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

Improving the Performance of Multi-GNSS (Global Navigation Satellite System) Ambiguity Fixing for Airborne Kinematic Positioning over Antarctica

Conventional relative kinematic positioning is difficult to be applied in the polar region of Earth since there is a very sparse distribution of reference stations, while precise point positioning (PPP), using data of a stand-alone receiver, is recognized as a promising tool for obtaining reliable and accurate trajectories of moving platforms. However, PPP and its integer ambiguity fixing performance could be much degraded by satellite orbits and clocks of poor quality, such as those of the geostationary Earth orbit (GEO) satellites of the BeiDou navigation satellite system (BDS), because temporal variation of orbit errors cannot be fully absorbed by ambiguities. To overcome such problems, a network-based processing, referred to as precise orbit positioning (POP), in which the satellite clock offsets are estimated with fixed precise orbits, is implemented in this study. The POP approach is validated in comparison with PPP in terms of integer ambiguity fixing and trajectory accuracy. In a simulation test, multi-GNSS (global navigation satellite system) observations over 14 days from 136 globally distributed MGEX (the multi-GNSS Experiment) receivers are used and four of them on the coast of Antarctica are processed in kinematic mode as moving stations. The results show that POP can improve the ambiguity fixing of all system combinations and significant improvement is found in the solution with BDS, since its large orbit errors are reduced in an integrated adjustment with satellite clock offsets. The four-system GPS+GLONASS+Galileo+BDS (GREC) fixed solution enables the highest 3D position accuracy of about 3.0 cm compared to 4.3 cm of the GPS-only solution. Through a real flight experiment over Antarctica, it is also confirmed that POP ambiguity fixing performs better and thus can considerably speed up (re-)convergence and reduce most of the fluctuations in PPP solutions, since the continuous tracking time is short compared to that in other regions

Characterization of multi-GNSS between-receiver differential code biases using zero and short baselines

© 2015, Science China Press and Springer-Verlag Berlin Heidelberg. Care should be taken to minimize adverse impact of receiver differential code biases (DCBs) on global navigation satellite system (GNSS)-derived ionospheric parameters. It is therefore of importance to ascertain the intrinsic characteristics of receiver DCBs, preferably in the context of new-generation GNSS. In this contribution, we present a method that enables time-wise retrieval of between-receiver DCBs (BR-DCBs) from dual-frequency, code-only measurements collected by a pair of co-located receivers. This method is applicable to the US GPS as well as to a new set of GNSS constellations including the Chinese BeiDou, the European Galileo and the Japanese QZSS. With the use of this method, we determine the multi-GNSS BR-DCB time-wise estimates covering a time period of up to 2 years (January 2013–March 2015) with a 30-s time resolution for five receiver-pairs (four zero and one short baselines). For the BR-DCB time-wise estimates pertaining to an arbitrary receiver-pair and constellation, we demonstrate their promising intraday stability by means of statistical hypothesis testing. We also find that the BeiDou BR-DCB daily weighted average (DWA) estimates show a dependence on satellite type, in particular for receiver-pairs of mixed types. Finally, we demonstrate that long-term variability in BR-DCB DWA estimates can be closely associated with hardware temperature variations inside the receivers

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

On the short-term temporal variations of GNSS receiver differential phase biases

As a first step towards studying the ionosphere with the global navigation satellite system (GNSS), leveling the phase to the code geometry-free observations on an arc-by-arc basis yields the ionospheric observables, interpreted as a combination of slant total electron content along with satellite and receiver differential code biases (DCB). The leveling errors in the ionospheric observables may arise during this procedure, which, according to previous studies by other researchers, are due to the combined effects of the code multipath and the intra-day variability in the receiver DCB. In this paper we further identify the short-term temporal variations of receiver differential phase biases (DPB) as another possible cause of leveling errors. Our investigation starts by the development of a method to epoch-wise estimate between-receiver DPB (BR-DPB) employing (inter-receiver) single-differenced, phase-only GNSS observations collected from a pair of receivers creating a zero or short baseline. The key issue for this method is to get rid of the possible discontinuities in the epoch-wise BR-DPB estimates, occurring when satellite assigned as pivot changes. Our numerical tests, carried out using Global Positioning System (GPS, US GNSS) and BeiDou Navigation Satellite System (BDS, Chinese GNSS) observations sampled every 30 s by a dedicatedly selected set of zero and short baselines, suggest two major findings. First, epoch-wise BR-DPB estimates can exhibit remarkable variability over a rather short period of time (e.g. 6 cm over 3 h), thus significant from a statistical point of view. Second, a dominant factor driving this variability is the changes of ambient temperature, instead of the un-modelled phase multipath

