In satellite positioning, both the reception of ranging signals and the acquisition of navigation messages are necessary. In general, the acquisition of navigation messages does not always require the reception of radiowaves; however, when radiowaves are used for acquisition, a period of continuous reception significantly longer than one second is required. The European satellite positioning system, Galileo, started broadcasting new navigation messages from August 2022. The improvement is based on a secondary synchronization pattern, secondary forward error correction, and reduced ephemeris to aid in the rapid recovery from interruptions in message acquisition caused by temporary deterioration in radio reception. This paper evaluates the recovery characteristics from interruptions in navigation message acquisition by moving reception of this improved I/NAV navigation message.

In this study, the most recent topics related to the precise global navigation satellite system (GNSS) positioning technology are discussed. Precise positioning here means that the position can be estimated with centimeter-level accuracy. Technologies supporting precise GNSS positioning include an increase in the number of positioning satellites and the availability of correction data. Smartphones are now capable of centimeter-level positioning. For correction data, real-time kinematic positioning (RTK)-GNSS, which has primarily been used in surveying, and the new precise point positioning-real-time kinematic (PPP-RTK) and PPP, are garnering attention. The Japanese Quasi-Zenith Satellite System was among the first to broadcast PPP-RTK and PPP correction data free of charge. RTKLIB has long been popular for both real-time and post-processing precise positioning. Here, I briefly present a method for improving this software. Precise positioning technology remains crucial as the use of GNSS in highly reliable applications, such as advanced driver-assistance systems, autonomous drones, and robots, is increasing. To ensure precise positioning, improving multipath mitigation techniques is essential; therefore, key factors related to these techniques are discussed. I also introduce my efforts to develop software GNSS receivers for young researchers and engineers as a basis for this purpose. This study is aimed at introducing these technologies in light of the most recent trends.

Low signal power and susceptibility to interference cause difficulties for traditional global navigation satellite system (GNSS) receivers in tracking weak signals. Extending coherent integration time is a common approach for enhancing signal gain. However, coherent integration time cannot be indefinitely increased owing to navigation bit sign transition, receiver dynamics, and clock noises. This study proposes a cross-correlation phase combining (CPC) algorithm suitable for distributed multi-antenna receivers to improve carrier-tracking performance in weak GNSS signal conditions. This algorithm cross-correlates each antenna’s intermediate frequency (IF) signal and local carrier to detect the phase differences. Subsequently, the IF signals are weighted to achieve phase alignment and coherently combined. The carrier-to-noise ratio (CNR) and carrier phase equation of the combined signal were derived for the CPC algorithm. Global positioning system (GPS) signals received by distributed antenna array with six elements were used to validate the performance of the algorithm. The results demonstrated that the CPC algorithm could effectively achieve signal phase alignment at 32 dB-Hz, resulting in a combined-signal CNR enhancement of 6 dB. The phase-tracking error variance was reduced by 72% at 30 dB-Hz compared with that of a single-antenna signal. The algorithm exhibited low phased array calibration requirements, overcoming the limitations associated with coherent integration time and effectively enhancing tracking performance in weak-signal environments.

The rise of next-generation logistics systems featuring autonomous vehicles and drones has brought to light the severe problem of Global navigation satellite system (GNSS) location data spoofing. While signal-based anti-spoofing techniques have been studied, they can be challenging to apply to current commercial GNSS modules in many cases. In this study, we explore using multiple sensing devices and machine learning techniques such as decision tree classifiers and Long short-term memory (LSTM) networks for detecting GNSS location data spoofing. We acquire sensing data from six trajectories and generate spoofing data based on the Software-defined radio (SDR) behavior for evaluation. We define multiple features using GNSS, beacons, and Inertial measurement unit (IMU) data and develop models to detect spoofing. Our experimental results indicate that LSTM networks using ten-sequential past data exhibit higher performance, with the accuracy F1 scores above 0.92 using appropriate features including beacons and generalization ability for untrained test data. Additionally, our results suggest that distance from beacons is a valuable metric for detecting GNSS spoofing and demonstrate the potential for beacon installation along future drone highways.

