Frequency Global Navigation Satellite System Research Articles

Multi-frequency and multi-system GNSS positioning data fusion algorithm based on Kalman filter

With the widespread application of Global Navigation Satellite System (GNSS) in the fields of positioning and navigation, traditional single frequency and single system positioning methods are gradually unable to meet the requirements of high accuracy and high reliability. Especially in complex and dynamic environments, GNSS signals are affected by multipath effects, occlusion, and interference, resulting in a significant decrease in positioning accuracy. Therefore, it is particularly important to develop a multi-frequency and multi-system GNSS positioning data fusion algorithm. This article used Kalman filtering technology and combined the data characteristics of multi-frequency and multi-system GNSS signals to study a new positioning data fusion algorithm. By comprehensively processing different GNSS systems and frequency signals, the positioning accuracy and anti-interference ability were significantly improved. The experimental results showed that the algorithm studied improved the average positioning accuracy by more than 6.23% in complex environments compared to traditional methods, and also exhibited good adaptability and stability under dynamic conditions. Fully utilizing the advantages of multi-frequency signals and combining advanced data fusion technology is an effective way to improve GNSS positioning performance, providing new ideas and methods for future intelligent navigation applications.

An open GNSS spoofing data repository: characterization and impact analysis with FGI-GSRx open-source software-defined receiver

Spoofing is becoming a prevalent threat to the users of Global Navigation Satellite Systems (GNSS). It is important to deepen our understanding of spoofing attacks and develop resilient techniques to effectively combat this threat. Detecting and mitigating these attacks requires thorough testing, typically conducted in a laboratory environment through the establishment of a spoofing test-bed. The complexity, cost and resource demands of creating such a test-bed underscore the necessity of utilizing openly available datasets. To address this need, this paper introduces a new GNSS spoofing data repository from Finnish Geospatial Research Institute (FGI) named hereafter as ‘FGI-SpoofRepo’. This data repository consists of raw In-phase and Quadrature (I/Q) data of live recordings of GPS L1 C/A, Galileo E1, GPS L5, and Galileo E5a signals. These datasets encompass three distinct types of spoofing characteristics (synchronous, asynchronous, and meaconing), making them very useful example candidates of open data for testing the performance of any anti-spoofing techniques (be it detection or mitigation). The inclusion of live signals in multiple GNSS frequencies and the presence of cryptographic signatures in Galileo E1 signal make these datasets potential benchmarks for assessing the resilience performance of multi-frequency multi-constellation receivers. The analysis of the datasets is carried out with an open-source MATLAB-based software-defined receiver, FGI-GSRx. An updated version of FGI-GSRx, equipped with the necessary modifications for processing and analyzing the new datasets, is released alongside the datasets. Therefore, the GNSS research community can utilize the open-source FGI-GSRx or any third-party SDR to process the publicly available raw I/Q data for implementation, testing and validation of any new anti-spoofing technique. The results show that time-synchronous spoofing seamlessly takes over positioning solution, while time-asynchronous spoofing acts as noise or in some cases, completely prevent the receiver from providing a positioning solution. Signal re-acquisition during an ongoing spoofing attack (cold start), the receiver tends to lock onto the spoofing signal with the highest peak, posing a potential threat to GNSS receivers without assisted information. Overall, this research aims to advance the understanding of complex spoofing attacks on GNSS signals, providing insight into enhancing resilience in navigation systems.

OBU for Accurate Navigation through Sensor Fusion in the Framework of the EMERGE Project

With the development of advanced driver assistance systems (ADAS) and autonomous vehicles (AV), recent years have seen an increasing evolution of onboard sensors and communication interfaces capable of interacting with available infrastructures, including satellite constellations, road structures, modern and heterogeneous network systems (e.g., 5G and beyond) and even adjacent vehicles. Consequently, it is essential to develop architectures that cover data fusion (multi–sensor approach), communication, power management, and system monitoring to ensure accurate and reliable perception in several navigation scenarios. Motivated by the EMERGE project, this paper describes the definition and implementation of an On Board Unit (OBU) dedicated to the navigation process. The OBU is equipped with the Xsens MTi–630 AHRS inertial sensor, a multi–constellation/multi–frequency Global Navigation Satellite System (GNSS) receiver with the u–blox ZED–F9P module and communication interfaces that afford access to the PointPerfect augmentation service. Experimental results show that GNSS, with corrections provided by augmentation, affords centimetre accuracy, with a Time To First Fix (TTFF) of about 30 s. During the on–road tests, we also collect: the output of fusion with inertial sensor data, monitoring information that assess correct operation of the module, and the OBU power consumption, that remains under 5 W even in high–power operating mode.

