Zofia Rzepecka

Troposphere modeling for precise GPS rapid static positioning in mountainous areas

In global navigation satellite system precise positioning, double differencing of the observations is the common approach that allows for significant reduction of correlated atmospheric effects. However, with growing distance between the receivers, tropospheric errors decorrelate causing large residual errors affecting the carrier phase ambiguity resolution and positioning quality. This is especially true in the case of height differences between the receivers. In addition, the accuracy achieved by using standard atmosphere models is usually unsatisfactory when the tropospheric conditions at the receiver locations are significantly different from the standard atmosphere. This paper presents an evaluation of three different approaches to troposphere modeling: (a) neglecting the troposphere, (b) using a standard atmosphere model, and (c) estimating tropospheric delays at the reference station network and providing interpolated tropospheric corrections to the user. All these solutions were repeated with various constraints imposed on the tropospheric delays in the least-squares adjustment. The quality of each solution was evaluated by analyzing the residual height errors calculated by comparing the estimated results to the reference coordinates. Several permanent GPS stations of the EUPOS (European Position Determination System) active geodetic network located in the Carpathian Mountains were selected as a test reference network. The distances between the reference stations ranged from 64 to 122 km. KRAW station served as a simulated user receiver located inside the reference network. The user receiver ellipsoidal height is 267 m and the reference station heights range from 277 to 647 m. The results show that regardless of station height differences, it is recommended to model the tropospheric delays at the reference stations and interpolate them to the user receiver location. The most noticeable influence of the residual (unmodeled) tropospheric errors is observed in the station height component. In many cases, mismodeling of the troposphere disrupts ambiguity resolution and, therefore, prevents the user from obtaining an accurate position.

Modified GPS/Pseudolite Navigation Message

One of the issues regarding integrated GPS/pseudolite measurements is how to deliver a pseudolites position to a receiver or to post-processing software and how to manage it. This paper presents a proposed solution to this problem. The standard navigation message is modified in such way that without changing receivers (or post-processing software), the calculated position of a transmitter is fixed at a pseudolites known position. The formulae for modification of standard Ephemeris Data are also derived. This algorithm can be implemented in a transmitters firmware or a navigation data file can be modified for post-processing.

Evaluation of the Possibility of Using the Predicted Tropospheric Delays in Real Time Gnss Positioning

ABSTRACT Among many sources of errors that influence Global Navigation Satellite System (GNSS) observations, tropospheric delay is one of the most significant. It causes nonrefractive systematic bias in the observations on the level of several meters, depending on the atmospheric conditions. Tropospheric delay modelling plays an important role in precise positioning. The current models use numerical weather data for precise estimation of the parameters that are provided as a part of the Global Geodetic Observation System (GGOS). The purpose of this paper is to analyze the tropospheric data provided by the GGOS Atmosphere Service conducted by the Vienna University of Technology. There are predicted and final delay data available at the Service. In real time tasks, only the predicted values can be used. Thus it is very useful to study accuracy of the forecast delays. Comparison of data sets based on predicted and real weather models allows for conclusions concerning possibility of using the former for real time positioning applications. The predicted values of the dry tropospheric delay component, both zenith and mapped, can be safely used in real time PPP applications, but on the other hand, while using the wet predicted values, one should be very careful.

Some considerations in designing a GPS pseudolite

Some Considerations in Designing a GPS Pseudolite Pseudolites are transmitters of GPS-like signals placed on the ground. Though pseudolites are well known devices and have already been used in the project where visibility to the GNSS satellites is limited, there are still many issues that need enhancement. A prototype of a low-cost pseudolite is being designed and assembled at the University of Warmia and Mazury. This will allow for conducting tests with various codes, signals and software. The goal of the project is to apply the pseudolite as an augmentation to GNSS positioning tasks in geodetic engineering projects. Some practical considerations crucial for the design are discussed in this paper.

Pseudolite signal tests

ABSTRACT Pseudolites are ground based GNSS signal transmitters that have already been used in the project where visibility to the GNSS satellites is limited, however there are still many issues that need enhancement. A prototype of a low-cost pseudolite is being designed and assembled at the University of Warmia and Mazury. The goal of the project is to apply the pseudolite as an augmentation to GNSS positioning tasks in geodetic engineering projects. This paper presents the results of first prototype testing in the area of code generation, carrier frequency and signal power.

Impact of Ocean Tides Loading on Precise Point Positioning Based on FES2004 Model

Abstract Precise Point Positioning (PPP) technique as an absolute positioning method requires modeling of effects that influence observations. One of the effects is a displacement of the measurement location due to ocean mass gravitational attraction - ocean tides loading (OTL). The model recommended by the International Earth Rotation and Reference Systems Service (IERS) is FES2004. The paper focuses on impact of applying the particular OTL model on PPP processing. The analysis is based on processing of observations from 24 globally distributed permanent stations and time span of 50 days. The analysis bases on processing intervals from 1 to 24 hours. In addition, the amplitudes of the loads in Poland are evaluated. The OTL model is location dependent, thus the importance of applying this model depends on the location environment. As the PPP is an absolute method, the loads cumulate and transfer nearly directly to the positioning solution. Consequently, for short observation intervals and small loads the application of the model does not play an important role. For the analysed station with high amplitudes of the loads the relative and absolute improvement, of the solution was the highest for height component. By applying the model, the solution improved by 19% or 7.3 mm (as for RMS and 8 hour interval). The distinct improvement for convergence exists for vertical component and threshold below 5 cm. For Poland the vertical component loads were about 5 times smaller and the highest improvement for the analysed station was 3.7% for 4 hour interval and vertical component.

TIME SERIES ANALYSIS OF RADIO SIGNAL WET TROPOSPHERIC DELAYS FOR SHORT-TERM FORECAST

The proposed short-term forecasting method bases on removing periodic signals basing on frequency analysis and then using modern tools of time series analysis on residuals. For this element the Auto-Regressive Integrated Moving Average forecasting model is used. The practical realization contains the analysis of tropospheric data obtained from the Vienna Mapping Function 1 service. The analysis contains time series data from four years (2010-2013) and two permanent stations located in Central Europe region. For both stations two main signals: annual and semiannual were removed using sine and cosine linear regression leaving residuals that still do not act as a white noise processes. For each of the analysed data sets appropriate parameters of the ARIMA model were evaluated and the accuracy of forecast values was analysed. The residuals of these expanded processes are white, therefore the estimated ARMA processes can be used for forecasting the future values. One-step forecasts based on the above models are estimated to be within ± 2.5 cm for 80 % of confidence level and ±3.8 cm for 95 % of confidence. Unfortunately, its confidence level quickly drops down, falling down to within ± 4 cm for the fourth forecasted epoch (four epochs completes 24h), at 80 % of level of confidence. ARTICLE INFO