Global Navigation Satellite System Receiver Research Articles

Global Navigation Satellite System Spoofing Detection in Inertial Satellite Navigation Systems

The susceptibility of global navigation satellite systems (GNSSs) to interference significantly limits the possibility of their use. From the standpoint of possible consequences, the most dangerous interference is the so-called spoofing. Simultaneously, in most cases of GNSS use, an inertial navigation system (INS) or an attitude and heading reference system (AHRS) is also present on the board of mobile objects. In this regard, the research goal is to assess the possibility of detecting GNSS spoofing in inertial satellite navigation systems. This paper examines the method for detecting GNSS spoofing by combining a pair of commercially available GNSS receivers and antennas with an INS or AHRS. The method is based on a comparison of the double differences of GNSS carrier phase measurements performed by receivers under conditions of resolved integer ambiguity and the values of the range double differences predicted using an INS. GNSS carrier phase integer ambiguity can be resolved using a strapdown inertial navigation system (SINS) or AHRS data. The mathematical model of GNSS phase difference measurements and the SINS-predicted satellite range differences model are given. The proposed algorithm calculates the moving average of the residuals between the SINS-predicted satellite range double differences and the measured GNSS carrier phase double differences. The primary criterion for spoofing detection is the specified threshold excess of the moving average of the double difference residuals. Experimental studies are performed using simulation and hardware-in-the-loop simulation. The experimental results allow us to evaluate the efficiency of the proposed approach and estimate the potential characteristics of the spoofing detection algorithm based on it.

Ground and Space-based response of the ionosphere during the geomagnetic storm of 02–06 November 2021 over the low-latitudes across different longitudes

The strong geomagnetic storm of class G3 that occurred on 03 November 2021 (Dst min = −118 nT, Kp = 8) was the first of this class recorded during the ascending phase of solar cycle 25. In this study, we examined the response of the ionosphere during the geomagnetic storm period from 02–06 November 2021 using the Total Electron Content (TEC) observations from a chain of Global Navigation Satellite System (GNSS) receiver stations in five longitudinal sectors i.e, Asian, East-African, West-African, South-American, and Pacific-west sectors, in the low-latitudes and space-based Swarm satellite electron density, Ne and TEC measurements. The Rate of Change of TEC Index (ROTI) was derived from the ground and space based TEC measurements to examine the occurrence of ionospheric irregularities. The Rate of change of electron density index (RODI) was also derived from Swarm Ne measurements to identify the occurrence of ionospheric irregularities at Swarm altitudes. A positive ionospheric storm effect was observed in all the longitudinal sectors considered in this study. A clear hemispherical asymmetry, with higher VTEC in the northern hemisphere was observed. The determining factors for ionospheric responses to this storm are; local time of the storm’s onset, local time of storm’s minimum SYM-H, and changes in thermospheric O/N2 ratio. These geomagnetic storm effects were discussed in terms of the Prompt Penetration Electric Field (PPEF) storm induced wind lifting effect and Disturbance Dynamo Electric Field (DDEF). The geomagnetic storm inhibited the occurrence of ionospheric irregularities in all the sectors, during the main phase, except for three IGS receiver stations in South American sector. Overall, a longitudinal dependence of the enhancement/inhibition of ionospheric irregularities was observed. The generation of post-sunset irregularities was attributed to the local time occurrence of maximum ring current, PPEF and DDEF.

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

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

ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING POTENTIAL AS TOOLS FOR GEOREFERENCING AND FEATURES DETECTION USING UAV IMAGERY

Abstract. While Satellite imagery holds the advantage of encompassing expansive geographical regions. spanning square kilometers, its Spatial Resolution (SR) might prove inadequate for specific tasks. Conversely, Unmanned Aerial Vehicles (UAVs) excel in capturing high-resolution images with spatial resolutions in the range of a few centimeters or even millimeters. However, the accuracy of sensor locations during UAV flights is non-accurate enough by the Global Navigation Satellite Systems (GNSS) technology onboard. One of the key objectives of this research is to evaluate a technique aimed at generating precise sensor locations. This technique employs raw data from the drone's GNSS receiver and minimum Ground Control Points (GCPs) placed within a 2-meter diameter circle in the study area. The goal is to achieve accurate Digital Elevation Models (DEM) and orthomosaic images. Another focus of this research is on addressing challenges related to road lane detection. This is achieved through the enhancement of the You Only Look Once (YOLO) v3 algorithm. The proposed approach optimizes grid division, detection scales, and network architecture to enhance accuracy and real-time performance. The experimental results showcase an impressive 92.03% accuracy with a processing speed of 48 frames per second (fps), surpassing the performance of the original YOLOv3. In the rapidly evolving landscape of Artificial Intelligence (AI) and drone technology, this investigation underscores both the potential and complexities inherent in utilizing advanced AI models, such as YOLOv8, for building detection using UAV and satellite imagery. Furthermore, the research delves into robustness and real-time capabilities within building detection algorithms. The outlined strategy encompasses precise pre-processing, Field-Programmable Gate Array (FPGA) validation, and algorithm refinement. This comprehensive framework aims to elevate feature detection in intricate scenarios, ensuring accuracy, real-time efficiency, and adaptability.