3D Traveling Ionospheric Disturbances During the 2022 Hunga Tonga–Hunga Ha’apai Eruption Using GNSS TEC

AbstractThe dual frequency Global Navigation Satellite System (GNSS) observations could determine the total electron content (TEC) in the ionosphere. In this study, GNSS TEC was applied to detect traveling ionospheric disturbances (TIDs) after the eruption of Hunga Tonga–Hunga Ha’apai (HTHH) on 15 January 2022. The eruption caused two types of tsunamis, first is tsunami generated by atmospheric wave (meteo‐tsunami) and second is caused by eruption induces water displacement or tsunami classic. At the same time with former tsunami, the atmospheric wave (shock and lamb waves) also caused TIDs at a speed of approximately ∼0.3 km/s. We found moderate correlation between this TIDs amplitude and the tsunami wave height model from tide gauge stations in New Zealand (0.64) and Australia (0.65). Further we attempted to reveal 3D structure of the TIDs in New Zealand, South Australia, and Philippines using 3D tomography. The tomography was set up > 1,170 blocks, as large as 1.0° (east–west) × 1.0° (north–south) × 100 km (vertical), up to 600 km altitude over selected regions. Tomogram shows beautiful concentric directivity of the first TIDs generated by atmospheric wave (AW).

On the strength of E and F region irregularities for GNSS scintillation in the dayside polar ionosphere

We present results of the study conducted to quantify the relative contribution of different ionospheric regions to phase scintillation in Global Navigation Satellite Systems (GNSS) at the dayside high latitude ionosphere. By taking advantage of the scanning capability of the 32-m EISCAT radar in Svalbard (ESR) and its recurrent favourable location below the dayside auroral region, we developed a methodology to identify conjunctions between the radar and GNSS satellite signals in order to compare density irregularities identified by the radar with scintillation observed in GNSS signals. The analysis revealed that the dayside ionosphere contained irregularities predominantly in the F region with scintillation occurring 77% of the times. The likelihood of observing irregularities in the E region were comparatively less with a scintillation occurrence rate of 42%. The study therefore strongly suggests that the dayside F region is more structured than the E region and is the predominant source region for irregularities that cause scintillation at GNSS frequencies. The associated ionospheric conditions revealed enhanced F region electron and ion temperatures to be collocated with scintillation for majority of the times. This supports the fact that cusp/auroral dynamics play a crucial role in creating F region irregularities which can act as sources of scintillation in GNSS signals. The presented results provide a quantitative estimate of the effectiveness of irregularities and the associated ionospheric conditions in different regions of the dayside ionosphere during scintillation, which are relevant for high latitude modelling and instability studies as well as for space weather applications.

GNSS interference monitoring and detection based on the Swedish CORS network SWEPOS

Abstract The presence of Global Navigation Satellite System (GNSS) interference poses a significant risk to both GNSS and the infrastructures that depend on them. This article describes how an existing GNSS infrastructure, the Swedish Continuously Operating Reference Stations network SWEPOS with more than 500 stations, can be leveraged to control the quality of GNSS signals and to be able to detect interferences in GNSS and adjacent frequency bands. This study introduces a SWEPOS-based automatic system that effectively detects GNSS interference by examining the signal-to-noise ratio (SNR) of Global Positioning System, Globalnaya Navigatsionnaya Sputnikovaya Sistema, Galileo, and BeiDou frequency bands. By comparing the SNR of tracked satellites against historical data, the system detects radio frequency interference (RFI) by statistically characterizing the SNR of simultaneously tracked satellites. Furthermore, based on the SNR characteristics across satellites, the system distinguishes between RFI and non-RFI sources. The effectiveness of the detection system is demonstrated through both simulated signal interference waves and real-world interference events.

