Ionospheric Delay Handling for Relative Navigation by Carrier-Phase Differential GPS (original) (raw)
Related papers
Impact of second-order ionospheric delay on GPS precise point positioning
Journal of Applied Geodesy, 2011
Traditionally, in GPS precise point positioning (PPP), ionosphere-free linear combinations of dual-frequency carrier-phase and pseudorange measurements are used. Unfortunately, with these linear combinations only the first-order ionospheric delay term is removed and higher order ionospheric delay terms are usually not taken into account. Such residual error components may deteriorate the PPP solution and slow down the convergence time. In this paper the second-order ionospheric delay term is modeled and it is shown that its e¤ect on GPS satellite orbit varies from 2.3 mm to 23.8 mm in the radial direction, 3.6 mm to 18.8 mm in the alongtrack direction and 2 mm to 16.3 mm in the crosstrack direction. In addition, GPS satellite clock corrections showed a di¤erence of up to 0.067 ns. To examine the e¤ect of the second-order ionospheric delay on the PPP solution, new data sets from several IGS stations were processed using a modified version of GPSPace software, which was originally developed by Natural Resources Canada (NRCan). The modified GPSPace accepts the second-order ionospheric corrections as well as the newly developed US National Oceanic and Atmospheric Administration (NOAA) tropospheric signal delay model (NOAATrop). The estimated precise satellite orbit and clock corrections, with secondorder ionospheric delay accounted for, were used in all PPP data processing. It is shown that accounting for the second-order ionospheric delay and applying the NOAATrop model improved the PPP solution convergence time by about 15% and improved the accuracy estimation by 3 mm.
On Modelling of Second-Order Ionospheric Delay for GPS Precise Point Positioning
Journal of Navigation, 2011
Recent developments in GPS positioning show that a user with a standalone GPS receiver can obtain positioning accuracy comparable to that of carrier-phase-based differential positioning. Such technique is commonly known as Precise Point Positioning (PPP). A significant challenge of PPP, however, is that about 30 minutes or more is required to achieve centimetre to decimetre-level accuracy. This relatively long convergence time is a result of the un-modelled GPS residual errors. A major residual error component, which affects the convergence of PPP solution, is higher-order Ionospheric Delay (IONO). In this paper, we rigorously model the second-order IONO, which represents the bulk of higher-order IONO, for PPP applications. Firstly, raw GPS measurements from a global cluster of International GNSS Service (IGS) stations are corrected for the effect of second-order IONO. The corrected data sets are then used as input to the Bernese GPS software to estimate the precise orbit, satellite...
Proceedings of the …, 2003
It has been shown in the past that differential GPS carrier phase kinematic position accuracy tends to degrade as baseline length increases. This position solution degradation is due to several factors, primarily, errors attributed to the spatial variation of atmospheric delays (and secondly, errors in the satellite orbit). This paper endeavours to assess the magnitude of these effects on the position solutions using various base stations located at distances between 1 and 200+ km. away from the vessel. The assessment will be based on data collected on the Chesapeake Bay during July 1999, in three consecutive days. The data were collected by an Ashtech Z12 receiver mounted on the NOS S/V Bay Hydrographer. The baselines used in the assessment were processed using an ionospheric delay-free processing technique. A local truth trajectory was established while the vessel was close enough to base station TANG to employ integer fixed RTK. This procedure yielded results that agreed with the "truth" trajectory to the decimetre level in latitude, longitude and height.
Weighting Ionospheric Correction to Improve Fast GPS Positioning Over Medium Distances
BIOGRAPHY Dennis Odijk is a Ph.D. student at the Department of Mathematical Geodesy and Positioning of the Delft University of Technology, where he is engaged in the development of GPS data processing strategies for medium-scaled networks, with an emphasis on ambiguity fixing and modelling of the ionospheric delays. ABSTRACT The success of precise GPS positioning over long baselines depends on the ability of resolving the integer phase ambiguities when short observation time spans are required. The ionosphere is the major error source for these kind of positioning problems and due to the current maximum of solar activity the ionospheric delay errors in GPS signals can be much larger than in periods of minimum activity. When measurements are carried out in the vicinity of a permanent GPS network, then from the long-time data of these permanent stations precise ionospheric delays can be estimated. Next, these ionospheric estimates at the permanent stations can be interpolated to the l...
Vertical ionospheric delay estimation for single-receiver operation
Journal of Applied Geodesy, 2019
An apparent delay is occurred in GPS signal due to both refraction and diffraction caused by the atmosphere. The second region of the atmosphere is the ionosphere. The ionosphere is significantly related to GPS and the refraction it causes in GPS signal is considered one of the main source of errors which must be eliminated to determine accurate positions. GPS receiver networks have been used for monitoring the ionosphere for a long time. The ionospheric delay is the most predominant of all the error sources. This delay is a function of the total electron content (TEC). Because of the dispersive nature of the ionosphere, one can estimate the ionospheric delay using the dual frequency GPS. In the current research our primary goal is applying Precise Point Positioning (PPP) observation for accurate ionosphere error modeling, by estimating Ionosphere delay using carrier phase observations from dual frequency GPS receiver. The proposed algorithm was written using MATLAB and was named VI...