Recently, Global navigation satellite system (GNSS) positioning has been widely used in various applications (e.g. car navigation system, smartphone map application, autonomous driving). In GNSS positioning, coordinates are calculated from observed satellite signals. The observed signals contain various errors, so the calculated coordinates also have some errors. Double-difference is one of the widely used ideas to reduce the errors of the observed signals. Although double-difference can remove many kinds of errors from the observed signals, some errors still remain (e.g. multipath error). In this paper, we define the remaining error as “double-difference-error (DDE)” and propose a method for estimating DDE using machine learning. In addition, we attempt to improve DGNSS positioning by feeding back the estimated DDE. Previous research applying machine learning to GNSS has focused on classifying whether the signal is LOS (Line Of Sight) or NLOS (Non Line Of Sight), and there is no study that attempts to estimate the amount of error itself as far as we know. Furthermore, previous studies had the limitation that their dataset was recorded at only a few locations in the same city. This is because these studies are mainly aimed at improving the positioning accuracy of vehicles, and collecting large amounts of data using vehicles is costly. To avoid this problem, in this research, we use a huge amount of openly available stationary point data for training. Through the experiments, we confirmed that the proposed method can reduce the DGNSS positioning error. Even though the DDE estimator was trained only on stationary point data, the proposed method improved the DGNSS positioning accuracy not only with stationary point but also with mobile rover. In addition, by comparing with the previous (detect and remove) approach, we confirmed the effectiveness of the DDE feedback approach.

Global Navigation Satellite System (GNSS) receivers often realize anti-jamming capabilities by combining array antennas with space-time adaptive processing (STAP). Unfortunately, in suppressing the interference, basic STAP degrades the GNSS signal. For one thing, additional carrier phase errors and code phase errors to the GNSS signal are introduced; for another, the shape of the cross-correlation function (CCF) will be distorted by STAP, introducing tracking errors when the receiver is in tracking mode. Both of them will eventually cause additional Pseudo-Range (PR) bias, and these problems prevent STAP from being directly applied to high-precision satellite navigation receivers. The paper proposes a novel anti-jamming method based on STAP that solves the above problems. First, the proposed method constructs a symmetric STAP by constraining the STAP coefficients. Subsequently, with the information of the steering vector, a compensation FIR filter is cascaded after the symmetric STAP. This approach ensures that the proposed method introduces only a fixed offset to the code phase and carrier phase, and the order of the STAP completely determines the offset, which can be compensated during PR measurements. Meanwhile, the proposed method maintains the symmetry of the CCF, and the receiver can accurately track the carrier phase and code phase in tracking mode. The effectiveness of the proposed method is validated through simulations, which suggest that, in the worst case, our method does not increase carrier and code phase errors and tracking error at the expense of only a 2.86dB drop in interference suppression performance.

Cloud-based Global Navigation Satellite Systems (CB-GNSS) positioning architecture that offloads part of GNSS positioning computation to cloud/edge infrastructure has been studied as an architecture that adds valued functions via the network. The merits of CB-GNSS positioning are that it can take advantage of the abundant computing resources on the cloud/edge to add unique functions to the positioning calculation and reduce the cost of GNSS receiver terminals. An issue in GNSS positioning is the degradation in positioning accuracy in unideal reception environments where open space is limited and some satellite signals are blocked. To resolve this issue, we propose a satellite selection algorithm that effectively removes the multipath components of blocked satellite signals, which are the main cause of drop in positioning accuracy. We build a Proof of Concept (PoC) test environment of CB-GNSS positioning architecture implementing the proposed satellite selection algorithm and conduct experiments to verify its positioning performance in unideal static and dynamic conditions. For static long-term positioning in a multipath signal reception environment, we found that CB-GNSS positioning with the proposed algorithm enables a low-end GNSS receiver terminal to match the positioning performance comparable to high-end GNSS receiver terminals in terms of the FIX rate. In an autonomous tractor driving experiment on a farm road crossing a windbreak, we succeeded in controlling the tractor's autonomous movement by maintaining highly precise positioning even in the windbreak. These results indicates that the proposed satellite selection algorithm achieves high positioning performance even in poor satellite signal reception environments.

In order to improve tracking, interference and multipath mitigation performance from that possible with existing signals, a new Global Navigation Satellite System (GNSS) signal is needed that can offer additional degrees of freedom for shaping its pulse waveform and spectrum. In this paper, a new modulation scheme called Quinary Offset Carrier modulation (QOC) is proposed as a new GNSS signal design. The pulse waveforms of QOC modulation are divided into two types: convex and concave waveforms. QOC modulations can be easily constructed by selecting different modulation parameters. The spectra and autocorrelation characteristics of QOC modulations are investigated and discussed. Simulations and analyses show that QOC modulation can achieve similar performance to traditional BOC modulation in terms of code tracking, anti-multipath, and compatibility. QOC modulation can provide a new option for satellite navigation signal design.

In this letter, we simulate GNSS/LEO measurements and propose a process strategy for LEO-augmented GNSS medium length baseline RTK. Experiments show that, the performance of GNSS medium length baseline RTK can be significantly improved by introducing LEO satellites. The convergence speed of LEO-augmented GPS or BDS float solution maybe better than GPS/BDS combined under the conditions of similar satellite geometry. Besides, the RMS error of fixed solutions are improved to better than 4cm from sub-decimeter level.