IONOSPHERIC IRREGULARITIES MEASURED BY GROUND-BASED AND SATELLITE-EMBEDDED RECEIVERS: ANALYSIS OF S4 INDEX IN A LOW LATITUDE REGION

Abstract. Ionosphere is an important layer of Earth’s atmosphere which can interfere in the transmission of radio signals, affecting several activities, such as the ones related to global navigation satellite systems (GNSS) positioning. In this intend, many efforts have been made in the last decades in order to better understand and model this region of atmosphere. The observation of ionosphere and its irregularities can be performed by several techniques, including classic methods such as ionosondes. Besides that, the use of GNSS signals as source of atmospheric observations have allowed the development of different methodologies and techniques to obtain ionospheric information. Among those, the use of data collected by receivers embedded in low earth orbiting (LEO) satellites, such as the ones used in radio occultation (RO) missions can be relevant due to the amount and distribution of the data obtained. Besides that, GNSS receivers has also been used in ground stations networks to continuously monitor the ionosphere. In this sense, the present work aims to compare irregularities observed by two different techniques using data from ground-based (GNSS monitoring stations) and satellite-embedded (RO mission) receivers. The study is performed over one of the most challenging scenarios, the Brazilian region, considering seasonal variability in two months (low and high solar flux) from 2014 (solar cycle peak). The results obtained show agreement in the general behavior of the ionospheric irregularities observed by the two different techniques.

ALTERNATIVE LIDAR TECHNOLOGIES FOR STOCKPILE MONITORING AND REPORTING

Abstract. Accurate volume estimation of salt stockpiles stored in covered facilities is essential for effective management and budgeting in the transportation industry. Due to environmental concerns, salt is stored in indoor facilities. The surveying tools that are widely applied for outdoor stockpile estimation such as Global Navigation Satellite System (GNSS) Receivers and Uncrewed Aerial Vehicles (UAV) are not applicable for indoor mapping. To address this limitation, our prior research proposed and developed a Stockpile Monitoring and Reporting Technology (SMART) which was designed for indoor stockpile volume estimation. This study builds upon that prior research to evaluate the feasibility and performance of different LiDAR alternatives within the SMART system. Three LiDAR sensors (Velodyne VLP-16, Ouster OS1-32-U, and Blickfeld Cube 1) are compared in terms of system calibration, point cloud registration, and volume estimation. Results demonstrate the impact of LiDAR sensor choice on system performance, occlusion rates, and volumetric accuracy. The findings contribute to expanding the versatility and adaptability of LiDAR technology in SMART applications, allowing for more efficient and accurate stockpile volume estimation.

Robust factor graph optimisation method for shipborne GNSS/INS integrated navigation system

AbstractRobust Global Navigation Satellite System (GNSS) factors are introduced into a factor graph optimisation based integrated navigation system to address the challenge of occluded GNSS signals during ship navigation, which leads to increased errors in positioning results. To enhance the robustness of the GNSS tracking loop, a vector tracking method is applied to receiver tracking loop. Then, the Mahalanobis distance was employed to assess the pseudorange residual and identify and reject signals that exhibit anomalies. Specifically, the pseudorange residual is computed as the difference between the predicted pseudorange of the GNSS receiver and the measured pseudorange. Using the historical information in the window, robust GNSS factors were constructed for use in the factor graph. The robust factor graph optimisation method for a shipborne GNSS/Inertial Navigation System integrated navigation system was implemented by constructing robust GNSS factors and Inertial Measurement Unit factors. The experimental results confirm that the positioning accuracy of the proposed method is superior to those of the factor graph optimization and extended Kalman filter.