Design of Light, Small, and High-precision Digital Servo Clock for LEO Constellation

Modern low earth orbit (LEO) satellite systems have placed increasingly stringent requirements on spaceborne time-frequency systems in the fields of constellation autonomous management, distributed synthetic aperture radar (SAR) imaging, and navigation time service. Admittedly, the original high-stability constant-temperature crystal oscillator and high-stability temperature-compensated crystal oscillator can no longer comply with the indicator requirements of clock source frequency characteristics and clock synchronization accuracy. Likewise, traditional satellites use atomic clocks (rubidium atomic clocks and cesium atomic clocks). On account of their inherent characteristics, the ground receiving system needs to observe and count the clock parameter characteristics for a long time after the satellite enters orbit and frequently modify the future working state parameters. The features of being expensive and bulky increase the operation and maintenance costs of the ground system and the complexity of engineering implementation. In this paper, a kind of light and small high-precision digital servo clock based on the deep coupling of the global navigation satellite system (GNSS) is designed for the LEO satellite constellation. The tame clock is deeply coupled with the GNSS navigation receiver, and the high precision time-frequency difference between the local clock frequency source and GNSS is obtained by using the carrier and pseudo-range measurement information of visible satellite and carrier phase measurement information of the receiver. It not only utilizes the short-term high stability of OCXO but also employs the long-term time-frequency maintenance ability of GNSS so that the tamed OCXO is locked in GNSS for a long time, which can achieve frequency calibration of local clock sources and long-term output to various space-borne systems. The system is small in size and low in power consumption, with output frequency stability better than 3E-13 (10000 s), accuracy better than ±2E-13, and timing accuracy better than ±10 ns, which is comparable to the key technical indexes of spaceborne miniaturized rubidium clocks, in line with the current demand of miniaturization, low power consumption, and low cost of LEO constellations.

Machine learning approach for detection of plasma depletions from TEC

Ionospheric delay is of concern for trans-ionospheric radio communication, especially for the navigation systems relying on these satellite signals. Most of the ionospheric delays are estimated to a degree of first-order using dual frequency global navigation satellite system (GNSS) receivers except during irregularities and equatorial plasma bubbles. The plasma bubbles are observed as a decrease or reduction in total electron content (TEC) as a result of large-scale irregularities that are generated at the equatorial ionosphere. These plasma bubbles can be detected from TEC values visually or by using mathematical algorithms. The mathematical algorithms may have limitations based on assumptions made for the current dataset. Therefore, various machine learning (ML) techniques were tried by training them with selected TEC depletions that are verified for accuracy. From this study, the Random Forest Method (RFM) has performed well compared to other ML methods. The RFM is trained to use for the detection of TEC depletions from the Indian low-latitude region. The training accuracy obtained is 97.6%, with a minimum classification error of 0.023%. The result obtained from the confusion matrix ascertained that the proportion of positively classified cases that are truly positive that is the positive predictive value (PPV) is 96.8%. These statistical results are validated after plotting the observed TEC depletion patch obtained from the ML method. There are cases in which depletions detected by the ML method are appreciable over the mathematical algorithm. The ML technique once trained will not have inherent limitations, as there are no assumptions or threshold values needed to set as required by most of the mathematical algorithms. Thus, the results are encouraging and have scope for further improvement and advancement.

State transformation extended Kalman filter–based tightly coupled strapdown inertial navigation system/global navigation satellite system/laser Doppler velocimeter integration for seamless navigation of unmanned ground vehicle in urban areas

With the rapid development of unmanned ground vehicle industry, how to achieve continuous, reliable, and high-accuracy navigation becomes very important. At present, the integrated navigation with global navigation satellite system and strapdown inertial navigation system is the most mature and effective navigation technology for unmanned ground vehicle. However, this technique depends on the signal accuracy of global navigation satellite system. When the receiver cannot capture four or more satellite signals for a long time or the satellite completely invalid, it cannot provide accurate navigation and positioning information for the unmanned ground vehicle. Therefore, this article combine the observation information of strapdown inertial navigation system, global navigation satellite system, and laser Doppler velocimeter to propose a high-precision seamless navigation technique of unmanned ground vehicle based on state transformation extended Kalman filter. Under different land vehicle driving environments and global navigation satellite system signal quality conditions, the seamless navigation technique is evaluated through global navigation satellite system interruption simulation and land vehicle experiments. The experimental results show that the strapdown inertial navigation system/global navigation satellite system/laser Doppler velocimeter tightly coupled integration seamless navigation has good environmental adaptability and reliability and can maintain high navigation accuracy under high frequency global navigation satellite system–signal blockage conditions in urban areas.

