GNSS Research Articles

Evaluation of Best Satellite-Receiver Geometry for Improved IRNSS/GPS Position Accuracy

A GPS-IRNSS combined navigation system is emerging in India. It is possible to increase the accuracy of the receiver or user's position at any time and under any weather conditions with a combined system. It is possible to use these navigation systems for finding the precise location of receivers in civil aviation, precision applications such as surveying, disaster management, and other applications. Usually, satellite navigation systems are based on a geometric relationship between satellite and receiver, with errors caused by atmospheric conditions, multipath, and other factors affecting accuracy. Geometry of satellite receivers is measured by the Dilution of Precision (DOP), a unit less quantity. This paper investigates the possibility possible to obtain better accuracy by combining GPS and IRNSS constellations. This improved accuracy is typically useful for precision applications such as surveying and disaster management.

Vision-Aided Localization and Mapping in Forested Environments Using Stereo Images.

Forests are traditionally characterized by stand-level descriptors, such as basal area, mean diameter, and stem density. In recent years, there has been a growing interest in enhancing the resolution of forest inventory to examine the spatial structure and patterns of trees across landscapes. The spatial arrangement of individual trees is closely linked to various non-monetary forest aspects, including water quality, wildlife habitat, and aesthetics. Additionally, associating individual tree positions with dendrometric variables like diameter, taper, and species can provide data for highly optimized, site-specific silvicultural prescriptions designed to achieve diverse management objectives. Aerial photogrammetry has proven effective for mapping individual trees; however, its utility is limited due to the inability to directly estimate many dendrometric variables. In contrast, terrestrial mapping methods can directly observe essential individual tree characteristics, such as diameter, but their mapping accuracy is governed by the accuracy of the global satellite navigation system (GNSS) receiver and the density of the canopy obstructions between the receiver and the satellite constellation. In this paper, we introduce an integrated approach that combines a camera-based motion and tree detection system with GNSS positioning, yielding a stem map with twice the accuracy of using a consumer-grade GNSS receiver alone. We demonstrate that large-scale stem maps can be generated in real time, achieving a root mean squared position error of 2.16 m. We offer an in-depth explanation of a visual egomotion estimation algorithm designed to enhance the local consistency of GNSS-based positioning. Additionally, we present a least squares minimization technique for concurrently optimizing the pose track and the positions of individual tree stem[s].

High-Gain Dual-Band Aperture-Shared CP Patch Antenna With Wide AR Beamwidth for Satellite Navigation System

This paper presents a compact dual-band, high-gain, light-weight, circularly polarized (CP) microstrip patch antenna with wide axial ratio (AR) beamwidth for multiple satellite communication, positioning and navigation systems The antenna consists of a main dual-frequency coplanar metal frame radiator, a circular metal capacity-loaded radiator, and some coaxial feeding probes. Due to the use of air dielectric, the maximum right-hand circularly polarized gain of the antenna is up to 6.2 dBic in the lower bands and 6.3 dBic in the upper bands. By utilization of dual-frequency coplanar patch and metal capacity-loaded technology, the dimensions of the aperture-shared CP antenna are only 0.38 λ × 0.38 λ × 0.04 λ. To increase the 3-dB AR beamwidth, a novel vertically grounded shorting sheet is introduced. The 3-dB AR beamwidth ranges from −120° to 100° at 1.227 GHz and from −90° to 95° at 1.575 GHz. As a result, the proposed antenna is an excellent candidate for high gain, wide AR beamwidth and compact air dielectric antenna.

Optimization of the production of varieties of grain crops using a satellite navigation system in the forest-steppe of the Priobye region