Giant ionospheric density hole near the 2022 Hunga-Tonga volcanic eruption: multi-point satellite observations

A giant ionospheric hole was simultaneously detected in the in situ measurements of FORMOSAT-7/COSMIC-2 (F7/C2), Ionospheric Connection Explorer (ICON), Swarm missions, and ground-based total electron content (TEC) by global navigation satellite system receivers, and F7/C2 Global Ionosphere Specification (GIS) data near Tonga, following the explosive volcano eruption on 15 January 2022. The TEC maps displayed the huge depletions that developed near Tonga after the eruption and gradually evolved. The ICON IVM, F7/C2 IVM and Swarm-LP detected large depletions not only near Tonga, but also in the EIA trough region. The GIS observations clearly show the ionospheric hole that extends spatially near Tonga, especially strongly south/southward. The simultaneous observations showed that the ionosphere hole near Tonga combined with the EIA trough and finally evolved into a giant ionosphere hole around 07 UT. The ionospheric hole, which occurred at 05 UT near Tonga, extended over a wide area of 160°-200°E and 25°S-20°N and lasted for about 11 h. The F7/C2 and ICON satellites overpasses showed large ion density depletions by the hole at orbit altitudes, accompanied by enhancements in ion temperature and field-aligned and perpendicular ion drift. Such a long-lasting giant ionospheric hole by a seismic event has not been reported earlier, creating a unique ionospheric environment near Tonga after the eruption. The strong successive impulses by multiple volcano eruptions, together with O/N2 decrease in the summer hemisphere, interhemispheric wind, and water vapor injection into high altitudes apparently yielded such a giant ionospheric hole, 4–6 times larger than that observed during the Tohoku earthquake.Graphical

A lane-level localization method via the lateral displacement estimation model on expressway

The gradual proliferation of high-definition (HD) maps has played a pivotal role in the advancement of intelligent vehicles. However, a considerable number of vehicles still face limitations in harnessing HD maps for high-precision navigation due to the absence of lane-level localization information. To address this challenge, this paper presents a lightweight lane-level localization method based on ubiquitous low-cost on-board vehicle cameras and Global Navigation Satellite System (GNSS) receivers. Initially, the line anchor-based feature refinement network is combined with the DeepSort-based lane tracking algorithm to detect and track the lanes in the image sequences. Subsequently, a lateral displacement estimation (LDE) model is proposed to establish the relationship between the vehicle's lateral displacement value in the ego lane and the slope of the lanes on both sides. Moreover, a lateral motion estimation (LME) method is employed to track the motion of the vehicle across multiple lanes. Finally, a lane-level map matching method is proposed based on the GNSS data and lateral displacement information. In the experimental section, three distinct types of dashcams have been installed in a vehicle, and high-precision positioning equipment is utilized as the ground truth for algorithm validation. The experimental results indicate that the proposed method can be effectively deployed in vehicles, enabling lane-level vehicle positioning on expressway. The code has been open-sourced and can be accessed at https://codeocean.com/capsule/6640813/.

Enhanced GNSS Reliability on High-Dynamic Platforms: A Comparative Study of Multi-Frequency, Multi-Constellation Signals in Jamming Environments

The global navigation satellite system (GNSS) signals are vulnerable to disruption sources, such as signal jamming. This, in turn, can cause severe degradation or discontinuities of the GNSS-based position, navigation, and timing services. The availability of multi-frequency signals from multi-constellation GNSS systems, such as Galileo and GLONASS, along with the modernization of GPS with multi-frequency signals, has the potential to increase the immunity of GNSS-based navigation systems to signal jamming. Despite various studies completed on the utilization of multi-frequency and multi-constellation global navigation satellite system (GNSS) signals to resist receiver jamming, there is still an urge to further investigate this concern under different circumstances. This paper presents an experimental evaluation of the advantages of the employment of multi-frequency multi-constellation GNSS signals for better GNSS receivers’ performance during signal jamming situations for high-dynamic platforms such as aircraft/drones. Additionally, the study examines the effects of both simulated and real jamming signals on all possible combinations of the GPS, Galileo, and GLONASS signal frequencies and constellations. Two airplane trajectory routes were built, and their corresponding RF signals were generated using the Spirent and Orolia GNSS signal simulators. The results indicated that the GPS multi-frequency-based solution maintains reliable positioning performance to some extent under low jamming scenarios. However, the combination of GPS, Galileo, and GLONASS signals proved its ability to provide a continuous and accurate positioning solution during both low and high jamming scenarios.