Undifferenced and uncombined GNSS time and frequency transfer with integer ambiguity resolution

Precise point positioning (PPP) has been a competitive global navigation satellite system (GNSS) technique for time and frequency transfer. However, the classical PPP is usually based on the ionosphere-free combination of dual-frequency observations, which has limited flexibility in the multi-frequency scenario. More importantly, the unknown integer ambiguities are not restored to the integer nature, making the advantage of high-precision carrier phase observations underutilized. In this contribution, using the undifferenced and uncombined (UDUC) observations, we derive the time and frequency transfer model suitable for multi-constellation and multi-frequency scenarios. Notably, in short- and medium-baseline time and frequency transfer, the ionosphere-fixed and ionosphere-weighted UDUC models are derived, respectively, by making full use of the single-differenced (SD) ionospheric constraints. The proposed model can be applied to short-, medium- and long-baseline time and frequency transfer. The ambiguities are solved in a double-differenced (DD) form and can thus be restored to integers. To verify the feasibility of the model, GPS data from several time laboratories were collected, and the performance of the time and frequency transfer were analyzed with different baseline lengths. The results showed that the ionosphere-fixed and ionosphere-weighted UDUC models with integer ambiguity resolution could improve the frequency stability by 25–60% and 9–30% at an averaging time of several tens of seconds to 1 day for short- and medium-baseline, respectively. Concerning the long-baseline, the UDUC model is 10–25% more stable than PPP for averaging time below a few thousands second and over 1 day.

Equatorial Plasma Bubbles Identification with Single Frequency GNSS Receiver Data

Ionosphere is the highest contributor of positional error in Global Navigation Satellite System (GNSS) owing to the trans-ionospheric signal delay, distortion and possible outage. Equatorial and Low latitudinal ionosphere experiences frequent perturbations in plasma density most of which is due to the presence of Equatorial Plasma Bubbles (EPBs). In order to improve positional and navigational precision of GNSS signals, EPBs must be identified and corrected. EPBs begin to manifest post-sunset and continue to thrive past midnight. This paper proposes a Rate of TEC Index (ROTI) based EPB identifier using single frequency GNSS receiver data. GNSS data has been collected from the archives of Scripps Orbit and Permanent Array Center (SOPAC). The raw data has been downloaded from the global continuous network station, IISC, located at Bangalore (13.0219°N, 77.5671°E) in Receiver Independent Exchange (RINEX) format. Analysis of EPB occurrence has been carried out for six consecutive years in the second half of the 24th solar cycle (2014-2019). The results show a clear surge in the number of EPBs identified in the course of equinoxes.

Evaluation of the weighted least square based Receiver Autonomous Integrity Monitoring (RAIM) for single frequency GNSS receivers

Single frequency receivers for Global Navigation Satellite System (GNSS) are low-cost and easily accessible, deeming them cost-effective for commercial applications requiring localization and tracking. However, the positioning solution these receivers provide must conform to desired reliability standards. A reliability check is essential in the signal-degraded environment, where a position fix might be unacceptably inaccurate. Under such conditions, faulty measurements need to be identified and excluded to ensure the system's integrity and get a reliable solution. In this paper, a Receiver Autonomous Integrity Monitoring (RAIM) scheme is devised that employs different tests. The first test performs a global sweep on all epochs and raises the alarm after detecting the fault. Next, a group of tests are performed to identify the satellite responsible for producing the faulty measurements. Once identified, it is then excluded from the measurements to maintain the reliability of the positioning provided by the receiver. The results indicate that a polling scheme based on multiple tests identifies the faulty satellite correctly and minimizes the false alarm rate if either of these tests is performed individually.

