Open Sky Conditions Research Articles

NeQuick-G and Android Devices: A Compromise between Computational Burden and Accuracy

Ionospheric delay is one of the largest errors affecting Global Navigation Satellite System (GNSS) positioning in open-sky conditions, and different methods are currently available for mitigating ionospheric effects including dual-frequency measurements and corrections from augmentation systems. For single-frequency standalone receivers, the most widely used approach to correct ionospheric delays is to rely on a model. In this respect, Klobuchar and NeQuick-G Ionospheric Correction Algorithms (ICAs) are the approaches adopted by GPS and Galileo, respectively. While the latter outperforms the Klobuchar model, it requires a significantly higher computational load, which can limit its exploitation in some market segments such as smartphones. In order to foster adoption of the NeQuick-G model in this type of device, a smart application of NeQuick-G is proposed. The solution relies on the assumption that ionospheric delays are practically constant over short time intervals. Thus, the update rate of the ionospheric correction computation can be significantly reduced. This solution was implemented, tested, and evaluated using real data collected with a static smartphone in an ad hoc set-up. The impact of reducing the ionospheric correction update rate has been evaluated in terms of processing time, of ionospheric correction deviations and in the Ranging Error (RE) and position domains. The analysis shows that a significant reduction of the processing time can be obtained with negligible degradation of the navigation solution.

Estimation of Individual Exposure to Erythemal Weighted UVR by Multi-Sensor Measurements and Integral Calculation.

Ultraviolet radiation (UVR) can be hazardous to humans, especially children, and is associated with sunburn, melanoma, and the risk of skin cancer. Understanding and estimating adults’ and children’s UVR exposure is critical to the design of effective interventions and the production of healthy UVR environments. Currently, there are limitations to the ways computer modeling and field measurements estimate individual UVR exposure in a given landscape. To address these limitations, this study developed an approach of integral calculation using six-directional (up, down, south, north, east, and west) field-measured UVR data and the estimated body exposure ratios (ER) for both children and adults. This approach showed high agreement when compared to a validated approach using ambient UVR and estimated ER data with a high r-square value (90.72% for child and adult models), and a low mean squared error (6.0% for child model and 5.1% for adult model) in an open area. This approach acting as a complementary tool between the climatology level and individual level can be used to estimate individual UVR exposure in a landscape with a complicated shady environment. In addition, measuring daily UVR data from six directions under open sky conditions confirmed that personal dosimeters underestimate actual individual UVR exposure.

Analysis of BeiDou/Galileo combined pseudo-range positioning performance in urban environment

The observation conditions have a significant influence on the positioning performance. GNSS signals are easily blocked in urban environments, which leads to discontinuity and instability of position solution. With the construction of BeiDou and Galileo satellite navigation system in the final stage, multi-satellite fusion will be the future development trend of GNSSs. This paper introduces the mathematical fusion model of Galileo and BeiDou satellite navigation system, typical urban coverage conditions are simulated, and a detailed in the aspects of number of visible satellites, positioning error and PDOP values are analysed. The results show that the positioning accuracy of the integrated navigation system in the horizontal is within 3 m, the elevation is within 5 m, and the PDOP value are less than 1.5 in the open sky condition. In any coverage conditions, Galileo stand-alone system cannot guarantee the positioning continuity in the whole day, and positioning performance is the worst in the north coverage condition, unable to obtain the position solutions for more than 40% time in the whole day. In the north coverage condition, BeiDou has the best positioning performance, with a minimum of 4 visible satellites and 99% of PDOP values are less than 10.

