A unified model for multi-frequency PPP ambiguity resolution and test results with Galileo and BeiDou triple-frequency observations

With the modernization of Global Navigation Satellite System (GNSS), triple- or multi-frequency signals have become available from more and more GNSS satellites. The additional signals are expected to enhance the performance of precise point positioning (PPP) with ambiguity resolution (AR). To deal with the additional signals, we propose a unified modeling strategy for multi-frequency PPP AR based on raw uncombined observations. Based on the unified model, the fractional cycle biases (FCBs) generated from multi-frequency observations can be flexibly used, such as for dual- or triple- frequency PPP AR. Its efficiency is verified with Galileo and BeiDou triple-frequency observations collected from globally distributed MGEX stations. The estimated FCB are assessed with respect to residual distributions and standard deviations. The obtained results indicate good consistency between the input float ambiguities and the generated FCBs. To assess the performance of the triple-frequency PPP AR, 11 days of MGEX data are processed in three-hour sessions. The positional biases in the ambiguity-fixed solutions are significantly reduced compared with the float solutions. The improvements are 49.2%, 38.3%, and 29.6%, respectively, in east/north/up components for positioning with BDS, while the corresponding improvements are 60.0%, 29.0%, and 21.1% for positioning with Galileo. These results confirm the efficiency of the proposed approach, and that the triple-frequency PPP AR can bring an obvious benefit to the ambiguity-float PPP solution

Multi-frequency and multi-GNSS PPP phase bias estimation and ambiguity resolution

Multi-frequency and multi-GNSS measurements from modernized satellites are properly integrated for PPP with ambiguity resolution to achieve the state-of-the-art fast and accurate positioning, which provides an important contribution to GNSS precise positioning and applications. The multi-frequency and multi-GNSS PPP phase bias estimation and ambiguity resolution, which is accomplished by a unified model based on the uncombined PPP, are thoroughly evaluated with special focus on Galileo and BDS

Multi-frequency and multi-GNSS PPP phase bias estimation and ambiguity resolution

Multi-frequency and multi-GNSS measurements from modernized satellites are properly integrated for PPP with ambiguity resolution to achieve the state-of-the-art fast and accurate positioning, which provides an important contribution to GNSS precise positioning and applications. The multi-frequency and multi-GNSS PPP phase bias estimation and ambiguity resolution, which is accomplished by a unified model based on the uncombined PPP, are thoroughly evaluated with special focus on Galileo and BDS

Precise Point Positioning Augmentation for Various Grades of Global Navigation Satellite System Hardware

The next generation of low-cost, dual-frequency, multi-constellation GNSS receivers, boards, chips and antennas are now quickly entering the market, offering to disrupt portions of the precise GNSS positioning industry with much lower cost hardware and promising to provide precise positioning to a wide range of consumers. The presented work provides a timely, novel and thorough investigation into the positioning performance promise. A systematic and rigorous set of experiments has been carried-out, collecting measurements from a wide array of low-cost, dual-frequency, multi-constellation GNSS boards, chips and antennas introduced in late 2018 and early 2019. These sensors range from dual-frequency, multi-constellation chips in smartphones to stand-alone chips and boards. In order to be comprehensive and realistic, these experiments were conducted in a number of static and kinematic benign, typical, suburban and urban environments. In terms of processing raw measurements from these sensors, the Precise Point Positioning (PPP) GNSS measurement processing mode was used. PPP has become the defacto GNSS positioning and navigation technique for scientific and engineering applications that require dm- to cm-level positioning in remote areas with few obstructions and provides for very efficient worldwide, wide-array augmentation corrections. To enhance solution accuracy, novel contributions were made through atmospheric constraints and the use of dual- and triple-frequency measurements to significantly reduce PPP convergence period. Applying PPP correction augmentations to smartphones and recently released low-cost equipment, novel analyses were made with significantly improved solution accuracy. Significant customization to the York-PPP GNSS measurement processing engine was necessary, especially in the quality control and residual analysis functions, in order to successfully process these datasets. Results for new smartphone sensors show positioning performance is typically at the few dm-level with a convergence period of approximately 40 minutes, which is 1 to 2 orders of magnitude better than standard point positioning. The GNSS chips and boards combined with higher-quality antennas produce positioning performance approaching geodetic quality. Under ideal conditions, carrier-phase ambiguities are resolvable. The results presented show a novel perspective and are very promising for the use of PPP (as well as RTK) in next-generation GNSS sensors for various application in smartphones, autonomous vehicles, Internet of things (IoT), etc

Multi-GNSS integer ambiguity resolution enabled precise positioning

In this PhD thesis multi-Global Navigation Satellite System (GNSS) positioning results when combining the American Global Positioning System (GPS), Chinese BeiDou Navigation Satellite System (BDS), European Galileo and Japanese Quasi-Zenith Satellite System (QZSS) will be presented. The combined systems will be evaluated in comparison to the single-systems, for short (atmosphere-fixed) to long (atmosphere-present) baselines. It will be shown that the combined systems can provide for improved integer ambiguity resolution and positioning performance over the single-systems

Improving Reliability and Assessing Performance of Global Navigation Satellite System Precise Point Positioning Ambiguity Resolution

