236 research outputs found
A priori knowledge-free fast positioning approach for BeiDou receivers
A Global Navigation Satellite System (GNSS) receiver usually needs a
sufficient number of full pseudorange measurements to obtain a position
solution. However, it is time-consuming to acquire full pseudorange information
from only the satellite broadcast signals due to the navigation data features
of GNSS. In order to realize fast positioning during a cold or warm start in a
GNSS receiver, the existing approaches require an initial estimation of
position and time or require a number of computational steps to recover the
full pseudorange information from fractional pseudoranges and then compute the
position solution. The BeiDou Navigation Satellite System (BDS) has a unique
constellation distribution and a fast navigation data rate for geostationary
earth orbit (GEO) satellites. Taking advantage of these features, we propose a
fast positioning technique for BDS receivers. It simultaneously processes the
full and fractional pseudorange measurements from the BDS GEOs and non-GEOs,
respectively, which is faster than processing all full measurements. This
method resolves the position solution and recovers the full pseudoranges for
non-GEOs simultaneously within 1 s theoretically and does not need an estimate
of the initial position. Simulation and real data experiments confirm that the
proposed technique completes fast positioning without a priori position and
time estimation, and the positioning accuracy is identical with the
conventional single-point positioning approach using full pseudorange
measurements from all available satellites
A new approach for optimising GNSS positioning performance in harsh observation environments
Maintaining good positioning performance has always been a challenging task for Global Navigation Satellite Systems (GNSS) applications in partially obstructed environments. A method that can optimise positioning performance in harsh environments is proposed. Using a carrier double-difference (DD) model, the influence of the satellite-pair geometry on the correlation among different equations has been researched. This addresses the critical relationship between DD equations and its ill-posedness. From analysing the collected multi-constellation observations, a strong correlation between the condition number and the positioning standard deviation is detected as the correlation coefficient is larger than 0·92. Based on this finding, a new method for determining the reference satellites by using the minimum condition number rather than the maximum elevation is proposed. This reduces the ill-posedness of the co-factor matrix, which improves the single-epoch positioning solution with a fixed DD ambiguity. Finally, evaluation trials are carried out by masking some satellites to simulate common satellite obstruction scenarios including azimuth shielding, elevation shielding and strip shielding. Results indicate the proposed approach improves the positioning stability with multi-constellation satellites notably in harsh environments
Measurement signal quality assessment on all available and new signals of multi-GNSS (GPS, GLONASS, Galileo, BDS, and QZSS) with real data
Global Navigation Satellite Systems (GNSS) Carrier Phase (CP)-based high-precision positioning techniques have been widely used in geodesy, attitude determination, engineering survey and agricultural applications. With the modernisation of GNSS, multi-constellation and multi-frequency data processing is one of the foci of current GNSS research. The GNSS development authorities have better designs for the new signals, which are aimed for fast acquisition for civil users, less susceptible to interference and multipath, and having lower measurement noise. However, how good are the new signals in practice? The aim of this paper is to provide an early assessment of the newly available signals as well as assessment of the other currently available signals. The signal quality of the multi-GNSS (GPS, GLONASS, Galileo, BDS and QZSS) is assessed by looking at their zero-baseline Double Difference (DD) CP residuals. The impacts of multi-GNSS multi-frequency signals on single-epoch positioning are investigated in terms of accuracy, precision and fixed solution availability with known short baselines
Cost-Effective GNSS Hardware for High-Accuracy Surveys and Its Prospects for Post-Processed Kinematic (PPK) and Precise Point Positioning (PPP) Strategies
This dissertation determines for the first time the vertical accuracy achievable with low-cost mass-market multi-frequency, multi-GNSS (LM3GNSS) receivers, and antennas in the context of Ellipsoid Reference Survey (ERS), usually employed in bathymetric operations aboard survey platforms. LM3GNSS receivers are relatively new in the market, and their emergence is driven by the automobile industry and several mass-market applications requiring location-based solutions at high accuracies. It is foreseeable that emerging hydrographic survey platforms such as autonomous surface vehicles, small unmanned aircraft, crowd-sourced bathymetric platforms, and offshore GNSS buoy will find LM3GNSS receivers attractive since they are power- and cost-effective (often less than $1,000 per unit). Previous studies have shown that some mass-market GNSS receivers\u27 positioning accuracy is at the sub-meter level in some positioning strategies, but the authors rarely discussed the vertical accuracy. In rare cases where attention is given to the vertical component, the experiment design did not address the dynamic antenna scenario typical of hydrographic survey operations and the positioning performance that meets the hydrographic survey community\u27s aspirations.