Vehicle ECEF Position Accuracy and Reliability in the Presence of DGNSS Communication Latency

Commercial on-vehicle implementation of Earth-referenced positioning at submeter accuracy with 95% probability would require widely and reliably available differential corrections; however, such corrections delivered on a nationwide or global scale via satellite systems will incur latency between their time-of-applicability and their time-of-reception at the vehicle. This article presents the results of a study with two main goals: <list list-type="ordered" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <list-item> <label>1)</label> To investigate the sensitivity of differential Global Navigation Satellite System (DGNSS) corrections and position estimation accuracy to communication latency; </list-item> <list-item> <label>2)</label> To investigate the feasibility of achieving meter-level positioning accuracy for at least 95% of epochs. </list-item> </list> <p xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">The article presents a local base station approach designed for robustness to latency and lost packets. It then experimentally evaluates correction and position accuracy as a function of communication latency under open sky condition. The article demonstrates submeter horizontal position accuracy for communication latency exceeding 500 s. The article presents and experimentally analyzes two state estimation approaches suitable for moving platforms. One uses DGNSS data only. The other uses DGNSS and inertial data. Using the DGNSS correction approach presented herein both are shown to achieve position accuracy (one meter at 98%) that exceeds the SAE J2945 specification.

Modeling of Real Time Kinematics localization error for use in 5G networks

In 5G networks information about localization of a user equipment (UE) can be used not only for emergency calls or location-based services, but also for the network optimization applications, e.g., network management or dynamic spectrum access by using Radio Environment Maps (REM). However, some of these applications require much better localization accuracy than currently available in 4G systems. One promising localization method is Global Navigation Satellite System (GNSS)-based Real-Time Kinematics (RTK). While the signal received from satellites is the same as in traditional GNSS, a new reception method utilizing real-time data from a nearby reference station (e.g., 5G base station) results in cm-level positioning accuracy. The aim of this paper is to obtain a model of the RTK localization error for smartphone-grade GNSS antenna under open-sky conditions, that can be used in 5G network simulators. First, a tutorial-style overview of RTK positioning, and satellite orbits prediction is provided. Next, an RTK localization simulator is implemented utilizing GNSS satellites constellations. Results are investigated statistically to provide a simple, yet accurate RTK localization error framework, which is based on two Gauss-Markov process generators parametrized by visible satellites geometry, UE motion, and UE-satellite distance error variance.

Experimental Testbed and Methodology for the Assessment of RTK GNSS Receivers Used in Precision Agriculture

Precision Agriculture (PA) refers to applications asking for reliable and highly available precise positions, at centimeter level, in most of operational scenarios. Machinery guidance, automatic steering and controlled traffic farming enable machinery to move along repeatable tracks on the field, minimizing pass-to-pass errors and overlaps. In the recent years, satellite-based navigation has also opened the door to (semi) autonomous machineries for some specific farming scenarios and operations. Farming industry is now looking to use small robots to bring efficiencies and benefits to farms, capable of complex tasks that have not been possible with traditional large-scale agricultural machinery. Even though the state-of-the-art Real Time Kinematic (RTK) Global Navigation Satellite System (GNSS) receivers usually match the requirements posed by PA applications in open fields, propagation effects degrade the performance under foliage or with surrounding obstacles. This paper presents an experimental testbed and methodology suitable to assess the real performance of RTK GNSS-based devices in operational environments. Such testbed and methodology were effective to compare different devices, which resulted to be equivalent in open-sky conditions, but with significant differences in other types of environments. The paper also discusses opportunities and current limits of GNSS for emerging PA applications based on small robots and artificial intelligence.

Geospatial Opinion on Unusual Locust Swarm Invasions during Amphan Cyclone

The desert locust, Schistocerca gregaria Forsk. (Orthoptera: Acrididae) is a peculiar insect that exhibits density-dependent phase polyphenism. Gregarious phase enables desert locust to form a large groups and mass migrations during which significant crop loss and food security issues may occur. Currently, the most recent upsurge of desert locust is prevailing across Eastern Africa and Southwestern Asia. Usually desert locusts are restricted to regions like semi-arid and arid regions. A super cyclonic storm, namely Amphan originated during May 2020, in the Bay of Bengal of North Indian Ocean has influenced numerous swarms to migrate from the Thar desert region to other parts of India. In this research, satellite data were used to investigate the reasons for this sudden swarm migration. The results that revealed the wind jets passing above the Thar desert region have integrated with the cyclogenesis of Amphan and led to the formation of conduits. The favorable conditions in the conduits include the open sky conditions, air temperature and fresh vegetation availability. Moreover, the wind settings in the conduits have enabled the swarm migrate to follow the downwind facing the sunrays during early mornings for an easy and successful take-off. It is observed that during the take-off session the wind speed at 850 hPa pressure level is mostly double than that of surface wind in both the conduits.