Conventional Precise Point Positioning (PPP) has always required a relatively long initialization period (few tens of minutes at least) for the carrier-phase ambiguities to converge to constant values and for the solution to reach its optimal precision. The classical PPP convergence period is primarily caused by the estimation of the carrier-phase ambiguity from the relatively noisy pseudoranges and the estimation of atmospheric delay. If the underlying integer nature of the ambiguity is known, it can be resolved, thereby reducing the convergence time of conventional PPP. To recover the underlying integer nature of the carrier-phase ambiguities, different strategies for mitigating the satellite and receiver dependent equipment delays have been developed, and products made publicly available to enable ambiguity resolution without any baseline restrictions. There has been limited research within the scope of interoperability of the products, combining the products to improve reliability and assessment of ambiguity resolution within the scope of being an integrity indicator. This study seeks to develop strategies to enable each of these and examine their feasibility. The advantage of interoperability of the different PPP ambiguity resolution (PPP-AR) products would be to permit the PPP user to transform independently generated PPP-AR products to obtain multiple fixed solutions of comparable precision and accuracy. The ability to provide multiple solutions would increase the reliability of the solution for, e.g., real-time processing: if there were an outage in the generation of the PPP-AR products, the user could instantly switch streams to a different provider. The satellite clock combinations routinely produced within the International GNSS Service (IGS) currently disregard that analysis centers (ACs) provide products which enable ambiguity resolution. Users have been expected to choose either an IGS product which is a combined product from multiple ACs or select an individual AC solution which provides products that enable PPP-AR. The goal of the novel research presented was to develop and test a robust satellite clock combination preserving the integer nature of the carrier-phase ambiguities at the user end. mm-level differences were noted, which was expected as the strength lies mainly in its reliability and stable median performance and the combined product is better than or equivalent to any single ACs product in the combination process. As have been shown in relative positioning and PPP-AR, ambiguity resolution is critical for enabling cm-level positioning. However, what if specifications where at the few dm-level, such as 10 cm and 20 cm horizontal what role does ambiguity resolution play? The role of ambiguity resolution relies primarily on what are the user specifications. If the user specifications are at the few cm-level, ambiguity resolution is an asset as it improves convergence and solution stability. Whereas, if the users specification is at the few dm-level, ambiguity resolution offers limited improvement over the float solution. If the user has the resources to perform ambiguity resolution, even when the specifications are at the few dm-level, it should be utilized

Integer Ambiguity Resolution for Multi-GNSS and Multi-Signal Raw Phase Observations

The continuous modernisation of existing Global Navigation Satellite Systems (GNSS) and the development of new systems with a multitude of different carrier frequencies and a variety of signal modulations creates a true multi-GNSS and multi-signal environment available today. Still most precise GNSS processing strategies rely on dual-frequency measurements only by applying the Ionosphere-Free (IF) Linear Combination (LC) of GNSS observables and therefore do not benefit from the available multi-signal environment. While in this processing approach the first order effect of the ionospheric delay can be eliminated almost completely, the formation of linear combinations of GNSS observables leads to a noise increase for the resulting observations and a loss of some of the physical characteristics of the original signals, like the integer nature of the carrier phase ambiguity. In order to benefit from the multi-GNSS and multi-signal environment available today, the scientific analyses and precise applications presented in this work are based on the raw observation processing approach, which makes use of the original (raw) observations without forming any linear combinations or differences of GNSS observables. This processing strategy provides the flexibility to make use of all or a selection of available multi-GNSS and multi-signal raw observations, which are jointly processed in a single adjustment as there is no inherent limitation on the number of usable signals. The renunciation of linear combinations and observation differences preserves the physical characteristics of individual signals and implies that multi-signal biases and ionospheric delays need to be properly determined or corrected in the parameter estimation process. The raw observation processing approach is used in this work to jointly process measurements from up to three different GNSS, including eleven signals tracked on up to eight different carrier frequencies in one single adjustment. The bias handling for multi-GNSS and multi-signal applications is analysed with a focus on physically meaningful parameter estimates to demonstrate the benefits of handling clock offset parameters, multi-signal code biases and ionospheric delay estimates in a physically meaningful and consistent way. In this context, receiver-specific multi-GNSS and multisignal biases are analysed and calibrated by the use of a GNSS signal simulator. The disadvantages of eliminating physical characteristics due to the formation of linear combinations of observations or commonly used parameter estimation strategies are demonstrated and discussed. The carrier phase Integer Ambiguity Resolution (IAR) approach developed and implemented in the course of this work is based on the joint processing of multi-GNSS and multi-signal raw observations without forming any linear combinations or observation differences. Details of the implemented IAR approach are described and the performance is analysed for available carrier signal frequencies of different GNSS. Achieved results are compared to the conventional IAR approach based on IF linear combinations and the so called Widelane (WL) and Narrowlane (NL) ambiguities. In addition, the resolution of inter-system integer ambiguities is analysed for common GNSS signal frequencies. The performance of the implemented IAR approach is demonstrated and analysed by the joint Precise Orbit Determination (POD) of multi-GNSS satellites based on fixed multi-frequency carrier phase ambiguities. The improvement of the satellite orbit and clock quality by fixing raw observation ambiguities confirms the successful implementation of the IAR approach based on raw observation processing. Multi-GNSS satellite orbits and clock offsets determined with this approach are compared to results generated with the conventional IF linear combination processing approach and independent external products. This comparison demonstrates an at least equivalent performance of the implemented IAR approach based on raw observation processing. In addition, the fixed raw observation ambiguities are used to investigate and discuss characteristics of multi-GNSS and multi-frequency phase biases

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