The major weakness of global navigation satellite system receivers is their vulnerability to intentional and unintentional interference. Frequency domain interference suppression (FDIS) technology is one of the most useful countermeasures. The pseudo-range measurement is unbiased after FDIS filtering given an ideal analog channel. However, with the influence of the analog modules used in RF front-end, the amplitude response and phase response of the channel equivalent filter are non-ideal, which bias the pseudo-range measurement after FDIS filtering and the bias varies along with the frequency of the interference. This paper proposes an unbiased interference suppression method based on signal estimation and spectrum compensation. The core idea is to use the parameters calculated from the tracking loop to estimate and reconstruct the desired signal. The estimated signal is filtered by the equivalent filter of actual channel, then it is used for compensating the spectrum loss caused by the FDIS method in the frequency domain. Simulations show that the proposed algorithm can reduce the pseudo-range measurement bias significantly, even for channels with asymmetrical group delay and multiple interference sources at any location.

This paper proposes a dual-band dual-rectangular-loop circular polarization antenna for Global Navigation Satellite Systems (GNSSs). The proposed antenna combines two large outer rectangular loops with two small inner loops. Each large outer loop is connected to its corresponding small inner rectangular loop. Each loop has gaps located symmetrically with respect to a feed point to produce Right Handed Circular Polarization (RHCP). The gap position and the shape of the rectangular loops are very important to adjust both the impedance matching and circular polarization characteristics. The proposed antenna offers dual-band Voltage Standing Wave Ratio (VSWR) and Axial Ratio (AR) frequency characteristics that include the L1 (1575.42 MHz) and L2 (1227.60 MHz) bands. The antenna gains exceed 8.7 dBi. Broad AR elevation patterns are obtained. These antenna characteristics are well suited to precise positioning.

In GNSS (Global Navigation Satellite System) Distributed Simulation Environment (GDSE), the simulation task could be designed with the sharing models on the Internet. However, too much information and relation of model need to be managed in GDSE. Especially if there is a large quantity of sharing models, the model retrieval would be an extremely complex project. For meeting management demand of GDSE and improving the model retrieval efficiency, the characteristics of service simulation model are analysed firstly. A semantic management method of simulation model is proposed, and a model management architecture is designed. Compared with traditional retrieval way, it takes less retrieval time and has a higher accuracy result. The simulation results show that retrieval in the semantic management module has a good ability on understanding user needs, and helps user obtain appropriate model rapidly. It improves the efficiency of simulation tasks design.

Accurate pedestrian navigation remains a challenge in urban environments. GNSS receiver behaves poorly because the reflection and blockage of the GNSS signals by buildings or other obstacles. Integration of GNSS positioning and Pedestrian Dead Reckoning (PDR) could provide a more smooth navigation trajectory. However, the integration system cannot present the satisfied performance if GNSS positioning has large error. This situation often happens in the urban scenario. This paper focuses on improving the accuracy of the pedestrian navigation in urban environment using a proposed altitude map aided GNSS positioning method. Firstly, we use consistency check algorithm, which is similar to receiver autonomous integrity monitoring (RAIM) fault detection, to distinguish healthy and multipath contaminated measurements. Afterwards, the erroneous signals are corrected with the help of an altitude map. We called the proposed method altitude map aided GNSS. After correcting the erroneous satellite signals, the positioning mean error could be reduced from 17 meters to 12 meters. Usually, good performance for integration system needs accurately calculated GNSS accuracy value. However, the conventional GNSS accuracy calculation is not reliable in urban canyon. In this paper, the altitude map is also utilized to calculate the GNSS localization accuracy in order to indicate the reliability of the estimated position solution. The altitude map aided GNSS and accuracy are used in the integration with PDR system in order to provide more accurate and continuous positioning results. With the help of the proposed GNSS accuracy, the integration system could achieve 6.5 meters horizontal positioning accuracy in urban environment.

Location information is meaningful information for future ITS (Intelligent Transport Systems) world. Especially, the accuracy of the information is required because the accuracy decides the quality of ITS services. For realization of high precision positioning, Kinematic positioning technique has been attracting attention. The Kinematic positioning requires the configuration of many positioning parameters. However, the configuration is difficult because optimal parameter differs according to user's environment. In this paper, we will propose an estimation method of optimal parameter according to the environment. Further, we will propose an elimination method of unreliable positioning results. Hereby, we can acquire extensively only the reliable positioning results. By using the actual vehicle traveling data, the ability and the applicable range of the proposed method will be shown. The result will show that our proposed method improves the acquision rate of reliable positioning results and mitigates the acquision rate of the unreliable positioning results.

