1,721,062 research outputs found
What are the actual performances of GNSS positioning using smartphone technology?
No full text"Where I am?" is the typical question asked by a person when visiting a new city or unknown place. Knowing one's own location is generally a basic necessity for people, both in indoors and outdoors. Nowadays, thanks to new technologies, this position information is available in almost every moment and almost everywhere. For example, with a smartphone we can compute our position using the sensors available on the device that may include small inertial measurement units (IMUs), proximity sensors, barometer, and GPS/GNSS. GNSS is the most used because, in combination with a smartphone, it enables users to plan and carry out their activities, e.g., to calculate routes (used as a navigation system), to share their location on social networks, or to geolocalise images. But how accurate is the position provided by these sensors? And what accuracy can be achieved by GNSS-enabled smartphones? In outdoor scenarios, smartphone technology allows us to position ourselves with a good level of precision, thanks to the use of assisted GPS (A-GPS), radio-frequency positioning, and mapping. Despite that, in some cases the received GPS/GNSS signal is too noisy or not available at all (e.g., in urban canyons, inside buildings), and GNSS positioning is not possible. Because of this, many research groups are exploring prospective solutions that combine various kinds of sensors (GPS, INS, images, and so forth) and technologies (e.g., Wi-Fi, pedestrian tracking system, Bluetooth) in order to improve position accuracy and availability. However, this article focuses attention on GNSS-only positioning with smartphones, considering outdoor and urban canyon scenarios to give an overview of the precisions and accuracies available toda
UN METODO INNOVATIVO PER PREDIRE ED IDENTIFICARE I FALSI FISSAGGI DELL'AMBIGUITA' DI FASE GNSS IN RETI DI STAZIONI PERMANENTI
No full textUna delle criticità nel posizionamento GNSS NRTK (Real Time Kinematic Network) è il corretto fissaggio dell'ambiguità di fase. Questo lavoro vuole cercare di focalizzare l'attenzione sul controllo della qualità del posizionamento GNSS in tempo reale, sia dal punto di vista di ciò che la rete fornisce sia analizzando i prodotti di rete utilizzati da un generico ricevitore rover all'interno di una rete di stazioni permanenti. La qualità del posizionamento è un parametro che deve essere monitorata in tempo reale per evitare errati fissaggi dell'ambiguità di fase, chiamati anche FF (falso fissaggio); tali avvenimenti possono essere dovuti sia a problemi interni del software di rete sia, nella maggior parte dei casi, a fattori dipendenti dall'ambiente (ostruzioni, multipath etc.) nel quale il ricevitore opera. Al fine di poter identificare ma soprattutto predire tali accadimenti, è stato sviluppato uno strumento che, partendo dai dati disponibili in tempo reale da un utente connesso a un servizio di posizionamento RTK, può identificare con una certa soglia di probabilità della presenza effettiva, o la possibilità di accadimento, di un falso fissaggio. Lo stimatore dei FF sarà composto da una rete neurale, addestrata a priori con alcuni set di dati, ed avrà, come una singola uscita, un valore per ogni epoca che indicherà la probabilità che il fissaggio dell'ambiguità di fase sia corrett
Quality control of the kinematic positioning into GNSS networks
No full textGNSS (Global Navigation Satellite System) positioning is nowadays a common practice, not only in academia but also in the professional world, thanks to the development of several types of instruments and the decreasing costs of the receivers and antennae. Today, considering also the new constellations that are emerging, it is possible to affirm that GNSS positioning can be assessed almost everywhere: therefore, it is no longer necessary to ask whether satellite positioning is possible but rather how precise it can be. The main focus and goal of this thesis is to suggest new and innovative methodologies to control the quality of the positioning, focusing attention on the network positioning both in real time and post processing. Different types of instruments will be considered, in terms of both cost and performance: in fact, geodetic, GIS and mass-market receivers will be considered when used for Network Real-Time Kinematic (NRTK) or differential positioning. This thesis consists of five enlightening chapters. Chapter 1 includes a brief introduction to the subject as well as encompassing the research objectives and this outline. Chapter 2 outlines the quality control of geodetic and GIS receivers in a network of permanent stations, considering different types of networks, as a function of inter-station distances. Chapter 3 focuses attention on the quality of ambiguity fixing, considering an innovative method based on the creation of a tool that is able to predict a wrong geodetic receiver fix when it is used in a CORSs (Continuously Operating Reference Stations) network. Chapter 4 describes the quality control of the positioning when mass-market instruments (receivers and antennae) were used both in a network of permanent stations and as a network itself. Chapter 5 gives the conclusions and recommendations for further work. Two appendices conclude this work: the first concerns the Kalman filter in geodesy and its importance for real-time positioning, considering both the classical configuration and other versions (e.g. the extended Kalman filter and unscented Kalman filter); the second analyses more deeply the neural network concepts that are mentioned briefly in Chapter
The use of smartphone in the 21st century