The results of complex experiments on studying the effectiveness of the use of geoinformation technologies on grain crops of CJSC breeding farm "Irmen" of the Ordynsky district of the Novosibirsk region, which is part of the drained forest-steppe of Western Siberia, are presented. Varieties of soft spring wheat, spring barley and oats place increased demands on environmental factors and are characterized by high variability. The use and implementation of modern satellite navigation systems makes it possible to increase the yield and quality of the main grain crops in the zone of risky farming in Western Siberia. The purpose of the research is based on optimizing the technology of growing grain crops using a satellite navigation system in the forest-steppe of Western Siberia. The studies were carried out in 2029-2022. in the soil-climatic zone of drained forest-steppe, which is part of the northern forest-steppe of the foothills of the Ob. The soil of the experimental plots is leached chernozem with a humus content of 6.18%, gross nitrogen - 0.34, phosphorus - 0.22 and potassium - 1.23%. The content of easily hydrolysable nitrogen is 10.8, mobile phosphorus 21.9 and exchangeable potassium 19.8 mg/100 g of soil at pH 6.57. In the experiments we used a variety of spring soft wheat Likamero, spring barley Paustian and oat Rovesnik. The paper establishes regression equations between the yield and the sum of productive moisture reserves and precipitation in the interphase periods of different varieties of grain crops. Correlation parameters for each interphase period are marked. The dependence of the yield on the amount of precipitation for the interphase periods of grain crops was revealed. The role of geoinformation technologies in increasing the yield and quality of grain of spring wheat, spring barley and oats is determined.

An Improved GPS/INS Integration Based on EKF and AI During GPS Outages

Inertial navigation system (INS) is often integrated with satellite navigation systems to achieve the required precision at high-speed applications. In global navigation system (GPS)/INS integration systems, GPS outages are unavoidable and a severe challenge. Moreover, because of the usage of low-cost microelectromechanical sensors (MEMS) with noisy outputs, the INS will get diverged during GPS outages, and that is why navigation precision severely decreases in commercial applications. In this paper, we improve GPS/INS integration system during GPS outages using extended Kalman filter (EKF) and artificial intelligence (AI) together. In this integration algorithm, the AI receives the angular rates and specific forces from the inertial measurement unit (IMU) and velocity from the INS at [Formula: see text] and [Formula: see text]. Therefore, the AI has positioning and timing data of the INS. While the GPS signals are available, the output of the AI is compared with the GPS increment; so that the AI is trained. During GPS outages, the AI will practically play the GPS role. Thus, it can prevent the divergence of the GPS/INS integration system in GPS-denied environments. Furthermore, we utilize neural networks (NNs) as an AI module in five different types: multi-layer perceptron (MLP) NN, radial basis function (RBF) NN, wavelet NN, support vector regression (SVR) and adaptive neuro-fuzzy inference system (ANFIS). To evaluate the proposed approach, we utilize a real dataset that has been gathered by a mini-airplane. The results demonstrate that the proposed approach outperforms the INS and GPS/INS integration systems with the EKF during GPS outages. Meanwhile, the ANFIS also reached more than 47.77% precision compared to the traditional method.

Practical realization of space-time filtering of satellite navigation signals in real time

Background. The problem of satellite navigation signals’ jamming-protected receivers design is quite relevant due to the high vulnerability of such signals to the influence of interferences whose sources number is constantly increasing. Aim. To design a space-time adaptive filter and to implement its work in real-time as a part of jamming-protected satellite navigation system. Methods. The space-time filtering method fitted for the real-time realization is obtained based on the satellite signal space processing algorithm. The apparatus chosen for the satellite navigation signals reception, the filtering algorithm practical realization and the processed signal demodulation is described. The computer modeling of the signals records filtering and demodulation using the obtained algorithm as well as the real-time experiments in satellite signals processing with different numbers of outer jammers using the constructed jamming-protected receiver are carried out. Results. As a result of modeling and experiments with the designed set the values of performance characteristics of the jamming-protected navigation system are yielded which correspond to a good quality solution of the interference mitigation problem in a satellite navigation signal. Conclusion. The digital processing model based on the obtained space-time filter adequately describes the interference mitigation process in a real satellite signal. The obtained jamming-protected satellite navigation signal receiver is functional and can be used in practice.

