Modernized Approaches for GNSS Baseline Processing in Trimble Business Center

 

Starting with TBC version 4.00, static baseline processing is carried out using a specialized and automated processor. Some of the features of this new approach are presented below:

• Multifrequency and Mixed Signal Processing: The processor can handle triple-frequency data. It can also operate using only L2 or L5 frequencies. As in previous TBC processors, the new processor also provides the ability to specify which constellations to use for processing.
• Multiple Processing Modes with Dynamic Selection: The processor uses five different processing modes to produce highly reliable and confident baseline processing results. The software automatically selects the appropriate mode based on baseline length and observation time.
• Extended Tropospheric Modeling: The processor applies appropriate tropospheric modeling and corrections. Options include extended modeling, constant and variable biases, relative and absolute modeling, and a gradient tropospheric model with a priori gradient corrections.
• Increased processing capacity and efficiency: The processor handles static GNSS raw datasets more efficiently by automatically selecting the optimal epoch intervals for processing.
• Difference-Adjusted Precision Estimates: The processor contains an updated approach to better estimate differences induced by atmospheric effects. These differences are taken into account in the precision results of GNSS processing.

 

 

In particular, the Multiple Processing Modes with Dynamic Selection feature defines the following processing methods:

• Non-Combined Multifrequency Mode: For short baselines, atmospheric effects at both ends of the line can be considered similar. For these vectors, TBC uses a non-combined multifrequency mode, which calculates double-difference measurements for each of the available frequencies. This approach reduces ionospheric error, which has proven to be a valid technique for short baselines where each receiver experiences similar atmospheric effects. The mode has a large number of possible integer values to review and also provides lower noise. TBC can also incorporate an ionospheric model to further reduce ionospheric error and improve accuracy.
• Wide Lane Mode: For longer baselines, the software uses a wide-lane linear combination of carrier phase measurements. This approach eliminates tropospheric error and reduces ionospheric error. The wide-lane technique produces a longer wavelength (~86 cm), which facilitates easier ambiguity resolution but increases signal noise. Noise is mitigated by using longer observation times.
• Combined Mode: TBC uses the non-combined multifrequency mode with ionospheric modeling to process baselines between 2 and 20 km. It switches to wide-lane mode for longer baselines. If a network includes some shorter lines (under 20 km) and other longer lines (over 20 km), the results and precision estimates may seem inconsistent. To address this, Trimble developed a "Combined Mode" that provides a smooth transition between the non-combined multifrequency technique and the wide-lane modes. Network adjustment with non-homogeneous baseline lengths can benefit from a smaller scaling of a priori error estimates.
• Melbourne-Wübbena Mode: For baselines longer than 200 km, the processor uses the Melbourne-Wübbena approach. This mode uses wide-lane carrier phase measurements combined with narrow-lane code. The approach takes advantage of wide-lane benefits for integer fixing while eliminating atmospheric effects from the solution.
• Mixed Wide-Lane and Melbourne-Wübbena Mode: Acting as a transition between Wide-Lane and Melbourne-Wübbena modes, this mixed mode produces good reliability. Precision estimates are more consistent across lines of different lengths. As a result, in network adjustment, a priori scaling factors can be smaller.

 

Experiments:

To test the processing methods, different GNSS baseline configurations were used, depending on distances and acquisition intervals. In all cases, broadcast ephemerides were used.

Initially, baseline processing was performed for distances less than 120 m (Figure 1). Each recording was performed with an acquisition rate of 1 second. The results are presented in Figure 2.

 

Figure 1: Calculated baselines

 

Figure 2: Baseline processing with a 1-second logging rate and distances under 100 m.

 

From Figure 2, it can be seen that TBC optimized baseline processing using the Non-Combined Multifrequency mode, with a processing interval of 10 seconds.

In a second experiment, vectors greater than 30 km and less than 120 km were used. The determined baselines are presented in Figure 3.

 

Figure 3: Second experiment, medium baselines.

 

Figure 4 presents the baseline processing optimized by TBC. Here, the Wide Lane processing method and a 1-minute processing interval stand out.

 

Figure 4: GNSS baseline processing, 1-minute processing interval and Wide Lane method

 

For very long baselines, the SNTI GNSS station from GEOCOM and the HLN2 station from CSN were used, with an approximate distance of 212 km. Figure 5 shows the generated baseline.

Figure 5: Baseline of approximately 212 km

 

The results of this processing are presented in Figure 6. Here, a processing interval of 30 seconds and the Melbourne-Wubbena Lane method stand out.

 

Figure 6: GNSS baseline processing, 30-second processing interval and Melbourne-Wubbena Lane method

 

Finally, a network composed of vectors of different lengths and observation times depending on each distance was analyzed based on the processing methods available in TBC. Figure 7 presents the studied network.

 

Figure 7: GNSS Network

 

From Figure 7, the results of the processing of 2 baselines are presented (Figure 8).

 

Figure 8: GNSS baseline processing results

 

From Figure 8, the processing methods for each baseline are modified based on its length, and their processing intervals are automatically defined.

 

Conclusions:

Figures 2, 4, and 6 show millimeter and centimeter order accuracy for isolated ties. For longer baselines, the use of precise ephemerides is necessary to obtain better results. In the case of Figure 8, TBC automates the processing method and interval. Thus, the optimization in baseline processing proposed by TBC makes both the processing and its results more robust.