Search

UAVs are nowadays used for several surveying activities, some of which imply flying close to tall walls, in and out of tunnels, under bridges, and so forth. In these applications, RTK GNSS positioning delivers results with very variable quality. It allows for centimetric-level kinematic navigation in real time in ideal conditions, but limitations in sky visibility or strong multipath effects negatively impact the positioning quality. This paper aims at assessing the RTK positioning limitations for lightweight and low-cost drones carrying cheap GNSS modules when used to fly in some meaningful critical operational conditions. Three demanding scenarios have been set up simulating the trajectories of drones in tasks such as infrastructure (i.e., building or bridges) inspection. Different outage durations, flight dynamics, and obstacle sizes have been considered in this work to have a complete overview of the positioning quality. The performed tests have allowed us to define practical recommendations to safely fly drones in potentially critical environments just by considering common software and standard GNSS parameters.

This study documented the contribution of precise positioning involving a global navigation satellite system (GNSS) and a real-time kinematic (RTK) system in unmanned aerial vehicle (UAV) photogrammetry, particularly for establishing the coordinate data of ground control points (GCPs). Without augmentation, GNSS positioning solutions are inaccurate and pose a high degree of uncertainty if such data are used in UAV data processing for mapping. The evaluation included a comparative assessment of sample coordinates involving RTK and an ordinary GPS device and the application of precise GCP data for UAV photogrammetry in field crop research, monitoring nitrogen deficiency stress in maize. This study confirmed the superior performance of the RTK system in providing positional data, with 4 cm bias as compared to 311 cm with the non-augmented GNSS technique, making it suitable for use in agronomic research involving row crops. Precise GCP data in this study allow the UAV-based Normalized Difference Red-Edge Index (NDRE) data to effectively characterize maize crop responses to N nutrition during the growing season, with detailed analyses revealing the causal relationship in that a compromised optimum canopy chlorophyll content under limiting nitrogen environment was the reason for reduced canopy cover under an N-deficiency environment. Without RTK-based GCPs, different and, to some degree, misleading results were evident, and therefore, this study warrants the requirement of precise GCP data for scientific research investigations attempting to use UAV photogrammetry for agronomic field crop study.

Ruins, marked by decay and abandonment, present challenges for digital documentation due to their varied conditions and remote locations. Surveying inaccessible ruins demands innovative approaches for safety and accuracy. Drones with high-resolution cameras enable the detailed aerial inspection and imaging of these inaccessible areas. This study investigated how surveying technologies, particularly Unmanned Aerial Vehicles (UAVs), are used to document inaccessible ruins. Integration with Real-Time Kinematic (RTK) technologies allows direct georeferencing in photogrammetric processing. A case study of the Castle of Terracorpo in Italy was used to demonstrate UAV-only surveying feasibility in inaccessible environments, testing two different scenarios. The first scenario involved the use of a DJI Matrice 300 RTK coupled with the D-RTK2 base station to survey the Castle; both direct and indirect georeferencing were exploited and compared through the photogrammetric process. This first scenario confirmed that this approach can lead to a centimetre-level accuracy (about three times the GSD value for indirect georeferencing and seven times the GSD value for direct georeferencing exploting RTK). The second scenario testing the integration of data from drones at varying resolutions enabled the comprehensive coverage of ruinous structures. In this case, the photogrammetric survey performed with the dji Mavic 3 Cine drone (indirect georeferencing) was integrated with the photogrammetric survey performed with the dji Matrice 300 RTK drone (direct georeferencing). This scenario showed that GCPs extracted from a direct georeferencing photogrammetric survey could be successfully used to georeference and integrate other drone data. However, challenges persist in surveying underground or enclosed spaces that are inaccessible to UAVs. Future research will explore integrating robotic LiDAR survey systems and advanced data fusion techniques to enhance documentation.

Real-Time Kinematic Global Navigation Satellite System (RTK-GNSS) is currently the premier technique for achieving centimeter-level accuracy quickly and easily. However, the robustness of RTK-GNSS diminishes in challenging environments due to severe multipath effects and a limited number of available GNSS signals. This is a pressing issue, especially for GNSS users in the navigation industry. This paper proposes and evaluates several methodologies designed to overcome these issues by enhancing the availability and reliability of RTK-GNSS solutions in urban environments. Our novel approach involves the integration of conventional methods with a new technique that leverages surplus satellites—those not initially used for positioning—to more reliably detect incorrect fix solutions. We conducted three tests in densely built-up areas within the Tokyo region. The results demonstrate that our approach not only surpasses the fix rate of the latest commercial receivers and a popular open-source RTK-GNSS program but also improves positional reliability to levels comparable to or exceeding those of the aforementioned commercial technology.

Today, ground control points (GCPs) represent indispensable tools for products’ georeferencing in all the techniques concerning remote sensing (RS), particularly in monitoring activities from unmanned aircraft system (UAS) platforms. This work introduces an innovative tool, smart GCPs, which combines different georeferencing procedures, offering a range of advantages. It can serve three fundamental purposes concurrently: (1) as a drone takeoff platform; (2) as a base station, allowing the acquisition of raw global navigation satellite system (GNSS) data for post-processed kinematic (PPK) surveys or by providing real-time GNSS corrections for precision positioning; (3) as a rover in the network real-time kinematic (NRTK) mode, establishing its position in real time with centimetric precision. The prototype has undergone testing in a dedicated study area, yielding good results for all three geodetic correction techniques: PPK, RTK, and GCP, achieving centimeter-level accuracy. Nowadays, this versatile prototype represents a unique external instrument, which is also easily transportable and able to connect to the GNSS RING network, obtaining real-time positioning corrections for a wide range of applications that require precise positioning. This capability is essential for environmental applications that require a multitemporal UAS-based study. When the real-time RING data are accessible to the scientific community operating in RS surveying, this work could be a helpful guide for researchers approaching such investigations.

The performance of low-cost smart terminals is limited by the performance of their low-cost Global Navigation Satellite System (GNSS) hardware and chips, as well as by the impact of complex urban environments, which affect the positioning accuracy and stability of GNSS services. To this end, this paper proposes a robust adaptive Kalman filter for different environments that can be applied after data preprocessing. Based on the Kalman filter algorithm, a robust estimation approach is introduced into real-time kinematic (RTK) positioning to make judgments on the abnormal observation values of low-cost smart terminals, which amplifies the variance and covariance of the outlier observation equation, and reduces the impact of outliers on positioning performance. The Institute of Geodesy and Geophysics III (IGG III) function is used for regulation purposes, where prior information is modified and refreshed using the equivalent weight matrix and adaptive factors, thus reducing the impact of system model errors on system state estimation results. In addition, a robust factor is defined to adjust positioning deviation weighting between the pre- and post-test robust estimates. The experimental results show that after robust RTK positioning in the static experiments, the overall improvement in positioning accuracies of the Xiaomi 8, Huawei P40, Huawei mate40, and low-cost M8 receiver reached 29.6%, 31.3%, 32.1%, and 30.7%, respectively. Similarly, after applying the proposed robust method in the dynamic experiments, the overall positioning accuracies of the Xiaomi 8, Huawei P40, Huawei mate40, and the low-cost M8 receiver improved by 28.3%, 32.9%, 35.4%, and 26.2%, respectively. The experimental results reveal that an excellent positioning effect of a smartphone is positively correlated with robust RTK positioning performance. However, it is worth noting that when the positioning accuracy reaches a high level, such as the positioning results achieved using low-cost receivers, the robustness performance shows a relatively decreasing trend. This finding suggests that under the condition of high positioning accuracy, the sensitivity of specific positioning equipment to interference sources may increase, resulting in a decline in the effect of robust RTK positioning.