Full text linkSmartphone devices are nowadays common affordable devices not only for communication purposes but also for determining the user’s position, for sending emails, managing digital agendas and to allow internet access. Starting from last decade, they become interesting instruments also for engineering and biomedical applications, thanks to their high diffusion. In 2018, 66% of individuals in 52 key countries owned a smartphone, with an increment of about 3% in only one year. This fact permitted the rapid development of apps for different goals, starting from precise positioning both in outdoor and indoor scenarios, to the 3D reconstruction of the environment using images up to driving evaluation purposes or healthcare and biomedical engineering applications. This chapter resumes the main research fields where smartphone devices are considered, providing the main references. It also introduces and briefly describes the contributions contained in this book, guiding the reader through the logical structure of the book in order to point out new possible studies and future perspectives in different reserch fields
Un metodo innovativo per predire ed identificare i falsi fissaggi delle ambiguità di fase GNSS in reti di stazioni permanenti
No full textOne of the most critical points during the GNSS NRTK (Network Real Time Kinematic) positioning is the correct fixing of the phase ambiguity. This work wants to try to focus attention on the quality control of the real-time GNSS positioning, both from the point of view of what the network provides, and from one of the network products is used by the rover receiver. The quality of the positioning is a parameter that must be monitored in real time to avoid an incorrect ambiguity fixing, also called FF (false fixing), occurring; this can be due both to internal problems of the network software and, more often, to the environment (obstructions, multipath and so on) within which where the receiver works. To achieve this control a tool was designed that, starting from the data available in real time from a user connected to an NRTK positioning service, can identify with a certain probability threshold the effective presence, or the possibility, of a false fixing. The FF estimator will be composed of a neural network, trained a priori with some datasets, and will have, as a single output, the probability that the current fixing is a false fixing of the phase ambiguity. Interesting and surprising results with geodetic GNSS receivers were obtained: in fact FFs are not only identified but also predicted correctly in 95% of cases, regardless of differential correction and the size of the network of permanent stations. In this work only parameters available in real time from the user were considered, but in the future the goal will be to consider also some network parameters in order to analyze why there are still unexplained FF
Network real-time kinematic GNSS positioning assisted by tablets: the new frontier of the open source positioning and mapping
No full textKinematic satellite positioning consists in estimating the trajectory of a moving receiver, by processing observations from Global Navigation Satellite Systems (GNSS). This is a well-known techniques if geodetic or GIS receivers are considered but nowadays it is also possible to make a precise positioning with other devices, such as smartphones and tablets. This study shows the performances of an external mass-market GPS L1 receiver connected to a tablet in NRTK positioning for GIS purpose
An innovative method to predict and to detect the false fixing of the GNSS ambiguity phase
Full text linkThe NRTK positioning has got a great development in recent years, thanks to the appearence of some networks of GNSS permanent stations. One of the main goals of these networks is to extend the real-time differential positioning beyond the limit of 10-15 km, allowing a positioning useful for applications such as surveying, monitoring, precise navigation.
This work wants try to focus the attention on the quality control of the real-time GNSS positioning both from what the network provides, and from one of the network products is used by the rover receiver.
The primary purpose is the correct fixing of the ambiguity phase in the double difference approach, considering the rover receiver. The quality of the positioning is a parameter that must be monitored in real-time to avoid that a wrong ambiguity fixing, also called FF (False Fixing), occur; often this is due both to internal problems of the network software and, more often, to the environment (obstructions, multipath ...) where the receiver works.
To achieve this control a tool was designed that, starting from the data available in real time by a user connected to an NRTK positioning service, can identify with a certain probability threshold the effective presence, or the possibility of a false fixing in the position. The input data of this instrument will be some of the real-time data available from the NMEA message, extractable from the rover receiver.
The FF estimator will be composed of a neural network, trained a priori with some datasets, and will have, as a single output, the probability that the current fixing is a false fixing of the ambiguity phase. In this regard, it will be necessary to identify, among all available data in real time, those most sensitive both to the deterioration of the accuracy and the presence of the false fixing. These parameters will be those used to calibrate ("train") the neural network. Downstream of the estimator, a representative index is provided as an output of the algorithm (similar to a traffic light), of the quality of the fixing, possibly allowing the user to re-initialize the measurement session. The change over time of these probabilities is useful to forecast an incorrect positioning (not always considered as a false fix) before it actually occurs.