Analysis of navigation system accuracy characteristics for micro UAVs

The article analyzes the noise influence of the main types that arise in the process of exchanging navigational information between the GPS receiver of an micro-class unmanned aerial vehicle and the global satellite navigation system using an improved advanced simulation model in the Matlab – Simulink software environment, which allows building a representative statistical model in the process designing algorithms of the navigation system of unmanned aerial vehicles. With the help of modeling the process of choosing the receiver gain factor of an unmanned aerial vehicle and the study of the influence of the quality of reception and processing navigation signals during the increase of the distance relative to the satellite signal of the global navigation satellite system, it was established that with an increase in the gain factor of the antenna, the noise level decreases. However, an increase in the amplification factor leads to an increase in the dimensions of the antenna, as well as, accordingly, an increase in energy consumption, which does not meet the requirements for the mass-dimensional indicators of the microclass of unmanned aerial vehicles. Also, the article investigated the operation process of microelectromechanical systems of platformless inertial navigation systems, namely, at the moment of the disappearance of global satellite systems at a time interval of up to 300 seconds, to determine the error of calculating the parameter of the vertical component (height) and vertical speed of an unmanned aerial vehicle. According to the simulation results, it was found that the orientation and navigation of unmanned aerial vehicles in autonomous flight depend significantly on random errors of microelectromechanical systems of platformless inertial navigation systems, these include random angle wandering (zero noise drift); the influence of linear acceleration of the accelerometer sensor, by studying the noise model of errors microelectromechanical systems to determine the eight velocity parameter in autonomous flight mode, which is of a significant nature.

An Efficient Jarratt-Type Iterative Method for Solving Nonlinear Global Positioning System Problems

The global positioning system (GPS) is a satellite navigation system that determines locations. Whenever the baseline satellites are serviced or deactivated, the Space Force often flies more than 24 GPS satellites to maintain coverage. The additional satellites are not regarded as a part of the core constellation but may improve the performance of the GPS. In this study of GPS models, we solved various problems. We examined each set of four satellites separately. Advancements in computer softwares have made computations much more precise. We can use iterative methods to solve GPS problems. Iterative schemes for solving nonlinear equations have always been of great importance because of their applicability to real-world problems. This paper involves the development of an efficient family of sixth-order Jarratt-type iterative schemes for analyzing nonlinear global positioning systems.

LEO navigation augmentation constellation design and precise point positioning performance analysis based on BDS-3

Low Earth orbit (LEO) satellites have high signal strength and faster geometry changes over short periods, offering unique advantages in navigation augmentation. Integrating LEO satellites into the navigation system can help augment the performance of the global satellite navigation system and break the dilemma of the existing navigation system with limited services in challenging environments. Constellation design is the key before establishing a complete LEO navigation augmentation platform. Therefore, in this study, two LEO navigation augmentation constellations, Polar/Walker (S1) and Walker/Walker (S2) with different inclinations, are designed and optimized using the non-dominated sorting genetic algorithm III (NSGA-III). The global average geometric dilution of precision (GDOP) of BDS-3 is reduced from 1.56 to 0.92 and 0.95, and the average visible satellite number is improved from 11.74 to 27.83 and 25.72 with the navigation augmentation of the optimized constellations. To further validate the navigation augmentation effect of two LEO constellations on BDS-3 precision point positioning (PPP), nine stations at different latitudes were selected for LEO augmented BDS-3 PPP simulation experiments. The results show that after adding S1 and S2 constellations to BDS-3, respectively, the convergence times of the nine stations are reduced by 35.5%∼96.5% and 43.7%∼96.2%, and the positioning accuracy is improved by 5.7%∼71.9% and 24.2%∼69.5%, respectively. Overall, each S1 and S2 constellations can significantly improve the global service performance and PPP performance of BDS-3.

Continuous ground monitoring of vegetation optical depth and water content with GPS signals