Widely Linear Null Broadening GNSS Anti-Interference for Polarization-Sensitive Arrays

In this correspondence, we consider suppressing non-circular interferences for Global Navigation Satellite Systems (GNSS) receivers utilizing polarization sensitive arrays, regarding high dynamic scenarios. We model the widely linear array receive signal corrupted by potentially non-circular interferences. We analyze the second-order statistics of the widely linear receive signal and extend the covariance matrix taper (CMT) methodology to cope with the widely linear receive signal. We further develop widely linear null broadening algorithms to suppress high-dynamic non-circular interferences. Simulation results validate the superior performance of the proposed algorithms in suppressing high-dynamic non-circular interferences.

Analysis of Water Level Monitoring using GNSS Interferometric Reflectometry in River Waters

GNSS Interferometric Reflectometry (GNSS-IR) is one of the newest explorations of Global Navigation Satellite System (GNSS) signals which utilizes multipath signals to calculate the vertical distance from the reflecting surface to the geodetic antenna/receiver. However, scientific-grade or geodetic GNSS instruments are expensive, which is a limiting factor for their prompt and more widespread deployment as a dedicated environmental sensor. Hence, in this study, low-cost GNSS receiver devices were used to monitor the surface level of PT Garam River in Pamekasan Regency using the GNSS-IR method. The study location of PT Garam River which is quite close to the sea causes the water level to vary following the tides at the sea. This is because there are needs for advanced methodologies to limit GNSS observations in a much narrower area. The river in this case is a more challenging study location in terms of monitoring the water level. Calculation of river water level height with GNSS-IR observations is based on determining the peak frequency on the periodogram resulting from signal-to-noise ratio (SNR) data extraction. The two-weeks GNSS-IR observation in this study were applied by installing sideway orientation of GNSS antenna towards the river. This will be done to see how effective the strength of the reflected signal received by the low-cost GNSS devices are in narrow footprint area. Conventional tide gauge near the GNSS-IR site was used to evaluate the accuracy of GNSS-IR in river water level monitoring. Tide analysis is carried out to obtain tidal constituents and tide predictions using least square harmonics estimation (LSE). The resulting accuracy of the validation data is at an RMSE of 15.35 cm, with the correlation value of 0.94. The type of river tides in the study location based on the calculation results is mixed tide prevailing semidiurnal. Tide prediction for 20 days gives promising results with an RMSE of 16 cm. These results indicate that low-cost GNSS device has a promising capability for water level monitoring using GNSS-IR method in a narrow reflector area.

Aerial geodetic total station platform for precise active positioning in GNSS-degraded environments

One of the main applications of UAVs (Uncrewed Aerial Vehicles) is precise mapping; however, most of the studies are specialized either on rapid-mapping without focusing on characteristic point localization, or point positioning without concentrating upon the real-time or high accuracy. In this study, an active localization method for GNSS (Global Navigation Satellite System)-degraded environments is proposed using a custom-built UAV as an aerial geodetic total station platform. The UAV equipped with an RTK (Real-time-Kinematics)-GNSS receiver and an optimized gimbal that carries an optical sensor and a laser range-finder, is able to autonomously detect, track and localize fiducial targets, using the UAV's orientation and position, exporting their coordinates in WGS 84 geodetic reference system during the flight. The system has been validated with a significant number of experiments in various environments with increasing difficulty, providing a three-dimensional error in a range of 4–15 cm.