The development and growth of the eye depends on normal lens morphogenesis and its growth. This growth, in turn, is dependent on coordinated proliferation of the lens epithelial cells and their subsequent differentiation into fiber cells. These cellular processes are tightly regulated to maintain the precise cellular structure and size of the lens, critical for its transparency and refractive properties. Growth factor-mediated MAPK signaling driven by ERK1/2 has been reported as essential for regulating cellular processes of the lens, with ERK1/2 signaling tightly regulated by endogenous antagonists, including members of the Sprouty and related Spred families. Our previous studies have demonstrated the importance of both these inhibitory molecules in lens and eye development. In this study, we build on these findings to highlight the importance of Spreds in regulating early lens morphogenesis by modulating ERK1/2-mediated lens epithelial cell proliferation and fiber differentiation. Conditional loss of both Spred1 and Spred2 in early lens morphogenesis results in elevated ERK1/2 phosphorylation, hyperproliferation of lens epithelia, and an associated increase in the rate of fiber differentiation. This results in transient microphakia and microphthalmia, which disappears, owing potentially to compensatory Sprouty expression. Our data support an important temporal role for Spreds in the early stages of lens morphogenesis and highlight how negative regulation of ERK1/2 signaling is critical for maintaining lens proliferation and fiber differentiation in situ throughout life.

We compare the performance of dual-band (GPS L1/L2 and Galileo E1/E5a) real-time kinematic (RTK) positioning in an open sky and urban scenarios in southern Finland using two different authentication schemes: one using only satellites authenticated by Galileo’s open service navigation message authentication (OSNMA) service (which at the moment of our tests led to using only authenticated Galileo satellites) and the other with no authentication. The results show the actual trade-off between accuracy and availability vs. authenticity associated with using only OSNMA-authenticated satellites, while the authentication of only Galileo satellites is possible (e.g., a drop of RTK positioning availability from 96.67 to 86.01% in our open sky and from 73.55 to 18.65% in our urban scenarios, respectively), and an upper bound of the potential performance that could be reached in similar experimental conditions had the authentication of GPS satellites been supported (e.g., an overall 14 cm and 10.20 m 95% horizontal accuracy in our open sky and urban scenarios, with below 30, 20 and 10 cm during 97.39, 96.03 and 92.43% of the time in the open sky and 49.12, 45.96 and 39.63% in the urban scenarios, respectively).

Several trials have been carried out by various authors concerning autonomous mowers, which are battery-powered machines. The effects of these machines on turfgrass quality and energy consumption have been thoroughly investigated. However, there are still some aspects that have not been studied. Among these, random trajectory overlapping is one of the most important. To investigate these aspects, two RTK-GPS devices along with the custom-built software used for previous trials has been upgraded in order to precisely calculate how many times the mower drives over the same spot using random trajectories. This parameter, the number of passages in the same position, was hypothesized to explain the autonomous mower’s overlapping and trampling action. The trial has been carried out testing a commercial autonomous mower on three areas with different levels of complexity to assess its performances. The following variables were examined: the percentage of mowed area, the distance travelled, the number of intersections, the number of passages, and the autonomous mower’s work efficiency. The average percentage of area mown (average value for the three areas) was 54.64% after one hour and 80.15% after two hours of work. Percentage of area mown was 15% higher for the area with no obstacles after two hours of work. The number of passages was slightly different among the three garden designs. The garden with no obstacles obtained the highest number of passages with an average of 37 passages. The highest working efficiency was obtained in the garden with an intermediate number of obstacles with a value of 0.40 after two hours of work. The estimated energy consumption resulted 0.31 Wh m−2 after one hour and 0.42 Wh m−2 after two hours of working. These results highlight how the correct settings of cutting time may be crucial to consistently save energy during the long period and may be useful for a complete automation of the maintenance of green areas.

Advances in remote sensing and small unmanned aircraft systems (sUAS) have been applied to various precision agriculture applications. However, there has been limited research on the accuracy of real-time kinematic (RTK) sUAS photogrammetric elevation surveys, especially in preparation for precision agriculture practices that require precise topographic surfaces, such as increasing irrigation system efficiency. These practices include, but are not limited to, precision land grading, placement of levees, multiple inlet rice irrigation, and computerized hole size selection for furrow irrigation. All such practices rely, in some way, on the characterization of surface topography. While agro-terrestrial (ground-based) surveying is the dominant method of agricultural surveying, aerial surveying is emerging and attracting potential early adopters. This is the first study of its kind to assess the accuracy, precision, time, and cost efficiency of RTK sUAS surveying in comparison to traditional agro-terrestrial techniques. Our findings suggest sUAS are superior to ground survey methods in terms of relative elevation and produce much more precise raster surfaces than ground-based methods. We also showed that this emergent technology reduces costs and the time it takes to generate agricultural elevation surveys.

The spatial accuracy of unmanned aerial vehicles (UAVs) and the images they capture play a crucial role in the mapping process. Researchers are exploring solutions that use image-based techniques such as structure from motion (SfM) to produce topographic maps using UAVs while accessing locations with extremely high accuracy and minimal surface measurements. Advancements in technology have enabled real-time kinematic (RTK) to increase positional accuracy to 1–3 times the ground sampling distance (GSD). This paper focuses on post-processing kinematic (PPK) of positional accuracy to achieve a GSD or better. To achieve this, precise satellite orbits, clock information, and UAV global navigation satellite system observation files are utilized to calculate the camera positions with the highest positional accuracy. RTK/PPK analysis is conducted to improve the positional accuracies obtained from different flight patterns and altitudes. Data are collected at altitudes of 80 and 120 meters, resulting in GSD values of 1.87 cm/px and 3.12 cm/px, respectively. The evaluation of ground checkpoints using the proposed PPK methodology with one ground control point demonstrated root mean square error values of 2.3 cm (horizontal, nadiral) and 2.4 cm (vertical, nadiral) at an altitude of 80 m, and 1.4 cm (horizontal, oblique) and 3.2 cm (vertical, terrain-following) at an altitude of 120 m. These results suggest that the proposed methodology can achieve high positional accuracy for UAV image georeferencing. The main contribution of this paper is to evaluate the PPK approach to achieve high positional accuracy with unmanned aerial vehicles and assess the effect of different flight patterns and altitudes on the accuracy of the resulting topographic maps.

When surveying a large target area with a real-time kinematic unmanned aerial vehicle (RTK-UAV), the RTK signal tends to be disconnected when city canyons or macrocells are included. Thus, the accuracy is reduced due to the lack of RTK signal or the fact that RTK signal is not available in certain areas. The available methods to solve this problem are costly. Therefore, we used one GCP and performed post-process kinematics (PPK) to verify whether the accuracy reduction caused by the lack of RTK signal in certain areas could be solved. A data set detailing the percentage of time during which the RTK signal was received (100%, 90%, 5%, and 0%) was obtained, and ATs were conducted both with and without PPK using GCPs located at the four corners and center. In 40 experiments, the trend of root mean square error (RMSE) values based on the distance between the GCP used and the 41 check points (CPs) was analyzed. In the absence of PPK, the error tended to increase depending on the distance between the GCP and CPs, but there was no significant difference after PPK as up to 10 cm horizontal error and up to 20 cm vertical error were observed within a 1 km radius of the GCP. As a result, even if the RTK signal is disconnected during shooting, it is possible to achieve an accuracy within 3 GSD up to a radius of 1 km from the GCP.

