSS is not an error free technology. Differential GNSS techniques are used to mitigate these errors and different commercial brands of GNSS receivers have been developed to avoid some errors where quality and performance depends heavily on the price tag of such advance GNSS receivers due to the fact that technological capabilities adopted and embedded in each single GNSS receiver. There are user cases where the few or more those capabilities has to keep leave behind thereby compromise the cost to benefit ratio. As an alternative to above problem, some low-cost GNSS modules are now available in the market which has quite low position accuracy but can be developed to address unique requirements of some user cases. In practical situations, Real-Time-Kinematic (RTK) positioning systems cannot be used everywhere due to its technical limitations and GNSS receivers use different levels of techniques such as moving baseline system or Satellite Based Augmentation System (SBAS). Further, heading information is also a very important parameter in marine industry for obtaining the vessel’s orientation. This research attempts to assess the capability of u-blox NEO M8N GNSS module for hydrographic surveys by developing a moving baseline GNSS configuration and simple Kalman filter based algorithm. The developed prototype was tested in both static and kinematic observations. The prototype achieved 0.5-2.5 meters of position accuracy at the 95% confidence level in static observations, while it archived around 3 meters of positioning accuracy in kinematic observations. This is a sufficient accuracy for Order 1a, Order 1b and Order 2 standards of hydrographic surveys according to the IHO S-44 guidelines.

Multi-Phase Fusion for Pedestrian Localization Using Mass-Market GNSS and MEMS Sensors

Precise pedestrian positioning based on smartphone-grade sensors has been a research hotspot for several years. Due to the poor performance of the mass-market Micro-Electro-Mechanical Systems (MEMS) Magnetic, Angular Rate, and Gravity (MARG) sensors, the standalone pedestrian dead reckoning (PDR) module cannot avoid long-time heading drift, which leads to the failure of the entire positioning system. In outdoor scenes, the Global Navigation Satellite System (GNSS) is one of the most popular positioning systems, and smartphone users can use it to acquire absolute coordinates. However, the smartphone's ultra-low-cost GNSS module is limited by some components such as the antenna, and so it is susceptible to serious interference from the multipath effect, which is a main error source of smartphone-based GNSS positioning. In this paper, we propose a multi-phase GNSS/PDR fusion framework to overcome the limitations of standalone modules. The first phase is to build a pseudorange double-difference based on smartphone and reference stations, the second phase proposes a novel multipath mitigation method based on multipath partial parameters estimation (MPPE) and a Double-Difference Code-Minus-Carrier (DDCMC) filter, and the third phase is to propose the joint stride lengths and heading estimations of the two standalone modules, to reduce the long-time drift and noise. The experimental results demonstrate that the proposed multipath error estimation can effectively suppress the double-difference multipath error exceeding 4 m, and compared to other methods, our fusion method achieves a minimum error RMSE of 1.63 m in positioning accuracy, and a minimum error RMSE of 4.71 m in long-time robustness for 20 min of continuous walking.

Automatic travelling of agricultural support robot for a fruit farm -Verification of effectiveness of RTK-GNSS and developed simulator for specification design

Labour shortages and fatal accidents in agricultural work have recently emerged as critical problems in Japan, necessitating productivity enhancement, workload reduction, and safety assurance. Therefore, in Japan and countries with similar agricultural environments, the use of small and inexpensive agricultural robots that can be used in mountain farms and orchards is desirable. In this study, a dynamic positioning test was performed in orchards in a mountainous region to verify the positioning accuracy and stability of the Global Navigation Satellite System (GNSS) and real time kinematic (RTK)-GNSS. In addition, a simulator for an agricultural robot that could consider the environmental information of orchards was developed, and driving tests were conducted using the GNSS data acquired in the simulation. The error of the GNSS module was set to be higher than that for the measured value, and robot travelling in the orchard was simulated. The results of GNSS positioning tests in an orchard near a mountainous area indicate that in the specific environmental conditions, the RTK-GNSS and stand-alone (SA)-GNSS can attain a positioning accuracy with an order of tens of centimetres and few metres, respectively. Moreover, the simulation results based on the GNSS positioning results indicate that a vehicle implementing RTK-GNSS and a simple obstacle detection sensor can travel autonomously in a farmyard without colliding with the tree rows. In contrast, a vehicle implementing SA-GNSS and a simple obstacle detection sensor cannot drive autonomously in an orchard and must realise self-positioning using a more accurate sensor. Therefore, the proposed approach of realising simulations of autonomous agricultural robots based on GNSS data from a real orchard can facilitate the evaluation of practical agricultural robots and confirming safety traveling root. The results demonstrate the possibility of development of small agricultural robot for orchards. We conducted the GNSS positioning test in an orchard at an altitude of approximately 830 m, and a similar performance can be expected under similar agricultural situations because the error of the GNSS module was set to be higher than the measured value in driving simulation test.

