Long-Range RTK Positioning Using Virtual Reference Stations

Long-Range RTK positioning is limited due to the growth of the influence of systematic errors with the baseline length. Especially during periods of high ionospheric influences the maximum distance from the reference station allowing high productivity work for RTK positioning might become as low as 10 km or less. The concept of virtual reference stations allows performing RTK positioning in reference station networks with distances of up to 40 km or more from the next reference station while providing the performance of short baseline positioning. The paper presents results from practical tests with a RTK system using standard reference stations and virtual reference stations. A special set-up was used to allow the comparison of the two different RTK techniques using the identical GPS raw data stream by two different rovers. While the rover data was identical the RTCM data stream is different for the two RTK rovers, one is using the standard RTCM coming directly from the next reference station and the other is using the virtual reference station (VRS) data created from the GPS-Network. In that way we are able to compare the positioning results nicely with respect to accuracy, reliability and initializations time performance. It is shown, that the use of VRS data results in a significant performance gain of the RTK rover system. While the rover with the standard RTCM data stream experiences a lot of problems with ambiguity initialization, the VRS rover has a far higher success rate and significantly less time for ambiguity initialization. The VRS rover reaches accuracies of 2 cm in horizontal coordinates with a high reliability on distances of up to 32 km. INTRODUCTION Differential GPS is a well-established technique to improve the positioning precision since many years. This allows even centimeter-level accurate positioning using the so-called integer ambiguity resolution technique. The basic concept is to mitigate the main error sources, ionospheric and tropospheric delay, orbit errors and satellite clock errors (where we had S/A effects, too until recently) by receiving satellite data at a well-known location. All common errors between this reference receiver and the user receiver cancel out. Though this already works quite well for many applications, the special de-correlation (i.e. the change of the errors when moving away from the reference station) of the errors leaves large error contributions in the corrected signals. A new concept addresses this problem. The idea is to generate Virtual Reference Stations (VRS) that simulate a local reference station near by the user receiver. Thus, the errors cancel out better than by using a more distant reference station. Using networks of reference stations with distances of about 70 km between the reference receivers, performance tests were done. Two brands of real-time kinematic receivers were operated on 16 km and 32 km baselines during a period of medium solar activity. For every network, one receiver received normal single base station reference data. The other was operating with Virtual Reference Station data. The results are very promising, showing improvements in time to fix as well as positioning accuracy by a factor of 2. VIRTUAL REFERENCE STATION OVERVIEW The basic principles of Virtual Reference Stations operation are given in the following overview: • Data from the reference station network is transferred to a computing center. • The network data is used to compute models of ionospheric, tropospheric and orbit errors. • The carrier phase ambiguities are fixed for the network baselines. • The actual errors on the baselines are derived in centimeter accuracy using the fixed carrier phase observations. • Linear of more sophisticated error models are used to predict the errors at the user location. • A Virtual Reference Station (VRS) is created at the user location. • The VRS data is transmitted to the user in standard formats (RTCM). This concept is visualized in Figure 1. Base station data from A,B,C and D are used to predict the errors at the Rover location. The user set-up in the field follows this procedure: • The field receiver determines the user location with a navigation solution (no reference) or by DGPS (uncorrected data) • The receiver dials into the computing center via mobile phone and is authenticated. • The navigation solution is transferred to the computing center. • The computing center immediately starts to send Virtual Reference Station data to the field user. Figure 1: Virtual Reference Station Network Figure 2 shows a typical setup procedure. Figure 2: Virtual Reference Station Set-Up THE TEST SET-UP The following set-ups were used to assess the performance of VRS operation in comparison with traditional reference station methods. 1. The SAPOS networking system of the Bavarian land surveying authorities (BLVA) was used to generate VRS and traditional uncorrected data on a baseline of 16 km (Figure 3). Rover receiver brand A was used. 2. The Trimble Terrasat test network generated VRS and uncorrected reference data on a 32 km baseline. (Figure 4). Rover receiver brand B was used. A D C B