Multi-dimensional particle filter-based estimation of phase line biases for single-differenced ambiguity resolution in GNSS-based attitude determination

Global navigation satellite systems (GNSSs) have been widely used to provide real-time and high-precision attitude information for land vehicles, ships and aircraft over the past few decades. With the joint use of emerging multi-GNSS common-clock receivers and the single-differenced (SD) model, the accuracy of pitch and roll can be significantly improved to the same level as that of yaw. However, the prerequisite is that the frequency-dependent phase line biases (LBs) in multiple GNSS systems and frequencies are accurately and rapidly estimated. In this contribution, we intend to solve this problem by using a multi-dimensional particle filter (PF)-based approach. We first investigate the relationship between the ratio value and the multi-dimensional phase LBs. Results have revealed that the ratio value can be used to judge the quality of multi-dimensional phase LBs and represent the likelihood function of the observations. We then present the procedure of multi-dimensional PF-based phase LBs estimation for SD ambiguity resolution and attitude determination. An improved strategy is also proposed to reduce the computation time. Finally, we take the two-dimensional case as a representative example to evaluate the performance of the proposed method in aspects of the convergence and accuracy of phase LB estimates, the attitude determination accuracy, and the computation time. Experimental results from two static datasets have demonstrated that the two-dimensional phase LBs basically rapid converge within 20 epochs. Moreover, compared with the double-differenced method, the proposed multi-dimensional PF-based SD method could provide comparable yaw accuracy and much better pitch accuracy. The pitch accuracy is improved to the same level as yaw by approximately 42.9%–50.0%. With regard to the computation time, it is found that with the proposed modification strategy, the single-epoch computation times are significantly reduced by approximately 90.7%–93.5%, and they are mostly within 0.05 s for most of the epochs on a personal computer.

NeQuick2 validation using multi-satellite and ground data

Global Navigation Satellite System’s (GNSS) positioning calculation is prone to ionospheric errors. Single frequency GNSS users receive ionospheric corrections through broadcast ionospheric models. Therefore, the accuracy of ionospheric models must be validated based on various geographic and geomagnetic conditions. In this work, an attempt is made to validate NeQuick2 electron density (Ne) using multiple sources of space-based and ground-based data at the Arabian Peninsula and for low solar activity conditions. These sources include space-based data from Swarm, DMSP and COSMIC-2 satellite constellations and ground-based data from GNSS receiver and the ionosonde. The period of this study is 1 year from October 2019 to September 2020. Analysis shows that the agreement between NeQuick2 and experimental Ne close to the peak density height depends on seasons and time of the day with the largest errors found in Autumn and during the daytime. NeQuick2 generally overestimates Ne during the daytime. During the early morning and evening hours, Ne estimates seem to be fairly accurate with slight underestimation in Winter and Spring. Estimation of slab thickness by NeQuick2 is found to be close to the values calculated using collocated ionosonde and GNSS receiver.

Experimental Evaluation of Smartphone Accelerometer and Low-Cost Dual Frequency GNSS Sensors for Deformation Monitoring.

Smartphone accelerometers and low-cost Global Navigation Satellite System (GNSS) equipment have faced rapid and important advancement, opening a new door to deformation monitoring applications such as landslide, plate tectonics and structural health monitoring (SHM). The precision potential and operational feasibility of the equipment play an important role in the decision making of campaigning for affordable solutions. This paper focuses on the evaluation of the empirical precision, including (auto)time correlation, of a common smartphone accelerometer (Bosch BMI160) and a low-cost dual frequency GNSS reference-rover pair (u-blox ZED-F9P) set to operate at high rates (50 and 5 Hz, respectively). Additionally, a high-rate (5 Hz) GPS-only baseline-based multipath (MP) correction is proposed for effectively removing a large part of this error and allowing to correctly determine the instrumental noise of the GNSS sensor. Furthermore, the benefit of smartphone-based validation for the tracking of dynamic displacements is addressed. The estimated East-North-Up (ENU) precision values () of , and 9.6 are comparable with the declared precision potential () of the smartphone accelerometer of . Furthermore, the acceleration noise shows only mild traces of (auto)correlation. The MP-corrected 3D (ENU) empirical precision values of , and mm were found to be better by 30–40% than the straight-out-of box precision of the GNSS sensor, attesting the usefulness of the MP correction. The GNSS sensors output position information with time correlation of typically tens of seconds. The results indicate exceptional precision potential of these low-power-consuming, small-scale, affordable sensors set to operate at a high-rate over small regions. The smartphone-based dynamic displacement validation shows that GNSS data of a low-cost sensor at a 5 Hz sampling rate can be successfully used for tracking dynamic processes.