Development of a Moving Baseline RTK/Motion Sensor-Integrated Positioning-Based Autonomous Driving Algorithm for a Speed Sprayer

To address problems such as pesticide poisoning and accidents during pest control work and to enable efficient work in this area, the development of a competitively prices speed sprayer with autonomous driving is required. Accordingly, in order to contribute to developing the commercialization of a low-cost autonomous driving speed sprayer, we developed a positioning algorithm and an autonomous driving-based spraying algorithm by using two low-cost global navigation satellite system (GNSS) modules and a low-cost motion sensor. In order to provide stable navigation solutions from the autonomous driving hardware despite disturbances from the electromagnetic field generated by the spraying device, the proposed positioning algorithm, a moving baseline (MB) real-time kinematic (RTK)/motion sensor-integrated positioning algorithm, was developed using a loosely coupled extended Kalman filter. To compare the yaw estimation performance provided by the MB RTK positioning technique, yaw was calculated by post-processing with two types of positioning algorithms: the MB RTK/motion sensor-integrated positioning algorithm and the GNSS RTK/motion sensor-integrated positioning algorithm. In the static test, the precision of the yaw provided by the MB RTK/motion sensor-integrated positioning algorithm was 0.14°, but with the GNSS RTK/motion sensor-integrated positioning algorithm, the precision of the yaw was 4.53°. The static test results confirmed that the proposed positioning algorithm using the yaw provided by the MB RTK positioning technique based on two GNSS modules for measurement, precisely estimated the yaw even when the spray engine was operating. To perform autonomous driving and spraying, an autonomous driving-based spraying algorithm was developed using the MB RTK/motion sensor-integrated positioning algorithm. As a result of two performance tests based on the proposed algorithm in an orchard, autonomous driving and spraying were stably performed according to the set autonomous driving route and spraying method, and the root mean square (RMS) of the path-following error was 0.06 m.

TIGHTLY-COUPLED RTK/INS INTEGRATED NAVIGATION USING A LOW-COST GNSS RECEIVER AND A MEMS IMU

Abstract. The Global Navigation Satellite System (GNSS) real-time kinematics (RTK) is a technology to provide centimeter-level navigation services in outdoor areas. GNSS/INS integration is a typical integrated navigation system, including loosely, tightly, and ultra-tightly coupled integration, which has been studied for decades. Although GNSS aiding INS is a relatively mature system, RTK is rarely used to be integrated with INS. In this work, we present a model with a tightly-coupled (TC) scheme to integrate RTK and INS using an extended Kalman Filter (EKF). Multi-GNSS multi-frequency double-differenced pseudo-ranges and carrier phases are the updates of the measurement model. To make the ambiguity resolution, we used the well-known LAMBDA algorithm to search for the possible ambiguity series, and then use the best integer equivariant (BIE) method to decide on the most likely ambiguities with a proper weighting strategy to select from the ambiguity candidates. To test the performance of the proposed TC integration model, we implemented two field vehicular tests with a low-cost GNSS module equipped with a Micro-Electro-Mechanical System (MEMS) IMU. Using this low-cost platform, our RTK/INS integrated navigation engine can achieve centimeter-level navigation solutions under open sky conditions. In harsh environments, our TC integration system navigates on two scenarios with mean errors of 0.48 and 0.57 m, which is 51% and 28% better than a loosely-coupled system.