Unmanned Aircraft Systems (UAS) are used in a variety of applications with the aim of mapping detailed surfaces from the air. Despite the high level of map automation achieved today, there are still challenges in the accuracy of georeferencing that can limit both the speed and the efficiency in mapping urban areas. However, the integration of topographic grade Global Navigation Satellite System (GNSS) receivers on UAS has improved this phase, leading to a reach of up to a centimeter-level accuracy. It is therefore necessary to adopt direct georeferencing (DG), real-time kinematic positioning (RTK)/post-processed kinematic (PPK) approaches in order to largely automate the photogrammetric flow. This work analyses the positional accuracy using Ground Control Points (GCP) and the repeatability and reproducibility of photogrammetric products (Digital Surface Model and ortho-mosaic) of a commercial multi-rotor system equipped with a GNSS receiver in an urban environment with a DG approach. It was demonstrated that DG is a viable solution for mapping urban areas. Indeed, PPK with at least 1 GCP considerably improves the RMSE (x: 0.039 m, y: 0.012 m, and z: 0.034 m), allowing for a reliable 1:500 scale urban mapping in less time when compared to conventional topographic surveys.

Global Navigation Satellite Systems provide autonomous vehicles with precise position information through the process of position augmentation. This paper presents a series of performance tests aimed to compare the position accuracy of augmentation techniques such as classical Differential Global Navigation Satellite System, Real-time Kinematic and Real-time eXtended. The aim is to understand the limitations and choose the best position augmentation technique in order to obtain accurate, trustworthy position estimates of a vehicle in urban environments. The tests are performed in and around the German cities of Wuppertal and Duesseldorf, using a vehicle fitted with the navigation system POS-LV 220, developed by Applanix Corporation. In order to evaluate the real-time performance of position augmentation techniques in a highly challenging environment, a total of four test regions are selected. The four test regions are characterized mainly by uneven terrain with tall buildings around the University of Wuppertal, flat terrain with roads of varying width in the city centre of Wuppertal and Duesseldorf and flat terrain in a tunnel section located in the city of Wuppertal. The performances of the different position augmentation are compared using a Root Mean Square (RMS) error estimate obtained as an output from the Applanix system. Furthermore, a High-Definition map of the environment is used for the purpose of model validation, which justifies the use of RMS error estimate as an evaluation metric for the performance analysis tests. According to the performance tests carried out as per the conditions specified in this paper, the Real-time eXtended (RTX) position augmentation method enables to obtain a more robust position information of the vehicle than Real-time Kinematic (RTK) method, with a typical accuracy of a few centimeter in an urban environment.

The global navigation satellite system (GNSS) real-time kinematic (RTK) technique is used to achieve relative positioning centimeter levels among multiple agents on the move. A typical GNSS RTK estimates the relative positions of multiple rover receivers with respect to a single-base receiver. In a fleet of rover GNSS receivers, this approach is inefficient because each rover receiver only uses GNSS measurements of its own and those sent from a single-base receiver. In this study, we propose a novel GNSS RTK framework that facilitates the precise positioning of a swarm of moving vehicles through the GNSS measurements of multiple receivers and broadcasts fixed-integer ambiguities of GNSS carrier phases. The proposed framework not only provides efficient RTK positioning but also reliable performance with a limited number of GNSS satellites in view. Our experimental flight tests with six GNSS receivers showed that the systematic procedure of the proposed framework could maintain lower than 6 cm of 3D RMS positioning errors, whereas the conventional RTK failed to resolve the correct integer ambiguities of double difference carrier phase measurements more than 13% in five out of nine total baselines.

Global Navigation Satellite Systems (GNSS)-based technologies have become an indispensable part of current structural health monitoring (SHM) systems because of the unique capability of the GNSS technologies to provide accurate real-time displacement information. GNSS equipment with a data sampling rate of up to about 20 Hz has been widely used for this purpose. High-rate GNSS systems (typically up to about 100 Hz) offer additional advantages in structural health monitoring as some highly dynamic civil structures, such as some bridges, require high-rate monitoring data to capture the dynamic behaviors. However, the performance of high-rate GNSS positioning in the context of structural health monitoring is not entirely known, as studies on structural monitoring with high-rate GNSS positioning are very limited, especially considering that some of the satellite systems just reached their full constellations very recently. We carried out a series of experiments with the help of a shaking table to assess the SHM performance of a set of 100 Hz GNSS equipment and three commonly used GNSS positioning techniques, PPP (precise point positioning), PPP-AR (precise point positioning with ambiguity resolution), and RTK (real-time kinematic). We found that the standard deviations of the 100 Hz GNSS displacement solutions derived from PPP, PPP-AR, and RTK techniques were 5.5 mm, 3.6 mm, and 0.8 mm, respectively, when the antenna was in quasi-static motion, and about 9.2 mm, 6.2 mm, and 3.5 mm, respectively, when the antenna was in vibration (up to about 0.7 Hz), under typical urban observational conditions in Hong Kong. We also found that the higher a sampling rate is, the lower the accuracy of a measured displacement series is. On average, the 10 Hz and 100 Hz results are 5.5% and 10.3%, respectively, noisier than the 1 Hz results.

Recently, FGFR inhibitors have been highlighted as promising targeted drugs due to the high prevalence of FGFR1 amplification in cancer patients. Although various potential biomarkers for FGFR inhibitors have been suggested, their functional effects have been shown to be limited due to the complexity of the cancer signaling network and the heterogenous genomic conditions of patients. To overcome such limitations, we have reconstructed a lung cancer network model by integrating a cell line genomic database and analyzing the model in order to understand the underlying mechanism of heterogeneous drug responses. Here, we identify novel genomic context-specific candidates that can increase the efficacy of FGFR inhibitors. Furthermore, we suggest optimal targets that can induce more effective therapeutic responses than that of FGFR inhibitors in each of the FGFR-resistant lung cancer cells through computational simulations at a system level. Our findings provide new insights into the regulatory mechanism of differential responses to FGFR inhibitors for optimal therapeutic strategies in lung cancer.

To improve the positioning accuracy and reliability of autonomous navigation agricultural machinery and reduce the cost of high-precision positioning, an integrated navigation system based on Real-Time Dynamic Kinematic BeiDou Navigation Satellite System (RTK-BDS) and Inertial Navigation System (INS) is designed in this study. On the one hand, an autonomous navigation control board is designed and made in the system, which integrates BDS high-precision analysis module, Inertial Measurement Unit (IMU) module, and radio module, and realizes the integrated navigation algorithm on the control board. On the other hand, low-cost RTK technology is realized by building differential reference stations and vehicle-mounted mobile stations. Experiments are carried out on actual farm machinery under different road conditions including open road, signal-shielded road, and urban congested road. According to the angular velocity and acceleration information from INS and the position and velocity information from the BDS high-precision analysis module, the system uses Kalman filter algorithm for data fusion to calculate the precise position, velocity, and attitude information of agricultural machinery in real time. The experimental results show that the position error of the integrated navigation system on the open road is within 3 cm, the azimuth error is within 0.6°, and the inclination error is within 1°, all of which converge rapidly when encountering bad road conditions. It can be known from the experimental results that the RTK-BDS/INS integrated navigation system has high positioning accuracy, strong adaptive anti-interference ability, and low implementation cost of RTK technology, which provides a reliable way for automatic navigation control of agricultural machinery.

