Standalone Global Navigation Satellite System Research Articles

Multisource‐multitarget cooperative positioning using probability hypothesis density filter in internet of vehicles

AbstractAccurate positioning of intelligent connected vehicle (ICV) is a key element for the development of cooperative intelligent transportation system. In vehicular networks, lots of state‐related measurements, especially the mutual measurements between ICVs, are shared. It is an advisable strategy to fuse these measurements for a more robust positioning. In this context, an innovative framework, referred to as multisource‐multitarget cooperative positioning (MMCP) is presented. In MMCP, ICVs are local information source, that upload both the states of ICVs estimated by on‐board sensors and the relative vectors between surrounding objects and vehicles to a fusion centre. In the fusion centre, ICVs are selected as the global targets, and the relative vectors are converted into global measurements. Then, the MMCP is modelled into a multi‐target tracking problem with specific targets. This paper proposes a low complexity Gaussian mixture probability hypothesis density (GM‐PHD‐LC) filter to match and fuse the global measurements to further improve the estimation of ICVs. The evaluation results show that our GM‐PHD‐LC can provide 10 Hz positioning services in urban area, and significantly improve the positioning accuracy compared to the standalone global navigation satellite system.

Testing Galileo High-Accuracy Service (HAS) in Marine Operations

Global Navigation Satellite System (GNSS) technology supports all phases of maritime navigation and serves as an integral component of the Automatic Identification System (AIS) and, by extension, Vessel Traffic Service (VTS) systems. However, the accuracy of standalone GNSS is often insufficient for specific operations. To address this limitation, various regional and local-area solutions have been developed, such as Differential GNSS (DGNSS), Satellite Based Augmentation Service (SBAS) and Real Time Kinematic (RTK) techniques. A notable development in this field is the recent introduction of the Galileo High-Accuracy Service (HAS), which saw its initial service declared operational by the European Commission (EC) on 24 January 2023. Galileo HAS provides high-accuracy Precise Point Positioning (PPP) corrections (orbits, clocks and signal biases) for Galileo and GPS, enhancing real-time positioning performance at no additional cost to users. This article presents the results of the first Galileo HAS testing campaign conducted at sea using a buoy-laying vessel temporarily equipped with a Galileo HAS User Terminal. The results presented in this Article include accuracy and position availability performance achieved using the Galileo HAS User Terminal. The article also highlights challenges posed by high-power radio-frequency interference, which likely originated from the Long-Range Identification and Tracking (LRIT) system antenna on board the vessel. Furthermore, the article provides additional assessments for different phases of navigation, demonstrating better performance in slow-motion scenarios, particularly relevant to mooring and pilotage applications. In these scenarios, values for horizontal accuracy reached 0.22 m 95% and 0.13 m 68% after removing interference periods. These results are in line with the expectations outlined in the Galileo HAS Service Definition Document (SDD).

A Novel Single Differencing Measurement for Multipath Detection

Increased global dependence on Global Navigation Satellite Systems (GNSSs) has resulted in a high demand for greater precision and reliable measurements from GNSS receivers. The multipath problem is the single largest source of errors in modernised GNSSs. Double differencing techniques, such as Code Minus Carrier (CMC) have been shown to accurately detect and measure multipath, allowing for corrections to be made via Ground Base Augmentation Systems (GBAS), for example. However, these techniques require at least two receivers and the protection provided is not extended to stand-alone receivers. This paper introduces a new single differencing technique for the accurate detection of multipath in standalone GNSS receivers receiving modernised Binary Offset Carrier (BOC)-modulated signals. Similarities to CMC are drawn before the novel measurement, Code minus Subcarrier, (CMS) is characterised statistically and a threshold for multipath detection is determined. The effectiveness and sensitivity of this novel measurement as a multipath detection technique are analysed through simulation and multipath error envelope analysis. It will be shown that multipath echos capable of inducing a psuedorange error larger than the threshold are detectable at any amplitude. The method is finally verified using simulated fixed offset multipath, confirming that when code and subcarrier early–late spacings are optimal, all ranges of multipath delays, even as small as 21 meters, are detectable. This novel method of multipath detection requires no additional complex correlators than already exist in the chosen tracking algorithm, thus, providing excellent detection with minimum complexity added to the receiver structure.