Microclima, produção e composição do mosto da ‘Syrah’ cultivada sob cobertura de plástico

Foi feita a caracterização do microclima do vinhedo, das variáveis de produção das videiras e das propriedades físico-químicas do mosto da uva para vinho ‘Syrah’ cultivada com cobertura e sem cobertura de plástico impermeável (ráfia). As videiras foram sustentadas em Y e manejadas em regime de safra de inverno na região produtora de uvas de Louveira, SP. Durante o período da maturação das uvas foram feitas determinações, na altura dos cachos, da radiação solar e da temperatura do ar. Na colheita foram determinadas as variáveis fitotécnicas (número de ramos, número de cachos, massa dos cachos e produtividade) e físico-químicas do mosto (teor de sólidos solúveis, acidez total, teor de ácido tartárico, antocianinas, polifenóis totais e taninos). Os valores de temperatura máxima do ar foram superiores nas videiras sob cobertura de plástico em comparação às cultivadas a céu aberto enquanto a radiação solar foi mais elevada na condição sem cobertura. A produtividade e o teor de sólidos solúveis totais foram mais elevados para as videiras sob cobertura de plástico. Não foi observada influência da cobertura de plástico impermeável nos teores de antocianina, polifenóis totais e taninos das uvas.

Improving Localization Accuracy in Connected Vehicle Networks Using Rao–Blackwellized Particle Filters: Theory, Simulations, and Experiments

A crucial function for automated vehicle technologies is accurate localization. Lane-level accuracy is not readily available from low-cost global navigation satellite system (GNSS) receivers because of factors such as multipath error and atmospheric bias. Approaches such as differential GNSS can improve localization accuracy, but usually require investment in expensive base stations. Connected vehicle technologies provide an alternative approach in improving the localization accuracy. It will be shown in this paper that localization accuracy can be enhanced using crude GNSS measurements from a group of connected vehicles, by matching their locations to a digital map. A Rao–Blackwellized particle filter is used to jointly estimate the common biases of the pseudo-ranges and the vehicle positions. Multipath biases, which introduce receiver-specific (non-common) error, are mitigated by a multi-hypothesis detection-rejection approach. The temporal correlation of the estimations is exploited through the prediction-update process. The proposed approach is compared with existing methods using both simulations and experimental results. It was found that the proposed algorithm can eliminate the common biases and reduce the localization error to below 1 m under open sky conditions.

Tight Fusion of a Monocular Camera, MEMS-IMU, and Single-Frequency Multi-GNSS RTK for Precise Navigation in GNSS-Challenged Environments

Precise position, velocity, and attitude is essential for self-driving cars and unmanned aerial vehicles (UAVs). The integration of global navigation satellite system (GNSS) real-time kinematics (RTK) and inertial measurement units (IMUs) is able to provide high-accuracy navigation solutions in open-sky conditions, but the accuracy will be degraded severely in GNSS-challenged environments, especially integrated with the low-cost microelectromechanical system (MEMS) IMUs. In order to navigate in GNSS-denied environments, the visual–inertial system has been widely adopted due to its complementary characteristics, but it suffers from error accumulation. In this contribution, we tightly integrate the raw measurements from the single-frequency multi-GNSS RTK, MEMS-IMU, and monocular camera through the extended Kalman filter (EKF) to enhance the navigation performance in terms of accuracy, continuity, and availability. The visual measurement model from the well-known multistate constraint Kalman filter (MSCKF) is combined with the double-differenced GNSS measurement model to update the integration filter. A field vehicular experiment was carried out in GNSS-challenged environments to evaluate the performance of the proposed algorithm. Results indicate that both multi-GNSS and vision contribute significantly to the centimeter-level positioning availability in GNSS-challenged environments. Meanwhile, the velocity and attitude accuracy can be greatly improved by using the tightly-coupled multi-GNSS RTK/INS/Vision integration, especially for the yaw angle.