The BeiDou Navigation Satellite System (BDS) is fully operational and provides positioning, navigation, and timing services to users worldwide. To comprehensively evaluate the BeiDou-3 Navigation Satellite System (BDS-3) global real-time kinematic (RTK) positioning performance, five sets of IGS/MEGX stations with different baseline lengths are selected in this research, and the visibility of current BDS-3, BDS-2+BDS-3, and Global Positioning System (GPS) system satellites are analyzed. The single frequency, dual-frequency, and triple-frequency positioning accuracy as well as ambiguity fixing rate under short baseline and long baseline are also analyzed. The experimental results show that the positioning accuracies of B1C, BII, L1, and B3I single-frequency bands were about the same, while for band B2a it was lower. For the short baseline dual-frequency RTK positioning mode, the accuracy of BDS-3 (B1C/B2a), BDS-3 (B1I/B3I), triple-frequency BDS-3 (B1C/B2a/B3I), and GPS (L1L2) is comparable and slightly better than that of BDS-3 (B1I/B3I). With the increase in baseline length, the advantages of dual-frequency BDS-3 (B1C/B2a) and triple frequency BDS (B1C/B2a/B3I) are more obvious, with triple-frequency BDS-3 (B1C/B2a/B3I) having the best positioning accuracy. In terms of ambiguity fixing performance, dual-frequency BDS-2+BDS-3 (B1I/B3I) and dual-frequency GPS (L1L2) have the highest ambiguity fixing rate. The ambiguity fixing rate of dual-frequency BDS-3 (B1C/B2a) and triple-frequency BDS-3 (B1C/B2a/B3I) can be higher than 90% within 100 km. In the case of positioning using only the BDS-3 system, the triple-frequency BDS-3 (B1C/B2a/B3I) is superior to both the dual-frequency BDS-3 (B1I/B3I) and dual-frequency BDS-3 (B1C/B2a) in terms of both positioning accuracy and ambiguity fixing rate. The BDS-2+BDS-3 (B1I/B3I) dual-frequency RTK, which has reached a level comparable to GPS, can provide global users with real-time centimeter-level differential positioning services.

The Real-Time Kinematic (RTK) positioning algorithm is a promising positioning technique that can provide real-time centimeter-level positioning precision in GNSS-friendly areas. However, the performance of RTK can degrade in GNSS-hostile areas like urban canyons. The surrounding buildings and trees can reflect and block the Global Navigation Satellite System (GNSS) signals, obstructing GNSS receivers’ ability to maintain signal tracking and exacerbating the multipath effect. A common method to assist RTK is to couple RTK with the Inertial Navigation System (INS). INS can provide accurate short-term relative positioning results. The Extended Kalman Filter (EKF) is usually used to couple RTK with INS, whereas the GNSS outlying observations significantly influence the performance. The Robust Kalman Filter (RKF) is developed to offer resilience against outliers. In this study, we design an algorithm to improve the traditional RKF. We begin by implementing the tightly coupled RTK/INS algorithm and the conventional RKF in C++. We also introduce our specific implementation in detail. Then, we test and analyze the performance of our codes on public datasets. Finally, we propose a novel algorithm to improve RKF and test the improvement. We introduce the Carrier-to-Noise Ratio (CNR) to help detect outliers that should be discarded. The results of the tests show that our new algorithm’s accuracy is improved when compared to the traditional RKF. We also open source the majority of our code, as we find there are few open-source projects for coupled RTK/INS in C++. Researchers can access the codes at our GitHub.

In emergency response and disaster rescue, unmanned aerial vehicles (UAVs) onboard thermal infrared (TIR) sensors are an essential means of acquiring ground information in the nighttime working environment. To enable field personnel to make better decisions based on TIR video streams returned from a UAV, the geographic information enhancement of TIR video streams is required. At present, it is difficult for low-cost UAVs to carry high-precision attitude sensors and thus obtain high-precision camera attitude information to meet the enhanced processing requirements of UAV TIR video streams. To this end, this paper proposes an improved Kalman filter algorithm to improve the geographic registration (geo-registration) accuracy by fusing the positioning and heading data from the dual-antenna real-time kinematic global positioning system (RTK-GPS) with onboard internal measurement unit (IMU) data. This method can yield high-precision position and attitude data in real time based on low-cost UAV hardware, based on which high-precision geo-registration results can be obtained. The computational complexity can be reduced compared with video stream feature tracking algorithms. Furthermore, the problem of unstable matching due to the low resolution and texture level of TIR video streams can be avoided. The experimental results prove that the proposed method can reduce the registration error by 66.15%, and significantly improve the geo-registration accuracy of UAV TIR video streams. Thus, it can strongly support the popularization and practicality of the application of augmented reality (AR) technology to low-cost UAV platforms.

The Google Smartphone Decimeter Challenge (GSDC) was a competition held in 2021, where data from a variety of instruments useful for determining a phone’s position (signals from GPS satellites, accelerometer readings, gyroscope readings, etc.) using Android smartphones were provided to be processed/assessed in regard to the most accurate determination of the longitude and latitude of user positions. One of the tools that can be utilized to process the GNSS measurements is RTKLIB. RTKLIB is an open-source GNSS processing software tool that can be used with the GNSS measurements, including code, carrier, and doppler measurements, to provide real-time kinematic (RTK), precise point positioning (PPP), and post-processed kinematic (PPK) solutions. In the GSDC, we focused on the PPK capabilities of RTKLIB, as the challenge only required post-processing of past data. Although PPK positioning is expected to provide sub-meter level accuracies, the lower quality of the Android measurements compared to geodetic receivers makes this performance difficult to achieve consistently. Another latent issue is that the original RTKLIB created by Tomoji Takasu is aimed at commercial GNSS receivers rather than smartphones. Therefore, the performance of the original RTKLIB for the GSDC is limited. Consequently, adjustments to both the code-base and the default settings are suggested. When implemented, these changes allowed RTKLIB processing to score 5th place, based on the performance submissions of the prior GSDC competition. Detailed information on what was changed, and the steps to replicate the final results, are presented in the paper. Moreover, the updated code-base, with all the implemented changes, is provided in the public repository. This paper outlines a procedure to optimize the use of RTKLIB for Android smartphone measurements, highlighting the changes needed given the low-quality measurements from the mobile phone platform (relative to the survey grade GNSS receiver), which can be used as a basis point for further optimization for future GSDC competitions.