Sky-view images aided NLOS detection and suppression for tightly coupled GNSS/INS system in urban canyon areas

Although the global navigation satellite system (GNSS) and inertial navigation system (INS) integration framework has many advantages compared to the standalone GNSS and INS systems, its accuracy can be severely degraded in urban canyon areas, due to non-line-of-sight (NLOS) signals. Detection and suppression of NLOS signals are the key to improving the location accuracy of urban areas. Therefore, this paper proposes a method for NLOS detection using the improved region growing algorithm on sky-view images captured by a fish-eye camera. After obtaining NLOS detection results, this paper constructs a weighted model with an adaptive scale factor to suppress the influence of NLOS signals. Experimental results show that the proposed method can effectively improve the performance of NLOS detection and suppression. On this basis, a tightly coupled GNSS/INS integration system based on an extended Kalman filter is developed and tested on the vehicle equipment. Results show that the proposed method outperforms the traditional GNSS single point positioning (SPP) and tightly coupled GNSS SPP/INS integration on positioning accuracy. The root mean square error can be reduced by 33.7% and 24.6% in the north and east directions respectively. It indicates that the tightly coupled GNSS SPP/INS integration aided by the fish-eye camera has certain research value and potential on positioning in urban canyon areas.

Unscented Kalman filter for a low-cost GNSS/IMU-based mobile mapping application under demanding conditions

For the last two decades, low-cost Global Navigation Satellite System (GNSS) receivers have been used in various applications. These receivers are mini-size, less expensive than geodetic-grade receivers, and in high demand. Irrespective of these outstanding features, low-cost GNSS receivers are potentially poorer hardwares with internal signal processing, resulting in lower quality. They typically come with low-cost GNSS antenna that has lower performance than their counterparts, particularly for multipath mitigation. Therefore, this research evaluated the low-cost GNSS device performance using a high-rate kinematic survey. For this purpose, these receivers were assembled with an Inertial Measurement Unit (IMU) sensor, which actively transmited data on acceleration and orientation rate during the observation. The position and navigation parameter data were obtained from the IMU readings, even without GNSS signals via the U-blox F9R GNSS/IMU device mounted on a vehicle. This research was conducted in an area with demanding conditions, such as an open sky area, an urban environment, and a shopping mall basement, to examine the device's performance. The data were processed by two approaches: the Single Point Positioning-IMU (SPP/IMU) and the Differential GNSS-IMU (DGNSS/IMU). The Unscented Kalman Filter (UKF) was selected as a filtering algorithm due to its excellent performance in handling nonlinear system models. The result showed that integrating GNSS/IMU in SPP processing mode could increase the accuracy in eastward and northward components up to 68.28% and 66.64%. Integration of DGNSS/IMU increased the accuracy in eastward and northward components to 93.02% and 93.03% compared to the positioning of standalone GNSS. In addition, the positioning accuracy can be improved by reducing the IMU noise using low-pass and high-pass filters. This application could still not gain the expected position accuracy under signal outage conditions.

Image Mapping Accuracy Evaluation Using UAV with Standalone, Differential (RTK), and PPP GNSS Positioning Techniques in an Abandoned Mine Site.