Baltic Surveying
Currently, Global Navigation Satellite Systems (GNSS) are developing at a fairly rapid pace. Over the last years US GPS and Russian GLONASS were modernizing, whilst new systems like European Galileo and Chinese BDS are launched. The modernizations of the existing and the deployment of new GNSS made a whole range of new signals available to the users, and create a new concept multi-GNSS. Ionospheric delay is one of the major error sources in multi-GNSS observations. At present, GNSS users usually eliminate the influence of ionospheric delay of the first order items by dual-frequency ionosphere-free combinations. But there is still residual ionospheric delay error of higher orders. In this paper we present four different processing scenarios to exclude the higher orders ionospheric delay effects on multi-GNSS Precise Point Positioning (PPP) performance, including: “only GPS” and “GPS+GLONASS+Galileo+BDS” – without/with eliminating ionospheric delay error of higher orders. Dataset co...
Survey Review, 2007
The primary objective of this paper is to estimate the influence of the double-difference (DD) ionospheric corrections latency on the instantaneous (one-epoch) ambiguity resolution (AR) in longrange RTK under typical ionospheric conditions. The key to the success in integer AR rests mainly in the mitigation of the atmospheric errors, i.e., the ionospheric and tropospheric delays. Between these two, the former has the greatest influence on the AR, since both ambiguities and ionospheric delay are frequency-dependent. Instantaneous RTK is presently one of the most challenging topics in precise GPS applications. The research presented here addresses this topic through the development and testing of a multiple reference station approach implemented in the MPGPS™ (Multi Purpose GPS Processing Software) software. Atmospheric corrections are used in order to obtain a high quality RTK position over long distances. In our approach, DD ionospheric correction prediction derived from the previous correctly resolved epoch is applied. Yet, at the beginning of the session, a short initialization period is still required in order to produce the initial prediction. After the initialization the method is based on single epoch solution. This method assures a high success rate of the instantaneous AR for long baselines (over 100 km). Since the previous-epoch ionospheric delay is used, and instantaneous mode is applied in the algorithm, the proposed method is robust against cycle slips and data gaps, and still capable of producing centimetre-level RTK positions. The RTK solution was simulated in the postprocessing mode. Namely, different DD ionospheric delay correction latencies were simulated in 10 s increments and sent to the (simulated) rover in order to test the AR performance. The AR results were compared and analyzed, and the performance of the RTK positioning was assessed based on the static true solution. Several hours of GPS data, collected by the State of Israel permanently tracking network, were processed. The analyses show that about 90 s latency may exist while the instantaneous ambiguities could still be resolved correctly. The numerical tests presented in this study show the centimetre-level positioning results for mobile receiver.
Vertical Ionosphere Delay Estimation using Zero Difference GPS Phase Observation
Annales Geophysicae Discussions
An apparent delay is occurred in GPS signal due to both refraction and diffraction caused by the atmosphere. The second region of the atmosphere is the ionosphere. The ionosphere is significantly related to GPS and the refraction it causes in GPS signal is considered one of the main source of errors which must be eliminated to determine accurate positions. GPS receiver networks have been used for monitoring the ionosphere for a long time. the ionospheric delay is the most predominant of all the error sources. Thisidelay is a function of theitotalielectronicontent (TEC). Because ofithe dispersive nature of the ionosphere, one caniestimateitheiionosphericidelay using the dual frequency GPS. In the current research our primary goal is applying PreciseiPointiPositioningi(PPP) observation for accurate ionosphere error modeling, by estimating Ionosphere delay using carrier phase observations from dual frequency GPS receiver. The proposed algorithm was written using MATLAB. The proposed Algorithm depends on the geometry-free carrier-phaseiobservations afteridetectingicycle slip to estimates the ionosphericidelayiusingia spherical ionospheric shell model, in which the vertical delays are described by means of a zenithidelayiatitheistationipositioniandilatitudinaliandilongitudinal gradients. geometry-free carrier-phase observations were applied to avoid unwanted effects of pseudorange measurements, such as code multipath. The ionospheric estimation in this algorithm is performed by means of sequential leastsquares adjustment. Finally, an adaptable user interface MATLAB software are capable of estimating ionosphere delay, ambiguity term and ionosphere gradient accurately.
Ionospheric path delay models for spaceborne GPS receivers flying in formation with large baselines
Advances in Space Research, 2011
GPS relative navigation filters could benefit notably from an accurate modeling of the ionospheric delays, especially over large baselines (>100 km) where double difference delays can be higher than several carrier wavelengths. This paper analyzes the capability of ionospheric path delay models proposed for spaceborne GPS receivers in predicting both zero-difference and double difference ionospheric delays. We specifically refer to relatively simple ionospheric models, which are suitable for real-time filtering schemes. Specifically, two ionospheric delay models are evaluated, one assuming an isotropic electron density and the other considering the effect on the electron density of the Sun aspect angle. The prediction capability of these models is investigated by comparing predicted ionospheric delays with measured ones on real flight data from the Gravity Recovery and Climate Experiment mission, in which two satellites fly separated of more than 200 km. Results demonstrate that both models exhibit a correlation in the excess of 80% between predicted and measured double-difference ionospheric delays. Despite its higher simplicity, the isotropic model performs better than the model including the Sun effect, being able to predict double differenced delays with accuracy smaller than the carrier wavelength in most cases. The model is thus fit for supporting integer ambiguity fixing in real-time filters for relative navigation over large baselines. Concerning zerodifference ionospheric delays, results demonstrate that delays predicted by the isotropic model are highly correlated (around 90%) with those estimated using GPS measurements. However, the difference between predicted and measured delays has a root mean square error in the excess of 30 cm. Thus, the zero-difference ionospheric delays model is not likely to be an alternative to methods exploiting carrier-phase observables for cancelling out the ionosphere contribution in single-frequency absolute navigation filters.