An Efficient UD Factorization Implementation of Kalman Filter for RTK Based on Equivalent Principle

Real-time kinematic (RTK) is a technique frequently utilized to provide real-time highly precise positioning services for mobile Internet-of-Things (IoT)-embedded terminals from intelligence appliances and smartphones to autonomous drones and self-driving vehicles. To fully utilize hardware resources, the internal GNSS chips or modules equipped in IoT terminals should satisfy the traits of energy efficiency and low computational complexity. As the number of global navigation satellite system (GNSS) increases, the continuous accumulation of high-dimensional rounding errors, the rough system model, and seriously distorted observations will result in divergence and considerable processing burden in the conventional Kalman filter (KF) process. Computational efficiency is significant in the reduction in the power consumption and intensifies the positioning performance of GNSS receivers. Here, a new filter strategy based on UD factorization, where U stands for the unit upper-triangular factor and D indicates the diagonal factor, is proposed for RTK positioning to enhance the numerical stability and reduce the computational effort. The equivalent principle was applied to turn double-difference (DD) observations into zero-difference (ZD) observations. Then, the UD-factorization-based Kalman filter (UD-KF) is proposed as a way to sequentially provide accurate real-time estimations of the filter states and variance–covariance (VC) matrix. Both static and dynamic tests were carried out with single-frequency data from a GPS to evaluate the performance of UD-KF. The results of the zero-baseline test show that UD-KF can obtain smaller RMS of the estimated parameters as the noise of DD observations was twice that of the ZD observations. A short baseline test showed that, compared to the regular filter approach with DD observations, UD-KF achieved a shorter computation time with a higher data utilization rate for both filtering and fixing stages, with an average improvement of 32% and 18%. Finally, a dynamic test showed that the UD-KF can avoid the undesirable effect of satellite changes. Therefore, compared to KF with DD observations, the UD-KF with equivalent ZD observations can enhance the robustness as well as improve the positioning accuracy of RTK positioning.

Trigger time acquisition system for ground based air shower experiments

For observations of cosmic gamma rays of several TeV or more, many experimental groups conduct ground-based air shower observation experiments. New projects such as Andes Large area PArticle detector for Cosmic ray physics and Astronomy (ALPACA) are also underway. In these experiments, an accurate trigger time measurement system is required when sudden cosmic phenomena are observed. To record such sudden astronomical phenomena, we have developed an event-trigger time recording system that accurately measures the arrival times of air showers. The system consists of a commercial global navigation satellite system module, a high-precision clock, a multi-hit type time-to-digital converter with a reset function for accurate time measurement, and a network-time-protocol server installed on a computer. It was confirmed that the time accuracy compared to UTC was approximately 1μs, and the time deviation was approximately 11.4 ns with one standard deviation. The developed system is versatile and can also be used for the ALPACA experiment. It is expected that the time accuracy of this system can be improved to approximately ±40 ns.

On Use of Low Cost, Compact GNSS Receiver Modules for Ionosphere Monitoring

AbstractGeodetic or special purpose Global Navigation Satellite System (GNSS) receivers are used for ionosphere monitoring and research. Dual frequency, compact, low‐cost commercial GNSS modules can provide raw GNSS data and are commonly used for positioning applications. This paper presents the applicability of these compact modules for monitoring ionospheric activities. A comparative study between Javad Triumph LS, a costly geodetic receiver, and an Ublox ZED‐F9P, a low‐cost, dual‐frequency, compact module is carried out to explore the potential of the low‐cost devices for ionosphere probing. Studies are carried out on signal strength values (C/N0) and vertical total electron content (VTEC) values. From the concurrently collected GPS data, a bias of 2.2–4.9 dBHz in signal strength values are observed between the two types of receivers depending on the signal frequency band. The VTEC values calculated from the Ublox module are in close agreement with the values obtained from the Triumph LS receiver. Therefore, the compact module shows the potential for use in ionosphere monitoring with clear advantages in cost, size, and power consumption. However, the signal strength values obtained from such compact modules need to be calibrated using standard GNSS receivers. A GNSS‐based Ionosphere Monitoring Unit (GIMU) is also proposed in this manuscript by the integration of a compact, low‐cost GNSS module with a single‐board computer and a wireless data communication module. Real‐time, cost‐effective, concurrent ionosphere monitoring over a geographically distributed network is possible using a network of such units.