Global navigation satellite systems (GNSSs) provide a common positioning method that utilizes satellite signals to determine the spatial location of a receiver. However, there are several error factors in standalone GNSS positioning due to instrumental, procedural, and environmental factors that arise during the signal transmission process, and the final positioning error can be up to several meters or greater in length. Thus, real-time kinematic (RTK) correction and post-mission precise point positioning (PPP) processing technologies are proposed to improve accuracy and accomplish precise position measurements. To evaluate the geolocation accuracy of mosaicked UAV images of an abandoned mine site, we compared each orthomosaic image and digital elevation model obtained using standalone GNSS positioning, differential (RTK) GNSS positioning, and post-mission PPP processing techniques. In the three types of error evaluation measure (i.e., relative camera location error, ground control points-based absolute image mapping error, and volumetric difference of mine tailings), we found that the RTK GNSS positioning method obtained the best performance in terms of the relative camera location error and the absolute image mapping error evaluations, and the PPP post-processing correction effectively reduced the error (69.5% of the average total relative camera location error and 59.3% of the average total absolute image mapping error) relative to the standalone GNSS positioning method. Although differential (RTK) GNSS positioning is widely used in positioning applications that require very high accuracy, post-mission PPP processing can also be used in various fields in which it is either not feasible to operate expensive equipment to receive RTK GNSS signals or network RTK services are unavailable.

A methodology for long-term offshore structural health monitoring using stand-alone GNSS: case study in the Gulf of Mexico

This article presents a robust methodology for long-term offshore structural health monitoring (SHM) using the Global Navigation Satellite Systems (GNSS). The methodology relies on recently developed regional reference frames and single-receiver phase-ambiguity-fixed Precise Point Positioning techniques. The stable Gulf of Mexico Reference Frame 2020 (GOM20) provides a robust and consistent reference system for long-term offshore SHM in the Gulf of Mexico (GOM). Continuous GNSS observations (DEV1, 2010–2020) on a fixed platform in the Eugene Island 330 oil field are used to illustrate the methodology. The platform was installed in 1982 in 82-m water about 130 km away from the Mississippi Delta coastline. The major monitoring items include horizontal movements, seafloor subsidence, structure submergence, and seasonal oscillations. The stand-alone GNSS monitoring achieves 3- to 4-mm root-mean-square accuracy in the horizontal direction and 7 mm in the vertical direction for daily positions in the GOM region. According to this study, the GNSS antenna (DEV1) has moved 6 cm toward the northeast with respect to GOM20 since 2010; the ongoing structure submergence rate in the Eugene Island 330 oil field area is approximately 15 mm/year, a combination of seafloor subsidence (12 mm/year) and sea-level rise (2.6 mm/year) with respect to GOM20. The submergence in the future 40 years (2021–2060) would be greater than 0.6 m, likely between 0.8 and 1.0 m, but is unlikely to exceed 1.3 m. The peak-to-trough amplitudes of the seasonal movements at the top of the platform are below 5 mm in all three directions, comparable with the seasonal movements recorded by onshore GNSS in the Louisiana coastal region. The methodology introduced in this article can be applied to SHM in other offshore regions where stable regional reference frames are available.

Methods to assess validity of positioning systems in team sports: can we do better?

ObjectivesThere is previously reported a large variety of criterion measures and reference systems applied to validate position tracking systems in sports. This study aims to investigate the effect of different...

A Positioning System in an Urban Vertical Heterogeneous Network (VHetNet)

Global navigation satellite systems (GNSSs) are essential in providing localization and navigation services to most of the world due to their superior coverage. However, due to high pathloss and inevitable atmospheric effect, the positioning performance of any standalone GNSS is still poor in urban areas. To enhance the positioning performance of legacy GNSSs in urban areas, a positioning system, which utilizes high altitude platform station (HAPS) and 5G gNodeBs (gNBs), in a futuristic urban vertical heterogeneous network (VHetNet) is proposed. In this paper, we demonstrate the effectiveness of gNBs in improving the vertical positioning performance for both the GPS-only system and the HAPS-aided GPS system by analyzing the impact of the density of gNBs and the pseudorange error of gNB on the positioning performance of the gNB augmented positioning systems. We also demonstrate the effectiveness of receiver autonomous integrity monitoring (RAIM) algorithms on the HAPS and/or gNB aided GPS systems in urban areas.

