What are the best practices for PPP data processing and quality control?

1 Data collection

The first step for PPP data processing and quality control is to collect high-quality GNSS data from your receiver. You should use a geodetic-grade receiver and antenna, and ensure that they are properly configured and calibrated. You should also select a suitable site for your receiver, avoiding obstructions, multipath, and interference sources. You should record raw data in RINEX format, and collect at least 2 hours of continuous data for static PPP, or at least 15 minutes of data for kinematic PPP.

2 Data quality

The next step for PPP data processing and quality control is to check the quality of your GNSS data, before submitting it to a PPP software. You should inspect your data for gaps, outliers, cycle slips, noise, and other anomalies, using a GNSS data analysis tool, such as TEQC or RTKLIB. You should also check the availability and quality of the satellite signals, using a GNSS constellation plot or a sky plot. You should discard or correct any bad or corrupted data, and only use data that meets the quality standards of your PPP software.

3 Software selection

The third step for PPP data processing and quality control is to choose a suitable PPP software for your data processing. There are many PPP software options available, both online and offline, each with different features, models, and corrections. You should compare and evaluate different PPP software, based on your needs, preferences, and budget. You should also check the compatibility and reliability of the PPP software, and the availability and quality of the corrections and products that it uses.

4 Data processing

The fourth step for PPP data processing and quality control is to process your GNSS data with your chosen PPP software. You should follow the instructions and guidelines of your PPP software, and input the required parameters and settings. You should also select the appropriate processing mode, such as static or kinematic, and the desired output format, such as XYZ or LLH. You should monitor the progress and status of your data processing, and check for any errors or warnings.

5 Results validation

The final step for PPP data processing and quality control is to validate your results and assess their accuracy and precision. You should compare your results with a known reference position, such as a benchmark or a survey point, or with another independent GNSS technique, such as RTK or DGNSS. You should also analyze your results with a GNSS post-processing tool, such as GAPS or OPUS, and inspect the statistics, residuals, and plots of your results. You should identify and correct any systematic or random errors, and report any uncertainties or limitations of your results.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?