The LM3GNSS receivers and low-cost antennas considered in this dissertation achieved vertical accuracies within 0.15 m at a 95% confidence level in simulated precise point positioning (PPP) and post-processed kinematic positioning strategies. This dissertation characterizes the signal strength, multipath, carrier-phase residuals, and code residuals in the measurement quality assessment of four LM3GNSS receivers and four low-cost antennas. The dissertation investigates the performances of the LM3GNSS receivers and low-cost antennas in different antenna-receiver pairings, relative to a high-grade GNSS receiver and antenna in simulated-kinematic and precise point positioning (PPP) strategies. This dissertation also shows that solutions with an uncalibrated antenna improve with a cloned ANTEX file making the results comparable to those achieved with high-end GNSS antenna. This dissertation also describes a GNSS processing tool (with graphic user interface), developed from scratch by the author, that implements, among others, orbit interpolation and geodetic computations as steps towards multipath computation and analysis. The dissertation concludes as follows: (1) The LM3GNSS hardware considered in this dissertation provides effective alternative positioning and navigation performance for emerging survey platforms such as ASV and sUAS. (2) LM3GNSS hardware can meet vertical positioning accuracy on the order of 0.15 m at a 95% confidence level in PPP strategy on less dynamic platforms. (3) LM3GNSS receivers can provide PPK solutions at medium (30 – 40 km) baselines with a vertical positioning accuracy better than 0.15m at a 95% confidence level. (4) LM3GNSS receivers in PPP strategy should meet IHO S-44 order-1 and order-2 in shallow waters. (5) Zephyr3 antenna, being a high-end GNSS antenna, may not always offer the best performance with the LM3GNSS receiver, especially in a dynamic environment. (6) Given the current tracking capabilities, the measurement quality, and positioning performances of LM3GNSS receivers relative to the geodetic grade receiver, it is foreseeable that the distinction between high-end GNSS and LM3GNSS receivers will most likely fade away as GNSS hardware technology advances. (7) Maximizing an LM3GNSS receiver in PPK strategy requires a multi-constellation-enabled reference station and high (i.e., 1 Hz) data tracking rate; otherwise, the PPK solutions will likely drift up to 20 cm
Analysis and Detection of Outliers in GNSS Measurements by Means of Machine Learning Algorithms
L'abstract è presente nell'allegato / the abstract is in the attachmen
Datalähtöinen lähestymistapa satelliittien valintaan globaaleissa satelliittipaikannusjärjestelmissä
The main goal of this work was to develop an algorithm for multi-constellation GNSS receivers that would select satellites out of the tracked ones to be used in the location solution. As the receiver has very limited computational resources, the complexity of the algorithm needed to be kept low.
The work began by exploratory analysis of GNSS data. This analysis gave insight into the differences of the various satellite navigation systems as well as into the nature of the pseudorange residuals. These observations helped in shaping the algorithm that we proposed for the problem of satellite selection. The algorithm itself was developed using data science techniques to filter out bad pseudorange measurements and borrowed some earlier ideas to optimize the geometric dilution of precision of the solution set as well.
The approach we chose was shown to work very well when applied to real data measured from road tests in varying surroundings. Even with practically non-existent parameter tuning the algorithm was able to spot almost 90% of the bad pseudorange measurements, keeping the specificity, i.e., ability to hold on to the good measurements at over 90% level.