Assessing horizontal accuracy of inventory plots in forests with different mix of tree species composition and development stage

Global navigation satellite systems (GNSS) have a wide range of applications in forest industry, including forest inventory. In this study, the horizontal accuracy of 45 inventory plots in different forest environments and 5 inventory plots under open sky conditions were examined. The inventory plots were located using a mapping-grade GNSS receiver during leaf-on season in 2017. True coordinates of the plot centres were acquired using a survey-grade GNSS receiver during leaf-off season in 2018. A study was conducted across a range of forest conditions in the forest unit Vígľaš, which is located in Slovakia (Central Europe). Root mean square error of horizontal accuracies was 8.45 m in the plots under forest canopy and 6.61 m under open sky conditions. We note decreased positional errors in coniferous forests as well as in younger forests. However, results showed that there is no statistically significant effect of tree species composition and stand age on horizontal accuracy.

Multi-UAV Path Planning for Autonomous Missions in Mixed GNSS Coverage Scenarios.

This paper presents an algorithm for multi-UAV path planning in scenarios with heterogeneous Global Navigation Satellite Systems (GNSS) coverage. In these environments, cooperative strategies can be effectively exploited when flying in GNSS-challenging conditions, e.g., natural/urban canyons, while the different UAVs can fly as independent systems in the absence of navigation issues (i.e., open sky conditions). These different flight environments are taken into account at path planning level, obtaining a distributed multi-UAV system that autonomously reconfigures itself based on mission needs. Path planning, formulated as a vehicle routing problem, aims at defining smooth and flyable polynomial trajectories, whose time of flight is estimated to guarantee coexistence of different UAVs at the same challenging area. The algorithm is tested in a simulation environment directly derived from a real-world 3D scenario, for variable number of UAVs and waypoints. Its solution and computational cost are compared with optimal planning methods. Results show that the computational burden is almost unaffected by the number of UAVs, and it is compatible with near real time implementation even for a relatively large number of waypoints. The provided solution takes full advantage from the available flight resources, reducing mission time for a given set of waypoints and for increasing UAV number.

Evaluation of a Low Cost Hand Held Unit with GNSS Raw Data Capability and Comparison with an Android Smartphone.

A newly available portable unit with GNSS raw data recording capability is assessed to determine static and kinematic position accuracy in various environments. This unit is the GPSMap 66, introduced by Garmin in early September. It is all-weather and robust for field use, and comes with a helix antenna. The high sensitivity chipset is capable of acquiring and tracking signals in highly attenuated environments. It can track single frequency GPS, GPS + GLONASS or GPS + Galileo and record code, Doppler and carrier phase data every second in the RINEX format. The evaluation presented herein focusses on GPS and Galileo. Static and kinematic test results obtained under a wide range of realistic field conditions are reported. Differential GNSS methods and Precise Point Positioning (PPP) are used to assess absolute position accuracy in ITRF coordinates, which is sufficiently close to the GPS and Galileo reference frame for the current purpose. Under low multipath conditions, measurements are found to be sufficiently accurate to provide single epoch, bias free position accuracy of a few metres. Accuracy is a function of signal attenuation and multipath conditions. The use of an external geodetic antenna significantly reduces measurement noise and multipath in high multipath environments. Carrier phase measurements, available more or less continuously under open sky conditions, significantly improve performance in differential mode. Accuracy in vehicular mode using code and carrier phase differential RTK solution is at the level of a few to several dm. Tests were conducted in parallel with a Huawei P10 Android 8.0 smartphone. The code measurement noise of this unit was found to be significantly higher than that of the GPSMap 66, a major reason being its lower performance PIFA antenna; carrier phase was only available for short time intervals, significantly degrading differential position accuracy performance.