Steep rock slopes present key opportunities and challenges within Earth science applications. Due to partial or complete inaccessibility, high-precision surveys of these high-relief landscapes remain a challenge. Direct georeferencing (DG) of unoccupied aerial vehicles (UAVs) with advanced onboard GNSS receivers presents opportunities to generate high-resolution 3D datasets without ground-based access to the study area. However, recent research has revealed large vertical errors using DG that may prove problematic in near-vertical terrain. To address these concerns, we examined more than 75 photogrammetric UAV-datasets with various imaging angles (nadir, oblique, and combinations) and ground control scenarios, including DG, along a steep slope exposure. Results demonstrate that mean errors in DG scenarios are up to 0.12 m higher than datasets using integrated georeferencing with well-distributed GCPs. Inclusion of GCPs greatly reduced mean error values but had limited influence on precision (

While the existing research provides a wealth of information about the static properties of RTK receivers, less is known about their dynamic properties, although it is clear that the vast majority of field operations take place when the machine is moving. A new method using a MRA for the evaluation of RTK receivers in movement with a precise circular reference trajectory (r = 3 m) was proposed. This reference method was developed with the greatest possible emphasis on the positional, time and repeatable accuracy of ground truth. Four phases of the measurement scenario (static, acceleration, uniform movement and deceleration) were used in order to compare four different types of RTK receiver horizontal operation accuracy over three measurement days. The worst result of one of the receivers was measured at SSR = 13.767% in dynamic movement. Since the same “low-cost” receiver without an INS unit had SSR = 98.14% in previous static measurements, so it can be assumed that the motion had a very significant effect on the dynamic properties of this receiver. On the other hand, the best “high-end” receiver with an INS unit had SSR = 96.938% during the dynamic testing scenarios. The median values of the deviations were always better during uniform movements than during acceleration or braking. In general, the positioning accuracy was worse in the dynamic mode than in the static one for all the receivers. Error indicators (RMSerr and Me) were found several times higher in the dynamic mode than in the static one. These facts should be considered in the future development of modern agricultural machinery and technology.

The real-time kinematic positioning technique (RTK) and visual–inertial odometry (VIO) are both promising positioning technologies. However, RTK degrades in GNSS-hostile areas, where global navigation satellite system (GNSS) signals are reflected and blocked, while VIO is affected by long-term drift. The integration of RTK and VIO can improve the accuracy and robustness of positioning. In recent years, smartphones equipped with multiple sensors have become commodities and can provide measurements for integrating RTK and VIO. This paper verifies the feasibility of integrating RTK and VIO using smartphones, and we propose an improved algorithm to integrate RTK and VIO with better performance. We began by developing an Android smartphone application for data collection and then wrote a Python program to convert the data to a robot operating system (ROS) bag. Next, we established two ROS nodes to calculate the RTK results and accomplish the integration. Finally, we conducted experiments in urban areas to assess the integration of RTK and VIO based on smartphones. The results demonstrate that the integration improves the accuracy and robustness of positioning and that our improved algorithm reduces altitude deviation. Our work can aid navigation and positioning research, which is the reason why we open source the majority of the codes at our GitHub.

GNSS real-time techniques and UAV photogrammetry can be alternative methods for the monitoring of sand beaches. This activity is particularly important in environments such as the Emilia-Romagna coastline. In this paper, two couples of surveys (year 2019 and 2020) performed using GNSS or a low-cost UAV equipment over a common area were compared in order to analyse: point-wise height differences, profile shapes along defined sections, and volumes variations over time. Both surveys were aligned to the same reference benchmark through GNSS measurements. The highest discrepancies between the two surveying methods (tens of cm) were found in vegetated areas and along the shoreline, otherwise, the height differences are mainly within the 10 cm level. In terms of volumes, excluding the most critical areas, differences close to zero can be found. Obtained results show that GNSS and UAV photogrammetry provides similar results, at least for quite flat terrains and when decimetre-level accuracy is required.

This work proposes a fully integrated ecosystem composed of three main components with a complex goal: to implement an autonomous system with a UAV requiring little to no maintenance and capable of flying autonomously. For this goal, was developed an autonomous UAV, an online platform capable of its management and a landing platform to enclose and charge the UAV after flights. Furthermore, a precision landing algorithm ensures no need for human intervention for long-term operations.

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

This paper investigated the achievable accuracy from a low-cost RTK (Real Time Kinematic)/PPK (Post Processing Kinematic) GNSS (Global Navigation Satellite Systems) system installed on board a UAV (Unmanned Aerial Vehicle), employing three different types of GNSS Bases (Alloy, RS2 and RING) working in PPK mode. To evaluate the quality of the results, a set of seven GCPs (Ground Control Points) measured by means of the NRTK (Network Real Time Kinematic) technique was used. The outcomes show a RMSE (Root Mean Square Error) of 0.0189 m for an ALLOY Base, 0.0194 m for an RS2 Base and 0.0511 m for RING Base, respectively, on the vertical value of DEMs (Digital Elevation Models) obtained by a photogrammetric process. This indicates that, when changing the Base for the PPK, the solutions are different, but they can still be considered adequate for precision positioning with UAVs, especially when GCPs could be used with some difficulty. Therefore, the integration of a RTK/PPK GNSS module on a UAV allows the reconstruction of a highly detailed and precise DEM without using GCPs and provides the possibility to carry out surveys in inaccessible areas.

As the modern navigation business evolves, demands for high-precision positioning in GNSS-challenged environments increase, and the integrated system composed of Global Navigation Satellite System (GNSS)-based Real-Time Kinematic (RTK), inertial system (INS), Light Detection and Ranging (LiDAR), etc., is accepted as the most feasible solution to the issue. For prior-map-free situations, as the only sensor with a global frame, RTK determines and maintains the global positioning precision of the integrated system. However, RTK performance degrades greatly in GNSS-challenged environments, and most of the existing integrated systems adopt loose coupling mode, which does nothing to improve RTK and, thus, prevents integrated systems from further improvement. Aiming at improving RTK performance in the RTK/LiDAR/INS integrated system, we proposed an innovative integrated algorithm that utilizes RTK to register LiDAR features while integrating the pre-registered LiDAR features to RTK and adopts parallel filters in the ambiguity-position-joint domain to weaken the effects of low satellite availability, cycle slips, and multipath. By doing so, we can improve the RTK fix rate and stability in GNSS-challenged environments. The results of the theoretical analyses, simulation experiments, and a road test proved that the proposed method improved RTK performance in GNSS-challenged environments and, thus, guaranteed the global positioning precision of the whole system.

Integer ambiguity resolution is required to obtain precise coordinates for the global navigation satellite system (GNSS). Poorly observed data cause unfixed integer ambiguity and reduce the coordinate accuracy. Previous studies mostly used denoise filters and partial ambiguity resolution algorithms to address this problem. This study proposes a sequential ambiguity resolution method that includes a float solution substitution process and a double-difference (DD) iterative correction equation process. The float solution substitution process updates the initial float solution, while the DD iterative correction equation process is used to eliminate the residual biases. The satellite-selection experiment shows that the float solution substitution process is adequate to obtain a more accurate float solution. The iteration-correction experiment shows that the double-difference iterative correction equation process is feasible with an improvement in the ambiguity success rate from 28.4% to 96.2%. The superiority experiment shows significant improvement in the ambiguity success rate from 36.1% to 83.6% and a better baseline difference from about 0.1 m to 0.04 m. It is proved that the proposed sequential ambiguity resolution method can significantly optimize the results for poorly-observed GNSS data.