Review of code and phase biases in multi-GNSS positioning

A review of the research conducted until present on the subject of Global Navigation Satellite System (GNSS) hardware-induced phase and code biases is here provided. Biases in GNSS positioning occur because of imperfections and/or physical limitations in the GNSS hardware. The biases are a result of small delays between events that ideally should be simultaneous in the transmission of the signal from a satellite or in the reception of the signal in a GNSS receiver. Consequently, these biases will also be present in the GNSS code and phase measurements and may there affect the accuracy of positions and other quantities derived from the observations. For instance, biases affect the ability to resolve the integer ambiguities in Precise Point Positioning (PPP), and in relative carrier phase positioning when measurements from multiple GNSSs are used. In addition, code biases affect ionospheric modeling when the Total Electron Content is estimated from GNSS measurements. The paper illustrates how satellite phase biases inhibit the resolution of the phase ambiguity to an integer in PPP, while receiver phase biases affect multi-GNSS positioning. It is also discussed how biases in the receiver channels affect relative GLONASS positioning with baselines of mixed receiver types. In addition, the importance of code biases between signals modulated onto different carriers as is required for modeling the ionosphere from GNSS measurements is discussed. The origin of biases is discussed along with their effect on GNSS positioning, and descriptions of how biases can be estimated or in other ways handled in the positioning process are provided.QC 20170922</p

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

GPS/GLONASS carrier phase elevation-dependent stochastic modelling estimation and its application in bridge monitoring

The Global Positioning System (GPS) based monitoring technology has been recognised as an essential tool in the long-span bridge health monitoring throughout the world in recent years. However, the high observation noise is still a big problem that limits the high precision displacement extraction and vibration response detection. To solve this problem, GPS double-difference model and many other specific function models have been developed to eliminate systematic errors e.g. unmodeled atmospheric delays, multipath effect and hardware delays. However, relatively less attention has been given to the noise reduction in the deformation monitoring area. In this paper, we first proposed a new carrier phase elevation-dependent precision estimation method with Geometry-Free (GF) and Melbourne-Wü bbena (MW) linear combinations, which is appropriate to regardless of Code Division Multiple Access (CDMA) system (GPS) or Frequency Division Multiple Access (FDMA) system (GLONASS). Then, the method is used to estimate the receiver internal noise and the realistic GNSS stochastic model with a group of zero-baselines and short-baselines (served for the GNSS and Earth Observation for Structural Health Monitoring of Bridges (GeoSHM) project), and to demonstrate their impacts on the positioning. At last, the contribution of integration of GPS and GLONASS is introduced to see the performance of noise reduction with multi-GNSS. The results show that the higher level receiver internal noise in cost effective receivers has less influences on the short-baseline data processing. The high noise effects introduced by the low elevation satellite and the geometry variation caused by rising and dropping satellites, can be reduced by 10–20% with the refined carrier phase elevation-dependent stochastic model. Furthermore, based on observations from GPS and GLONASS with the refined stochastic model, the noise can be reduced by 30–40%, and the spurious signals in the real-life bridge displacements tend to be completely eliminated

On biases in precise point positioning with multi-constellation and multi-frequency GNSS data

© 2016 IOP Publishing Ltd. Various types of biases in Global Navigation Satellite System (GNSS) data preclude integer ambiguity fixing and degrade solution accuracy when not being corrected during precise point positioning (PPP). In this contribution, these biases are first reviewed, including satellite and receiver hardware biases, differential code biases, differential phase biases, initial fractional phase biases, inter-system receiver time biases, and system time scale offset. PPP models that take account of these biases are presented for two cases using ionosphere-free observations. The first case is when using primary signals that are used to generate precise orbits and clock corrections. The second case applies when using additional signals to the primary ones. In both cases, measurements from single and multiple constellations are addressed. It is suggested that the satellite-related code biases be handled as calibrated quantities that are obtained from multi-GNSS experiment products and the fractional phase cycle biases obtained from a network to allow for integer ambiguity fixing. Some receiver-related biases are removed using between-satellite single differencing, whereas other receiver biases such as inter-system biases are lumped with differential code and phase biases and need to be estimated. The testing results show that the treatment of biases significantly improves solution convergence in the float ambiguity PPP mode, and leads to ambiguity-fixed PPP within a few minutes with a small improvement in solution precision