Performance Assessment of Real-Time Multiconstellation GNSS PPP Using a Low-Cost Dual-Frequency GNSS Module

Abstract The release of low-cost dual-frequency (DF) global navigation satellite system (GNSS) modules provides an opportunity for low-cost precise positioning to support autonomous vehicle applications. The new GNSS modules support the US global positioning system (GPS) L1C/L2C or L5 civilian signals, the Russian GNSS Globalnaya Navigazionnaya Sputnikovaya Sistema (GLONASS) L1/L2, Europe’s GNSS Galileo E1/E5b, and Chinese GNSS BeiDou B1/B2 signals. The availability of the DF measurements allows for removal of the ionospheric delay, enhancing the obtained positioning accuracy. Unfortunately, however, the L2C signals are only transmitted by modernized GPS satellites. This means that fewer GPS DF measurements are available. This, in turn, might affect the accuracy and the convergence of the GPS-only precise point positioning (PPP) solution. Multi-constellation GNSS PPP has the potential to improve the positioning accuracy and solution convergence due to the high redundancy of GNSS measurements. This paper aims to assess the performance of real-time quad-constellation GNSS PPP using the low-cost u-blox Z9D-F9P module. The assessment is carried out for both open-sky and challenging environment scenarios. Static, simulated-kinematic, and actual field-kinematic trials have been carried out to evaluate real-time PPP performance. Pre-saved real-time precise orbit and clock products from the Centre National d’Etudes Spatiales are used to simulate the real-time scenario. It is shown that the quad-constellation GNSS PPP using the low-cost u-blox Z9D-F9P module achieves decimeter-level positioning accuracy in both the static and simulated-kinematic modes. In addition, the PPP solution convergence is improved compared to the dual- and triple-constellation GNSS PPP counterparts. For the actual kinematic trial, decimeter-level horizontal positioning accuracy is achieved through the GPS + GLONASS + Galileo PPP compared with submeter-level positioning accuracy for the GPS + GLONASS and GPS + Galileo PPP counterparts. Additionally, submeter-level vertical positioning accuracy is achieved through the GPS + GLONASS + Galileo PPP compared with meter-level positioning accuracy for GPS + GLONASS and GPS + Galileo PPP counterparts.

A Study on Obtaining Tree Data from Green Spaces in Parks Using Unmanned Aerial Vehicle Images: Focusing on Mureung Park in Chuncheon

Background and objective The purpose of study is to analyze the three-dimensional (3D) structure by creating a 3D model for green spaces in a park using unmanned aerial vehicle (UAV) images. Methods After producing a digital surface model (DSM) and a digital terrain model (DTM) using UAV images taken in Mureung Park in Chuncheon-si, we generated a digital tree height model (DHM). In addition, we used the mean shift algorithm to test the classification accuracy, and obtain accurate tree height and volume measures through field survey. Results Most of the tree species planted in Mureung Park were Pinus koraiensis, followed by Pinus densiflora, and Zelkova serrata, and most of the shrubs planted were Rhododendron yedoense, followed by Buxus microphylla, and Spiraea prunifolia. The average height of trees measured at the site was 7.8 m, and the average height estimated by the model was 7.5 m, showing a difference of about 0.3 m. As a result of the t-test, there was no significant difference between height values of the field survey data and the model. The estimated green coverage and volume of the study site using the UAV were 5,019 m2 and 14,897 m3, respectively, and the green coverage and volume measured through the field survey were 6,339 m2 and 17,167 m3. It was analyzed that the green coverage showed a difference of about 21% and the volume showed a difference of about 13%. Conclusion The UAV equipped with RTK (Real-Time Kinematic) and GNSS (Global Navigation Satellite System) modules used in this study could collect information on tree height, green coverage, and volume with relatively high accuracy within a short period of time. This could serve as an alternative to overcome the limitations of time and cost in previous field surveys using remote sensing techniques.

Point Positioning Capability of Compact, Low-Cost GNSS Modules: A Case Study

Global Navigation Satellite System (GNSS) provides precise Position, Velocity, and Timing (PVT) information. Various types of receivers of varying cost and complexity are used for collection and use of GNSS data. Currently, cost-effective, compact, low power consuming, multi-constellation enabled, single, or dual-frequency GNSS modules are being increasingly available having the capability of providing modest position solution accuracy. This paper presents the results of GPS, BeiDou, and GPS + BeiDou hybrid positioning capabilities of few commercially available modules based on systematic analysis from data collected during two time periods from two locations of India using geodetic and commercial patch antennas w.r.t. the reference points created through PPP (Precise Point Positioning). The results are compared with those provided a survey-grade GNSS receiver. It is witnessed that, selected single frequency module can provide 3-4m 2DRMS (Distance Root Means Square) precision and their dual frequency counterparts can provide 2DRMS solution precision around 3 m in GPS-only operation, around 7 m in BeiDou-only operation and around 3.5 m in case of GPS + BeiDou hybrid operation. The performance of the compact modules clearly presents the cost-performance benefit of the compact modules for real-time applications and the results of this study would help in understanding the capabilities of these modules for mass-market applications.