Decoding Performance Analysis of GNSS Messages with Land Mobile Satellite Channel in Urban Environment

Demand for Global Navigation Satellite System (GNSS) applications in the urban environment has experienced a remarkable growth in recent years. However, the received signals are subjected to various urban channel impairments, like shadowing and multipath fading. Therefore, the decoding performance is different from that in open-sky conditions. In this paper, a two-state Land Mobile Satellite (LMS) channel based on the Markov process is used to model the urban channel properties, and then, the analysis of decoding performance in terms of frame error rate (FER) in the LMS channel is performed by evaluating the effect of three major influencing factors, specifically, coding and interleaving in the GNSS message, terminal speed, and satellite elevation angle. Extensive simulations are conducted on BDS-3 B1C B-CNAV1 message and GALILEO E5a F/NAV message. The results validate the excellent error correcting performance of the nonbinary low density parity check (NB-LDPC) code of the B-CNAV1 message and the effectiveness of interleaving in both of the messages in urban condition. Furthermore, it also shows that decoding performance improvement can be achieved with higher terminal speed and higher elevation angle in urban scenarios.

An Enhanced Multi-GNSS Navigation Algorithm by Utilising a Priori Inter-System Biases

The integration of multi-constellation Global Navigation Satellite System (GNSS) measurements can effectively improve the accuracy and reliability of navigation and positioning solutions, while the Inter-System Bias (ISB) is a key issue for compatibility. The ISB is traditionally estimated as an unknown parameter along with three-dimensional position coordinates and a receiver clock offset with respect to Global Positioning System (GPS) time. ISB estimation of this sort will sacrifice a satellite observation for each integrated GNSS system. These sacrificed observations could be vital in situations of limited satellite visibility. In this study, an enhanced multi-GNSS navigation algorithm is developed to avoid sacrificing observations under poor visibility conditions. The main idea of this algorithm is to employ a moving average filter to smooth the ISBs estimated at previous epochs. The filtered value is utilised as a priori information at the current epoch. Experimental tests were conducted to evaluate the enhanced algorithm under open and blocked sky conditions. The results show that the enhanced algorithm effectively improves the accuracy and availability of navigation solutions under the blocked sky condition, with performance being comparable to traditional ISB estimation algorithms in open sky conditions. The improvement rates of the three-dimensional position accuracy and availability reach up to 63% and 21% in the blocked sky environment. Even in the case of only four different GNSS satellites, a position solution can still be obtained using the enhanced algorithm.

Rigorous Performance Evaluation of Smartphone GNSS/IMU Sensors for ITS Applications.

With the rapid growth in smartphone technologies and improvement in their navigation sensors, an increasing amount of location information is now available, opening the road to the provision of new Intelligent Transportation System (ITS) services. Current smartphone devices embody miniaturized Global Navigation Satellite System (GNSS), Inertial Measurement Unit (IMU) and other sensors capable of providing user position, velocity and attitude. However, it is hard to characterize their actual positioning and navigation performance capabilities due to the disparate sensor and software technologies adopted among manufacturers and the high influence of environmental conditions, and therefore, a unified certification process is missing. This paper presents the analysis results obtained from the assessment of two modern smartphones regarding their positioning accuracy (i.e., precision and trueness) capabilities (i.e., potential and limitations) based on a practical but rigorous methodological approach. Our investigation relies on the results of several vehicle tracking (i.e., cruising and maneuvering) tests realized through comparing smartphone obtained trajectories and kinematic parameters to those derived using a high-end GNSS/IMU system and advanced filtering techniques. Performance testing is undertaken for the HTC One S (Android) and iPhone 5s (iOS). Our findings indicate that the deviation of the smartphone locations from ground truth (trueness) deteriorates by a factor of two in obscured environments compared to those derived in open sky conditions. Moreover, it appears that iPhone 5s produces relatively smaller and less dispersed error values compared to those computed for HTC One S. Also, the navigation solution of the HTC One S appears to adapt faster to changes in environmental conditions, suggesting a somewhat different data filtering approach for the iPhone 5s. Testing the accuracy of the accelerometer and gyroscope sensors for a number of maneuvering (speeding, turning, etc.,) events reveals high consistency between smartphones, whereas the small deviations from ground truth verify their high potential even for critical ITS safety applications.