Molecular alterations in cancer genes and associated signaling pathways are used to inform new treatments for precision medicine in cancer. Small molecule inhibitors and monoclonal antibodies directed at relevant cancer-related proteins have been instrumental in delivering successful treatments of some blood malignancies (e.g., imatinib with chronic myelogenous leukemia (CML)) and solid tumors (e.g., tamoxifen with ER positive breast cancer and trastuzumab for HER2-positive breast cancer). However, inherent limitations such as drug toxicity, as well as acquisition of de novo or acquired mechanisms of resistance, still cause treatment failure. Here we provide an up-to-date review of the successes and limitations of current targeted therapies for cancer treatment and highlight how recent technological advances have provided a new level of understanding of the molecular complexity underpinning resistance to cancer therapies. We also raise three basic questions concerning cancer drug discovery based on molecular markers and alterations of selected signaling pathways, and further discuss how combination therapies may become the preferable approach over monotherapy for cancer treatments. Finally, we consider novel therapeutic developments that may complement drug delivery and significantly improve clinical response and outcomes of cancer patients.

Global Navigation Satellite Systems (GNSS) have revolutionized land surveying, by determining position coordinates with centimeter-level accuracy in real-time or up to sub-millimeter accuracy in post-processing solutions. Although low-cost single-frequency receivers do not meet the accuracy requirements of many surveying applications, multi-frequency hardware is expected to overcome the major issues. Therefore, this paper is aimed at investigating the performance of a u-blox ZED-F9P receiver, connected to a u-blox ANN-MB-00-00 antenna, during multiple field experiments. Satisfactory signal acquisition was noticed but it resulted as >7 dB Hz weaker than with a geodetic-grade receiver, especially for low-elevation mask signals. In the static mode, the ambiguity fixing rate reaches 80%, and a horizontal accuracy of few centimeters was achieved during an hour-long session. Similar accuracy was achieved with the Precise Point Positioning (PPP) if a session is extended to at least 2.5 h. Real-Time Kinematic (RTK) and Network RTK measurements achieved a horizontal accuracy better than 5 cm and a sub-decimeter vertical accuracy. If a base station constituted by a low-cost receiver is used, the horizontal accuracy degrades by a factor of two and such a setup may lead to an inaccurate height determination under dynamic surveying conditions, e.g., rotating antenna of the mobile receiver.

Global navigation satellite systems (GNSSs) play a key role in intelligent transportation systems such as autonomous driving or unmanned systems navigation. In such applications, it is fundamental to ensure a reliable precise positioning solution able to operate in harsh propagation conditions such as urban environments and under multipath and other disturbances. Exploiting carrier phase observations allows for precise positioning solutions at the complexity cost of resolving integer phase ambiguities, a procedure that is particularly affected by non-nominal conditions. This limits the applicability of conventional filtering techniques in challenging scenarios, and new robust solutions must be accounted for. This contribution deals with real-time kinematic (RTK) positioning and the design of robust filtering solutions for the associated mixed integer- and real-valued estimation problem. Families of Kalman filter (KF) approaches based on robust statistics and variational inference are explored, such as the generalized M-based KF or the variational-based KF, aiming to mitigate the impact of outliers or non-nominal measurement behaviors. The performance assessment under harsh propagation conditions is realized using a simulated scenario and real data from a measurement campaign. The proposed robust filtering solutions are shown to offer excellent resilience against outlying observations, with the variational-based KF showcasing the overall best performance in terms of Gaussian efficiency and robustness.

The National Park Service (NPS) Submerged Resources Center (SRC) documented the East Key Construction Wreck in Dry Tortugas National Park using Structure from Motion photogrammetry, traditional archaeological hand mapping, and real time kinematic GPS (Global Positioning System) survey to test the accuracy of and establish a baseline “worst case scenario” for 3D models created with NPS SRC’s tri-camera photogrammetry system, SeaArray. The data sets were compared using statistical analysis to determine accuracy and precision. Additionally, the team evaluated the amount of time and resources necessary to produce an acceptably accurate photogrammetry model that can be used for a variety of archaeological functions, including site monitoring and interpretation. Through statistical analysis, the team determined that, in the worst case scenario, in its current iteration, photogrammetry models created with SeaArray have a margin of error of 5.29 cm at a site over 84 m in length and 65 m in width. This paper discusses the design of the survey, acquisition and processing of data, analysis, issues encountered, and plans to improve the accuracy of the SeaArray photogrammetry system.

The recommended treatment for metastatic urothelial carcinoma (mUC) patients is platinum-based chemotherapy. Although initial response rates are moderate, the vast majority of patients experience a relapse due to chemoresistance and eventually succumb to their disease. Furthermore, platinum-based chemotherapy is toxic and approximately 30% of mUC patients are unfit for chemotherapy. Thus, there is a clear unmet need for novel, more efficacious treatment options in mUC with a safer toxicity profile. To propel the advancement of novel treatment options, we present a summary of key signaling pathways and molecular mechanisms that are known to be involved in bladder cancer tumorigenesis with a focus on promising candidate druggable molecular targets and innovative targeted therapies currently under clinical investigation. Targetable alterations were mainly described in fibroblast growth factor receptor (FGFR) and epidermal growth factor receptor (ErbB) tyrosine kinase receptor (RTK) families, downstream pathways, and chromatin remodelers, which are major bladder cancer driver genes. Drugs targeting the FGFR family members are emerging as personalized treatment options for selected mUC patients with tumor-specific FGFR alterations. The pan-FGFR inhibitor, erdafitinib, was first-in-class to receive U.S. Food and Drug Administration (FDA) approval in 2019, while inhibitors of ErbB family members have shown less potential. Antibody-drug conjugates (ADCs) are a class of targeted therapeutics that deliver cytotoxic drugs in close proximity to cancer cells by targeting RTKs or other transmembrane proteins. Enfortumab vedotin is the first-in-class ADC that was FDA approved for the treatment of locally advanced or mUC in 2019.

The use of unmanned aerial vehicles (UAVs) is nowadays a standard approach in several application fields. Researches connected with these systems cover several topics and the evolution of these platforms and their applications are rapidly growing. Despite the high level of automatization reached nowadays, there is still a phase of the overall UAVs’ photogrammetric pipeline that requires a high effort in terms of time and resources (i.e., the georeferencing phase). However, thanks to the availability of survey-grade GNSS (Global Navigation Satellite System) receivers embedded in the aerial platforms, it is possible to also enhance this phase of the processing by adopting direct georeferencing approaches (i.e., without using any ground control point and exploiting real time kinematic (RTK) positioning). This work investigates the possibilities offered by a multirotor commercial system equipped with a RTK-enabled GNSS receiver, focusing on the accuracy of the georeferencing phase. Several tests were performed in an ad-hoc case study exploiting different georeferencing solutions and assessing the 3D positional accuracies, thanks to a network of control points. The best approaches to be adopted in the field according to accuracy requirements of the final map products were identified and operational guidelines proposed accordingly.