Innovation-Based Fault Detection and Exclusion Applied to Ultra-WideBand Augmented Urban GNSS Navigation

Due to their ability to provide a worldwide absolute outdoor positioning, Global Navigation Satellite Systems (GNSS) have become a reference technology in terms of navigation technologies. Transportation-related sectors make use of this technology in order to obtain a position, velocity, and time solution for different outdoor tasks and applications. However, the performance of GNSS-based navigation is degraded when employed in urban areas in which satellite visibility is not good enough or nonexistent, as the ranging signals become obstructed or reflected by any of the numerous surrounding objects. For these situations, Ultra-Wideband (UWB) technology is a perfect candidate to complement GNSS as a navigation solution, as its anchor trilateration-based radiofrequency positioning resembles GNSS’s principle. Nevertheless, this fusion is vulnerable to interferences affecting both systems, since multiple signal-degrading error sources can be found in urban environments. Moreover, an inadequate location of the augmenting UWB transmitters can introduce additional errors to the system due to its vulnerability to the multipath effect. Therefore, the misbehavior of an augmentation system could lead to unexpected and critical faults instead of improving the performance of the standalone GNSS. Accordingly, this research work presents the performance improvement caused by the application of Fault Detection and Exclusion methods when applied to a UWB-augmented low-cost GNSS system in urban environments.

Unmodeled-error-corrected stochastic assessment for a standalone GNSS receiver regardless of the number of tracked frequencies

Appropriate stochastic modeling is crucial to Global Navigation Satellite System (GNSS) applications. However, traditional methods based on the zero baseline and ultra-short baseline cannot accurately estimate the stochastic characteristics of GNSS measurements of a complete receiving system, i.e., receiver, antenna, low-noise amplifier, and cable. We propose the unmodeled-error-corrected stochastic assessment methods that can be used for a standalone receiver regardless of the number of tracked frequencies. First, the raw observation equations considering the unmodeled errors are deduced based on the geometry-free or geometry-based model. Second, some parameters are chosen as the datum for rank deficiency elimination. Third, the multi-epoch parameterization is used to correct the unmodeled errors in the reparametrized observation model. Finally, the covariance component estimation can be applied to determine the variance components. Three different and representative measurement campaigns were conducted, including the low-cost board, integrated receiver, and smart phone. The results show that the proposed method based on a standalone receiver can assess the stochastic characteristics of GNSS measurements. Since the stochastic characteristics of different low-cost receivers share different patterns, and the noise from the internal antenna cannot be easily ignored, the proposed method is essential.

Infrastructure camera calibration with GNSS for vehicle localisation

Intelligent transportation and smart city applications are currently on the rise. In many applications, diverse and accurate sensor perception of vehicles is crucial. Relevant information could be conveniently acquired with traffic cameras, as there is an abundance of cameras in cities. However, cameras have to be calibrated in order to acquire position data of vehicles. This paper proposes a novel automated calibration approach for partially connected vehicle environments. The approach utilises Global Navigation Satellite System positioning information shared by connected vehicles. Corresponding vehicle Global Navigation Satellite System locations and image coordinates are utilised to fit a direct transformation between image and ground plane coordinates. The proposed approach was validated with a research vehicle equipped with a Real-Time Kinematic-corrected Global Navigation Satellite System receiver driving past three different cameras. On average, the camera estimates contained errors ranging from 1.5 to 2.0 m, when compared to the Global Navigation Satellite System positions of the vehicle. Considering the vast lengths of the overlooked road sections, up to 140 m, the accuracy of the camera-based localisation should be adequate for a number of intelligent transportation applications. In future, the calibration approach should be evaluated with fusion of stand-alone Global Navigation Satellite System positioning and inertial measurements, to validate the calibration methodology with more common vehicle sensor equipment.