Effects of shading nets on sunburn and quality of ‘Granny Smith’ apple fruits

Sunburn causes some damage to apple orchards and it results from heat stress to the fruit leading to injury of the affected cells. A net shield is a good option for protection of apple trees against damage by hail, strong wind, and birds. Also, it reduces sunburn and russeting of fruits, provides better color and skin uniformity. This study was carried out to determine the effects of two different light transmission shade nets (black and white) on 'Granny Smith' apple fruits sunburn and quality. The experiment was conducted in commercial apple orchard in Denizli, west part of Turkey during two consecutive years (2012-2013). Fruit sunburn ratio was 24% under open sky (without net) condition. Black or white shading nets reduced sunburn of fruits without negative effects on fruit quality and maturation.

Estimation of wet canopy bulk stomatal resistance from energy flux measurements during sprinkler irrigation

Bulk stomatal resistance, also known as surface resistance, is typically assumed to be zero during rainfall or other circumstances when a foliage canopy is wet, such as during sprinkler irrigation. However, some recent studies have suggested that resistance does not necessarily fall completely to zero. Although the assumption of zero bulk stomatal resistance for a wet canopy condition may be reasonable, estimation of actual evaporation as well as bulk stomatal resistance during wet conditions via the Penman-Montieth (P-M) equation is still problematic due to the difficulties in measuring the various energy fluxes in the energy balance. It has recently been demonstrated that eddy covariance (ECV) can be used to estimate the actual evapotranspiration during both irrigation and non-irrigation periods. It has also been shown that advection is important in sprinkler irrigation. . In Tthis paper it is demonstrateddemonstrates how the same technique can also provide an estimate of the bulk stomatal resistance for a wet crop canopy. It is shown that when all significant energy terms (including advected energy) are taken into account, the bulk stomatal resistance was effectively zero, in contrast to dry canopy values for the same crop of order 30 s m–1, both determined under midday, open sky conditions. The study also shows that ignoring advected energy can lead to an overestimation of bulk stomatal resistance and underestimation of ET when the canopy is wet.

Innovative Method to Avoid the Open-Sky Condition in Penetrating Keratoplasty and the Triple Procedure

Innovative Method to Avoid the Open-Sky Condition in Penetrating Keratoplasty and the Triple Procedure

GNSS space-time interference mitigation and attitude determination in the presence of interference signals.

The use of Space-Time Processing (STP) in Global Navigation Satellite System (GNSS) applications is gaining significant attention due to its effectiveness for both narrowband and wideband interference suppression. However, the resulting distortion and bias on the cross correlation functions due to space-time filtering is a major limitation of this technique. Employing the steering vector of the GNSS signals in the filter structure can significantly reduce the distortion on cross correlation functions and lead to more accurate pseudorange measurements. This paper proposes a two-stage interference mitigation approach in which the first stage estimates an interference-free subspace before the acquisition and tracking phases and projects all received signals into this subspace. The next stage estimates array attitude parameters based on detecting and employing GNSS signals that are less distorted due to the projection process. Attitude parameters enable the receiver to estimate the steering vector of each satellite signal and use it in the novel distortionless STP filter to significantly reduce distortion and maximize Signal-to-Noise Ratio (SNR). GPS signals were collected using a six-element antenna array under open sky conditions to first calibrate the antenna array. Simulated interfering signals were then added to the digitized samples in software to verify the applicability of the proposed receiver structure and assess its performance for several interference scenarios.