Abstract. Satellite microwave remote sensing techniques can be used to monitor vegetation optical depth (VOD), a metric which is directly linked to vegetation biomass and water content. However, these large-scale measurements are still difficult to reference against either rare or not directly comparable field observations. So far, in situ estimates of canopy biomass or water status often rely on infrequent and time-consuming destructive samples, which are not necessarily representative of the canopy scale. Here, we present a simple technique based on Global Navigation Satellite Systems (GNSS) with the potential to bridge this persisting scale gap. Because GNSS microwave signals are attenuated and scattered by vegetation and liquid water, placing a GNSS sensor under a vegetated canopy and measuring changes in signal strength over time can provide continuous information about VOD and thus on vegetation biomass and water content. We test this technique at a forested site in southern California for a period of 8 months. We show that variations in GNSS signal-to-noise ratios reflect the overall distribution of biomass density in the canopy and can be monitored continuously. For the first time, we show that this technique can resolve diurnal variations in VOD and canopy water content at hourly to sub-hourly time steps. Using a model of canopy transmissivity to assess these diurnal signals, we find that temperature effects on the vegetation dielectric constant, and thus on VOD, may be non-negligible at the diurnal scale or during extreme events like heat waves. Sensitivity to rainfall and dew deposition events also suggests that canopy water interception can be monitored with this approach. The technique presented here has the potential to resolve two important knowledge gaps, namely the lack of ground truth observations for satellite-based VOD and the need for a reliable proxy to extrapolate isolated and labor-intensive in situ measurements of biomass, canopy water content, or leaf water potential. We provide recommendations for deploying such off-the-shelf and easy-to-use systems at existing ecohydrological monitoring networks such as FluxNet or SapfluxNet.

Optimal decision for the satellite navigation system under navigation countermeasures based on spoofing effect evaluation results

AbstractThis paper realizes the evaluation and optimal decision of the spoofing effect on the global navigation satellite system (GNSS) under navigation countermeasures based on the game perspective, to overcome the limitations of current relevant research findings and maintain the secure application of the GNSS and maximize its defensive benefit during countering. An evaluation system based on the perspective of the game between spoofing strategies and defense measures is created to build the benefit matrix, which can solve the limitation in building a benefit matrix (the vital element in a game) that conforms to the confrontation‐oriented GNSS spoofing properties. Based on the built benefit matrix, a method integrating the grey expert‐based system with the hybrid evolutionary method is developed to realize quantifying the matrix and further make the optimal decision stably, which can solve the uncertainties of qualitative indices during quantifying and no global optimal solution for benefit equations deduced from the quantified matrix. Finally, based on various judgment principles, simulation and testing results verify the effectiveness of the obtained results and the superiority of the proposed method by comparing the results solved by the method in this paper with the results obtained by other decision‐making processing methods.

Changes in the long-term stability of GPS, GLONASS and Galileo clocks based on the IGS repro3 campaign

Abstract Time is the basis of satellite navigation systems. In precision studies, it is additionally important to ensure accuracy at the highest possible level, up to sub-millimetres. For this purpose, corrections of the clocks of satellites and GNSS reference stations are made available. This type of data is made available in real time in a navigation dispatch with an interval of 10 min–2 h depending on the GNSS system, or in a precision orbit file (interval of 15 min) or in the form of clock correction files (30 s or 300 s). This paper analyses the long-term stability of the clocks of satellites of four GNSS systems. For this purpose, IGS reprocessing data from 1994 to 2020 were used and ADEV (Allan deviation) and three related variances were adopted. The study showed the different nature of the satellite correction for each GNSS system and the increase of the stability over time.

Real‐time precise orbit determination for FY‐3C and FY‐3D based on BDS and GPS onboard observation

AbstractThe code multipath error associated with elevation in BDS‐2 is one of the main factors whose impact on the precision of real‐time reduced‐dynamic precise orbit determination (POD) using spaceborne multi‐global navigation satellite systems (GNSS) observation data for FengYun‐3C (FY‐3C) and FengYun‐3D (FY‐3D) satellites. The aim is to construct a code multipath piece‐wise linear error model and analyse the contribution of BDS‐2 to the performance of low earth orbit POD. Conclusions are drawn out from the experimental results: (1) the real‐time POD average precision of FY‐3C and FY‐3D is improved by about 11% and 12% after the correction of BDS‐2 code multipath error; (2) Due to the small number of available BDS‐2 satellites and the limited accuracy of geostationary earth orbit (GEO) satellite real‐time orbit products, the precision of the real‐time overlapping comparison for FY‐3C/FY‐3D by using the BDS‐2 onboard observation data can only reach the decimetre level. However, with the BDS‐2 signal capture capability of the FY‐3D onboard GNSS Occultation Sounder upgraded, the average precision of the BDS‐2‐based POD for FY‐3D is better than that of FY‐3C in each direction and with 10% improvement in the average 3 dimensional‐root mean square (3D‐RMS); (3) Cases of onboard global positioning system (GPS), GPS + BDS‐2 (with GEO), and GPS + BDS‐2 (without GEO) for real‐time POD can meet 5–8 cm precision requirement. The average 3D‐RMS of the real‐time POD for FY‐3C/FY‐3D, which utilises onboard GPS + BDS‐2 data is inferior only to GPS data, owing to the influence of the orbit accuracy of GEO satellites. However, after excluding the influence of GEO satellites, the average result (3D‐RMS) of the real‐time POD for FY‐3C (6.11 cm) and FY‐3D (5.95 cm) is better than those of other cases.