Decorin, the prototype member of the small leucine-rich proteoglycan gene family of extracellular matrix (ECM) proteins, acts as a powerful tumor suppressor by inducing the p21Waf1/Cip1 cyclin-dependent kinase inhibitor, as well as through its ability to directly bind and block the action of several tyrosine kinase receptors. Our previous studies suggested that the lack of decorin promotes hepatic carcinogenesis in mice. Based on this, we set out to investigate whether excess decorin may protect against the liver metastases of colon carcinoma. We also analyzed the effect of decorin in tissue microarrays of human colon carcinoma liver metastasis and examined whether the tumor cells can directly influence the decorin production of myofibroblasts. In humans, low levels of decorin in the liver facilitated the development of colon carcinoma metastases in proportion with more aggressive phenotypes, indicating a possible antitumor action of the proteoglycan. In vitro, colon carcinoma cells inhibited decorin expression in LX2 hepatic stellate cells. Moreover, liver-targeted decorin delivery in mice effectively attenuated metastasis formation of colon cancer. Overexpressed decorin reduced the activity of multiple receptor tyrosine kinases (RTKs) including the epidermal growth factor receptor (EGFR), an important player in colorectal cancer (CRC) pathogenesis. Downstream of that, we observed weakened signaling of ERK1/2, PLCγ, Akt/mTOR, STAT and c-Jun pathways, while p38 MAPK/MSK/CREB and AMPK were upregulated culminating in enhanced p53 function. In conclusion, decorin may effectively inhibit metastatic tumor formation in the liver.

This study proposes an algorithm that controls an autonomous, multi-purpose, center-articulated hydrostatic transmission rover to navigate along crop rows. This multi-purpose rover (MPR) is being developed to harvest undefoliated cotton to expand the harvest window to up to 50 days. The rover would harvest cotton in teams by performing several passes as the bolls become ready to harvest. We propose that a small robot could make cotton production more profitable for farmers and more accessible to owners of smaller plots of land who cannot afford large tractors and harvesting equipment. The rover was localized with a low-cost Real-Time Kinematic Global Navigation Satellite System (RTK-GNSS), encoders, and Inertial Measurement Unit (IMU)s for heading. Robot Operating System (ROS)-based software was developed to harness the sensor information, localize the rover, and execute path following controls. To test the localization and modified pure-pursuit path-following controls, first, GNSS waypoints were obtained by manually steering the rover over the rows followed by the rover autonomously driving over the rows. The results showed that the robot achieved a mean absolute error (MAE) of 0.04 m, 0.06 m, and 0.09 m for the first, second and third passes of the experiment, respectively. The robot achieved an MAE of 0.06 m. When turning at the end of the row, the MAE from the RTK-GNSS-generated path was 0.24 m. The turning errors were acceptable for the open field at the end of the row. Errors while driving down the row did damage the plants by moving close to the plants’ stems, and these errors likely would not impede operations designed for the MPR. Therefore, the designed rover and control algorithms are good and can be used for cotton harvesting operations.

Single-frequency GPS/BeiDou navigation satellite system (BDS) real-time kinematic (RTK) and inertial navigation system (INS) integration has wide range of application prospects due to the global deployment of GPS along with the rapid development of BDS. The instantaneous single-frequency ambiguity resolution will be significantly improved by the combined GPS/BDS and INS configuration. Owing to road conditions and an inertial measurement unit (IMU) on the carrier not being rigidly mounted, biased measurements in the IMU will occasionally emerge, leading to biased INS predictions. However, bias or inaccuracy from INS-predicted position can prevent the successful resolution of the whole set of ambiguities. This paper proposes the use of a positional polynomial fitting (PPF) constraint to compensate for the epochs with abnormal INS predictions. The aid from PPF is provided at two levels, i.e., at the ambiguity resolution (AR) level and at the solution level. In order to further increase the availability of ambiguity-fixed positioning solutions, a partial ambiguity resolution (PAR) strategy is introduced when full ambiguity resolution (FAR) fails. A field vehicular experiment was performed to show the validity of the proposed PPF-aided method by comparing different schemes regarding different INS-aided satellite system configurations, different AR strategies, and whether the PPF-aided method was adopted. The results show that the most attractive scheme is to combine the PAR with the PPF-aided dual-constellation and INS integration.

The reduction of multipath errors is a significant challenge in the Global Navigation Satellite System (GNSS), especially when receiving non-line-of-sight (NLOS) signals. However, selecting line-of-sight (LOS) satellites correctly is still a difficult task in dense urban areas, even with the latest GNSS receivers. This study demonstrates a new method of utilization of C/N0 of the GNSS to detect NLOS signals. The elevation-dependent threshold of the C/N0 setting may be effective in mitigating multipath errors. However, the C/N0 fluctuation affected by NLOS signals is quite large. If the C/N0 is over the threshold, the satellite is used for positioning even if it is still affected by the NLOS signal, which causes the positioning error to jump easily. To overcome this issue, we focused on the value of continuous time-series C/N0 for a certain period. If the C/N0 of the satellite was less than the determined threshold, the satellite was not used for positioning for a certain period, even if the C/N0 recovered over the threshold. Three static tests were conducted at challenging locations near high-rise buildings in Tokyo. The results proved that our method could substantially mitigate multipath errors in differential GNSS by appropriately removing the NLOS signals. Therefore, the performance of real-time kinematic GNSS was significantly improved.

The idea to verify the height of the highest peaks (summits) in the Crown of Polish Mountains arose after analyzing sources regarding the date and method of measuring the height of these mountain peaks. Our investigations revealed that this type of material is not usually available, and the first mention of height values is most often noted in the inter-war period, and occasionally before WWI (when Poland did not exist as an independent state); most of these values are still in use to this day. The problem of accurate measurement of the height of mountain peaks concerns not only the peaks analyzed by the authors, but also almost all mountain peaks worldwide. Therefore, as part of this work, several trips were organized to the highest peaks of several dozen mountain ranges in the territory of Poland. Measurement was made using a precise geodetic GNSS receiver an accuracy of within 10 cm and a DTM model based on ALS (airborne laser scanning). The results showed that commonly published heights can differ by up to several meters from the actual ones. The most important element of this work consists of the establishment of new measurements of the heights of the highest peaks of all mountain ranges in Poland, which may result in an alteration of the officially recorded heights based on this article. Apart from verification of these heights, this work also aimed to address the issue of the heights of all characteristic objects whose heights must be verified by using modern satellite techniques.

Integrity monitoring is an essential task for ensuring the safety of positioning services. Under a selected probability of hazardous misleading information, the protection levels (PLs) are computed according to a considered threat model to bound the positioning errors. A warning message is sent to users when the PL exceeds a pre-set alert limit (AL). In the short-baseline real-time relative kinematic positioning, the spatially correlated errors, such as the the orbital errors and the atmospheric delays are significantly reduced. However, the remaining atmospheric residuals and the multipath that are not considered in the observation model could directly bias the positioning results. In this contribution, these biases are analysed with the focus put on the multipath effects in different measurement environments. A new observation weighting model considering both the elevation angle and the signal-to-noise ratios is developed and their impacts on the positional results are investigated. The coefficients of the proposed weighting model are determined for the open-sky and the suburban scenarios with the positional benefits maximised. Next, the overbounding excess-mass cumulative distribution functions (EMCs) are searched on the between-receiver level for the weighted phase and code observations in these two scenarios. Based on the mean and standard deviations of these EMCs, horizontal protection levels (HPLs) are computed for the ambiguity-fixed solutions of real experiments. The HPLs are compared with the horizontal positioning errors (HPEs) and the horizontal ALs (HALs). Using the sequential exclusion algorithm developed for the ambiguity resolution in this contribution, the full ambiguity resolution can be achieved in around 100% and 95% of the time for the open-sky and the suburban scenarios, respectively. The corresponding HPLs of the ambiguity-fixed solutions are at the sub-dm to dm-level for both scenarios, and all the valid ambiguity-fixed HPLs are below a HAL of 0.5 m. For the suburban scenario with more complicated multipath environments, the HPLs increase by considering extra biases to account for multipath under a certain elevation threshold. In complicated multipath environments, when this elevation threshold is set to 30 degrees, the availability of the ambiguity-fixed solutions could decrease to below 50% for applications requiring HAL as low as 0.1 m.