Compact, Low-cost GNSS Modules for Precise Point Positioning

Global Navigation Satellite System (GNSS) uses Precise Point Positioning (PPP) technique to find out accurate geolocation information of any point. Generally, costly, geodetic GNSS receivers are used for PPP. This manuscript presents the results of studies on the usability of commercial, compact, cost-effective GNSS modules with commercial antennas for PPP in comparison to commonly used geodetic, costly receivers from India, which is a excellent location for GNSS use. Compact GNSS modules from two manufacturers are used in the study, and the encouraging results show the clear advantage of cost, size, and power requirements of such modules. The modules provide sub-cm horizontal solution accuracy which is very similar to those obtained using geodetic receivers, and around 20 cm accuracy in the vertical coordinate, which is slightly inferior to the results provided by the geodetic reveivers. Results of this novel study would be useful for implementing cost-efficient GNSS PPP in real life, in highly demanding geodetic applications including CORS establishment and PPP.

Cyberphysical system for controlling the movement of unmanned vehicles

The active development of unmanned vehicles, in control systems of which most of the currently created artificial intelligence technologies are used, from machine vision systems to decision-making in multi-criteria control tasks, has led to the emergence of such vehicles on public roads and, in fact, has become an objective reality of ours. life. In such a situation, the person driving needs additional information to drive safely. Currently, the road infrastructure is dynamically developing, forming into a developed distributed telecommunication system with accompanying services. And now it is increasingly associated with the concept of "intelligent transport system" (ITS), to which are connected automotive equipment subsystems, wireless communication subsystems, roadside equipment subsystems and a global navigation satellite system module. Unmanned vehicles, which are integrated into the road environment, form a single telecommunication system for controlling the movement of vehicles with it. Wireless technologies and digital models of road infrastructure are important components of such a system. The information technology concept, which implies the integration of computing resources into physical entities, in particular autonomous robots and unmanned vehicles, is called the concept of cyber-physical systems. The computational component in it is distributed throughout the system. The study of the possibility of constructing digital models of roads and road infrastructure with their subsequent intrasystem transfer between interacting objects is undoubtedly of considerable interest. At the research stage of the implementation of such a technology, it is important to analyze the possibility of building and deploying modern ITS, highlight the main problems associated with the visualization of digital ITS models, and propose ways to solve the tasks. As part of the study, an overview of modern wireless technologies and communication standards with the prospect of their application in the infrastructure of the road environment is given, foreign experience of deploying such systems, their features and limitations, is considered. The functional structure of the intelligent transport system is proposed. The results of modeling the road network (creating a digital model of roads) and the practical implementation of software for compiling local maps are presented. The developed software took into account the shortcomings of specialized products on the market, and also implemented the possibility of converting a digital model of roads into the MAPEM format. After preprocessing MAPEM files, they are placed on the server of the intelligent transport system, from where they are then sent via RSU. RSUs start broadcasting this information, and it goes to the unmanned vehicle, which, in turn, processes the received file and waits for a request to move. Upon receipt of such a request, it builds the trajectory of the path and starts moving. The techniques obtained as a result of the research were implemented and applied at the test site.

RTK-LoRa: High-Precision, Long-Range, and Energy-Efficient Localization for Mobile IoT Devices

High-precision global navigation satellite system (GNSS) is a crucial geolocalization feature enabling a wide range of applications, from mobile Internet-of-Things devices to autonomous drones and self-driving vehicles. Real-time kinematic (RTK) is a GNSS technology that attracting increased interest due to the centimeter precision achievable when wireless communication is present on the devices. On the other hand, sending continuously wireless data increases the energy consumption and the cost of the solution, especially when communication is carried over the 4G network. Due to those drawbacks, RTK is not much exploited in the localization of battery-operated devices. This work combines RTK with low-power long-range communication to achieve submeter precision in an energy-efficient RTK-based system. The proposed system exploits a state-of-the-art RTK-GNSS module combined with a long range (LoRa) to achieve geolocalization with minimal wireless radio infrastructure requirements. An energy-efficient algorithm is proposed and implemented in a microcontroller to have a quick startup and high accuracy. We evaluate three different GNSS modules and compare their performance in terms of power and accuracy. Experimental results, with in-field measurements, show that an average geolocalization precision of tens of centimeters is achievable on a battery-operated wireless end node connected to a single base station used as a geostationary reference anchor placed at kilometers of distance. The peak precision measured is below 10 cm.