Robust Autonomous Vehicle Computer-Vision-Based Localization in Challenging Environmental Conditions

In this paper, we present a novel autonomous vehicle (AV) localization design and its implementation, which we recommend to employ in challenging navigation conditions with a poor quality of the satellite navigation system signals and computer vision images. In the case when the GPS signal becomes unstable, other auxiliary navigation systems, such as computer-vision-based positioning, are employed for more accurate localization and mapping. However, the quality of data obtained from AV’s sensors might be deteriorated by the extreme environmental conditions too, which infinitely leads to the decrease in navigation performance. To verify our computer-vision-based localization system design, we considered the Arctic region use case, which poses additional challenges for the AV’s navigation and might employ artificial visual landmarks for improving the localization quality, which we used for the computer vision training. We further enhanced our data by applying affine transformations to increase its diversity. We selected YOLOv4 image detection architecture for our system design, as it demonstrated the highest performance in our experiments. For the computational platform, we employed a Nvidia Jetson AGX Xavier device, as it is well known and widely used in robotic and AV computer vision, as well as deep learning applications. Our empirical study showed that the proposed computer vision system that was further trained on the dataset enhanced by affine transformations became robust regarding image quality degradation caused by extreme environmental conditions. It was effectively able to detect and recognize images of artificial visual landmarks captured in the extreme Arctic region’s conditions. The developed system can be integrated into vehicle navigation facilities to improve their effectiveness and efficiency and to prevent possible navigation performance deterioration.

A Redundant Measurement-Based Maximum Correntropy Extended Kalman Filter for the Noise Covariance Estimation in INS/GNSS Integration

The resolution accuracy of the inertial navigation system/global navigation satellite system (INS/GNSS) integrated system would be degraded in challenging areas. This paper proposed a novel algorithm, which combines the second-order mutual difference method with the maximum correntropy criteria extended Kalman filter to address the following problems (1) the GNSS measurement noise estimation cannot be isolated from the state estimation and suffers from the auto-correlated statistic sequences, and (2) the performance of EKF would be degraded under the non-Gaussian condition. In detail, the proposed algorithm determines the possible distribution of the measurement noise by a kernel density function detection, then depending on the detection result, either the difference sequences–based method or an autoregressive correction algorithm’s result is utilized for calculating the noise covariance. Then, the obtained measurement noise covariance is used in MCEKF instead of EKF to enhance filter adaptiveness. Meanwhile, to enhance the numerical stability of the MCEKF, we adopted the Cholesky decomposition to calculate the matrix inverse in the kernel function. The road experiment verified that our proposed method could achieve more accurate navigation resolutions than the compared ones.

From the Editors of the Special Issue on Urban Air Mobility and UAS Airspace Integration: Vision, Challenges, and Enabling Avionics Technologies

The integration of unmanned aircraft systems (UAS) in all classes of airspace represents, at the same time, an evolutionary and a revolutionary step in air transport operations. As a result, new concepts have emerged for UAS traffic management to support the anticipated traffic density growth and the need for safe beyond visual line-of-sight operations. Closely linked with these developments, urban/advanced air mobility (UAM/AAM) has appeared as a new and disruptive dimension for aviation, potentially enabling mobility of goods and people at a different scale compared with current operations, while also emphasizing the need of seamless integration with the existing air traffic management (ATM) framework. These UAS capabilities are reshaping the future of aviation, but also challenge traditional paradigms, requiring significant advances both in technologies and regulations, while keeping strong links with public communities and the perception of societal benefits. As an example, a key role is played by the progress of communications, navigation and surveillance technologies, such as sense-and-avoid and global navigation satellite systems-resilient, alternate position, navigation, and timing systems, and by the seamless integration of airborne and ground infrastructure within a cyber-aware context. Similarly, significant restructuring of the existing regulatory framework is needed to ensure that the integrity and safety of the AAM/ATM integrated airspace is maintained while enabling autonomous operations with higher technological flexibility and refresh rates.