Performance of Multi-GNSS Real-Time UTC(NTSC) Time and Frequency Transfer Service Using Carrier Phase Observations

The technique of carrier phase (CP), based on the global navigation satellite system (GNSS), has proven to be a highly effective spatial tool in the field of time and frequency transfer with sub-nanosecond accuracy. The rapid development of real-time GNSS satellite orbit and clock determinations has enabled GNSS time and frequency transfer using the CP technique to be performed in real-time mode, without any issues associated with latency. In this contribution, we preliminarily built the prototype system of real-time multi-GNSS time and frequency transfer service in National Time Service Center (NTSC) of the Chinese Academy of Sciences (CAS), which undertakes the task to generate, maintains and transmits the national standard of time and frequency UTC(NTSC). The comprehensive assessment of the availability and quality of the service system were provided. First, we assessed the multi-GNSS state space representation (SSR) correction generated in real-time multi-GNSS prototype system by combining broadcast ephemeris through a comparison with the GeoForschungsZentrum (GFZ) final products. The statistical results showed that the orbit precision in three directions was smaller than 6 cm for global positioning system (GPS) and smaller than approximately 10 cm for BeiDou satellite system (BDS). The root mean square (RMS) values of clock differences for GPS were approximately 2.74 and 6.74 ns for the GEO constellation of BDS, 3.24 ns for IGSO, and 1.39 ns for MEO. The addition, the GLObal NAvigation Satellite System (GLONASS) and Galileo satellite navigation system (Galileo) were 4.34 and 1.32 ns, respectively. In order to assess the performance of real-time multi-GNSS time and frequency transfer in a prototype system, the four real-time time transfer links, which used UTC(NTSC) as the reference, were employed to evaluate the performance by comparing with the solution determined using the GFZ final products. The RMS could reach sub-nanosecond accuracy in the two solutions, either in the SSR or GFZ solution, or in GPS, BDS, GLONASS, and Galileo. The frequency stability within 10,000 s was 3.52 × 10−12 for SSR and 3.47 × 10−12 for GFZ and GPS, 3.63 × 10−12 for SSR and 3.53 × 10−12 for GFZ for BDS, 3.57 × 10−12 for SSR and 3.52 × 10−12 for GFZ for GLONASS, and 3.56 × 10−12 for SSR and 3.48 × 10−12 for GFZ for Galileo.

Precision-Aided Partial Ambiguity Resolution Scheme for Instantaneous RTK Positioning

The use of carrier phase data is the main driver for high-precision Global Navigation Satellite Systems (GNSS) positioning solutions, such as Real-Time Kinematic (RTK). However, carrier phase observations are ambiguous by an unknown number of cycles, and their use in RTK relies on the process of mapping real-valued ambiguities to integer ones, so-called Integer Ambiguity Resolution (IAR). The main goal of IAR is to enhance the position solution by virtue of its correlation with the estimated integer ambiguities. With the deployment of new GNSS constellations and frequencies, a large number of observations is available. While this is generally positive, positioning in medium and long baselines is challenging due to the atmospheric residuals. In this context, the process of solving the complete set of ambiguities, so-called Full Ambiguity Resolution (FAR), is limiting and may lead to a decreased availability of precise positioning. Alternatively, Partial Ambiguity Resolution (PAR) relaxes the condition of estimating the complete vector of ambiguities and, instead, finds a subset of them to maximize the availability. This article reviews the state-of-the-art PAR schemes, addresses the analytical performance of a PAR estimator following a generalization of the Cramér–Rao Bound (CRB) for the RTK problem, and introduces Precision-Driven PAR (PD-PAR). The latter constitutes a new PAR scheme which employs the formal precision of the (potentially fixed) positioning solution as selection criteria for the subset of ambiguities to fix. Numerical simulations are used to showcase the performance of conventional FAR and FAR approaches, and the proposed PD-PAR against the generalized CRB associated with PAR problems. Real-data experimental analysis for a medium baseline complements the synthetic scenario. The results demonstrate that (i) the generalization for the RTK CRB constitutes a valid lower bound to assess the asymptotic behavior of PAR estimators, and (ii) the proposed PD-PAR technique outperforms existing FAR and PAR solutions as a non-recursive estimator for medium and long baselines.