The rapid increase of low-cost consumer-grade to enterprise-level unmanned aerial systems (UASs) has resulted in the exponential use of these systems in many applications. Structure from motion with multiview stereo (SfM-MVS) photogrammetry is now the baseline for the development of orthoimages and 3D surfaces (e.g., digital elevation models). The horizontal and vertical positional accuracies (x, y and z) of these products in general, rely heavily on the use of ground control points (GCPs). However, for many applications, the use of GCPs is not possible. Here we tested 14 UASs to assess the positional and within-model accuracy of SfM-MVS reconstructions of low-relief landscapes without GCPs ranging from consumer to enterprise-grade vertical takeoff and landing (VTOL) platforms. We found that high positional accuracy is not necessarily related to the platform cost or grade, rather the most important aspect is the use of post-processing kinetic (PPK) or real-time kinetic (RTK) solutions for geotagging the photographs. SfM-MVS products generated from UAS with onboard geotagging, regardless of grade, results in greater positional accuracies and lower within-model errors. We conclude that where repeatability and adherence to a high level of accuracy are needed, only RTK and PPK systems should be used without GCPs.

Precise real-time kinematic (RTK) Global Navigation Satellite System (GNSS) positioning requires fixing integer ambiguities after a short initialization time. Originally, it was assumed that it was only possible at a relatively short distance from a reference station (

This paper presents an evaluation of real-time kinematic (RTK)/Pseudolite/landmarks assistance heuristic drift elimination (LAHDE)/inertial measurement unit-based personal dead reckoning systems (IMU-PDR) integrated pedestrian navigation system for urban and indoor environments. Real-time kinematic (RTK) technique is widely used for high-precision positioning and can provide periodic correction to inertial measurement unit (IMU)-based personal dead reckoning systems (PDR) outdoors. However, indoors, where global positioning system (GPS) signals are not available, RTK fails to achieve high-precision positioning. Pseudolite can provide satellite-like navigation signals for user receivers to achieve positioning in indoor environments. However, there are some problems in pseudolite positioning field, such as complex multipath effect in indoor environments and integer ambiguity of carrier phase. In order to avoid the limitation of these factors, a local search method based on carrier phase difference with the assistance of IMU-PDR is proposed in this paper, which can achieve higher positioning accuracy. Besides, heuristic drift elimination algorithm with the assistance of manmade landmarks (LAHDE) is introduced to eliminate the accumulated error in headings derived by IMU-PDR in indoor corridors. An algorithm verification system was developed to carry out real experiments in a cooperation scene. Results show that, although the proposed pedestrian navigation system has to use human behavior to switch the positioning algorithm according to different scenarios, it is still effective in controlling the IMU-PDR drift error in multiscenarios including outdoor, indoor corridor, and indoor room for different people.

Single frequency real-time kinematic (RTK) positioning is expected to be the leading implementation platform for a variety of emerging GNSS mass-market applications. During RTK positioning, the most common source of measurement errors is carrier-phase cycle slips (CS). The presence of CS in carrier-phase measurements is tested by a CS detection technique and correspondingly taken care of. While using CS prone measurement data, positioning reliability is an area of concern for RTK users. Reliability can be linked with the CS detection scheme through a least squares (LS) adjustment process. This paper proposes a CS detection framework for reliable RTK positioning using single-frequency GNSS receivers. The scheme uses double differenced measurements for CS detection via LS adjustment using a detection, identification, and adaptation approach. For reliable positioning, the procedure to link the detection and identification stages is described. Through tests conducted on kinematic data, internal and external reliability are theoretically determined by calculating minimal detectable bias (MDB) and marginally detectable errors, respectively. After introducing CS, the actual values of MDB are found to be four cycles, which are higher than the theoretically obtained values of one and two cycles. Although CS detection for reliable positioning is implemented for single-frequency RTK users, the proposed procedure is generic and can be used whenever CS are detected through statistical tests during LS adjustment.

The c-Met receptor, also known as the HGF receptor, is one of the most studied tyrosine kinase receptors, yet its biological functions and activation mechanisms are still not fully understood. c-Met has been implicated in embryonic development and organogenesis, in tissue remodelling homeostasis and repair and in cancer metastasis. These functions are indicative of the many cellular processes in which the receptor plays a role, including cell motility, scattering, survival and proliferation. In the context of malignancy, sustained activation of c-Met leads to a signalling cascade involving a multitude of kinases that initiate an invasive and metastatic program. Many proteins can affect the activation of c-Met, including a variety of other cell surface and membrane-spanning molecules or receptors. Some cell surface molecules share structural homology with the c-Met extracellular domain and can activate c-Met via clustering through this domain (e.g., plexins), whereas other receptor tyrosine kinases can enhance c-Met activation and signalling through intracellular signalling cascades (e.g., EGFR). In this review, we provide an overview of c-Met interactions and crosstalk with partner molecules and the functional consequences of these interactions on c-Met activation and downstream signalling, c-Met intracellular localization/recycling and c-Met degradation.

GPS guidance of farm machinery has been increasingly adopted by farmers because of the perceived gains in efficiency that it provides. In the southeastern USA one of the reasons farmers adopt GPS guidance, and specifically automated steering (auto-steer), is that it can theoretically result in large yield gains when used to plant and invert peanuts—one of the region’s most important crops. The goal of our study was to quantify the yield benefit of using real time kinematic (RTK)-based auto-steer to plant and invert peanuts under a variety of terrain conditions. Yield benefits result from reduced digging losses. The study was conducted for two consecutive years (2010 and 2011) on a private farm in Georgia, USA. When all data are grouped together, auto-steer outperformed conventional by 579 kg/ha in 2010 and 451 kg/ha in 2011. We also evaluated the performance of auto-steer under different curvature conditions using low, medium, and high curvature rows. The results showed that auto-steer outperformed conventional under all curvature by a minimum of 338 kg/ha. Finally, we evaluated passive implement guidance in combination with auto-steer and found that it holds tremendous potential for further reducing digging losses. In many cases, auto-steer will pay for itself within a year.

Glioblastoma multiforme is the most frequent, aggressive and fatal type of brain tumor. Glioblastomas are characterized by their infiltrating nature, high proliferation rate and resistance to chemotherapy and radiation. Recently, oncologic therapy experienced a rapid evolution towards “targeted therapy,” which is the employment of drugs directed against particular targets that play essential roles in proliferation, survival and invasiveness of cancer cells. A number of molecules involved in signal transduction pathways are used as molecular targets for the treatment of various tumors. In fact, inhibitors of these molecules have already entered the clinic or are undergoing clinical trials. Cellular receptors are clear examples of such targets and in the case of glioblastoma multiforme, some of these receptors and their ligands have become relevant. In this review, the importance of glioblastoma multiforme in signaling pathways initiated by extracellular tyrosine kinase receptors such as EGFR, PDGFR and IGF-1R will be discussed. We will describe their ligands, family members, structure, activation mechanism, downstream molecules, as well as the interaction among these pathways. Lastly, we will provide an up-to-date review of the current targeted therapies in cancer, in particular glioblastoma that employ inhibitors of these pathways and their benefits.