Assessment of Real-Time PPP with Trimble RTX correction service for real-time dynamic displacement monitoring based on high-rate GNSS observations

Real-time displacement monitoring of earth crust and engineering structures with the Global Navigation Satellite System (GNSS) is highly important for detecting and preventing the damage and possible loss of life during natural phenomena. Nowadays, the Real-Time Kinematic Precise Point Positioning (RT-PPP) method using a stand-alone GNSS receiver can provide fast and accurate dynamic displacement. Trimble Real-Time Extended (RTX) technology enables real-time precise positioning with cm-level accuracy in a short convergence time. The present study investigates, for the first time, the dynamic displacement detection performance of RT-PPP based on CenterPoint RTX correction service for early warning systems and rapid risk assessment. To evaluate the performance of Trimble RTX technology, a series of shake table experiments were conducted and harmonic oscillations with different frequencies and amplitudes were generated. Trimble RTX solutions were obtained at 20 Hz sampling rate and compared with Linear Variable Differential Transformer (LVDT) data, considered as reference, in both frequency and time domains. Results show that Trimble RTX technology can accurately detect the frequency of harmonic motions, whose amplitudes are slightly different from LVDT values because of GNSS inherent noise. The average of Root Mean Square Error (RMSE) values obtained from the differences between LVDT and filtered RTX-derived time series for all events is 3.6 mm. These results indicated that the CenterPoint RTX technology could be employed for real-time and near-real-time applications to monitor structural and earthquake-induced motions accurately.

Loosely Coupled GNSS and IMU Integration for Accurate i-Boat Horizontal Navigation

Global Navigation Satellite System (GNSS) has been widely utilized as a navigation solution for a mobile vehicle, yet stand-alone GNSS is unable to achieve sufficient accuracy in some applications. For example, in aquatic environment, the accuracy position of Unmanned Surface Vehicle (USV) is affected by the wind, current, and waves dynamics. In this case, the integration of GNSS and Inertial Measurement Unit (IMU) is an approach that can be used to support USV localization to achieve an accurate navigation solution. This study integrates GNSS and IMU using Extended Kalman Filter (EKF) to process loosely coupled integration. The integration results show that the estimated x-position is 0.3058 m accurately and the y-position has an accuracy of 0.2780 m. Then, the loosely coupled integration results of EKF were compared with Unscented Kalman Filter (UKF) simulation in the previous studies. The integration of GNSS and IMU using EKF produces a higher RMSE value of 2D position and attitude angle than UKF Scenario I. However, due to the smoothing process, EKF can provide a visually smoother trajectory than UKF, although it has a significant difference from the observed trajectory. On the other hand, the linear velocity estimated by EKF shows better stability compared to UKF in both Scenario I and II.

Validity of the AdMos, Advanced Sport Instruments, GNSS Sensor for Use in Alpine Skiing

The AdMos receiver from Advanced Sport Instruments is a global navigation satellite system (GNSS) frequently used in alpine ski racing, with users from national and professional teams. Therefore, a validation was conducted for use of the AdMos in alpine skiing, using data from both recreational and competitive skiers. Athletes skied a total of 60 km in different measurement and skiing conditions, while carrying both an AdMos and a differential GNSS, which was used as the gold standard. From the GNSS position data, speed, acceleration, turn radius, trajectory incline and impulse were calculated as instantaneous and turn average measures for both GNSS systems and errors between the systems were calculated. The median and interquartile range (IQR) for the instantaneous errors were below 3.5 (3.5) m for horizontal plane position and below 7.0 (4.3) m for the 3D position. The median and IQR for instantaneous errors and turn average errors, respectively, were below 0.04 (0.24)/0.04 (0.16) m/s for speed, below 0.23 (1.06)/0.35 (0.63) m/s2 for acceleration, below 0.47 (5.65)/0.73 (5.3) m for turn radius, and below 0.043 (1.96)/0.42 (1.42) degrees for trajectory incline. The median and IQR for turn average impulse were 0.025 (0.099) BWs. The position error changed gradually and randomly over time, with low noise levels causing smooth trajectories of similar shape but spatially shifted from the true trajectory that allowed the position–time derivation of the performance parameters, and detection of turns with 3% median and 5% IQR error. The accuracy assessment revealed that (1) the error levels were comparable to other consumer-grade standalone GNSS units designed for sport; (2) the trajectories closely resembled the true trajectories but with a random shift that changed over time and had a low noise level; (3) there was a very low instantaneous speed error that may allow the detection of many performance aspects of skiing and other sports; and (4) there were larger instantaneous errors for the remaining performance parameters, which decreased substantially when averaged over a turn.