Potential of Multi constellation Global Navigation Satellite System in Indian Missile Test Range Applications

In this paper, the potentials of using Global Navigation Satellite System (GNSS) techniques in the complex calibration procedure of the tracking sensors for missile test range applications have been presented. The frequently used tracking sensors in test range applications are- electro-optical tracking stations (EOTS) and tracking radars. Over the years, the EOTS are used as the reference for bias estimation of the radars. With the introduction of GPS in test range applications, especially the DGPS, the reference for bias estimation got shifted to DGPS from the EOTS. However, the achievable position solution accuracy is limited to the order of a few meters for DGPS, EOTS, and Radars. With the evolution of Multi-constellation GNSS and carrier-phase based measurement techniques in satellite navigation, achievable position solution accuracies may be improved to sub-meter level. New navigation techniques like real time kinematic (RTK) and precise point positioning have the potentials for use in the calibration procedures of the missile test ranges to the accuracies of centimeter-level. Moreover, because of the availability of a large number of navigation signals over the Indian region, multi-constellation GNSS receivers can enhance signal availability, reliability, and accuracies during the calibration of missile test ranges. Currently available compact, low-cost GNSS modules also offer the possibilities of using these for cost-effective, networked RTK for dynamic calibration of test ranges reducing cost and resource requirements.

INTEGRATION OF A LOW-COST GLOBAL NAVIGATION SATELLITE SYSTEM TO A SINGLE-BOARD COMPUTER USING KALMAN FILTERING

ABSTRACT The global navigation satellite system (GNSS) is the basis for localized crop management by allowing the georeferencing of collected data and the generation of maps by different systems that compose precision agriculture. There is a demand for low-cost navigation systems to enable their use in agriculture. Therefore, the objective of this study is to integrate a low-cost GNSS module to a single-board computer using Kalman filtering to obtain navigation data. The system was evaluated by performing one static and two kinematic experiments, with three repetitions each. In the static experiment, the mean error was 3.25 m with a root mean square error (RMSE) of 3.73 m. In the first kinematic experiment, data variability was lower at a velocity of 1.39 m s−1. In the second kinematic experiment, the mean error was 1.26 and 1.13 m, and the RMSE was 1.45 and 1.27 m for data obtained before and after filtering, respectively. In conclusion, the system reduces the lateral errors in linear sections but is not indicated for sections that change direction. Moreover, this system can be used in agricultural applications such as soil sampling and crop yield monitoring.

Optimal, Recursive and Sub-Optimal Linear Solutions to Attitude Determination from Vector Observations for GNSS/Accelerometer/Magnetometer Orientation Measurement

The integration of the Accelerometer and Magnetometer (AM) provides continuous, stable and accurate attitude information for land-vehicle navigation without magnetic distortion and external acceleration. However, magnetic disturbance and linear acceleration strongly degrade the overall system performance. As an important complement, the Global Navigation Satellite System (GNSS) produces the heading estimates, thus it can potentially benefit the AM system. Such a GNSS/AM system for attitude estimation is mathematically converted to a multi-observation vector pairs matching problem in this paper. The optimal and sub-optimal attitude determination and their time-varying recursive variants are all comprehensively investigated and discussed. The developed methods are named as the Optimal Linear Estimator of Quaternion (OLEQ), Suboptimal-OLEQ (SOLEQ) and Recursive-OLEQ (ROLEQ) for different application scenarios. The theory is established based on our previous contributions, and the multi-vector matrix multiplications are decomposed with the eigenvalue factorization. Some analytical results are proven and given, which provides the reader with a brand new viewpoint of the attitude determination and its evolution. With the derivations of the two-vector case, the n-vector case is then naturally formed. Simulations are carried out showing the advantages of the accuracy, robustness and time consumption of the proposed OLEQs, compared with representative methods. The algorithms are then implemented using the C++ programming language on the designed hardware with a GNSS module, three-axis accelerometer and three-axis magnetometer, giving an effective validation of them in real-world applications. The designed schemes have proven their fast speed and good accuracy in these verification scenarios.