Efficient FPGA Implementation of a Dual-Frequency GNSS Receiver with Robust Inter-Frequency Aiding.

Multiple frequency global navigation satellite system (GNSS) has become more complex due to the existence of extra channels. Typically, auxiliary methods are used to synchronize the second signals at other bands by aiding the acquired channel parameters. However, there are critical limitations because the reception of GNSS signals is subject to uncertainties due to noise carrier injection or circuit interference. The relationship between the two Doppler frequencies can be affected by uncertainties. Therefore, we aimed to implement an efficient dual-frequency field-programmable gate array (FPGA), performing a direct aid tracking method for the secondary channel to achieve resource efficiency and inner aid robustness. A robust estimator that directly links two loops in the two bands is proposed. In this scheme, (1) a robust estimator able to cope with uncertainty; (2) a primary tracking scheme to obtain the error boundary, and (3) a tracked bit-boundary for the initial code phase of the second channel are used. Based on experiments on the FPGA, the robust channel link can achieve direct aid tracking, and 31.02% of the original hardware resources from the aided acquisition module were released satisfactorily.

Feasibility of retrieving effective reflector height using GNSS-IR from a single-frequency android smartphone SNR data

Global Navigation Satellite Systems (GNSS) have been routinely used for geodetic-based survey and mapping studies such as precise point positioning, landslide, earthquake and crustal deformation monitoring, engineering surveys, in short, where accurate positioning is required. To do that, the GNSS observables should be eliminated from the error sources. Among the error sources affected to GNSS data, multipath stands for one of the largest error sources and should be removed. This multipath affects the strength of received microwave signal or signal-to-noise ratio (SNR), which is recorded at the GNSS antenna. As of now, many studies are successfully conducted to retrieve reflector height from signal-to-noise ratio (SNR) data gathered with a geodetic GNSS receiver. However, GNSS SNR data collected from a smartphone may also show a pattern for interferences of the direct and reflected signals from where the aforementioned heights are retrieved. In this study, an experimental site was setup to retrieve effective reflector height from a permanent mast attaching both smartphone with single frequency and geodetic GNSS receiver. The GNSS SNR data were gathered by the same time interval for a specific vertical height from the ground for three days and for approximately 5-h daily observation durations. The validation of the estimated reflector heights was performed by the root mean square error (RMSE) analysis. The RMSEs of estimated reflector heights for Xiaomi Mi 8 Lite and Trimble NetR9 geodetic receiver are computed as 1.9 and 3.7 cm, respectively. The initial results show that the outcomes of the analysis agree well with whether the in-situ measurements or the mean values via RMSEs. According to the performance assessments for accurate height detection and cost efficiency, single-frequency smartphones can be used to extract the reflector height from the collected raw SNR data.

Study on Multi-GNSS Precise Point Positioning Performance with Adverse Effects of Satellite Signals on Android Smartphone.

The emergence of dual frequency global navigation satellite system (GNSS) chip actively promotes the progress of precise point positioning (PPP) technology in Android smartphones. However, some characteristics of GNSS signals on current smartphones still adversely affect the positioning accuracy of multi-GNSS PPP. In order to reduce the adverse effects on positioning, this paper takes Huawei Mate30 as the experimental object and presents the analysis of multi-GNSS observations from the aspects of carrier-to-noise ratio, cycle slip, gradual accumulation of phase error, and pseudorange residual. Accordingly, we establish a multi-GNSS PPP mathematical model that is more suitable for GNSS observations from a smartphone. The stochastic model is composed of GNSS step function variances depending on carrier-to-noise ratio, and the robust Kalman filter is applied to parameter estimation. The multi-GNSS experimental results show that the proposed PPP method can significantly reduce the effect of poor satellite signal quality on positioning accuracy. Compared with the conventional PPP model, the root mean square (RMS) of GPS/BeiDou (BDS)/GLONASS static PPP horizontal and vertical errors in the initial 10 min decreased by 23.71% and 62.06%, respectively, and the horizontal positioning accuracy reached 10 cm within 100 min. Meanwhile, the kinematic PPP maximum three-dimensional positioning error of GPS/BDS/GLONASS decreased from 16.543 to 10.317 m.