Some tests were made and great results were obtained: the developed tool is able to predict approximately the 98% (on a sample of about 90 days of independent data with a rate of acquisition of 1 second) of false fixing considering parameters that are available for the rover receiver. This innovation will probably have a great importance in the future to increase the accuracy of the NRTK positioning
Single-frequency receivers as master permanent stations in GNSS networks: precision and accuracy of the positioning in mixed networks
Full text linkThe use of GPS/GNSS instruments is a common practice in the world at both a commercial and academic research level. Since last ten years, Continuous Operating Reference Stations (CORSs) networks were born in order to achieve the possibility to extend a precise positioning more than 15 km far from the master station. In this context, the Geomatics Research Group of DIATI at the Politecnico di Torino has carried out several experiments in order to evaluate the achievable precision obtainable with different GNSS receivers (geodetic and mass-market) and antennas if a CORSs network is considered. This work starts from the research above described, in particular focusing the attention on the usefulness of single frequency permanent stations in order to thicken the existing CORSs, especially for monitoring purposes. Two different types of CORSs network are available today in Italy: the first one is the so called "regional network" and the second one is the "national network", where the mean inter-station distances are about 25/30 and 50/70 km respectively. These distances are useful for many applications (e.g. mobile mapping) if geodetic instruments are considered but become less useful if mass-market instruments are used or if the inter-station distance between master and rover increases. In this context, some innovative GNSS networks were developed and tested, analyzing the performance of rover's positioning in terms of quality, accuracy and reliability both in real-time and post-processing approach. The use of single frequency GNSS receivers leads to have some limits, especially due to a limited baseline length, the possibility to obtain a correct fixing of the phase ambiguity for the network and to fix the phase ambiguity correctly also for the rover. These factors play a crucial role in order to reach a positioning with a good level of accuracy (as centimetric o better) in a short time and with an high reliability. The goal of this work is to investigate about the real effect and how is the contribute of L1 mass-market permanent stations to the CORSs Network both for geodetic and low-cost receivers; in particular is described how the use of the network products which are generated by the network (in real-time and post-processing) can improve the accuracy and precision of a rover 5, 10 and 15 km far from the nearest station. Some tests have been carried out considering different types of receivers (geodetic and mass market) and antennas (patch and geodetic). The tests have been conducted considering several positioning approaches (static, stop and go and real time) in order to make the analysis more complete. Good and interesting results were obtained: the followed approach will be useful for many types of applications (landslides monitoring, traffic control), especially where the inter-station distances of GNSS permanent station are greater than 30 k
Accurate Real-time GNSS positioning assisted by tablets: An innovative method for positioning and mapping
No full textKinematic satellite positioning consists in estimating the trajectory of a moving receiver, by processing observations from Global Navigation Satellite Systems (GNSS). This is a well-known technique if geodetic or GIS receivers are considered but nowadays it is also possible to make a precise positioning with other devices, such as smartphones and tablets. This study shows the performances of an external mass-market GPS L1 receiver connected to a tablet in NRTK positioning for GIS purposes. Impressive performances of mass-market GNSS instruments coupled with tablets are shown: with this kind of confguration it is possible to reach a centimetric level of accuracy in real-time. This means that interesting future developments could arise for different purposes, such as mapping and navigation
Quality control of the NRTK positioning with mass-market receivers
No full textThe employment of mass market receivers in a differential mode is not a standard procedure, especially into a network for NRTK positioning. This is because only few mass market receivers are able to yield raw data as output, almost no one accepts differential corrections, and for many applications is sufficient the WAAS augmentation. In actual fact, the improvements that can lead to the establishment of a network of CORSs (Continuous Operating Reference Stations) can be much higher with regard to these receivers, on condition that the raw data (code or carrier phase measurements) are used with special precautions. These receivers are very often used for the purpose of infomobility, but can also be used for precise farming.
In this chapter, attention is focused on the quality control of GNSS positioning in real time. The goal is to show how networks using NRTK (Network Real Time Kinematic) positioning for different inter-station distances may also be useful in a real-time approach. The objective is to show how CORSs networks are useful for mass-market receivers, considering the accuracy required for the purposes described above.
The accuracy of real-time positioning depends mainly on the type of receiver (whether it is single frequency or low-cost) and antenna (whether it is patch, mass-market or geodetic) used, as well as also the size of the network dimension (Dabove et al., 2011). Numerous experiments have been carried out on different types of networks and differential corrections, so we would like to show the results of such tests for the quality control of real-time positioning.
Excellent results are also been obtained with regard to two mass-market receivers and two antennas settled on the roof of a vehicle. The purpose of these experiments was not to determine the direction of the vehicle, but to constrain the ‘network’ and, simultaneously, to filter the outliers. Particular attention has been devoted to the increasing the quality of the positioning of a C/A-code receiver in real time, and to analyzing and investigating the innovative methods tested by the authors that involve the indicators provided by the rover itself, such as the signal to noise ratio (S/N) and the redundancy of the observations.
The experiments were conducted by splitting a single frequency antenna (Garmin) to both the receiver uBlox 6T and the geodetic receiver (Leica 1200), using the VRS correction and the differential correction of the Nearest station (about 20 km far away). With regard to the VRS correction, the correct fixing of the ambiguity phase is more than 60% of the trajectory and there were no false fixes. In such cases, the maximum planimetric error is less than 5 cm. Considering the positioning obtained by using float ambiguity (about 40%) the errors can be tightly controlled within the previously established parameters (S/N and HDOP). In this way, at least 50% of the trajectory has a maximum error of less than 20 cm. Using the Nearest correction, we have obtained a smaller quantity of integer ambiguity fix and, in this case, it is therefore possible to control the quality of the positioning using the HDOP and S/N parameters
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