Precise Positioning in Alpine Areas with Troposphere and Multipath Estimation

Real-time kinematic (RTK) positioning with Global Navigation Satellite System (GNSS) signals is widely used, e.g., for surveying, agriculture, and potentially for autonomous vehicles and unmanned air vehicles in the future. In this paper, an extended RTK positioning for significant height differences between two low-cost GNSS receivers with patch antennas is presented. In this case, the classical model for double difference measurements needs to be extended, i.e., a differential tropospheric zenith delay and pseudorange multipath errors need to be estimated besides the baseline and carrier phase integer ambiguities. The increased number of unknowns results in an ill-conditioned system of observation equations and a substantial correlation between the state estimates. We introduce prior information on the differential tropospheric zenith delay based on the differential air pressure and exploit the temporal correlation of pseudorange multipath errors. Moreover, a criterion for the integer ambiguity candidate vector selection is provided, which is robust over phase multipath and unavoidable errors in the float ambiguity covariance matrix. The proposed method is validated with two low-cost GNSS modules that were placed at the Zugspitzplatt (2601 m a.s.l.) and Eibsee (1018 m a.s.l.). The obtained estimates for the baseline and differential tropospheric zenith delay show a high repeatability over several independent ambiguity fixings. The residuals of the fixed carrier phase measurements are within 2 cm for almost all satellites, which confirms both the measurement model and the ambiguity fixing.

Improved GNSS-based indoor positioning algorithm for mobile devices

The widespread use of global navigation satellite system (GNSS) receiver in mobile devices induces the adoption of effective GNSS-based indoor positioning algorithms exploiting low-cost hardware. In a previous study, we proposed a new architecture for indoor positioning system to estimate the user position by utilizing the pseudoranges from the smartphone-embedded GNSS module. The advantages of such a system are low cost and low requirements in terms of hardware-level modification for end users. However, all end users and most application developers do not have permission to read the pseudoranges from the embedded GNSS modules. Instead of pseudoranges, the user positions are easily obtained from the GNSS module in any mobile device. Thus, we further improve our positioning algorithm based on the position obtained from the embedded GNSS module rather than the pseudoranges. This position does not correspond to the true one since the indoor signal is non-line-of-sight. Thus, it is named the pseudo-position. The key to the improved algorithm is that the distances from the user terminal to the indoor transmitting antennas are calculated using the differences between the position of the outside antenna and the pseudo-position. The algorithm is tested using a simulated GNSS-based indoor positioning system which is implemented on a GNSS software receiver. The simulation results show that the indoor positioning system is able to provide horizontal positioning with meter-level accuracy in both static and dynamic situations. Additionally, the proposed method improves the robustness of the indoor positioning system to the non-synchronization measurements.

Smart Device-Supported BDS/GNSS Real-Time Kinematic Positioning for Sub-Meter-Level Accuracy in Urban Location-Based Services.

Using mobile smart devices to provide urban location-based services (LBS) with sub-meter-level accuracy (around 0.5 m) is a major application field for future global navigation satellite system (GNSS) development. Real-time kinematic (RTK) positioning, which is a widely used GNSS-based positioning approach, can improve the accuracy from about 10–20 m (achieved by the standard positioning services) to about 3–5 cm based on the geodetic receivers. In using the smart devices to achieve positioning with sub-meter-level accuracy, a feasible solution of combining the low-cost GNSS module and the smart device is proposed in this work and a user-side GNSS RTK positioning software was developed from scratch based on the Android platform. Its real-time positioning performance was validated by BeiDou Navigation Satellite System/Global Positioning System (BDS/GPS) combined RTK positioning under the conditions of a static and kinematic (the velocity of the rover was 50–80 km/h) mode in a real urban environment with a SAMSUNG Galaxy A7 smartphone. The results show that the fixed-rates of ambiguity resolution (the proportion of epochs of ambiguities fixed) for BDS/GPS combined RTK in the static and kinematic tests were about 97% and 90%, respectively, and the average positioning accuracies (RMS) were better than 0.15 m (horizontal) and 0.25 m (vertical) for the static test, and 0.30 m (horizontal) and 0.45 m (vertical) for the kinematic test.