Structure and Performance Analysis of Signal Acquisition and Doppler Tracking in LEO Augmented GNSS Receiver.

Due to the low signal power, the Global Navigation Satellite System (GNSS) signal is vulnerable to interference and even cannot be captured or tracked in harsh environments. As an alternative, the Low Earth Orbit (LEO) satellite has been widely used in the navigation field due to the advantages of low cost and strong signals. It is becoming a significant component of the new combined navigation system with GNSS. The combination of an LEO Doppler signal and GNSS observables can improve the positioning accuracy and high-precision positioning convergence time of the GNSS receiver. However, the GNSS signal receiving capability cannot be improved from this data fusion level. We propose a novel assisted structure where GNSS signal acquisition and Doppler tracking are assisted by LEO Doppler positioning. The receiver uses the LEO signal to achieve Doppler positioning firstly. Then, the coarse position with the GNSS navigation messages received from LEO, as well as the estimated clock information, is used to assist in the acquisition and tracking of GNSS. In this way, the GNSS receiver’s sensitivity can get the benefit from this integrated system. The paper presents the structure of the assisted receiver and analyzes the assisted GNSS signal acquisition and carrier tracking performance in detail. Simulation experiments of this assisted structure are carried out to verify its superiority of acquisition and tracking sensitivity in comparison with standalone GNSS receivers. Theoretical analysis and experimental results show that the proposed acquisition method can achieve 90% detection probability at a carrier-to-noise ratio (C/N0) of 15 dB-Hz, which is about 8 dB higher than the conventional acquisition method without assistance; the proposed tracking method can track weak signals of 5 dB-Hz, which is about 4 dB higher than the conventional method. Therefore, this novel LEO-assisted receiver has significantly improved weak signal acquisition and tracking sensitivity.

Fast Multiple Fault Detection and Exclusion (FM-FDE) Algorithm for Standalone GNSS Receivers

Numerous applications and devices use Global Navigation Satellite System (GNSS)-provided position, velocity and time (PVT) information. However, unintentional interference and malicious attacks render GNSS-provided information unreliable. Receiver Autonomous Integrity Monitoring (RAIM) is considered an effective and lightweight protection method when a subset of the available satellite measurements is affected. However, conventional RAIM Fault Detection and Exclusion (FDE) can be computationally expensive, due to iterative search to exclude faulty signals, in case of many faults and more so for multi-constellation GNSS receivers. Therefore, we propose a fast multiple fault detection and exclusion (FM-FDE) algorithm, to detect and exclude multiple faults for both single and multi-constellation receivers. The novelty is that FM-FDE can effectively exclude faults without an iterative search for faulty signals. FM-FDE calculates position distances of any subset pairs with max{3 + P, 2P} measurements, where P is the number of constellations. Then, the algorithm utilizes statistical testing to examine the distances and identify faulty measurements to exclude from the computation of the resultant PVT solution. We evaluate FM-FDE with synthesized faulty measurements in a collected data set; it shows that FM-FDE is practically equally effective as the conventional Solution Separation (SS) FDE in a single constellation receiver. The computational advantage of FM-FDE is more pronounced in a multi-constellation setting, e.g., being more efficient for GPS-Galileo receivers facing more than 2 faults across both constellations. The trade-off is that FM-FDE slightly degrades performance in terms of detection and false alarm probabilities with small errors, compared to the conventional SS FDE.