Snapshot GNSS receivers for low-effort, high-gain space situational awareness

This paper proposes a novel concept of using highly efficient Snapshot Global Navigation Satellite Systems (GNSS) receivers to provide precise position fixes of single or multiple satellites in Low-Earth Orbit (LEO) to improve upper atmospheric modeling and thus contribute to superior space situational awareness (SSA). While tracking of LEO satellites and the use of onboard GNSS receivers for drag measurements and upper atmosphere modeling are well-established techniques, the expected advent of snapshot GNSS receivers for spaceborne scientific applications will allow massive improvements on the GNSS sensor’s Size, Weight, Power and Cost (SWaP-C). With chip-size dimensions of 4x4 mm2, a mass of less than 5 gr, an average power level below 0.1 mW, snapshot receiver technology is expected to provide position fixes in space with an accuracy of ∼19 m (3D r.m.s.), which will surpass the accuracy of Two-Line Elements (TLE) provided by the US Joint Space Operations Center (JSpOC) by at least two orders of magnitude. Equally important to their SWaP-C benefits, Snapshot GNSS receivers will allow mission and spacecraft designers to trade onboard-processing requirements versus payload downlink requirements, leading to either minimum onboard processing or a minimum amount of downlinked data. In this research, we establish the concept and architectural overview of using snapshot GNSS receivers for SSA, including the role of using them in a Distributed Space System (DSS), and detail their characterization and performance in terms of the required GNSS hardware and the impact of these payload on the power budget, the link budget and the OnBoard Data Handling (OBDH) budget of a satellite. It will be shown that these receivers lend themselves especially to their use on femto-, pico- and nano-satellites, although integrated snapshot modules may be flown as auxiliary payloads on micro- or mini-satellites as well. While this work focuses on the implications of the use of snapshot GNSS receivers on spacecraft design for the use of upper atmosphere modeling and SSA, their use may open up other science applications which avoid the need for expensive high-grade GNSS receivers.

A Flexible System-on-Chip Field-Programmable Gate Array Architecture for Prototyping Experimental Global Navigation Satellite System Receivers

Global navigation satellite system (GNSS) technology is evolving at a rapid pace. The rapid advancement demands rapid prototyping tools to conduct research on new and innovative signals and systems. However, researchers need to deal with the increasing complexity and integration level of GNSS integrated circuits (IC), resulting in limited access to modify or inspect any internal aspect of the receiver. To address these limitations, the authors designed a low-cost System-on-Chip Field-Programmable Gate Array (SoC-FPGA) architecture for prototyping experimental GNSS receivers. The proposed architecture combines the flexibility of software-defined radio (SDR) techniques and the energy efficiency of FPGAs, enabling the development of compact, portable, multi-channel, multi-constellation GNSS receivers for testing novel and non-standard GNSS features with live signals. This paper presents the proposed architecture and design methodology, reviewing the practical application of a spaceborne GNSS receiver and a GNSS rebroadcaster, and introducing the design and initial performance evaluation of a general purpose GNSS receiver serving as a testbed for future research. The receiver is tested, demonstrating the ability of the receiver to acquire and track GNSS signals using static and low Earth orbit (LEO)-scenarios, assessing the observables’ quality and the accuracy of the navigation solutions.

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.

Constructing a Regional Ionospheric TEC Model in China with Empirical Orthogonal Function and Dense GNSS Observation

Using Global Navigation Satellite Systems (GNSS) observation data for developing a high-precision ionospheric Total Electron Content (TEC) model is one of the essential subjects in ionospheric physics research and the application of satellite navigation correction. In this study, we integrate the Empirical Orthogonal Function (EOF) method with the TEC data provided by the Center for Orbit Determination in Europe (CODE), and observed by the dense GNSS receivers operated by the Crustal Movement Observation Network of China (CMONOC) to construct a regional ionospheric TEC model over China. The EOF analysis of CODE TEC in China from 1998 to 2010 shows that the first-order EOF component accounts for 90.3813% of the total variation of the ionospheric TEC in China. Meanwhile, the average value of CODE TEC is consistent with the spatial and temporal distribution characteristics of the first-order EOF base function, which mainly reflects the latitude and diurnal variations of TEC in China. The first-order coefficient after EOF decomposition shows an obvious 11-year period and semi-annual variations. The maximum amplitude of semi-annual variation mainly appears in March and October, which is closely associated with the variation in geographical longitude, the semi-annual change of the low-latitude electric field, and the ionospheric fountain effect. The second-order coefficient has an evident annual variation, the minimum amplitude mainly occurs in March, August, and September, and the amplitude values in the high solar activity years are more significant than those in the low solar activity years. The third-order coefficient mainly shows the characteristics of annual variation, and the fourth-order coefficient shows the noticeable semi-annual and annual variations. The third and fourth-order coefficients are both modulated by the solar activity index F10.7. The ionospheric TEC model in China, driven by CMONOC real-time GNSS observation data, can better reflect the latitude, local time and seasonal variation characteristics of ionospheric TEC over China. In particular, it can clearly show the spring and autumn asymmetry of ionospheric TEC in the low latitudes. The root mean square error of the absolute error between the model and the actual observation is mainly distributed around 2.45 TECU (1 TECU = 1016 electrons/m2). The values of the TEC model constructed in this study are closer to the actual observed values than those of the CODE TEC in China.