Two wideband circularly polarized (CP) equilateral triangular slot (ETS) antennas are proposed for communication system and the Global Navigation Satellite System (GNSS) Radio Occultation (RO) sensor of the GAIA-I microsatellite. These wide slot antennas use the ring slot antenna CP generation method due to their shape. The compact antennas employ truncated corners, grounded equilateral triangular perturbation patch and branched feed line to create CP radiation. A 3-dB axial ratio bandwidth (ARBW) enhancement is achieved by inserting a pair of slits into the ETS. A parametric study on the influence of those shape modifications in reflection coefficient and axial ratio is presented. An ETS antenna for communication system of the GAIA-I is fabricated and measured, which is shown to agree well with its simulated performance by providing CP fractional bandwidth of 52%. An ETS antenna designed for the GNSS RO sensor of GAIA-I delivers 3-dB ARBW of 41.6%. The ETS antenna offers uni-directional radiation by mounting a 3D printed truncated cone reflector underneath which also enhances antenna gain.

Powerful jammers are able to disable consumer-grade global navigation satellite system (GNSS) receivers under normal operating conditions. Conventional anti-jamming techniques based on the time-domain are unable to effectively suppress wide-band interference, such as chirp-like jammer. This paper proposes a novel anti-jamming architecture, combining wavelet packet signal analysis with adaptive filtering theory to mitigate chirp interference. Exploiting the excellent time-frequency resolution of wavelet technologies makes it possible to generate a reference chirp signal, which is basically a “de-noised” jamming signal. The reference jamming signal then is fed into an adaptive predictor to function as a refined jamming signal such that it predicts a replica of the jammer from the received signal. The refined chirp signal is then subtracted from the received signal to realize the aim of anti-jamming. Simulation results demonstrate the effectiveness of the proposed method in combating chirp interference in Galileo receivers. We achieved jamming-to-signal power ratio (JSR) of 50dB with an acquisition probability exceeding 90%, which is superior to many anti-jamming techniques based on the time-domain, such as conventional adaptive notch filters. The proposed method was also implemented in an software-defined GPS receiver for further validation.

Limited satellite visibility, multipath and non-line-of-sight signals reduce the performance of the stand-alone Global Navigation Satellite System (GNSS) receiver in urban environments. Embedding 3D model of urban structures in the condition of restricted visibility of the GNSS satellites due to urban canyons may improve position measurement accuracy significantly. State-of-the-art methods use raytracing or rasterization techniques applied on a 3D map to detect satellite visibility. But these techniques are computationally expensive and limit their widespread benefits for mobile and automotive applications. In this paper, a texture-based satellite visibility detection (TBSVD) methodology suitable for mobile and automotive grade Graphical Processing Units is presented. This methodology applies ray marching algorithm on a 2D height map texture of urban structures, and it is proposed as a more efficient alternative to 3D raytracing or rasterization methodology. Real road test in the business district of the metropolitan city is conducted in order to evaluate its performance. TBSVD is implemented in conventional ranging-based GNSS solution and the results illustrate the effectiveness of the proposed approach.

Outside wireless signals often obstruct GNSS receivers from acquiring satellite signals. Traditional anti-jamming algorithms are used to suppress interference using a convex optimization method based on minimizing output power. These algorithms can reduce interference. However, these models suppress satellite signals as well as jamming interference. Under the high-dynamic condition, the output signal-to-interference-and-noise ratio (SINR) deteriorates seriously and the success rate in acquiring satellite signals falls accordingly. This paper introduces a novel, broadened model with a no-main-lobe-and-multi-virtual-null-constraints (NMLCB) method based on maximizing output power and constraining interference sources. With the new method, GNSS receivers can receive satellite signals more easily than using the power inversion (PI) and power minimization with derivative constraints null (NB) methods under the high-dynamic condition.

Global navigation satellite system (GNSS) receivers equipped with the frequency domain interference suppression (FDIS) filter can operate in environments with harsh interference. The FDIS will not cause tracking error bias for an ideal analog receiver channel as its magnitude response and phase response are constant. However, the analog receiver channel distortion is induced by RF cables, amplifiers, and mixers. The distortion of the channel caused asymmetry correlation function. The correlation function is further deformed by the FDIS filter. More seriously, since the FDIS filter is adaptive, the bias will vary with the jamming pattern, especially when the frequency of interference is varying. For precision navigation applications, this bias must be mitigated. Fortunately, to prevent power loss, the analog receiver channel filter is a real function or the imaginary part is negligible. Therefore, the magnitude response and the phase response are even functions. Based on these channel features, a new FDIS filter based on mirror frequency amplitude compensation (MFAC) method is proposed in this paper. The amplitude of the symmetry position of the notch frequency is doubled in the MFAC method in order to mitigate the tracking bias. Simulation results show that the MFAC-based FDIS method is capable of reducing the bias error to less than 0.1ns, which is significant smaller than that achieved by the traditional FDIS method.

Incoming GPS signals through windows can be often observed indoors. However, conventional indoor positioning systems do not use Global Positioning System (GPS) generally because the signals may come in NLOS (Non Line of Sight). In this paper, we propose a positioning method by fingerprinting based on the incoming GPS signals.