Adaptive GNSS Velocimetry Combining Doppler and Carrier Phase Measurements Based on Online Variance Component Estimation

Instantaneous velocity is an important variable for navigation and measurement tasks, and its estimation using a stand-alone global navigation satellite system (GNSS) receiver has important theoretical and practical significance for many applications. Adopting a stand-alone receiver to determine the instantaneous velocity in real-time has the advantages of independence of reference station, simple equipment, superior real-time performance and low cost. With these advantages, a new method is proposed to determine the instantaneous velocity by combining Doppler and carrier phase measurements based on online variance component estimation. This is a data fusion problem described by a state space model, in which the uncertainty of the state space model is tuned online through adaptive filtering. The adaptive variables are optimized using the locally best invariant quadrature unbiased estimate (BIQUE), which are directly estimated without iteration. The GNSS velocimetry principle and Doppler and carrier phase combined velocimetry process are provided in the abstract figure. To verify the proposed approach, simulation and real GNSS data with different sampling intervals are used in experiments. All results demonstrate the efficacy and stability of the proposed approach compared to the conventional approaches.

GNSS velocimeter by adaptively combining carrier phase and Doppler measurements

In order to use a stand-alone global navigation satellite system (GNSS) receiver to determine the stable instantaneous velocity, a new hybrid GNSS velocimetry approach combining carrier phase and Doppler measurements is proposed. This is a data fusion problem. The problem is expressed as a state-space model, in which the deviation between the average velocity determined by the time difference carrier phase approach and the instantaneous velocity is represented by the uncertainty of the state model. In kinematic applications, this uncertainty is often variant and hard to be known in advance, a predefined process noise level of the state model is often not sufficiently accurate in the whole working time. Here, an adaptive Kalman filtering approach is employed to fix this problem. To verify the proposed approach, one static experiment and two dynamic experiments with different sampling intervals are performed, separately. All results demonstrate the validity and stability of the proposed approach.

Clock tuning technique for a disciplined high medium–long-stability GNSS oscillator with precise clock drifts for LEO users

A crucial issue of low earth orbit (LEO) navigation augmentation satellite constellation is to obtain a satellite clock of high medium–long stability (i.e., averaging time of 10–10,000 s) using a disciplined oscillator to reduce satellite size, weight, power consumption and cost, instead of using a large, heavy and expensive space atomic clock. To resolve this difficulty, we propose a new global navigation satellite system (GNSS) clock discipline technique via a stand-alone GNSS receiver. Consequently, high medium–long stability can be attained with the disciplined receiver oscillator. Based on the Doppler measurements calculated from carrier phases, precise clock drifts of the receiver oscillator are derived. According to the motion state of the LEO GNSS receiver, a precise clock drift estimation model is chosen to have good adaptability to the receiver's high dynamic movement. Then, the receiver oscillator is properly tuned to its nominal frequency at each epoch without loss of lock. An automatic closed-loop frequency control system using a third-order frequency-locked loop filter is proposed to periodically compensate the instantaneous frequency offsets of the user clock with respect to its nominal frequency. A nonlinear frequency steering method is proposed to overcome the receiver lost lock problem during the oscillator discipline process. The correctness and effectiveness of the proposed clock tuning technique were numerically verified with MATLAB first. Then, the oscillator discipline performances were tested with a VCH-1008 passive hydrogen maser, a LEO GNSS receiver and a PicoTime clock stability analyzer. With static real GPS data of a static receiver as well as with hardware simulated data of a LEO receiver, both the medium-term and long-term frequency stabilities of the disciplined oscillator were confirmed. Finally, the proposed oscillator discipline technique was implemented in a self-developed LEO GNSS receiver. A high-quality voltage-controlled crystal oscillator mounted on an onboard LEO receiver was used for our test both in a static situation and in a LEO dynamic environment. The experiment results show that the overlapping Allan deviation of the disciplined GNSS oscillator could be less than 7E-12 over periods of 1 to 4,000 s in both the static situation and the LEO moving situation for a 1070 km orbit with 1 Hz epoch sampling rate at the testing stage.