A Novel GNSS Sweep Interference Detection and Mitigation Method Based on Radon–Wigner Transform

In this paper, a novel Radon-Wigner transform (RWT) based sweep interference detection and mitigation method has been proposed for global navigation satellite system (GNSS) receivers working in the disturbing scenarios. The proposed GNSS sweep interference detection and mitigation method has been tested using real GPS L1-C/A data disturbed by the sweep interference in a controlled test bench experiment. The results have shown that the proposed method can effectively deal with the cross-term problems with the conventional time-frequency (TF) analysis techniques and provide much improved GNSS interference detection performance in comparison to the existed Wigner-Ville distribution (WVD) and Wigner-Hough transform (WHT) approaches; and the characteristic parameters of the GNSS sweep interfering signal can be efficiently estimated according to the peak position of the RWT computed in the parameter space. In order to excite the GNSS sweep interfering signal, the dechirping and notch filtering techniques have been suggested to realize the GNSS anti-interference functionality, providing satisfactory anti-interference performance for GNSS receivers, this has been further verified by the GNSS signal acquisition experiment in the interfering environment.

GPS Receiver Simplification for Low cost Applications and Multipath Mitigation Analysis on SDR based Re configurable Software Receiver

Many modern position-based applications rely heavily on the Global Navigation Satellite System (GNSS). Most applications require precise position data obtained through sophisticated hardware with a high computational capacity in the receiver. Some cost-effective applications may not require precise position data and require less complex signal processing. The use of efficient hardware and signal processing techniques to reduce the overall cost of a GNSS receiver is an active research topic. This paper considers Global Positioning System (GPS) constellation and proposes two factors to reduce the receiver complexity: sampling frequency and the number of tracking channels. A Keysight GNSS signal generator to record GPS signals, a Software Defined Radio board and a software-based GPS receiver are used in the experimentation. The sampling frequencies are 40, 20, 10 and 5 MHz considered, and tracking channels are reduced from 12 to 6 and then 4. The increase of error in the receiver position with 6 and 4 satellites is considerably small, but the number of tracking channels and signal processing requirements are reduced considerably. The GPS signals are affected by many errors; one of the significant sources of error is multipath propagation. Three distinct GPS multipath scenarios are generated for four satellite signal combinations with the GNSS simulator for the receiver performance analysis. Three multipath mitigation techniques, namely Early Minus Late (EML), Narrow correlator (NC) and strobe correlator (SC) methods, are considered because of their simple structure and fewer signal processing requirements. The error reductions of three multipath scenarios are compared, and the SC method performs better in all three multipath scenarios.

The impact of global navigation satellite system (GNSS) zenith total delay data assimilation on the short-term precipitable water vapor and precipitation forecast over Italy using the Weather Research and Forecasting (WRF) model

Abstract. The impact of assimilating GNSS-ZTD (global navigation satellite system–zenith total delay) on the precipitable water vapor and precipitation forecast over Italy is studied for the month of October 2019, which was characterized by several moderate to intense precipitation events, especially over northwestern Italy. The WRF (Weather Research and Forecasting) model, version 4.1.3, is used with its 3D-Var data assimilation system to assimilate ZTD observations from 388 GNSS receivers distributed over the country. The dataset was built collecting data from all the major national and regional GNSS permanent networks, achieving dense coverage over the whole area. The water vapor forecast is verified for the forecast hours of 1–6 h after the last data assimilation time. Results show that WRF underestimates the atmospheric water vapor content for the period, and GNSS-ZTD data assimilation improves this underestimation. The precipitation forecast is verified in the phases of 0–3 and 3–6 h after the last data assimilation time using more than 3000 rain gauges spread over Italy. The application of GNSS-ZTD data assimilation to a case study improved the precipitation forecast by increasing the rainfall maximum and by better focusing the precipitation pattern over northeastern Italy, with the main drawback being the prediction of false alarms. Considering the study over the whole period, GNSS-ZTD data assimilation had a positive impact on rainfall forecast, with an improvement in the performance up to 6 h and with statistically significant results for moderate to intense rainfall thresholds (25–30 mm (3 h)−1).