The ability to filter out bad pseudorange measurements translated to improved location accuracy as well. All in all, the results achieved in this work proved encouraging enough to begin implementing the algorithm in actual receiver software to study the performance of the data-driven approach in action
Investigation of Shadow Matching for GNSS Positioning in Urban Canyons
All travel behavior of people in urban areas relies on knowing their position. Obtaining position has become increasingly easier thanks to the vast popularity of ‘smart’ mobile devices. The main and most accurate positioning technique used in these devices is global navigation satellite systems (GNSS). However, the poor performance of GNSS user equipment in urban canyons is a well-known problem and it is particularly inaccurate in the cross-street direction. The accuracy in this direction greatly affects many applications, including vehicle lane identification and high-accuracy pedestrian navigation. Shadow matching is a new technique that helps solve this problem by integrating GNSS constellation geometries and information derived from 3D models of buildings. This study brings the shadow matching principle from a simple mathematical model, through experimental proof of concept, system design and demonstration, algorithm redesign, comprehensive experimental tests, real-time demonstration and feasibility assessment, to a workable positioning solution. In this thesis, GNSS performance in urban canyons is numerically evaluated using 3D models. Then, a generic two-phase 6-step shadow matching system is proposed, implemented and tested against both geodetic and smartphone-grade GNSS receivers. A Bayesian technique-based shadow matching is proposed to account for NLOS and diffracted signal reception. A particle filter is designed to enable multi-epoch kinematic positioning. Finally, shadow matching is adapted and implemented as a mobile application (app), with feasibility assessment conducted. Results from the investigation confirm that conventional ranging-based GNSS is not adequate for reliable urban positioning. The designed shadow matching positioning system is demonstrated complementary to conventional GNSS in improving urban positioning accuracy. Each of the three generations of shadow matching algorithm is demonstrated to provide better positioning performance, supported by comprehensive experiments. In summary, shadow matching has been demonstrated to significantly improve urban positioning accuracy; it shows great potential to revolutionize urban positioning from street level to lane level, and possibly meter level
BDS GNSS for Earth Observation
For millennia, human communities have wondered about the possibility of observing
phenomena in their surroundings, and in particular those affecting the Earth on which they live.
More generally, it can be conceptually defined as Earth observation (EO) and is the collection of
information about the biological, chemical and physical systems of planet Earth. It can be undertaken
through sensors in direct contact with the ground or airborne platforms (such as weather balloons and
stations) or remote-sensing technologies. However, the definition of EO has only become significant
in the last 50 years, since it has been possible to send artificial satellites out of Earth’s orbit.
Referring strictly to civil applications, satellites of this type were initially designed to provide
satellite images; later, their purpose expanded to include the study of information on land
characteristics, growing vegetation, crops, and environmental pollution. The data collected are used
for several purposes, including the identification of natural resources and the production of accurate
cartography. Satellite observations can cover the land, the atmosphere, and the oceans.
Remote-sensing satellites may be equipped with passive instrumentation such as infrared or
cameras for imaging the visible or active instrumentation such as radar. Generally, such satellites are
non-geostationary satellites, i.e., they move at a certain speed along orbits inclined with respect to the
Earth’s equatorial plane, often in polar orbit, at low or medium altitude, Low Earth Orbit (LEO) and
Medium Earth Orbit (MEO), thus covering the entire Earth’s surface in a certain scan time (properly
called ’temporal resolution’), i.e., in a certain number of orbits around the Earth.
The first remote-sensing satellites were the American NASA/USGS Landsat Program;
subsequently, the European: ENVISAT (ENVironmental SATellite), ERS (European Remote-Sensing
satellite), RapidEye, the French SPOT (Satellite Pour l’Observation de laTerre), and the Canadian
RADARSAT satellites were launched. The IKONOS, QuickBird, and GeoEye-1 satellites were
dedicated to cartography. The WorldView-1 and WorldView-2 satellites and the COSMO-SkyMed
system are more recent. The latest generation are the low payloads called Small Satellites, e.g., the
Chinese BuFeng-1 and Fengyun-3 series.
Also, Global Navigation Satellite Systems (GNSSs) have captured the attention of researchers
worldwide for a multitude of Earth monitoring and exploration applications. On the other hand,
over the past 40 years, GNSSs have become an essential part of many human activities. As is widely
noted, there are currently four fully operational GNSSs; two of these were developed for military
purposes (American NAVstar GPS and Russian GLONASS), whilst two others were developed for
civil purposes such as the Chinese BeiDou satellite navigation system (BDS) and the European
Galileo. In addition, many other regional GNSSs, such as the South Korean Regional Positioning
System (KPS), the Japanese quasi-zenital satellite system (QZSS), and the Indian Regional Navigation
Satellite System (IRNSS/NavIC), will become available in the next few years, which will have
enormous potential for scientific applications and geomatics professionals.
In addition to their traditional role of providing global positioning, navigation, and timing (PNT)
information, GNSS navigation signals are now being used in new and innovative ways. Across the
globe, new fields of scientific study are opening up to examine how signals can provide information
about the characteristics of the atmosphere and even the surfaces from which they are reflected before
being collected by a receiver.
EO researchers monitor global environmental systems using in situ and remote monitoring tools.
Their findings provide tools to support decision makers in various areas of interest, from security
to the natural environment. GNSS signals are considered an important new source of information
because they are a free, real-time, and globally available resource for the EO community
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