Circular Probability Error Based Inertial Navigation System Assists Ultra-Wide Band and Satellite Navigation System Intersection Area Fusion Positioning Algorithm

Circular Probability Error Based Inertial Navigation System Assists Ultra-Wide Band and Satellite Navigation System Intersection Area Fusion Positioning Algorithm

Analysis of Characteristics for Inter-System Bias on Multi-GNSS Undifferenced and Uncombined Precise Point Positioning

Multi Global Navigation Satellite System (GNSS) Precise Point Positioning (PPP) has become the mainstream of PPP technology. Due to the differences in the coordinates and time references of each GNSS, multi-GNSS PPP must include additional Inter-System Bias (ISB) parameters to ensure compatibility between different GNSSs. Therefore, research on the characteristics of ISB is also essential. To analyze the short- and long-term time characteristics of multi-GNSS ISBs, as well as their relationship with receiver type and receiver antenna type, the Undifferenced and Uncombined (UDUC) PPP model of Global Positioning System (GPS), BeiDou navigation satellite system (BDS), and Galileo satellite navigation system (Galileo) was rigorously derived, and the physical of ISBs was elaborated in depth. ISB parameters were estimated and analyzed using 31 days of data from the 31 Multi-GNSS Experimental stations (MGEX). The results indicate that: (1) the ISB value is dependent on the station receiver type, receiver antenna type, analysis center product utilized, and GNSS system. (2) The short-term time characteristics of ISB-COM, ISB-WUM, and ISB-GBM are similar for the same station but not for the long term. In addition, ISBs are more stable in the short term. (3) There is little correlation between the ISB time characteristics, the receiver type, and the receiver antenna type, and the day-boundary discontinuity(DBD) on the ISB can be ignored for the concussive days’ process.

Ground penetrating radar investigation and georeferencing without global satellite navigation systems: The case history of the amphitheatre of Lecce, Italy

AbstractIn this work, we present a case history relative to ground penetrating radar measurements performed close to the Roman amphitheatre of Lecce, Italy. We have performed a classical data elaboration with focusing of the data and slicing putting into evidence hidden details of the structure of the monument. It will be shown that the interpretation of the ground penetrating radar data is meaningfully helped by the consultation of ancient documents, which makes the final result multidisciplinary. Finally, we have georeferenced the data matching the shape of the depth slices with the shape of the investigated roads. In fact, we did not have at disposal any differential global satellite navigation systems. Indeed, this can be a method exploitable in cases when satellite data are not available, either because the area is shadowed or because the user does not have a differential global satellite navigation system. The proposed geographical matching is achieved by means of the matching between the shape of the slices and those of the physical obstacles present in the field. Therefore, it is essentially based on a continuous of points, and so it is probably more precise than a method based on the only vertexes. In particular, the proposed procedure does not require any deformation of the shape of the slice.

Robust state and protection-level estimation within tightly coupled GNSS/INS navigation system

In autonomous applications for mobility and transport, a high-rate and highly accurate vehicle-state estimation is achieved by fusing measurements of global navigation satellite systems (GNSS) and inertial sensors. The state estimation and its protection-level generation often suffer from satellite-signal disturbances in urban environments and subsequent poor parametrization of the satellite observables. Thus, we propose an innovative scheme involving an extended H∞ filter (EHF) for robust state estimation and zonotope for the protection-level generation. This scheme is shown as part of a tightly coupled navigation system based on an inertial navigation system and aided by the GPS/Galileo dual-constellation satellite navigation system. Specifically, GNSS pseudorange and deltarange observables are utilized. The experimental results of post-processing a real-world dataset show significant advantages of EHF against a conventional extended Kalman filter regarding the navigation accuracy and robustness under various GNSS measurement parametrizations and environmental circumstances. The zonotope-based protection-level calculation is proven valid, computationally affordable, and feasible for real-time implementations.