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Introduction

Accuracy of GNSS Observations from Three Real-Time Networks in Maryland, USA Daniel GILLINS , Jacob HECK, Galen SCOTT, Kevin JORDAN, and Ryan HIPPENSTIEL, National Geodetic Survey, USA. Introduction.

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Introduction

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  1. Accuracy of GNSS Observations from Three Real-Time Networks in Maryland, USADaniel GILLINS, Jacob HECK, Galen SCOTT, Kevin JORDAN, and Ryan HIPPENSTIEL, National Geodetic Survey, USA

  2. Introduction • Real-time Networks have become popular and many regional, national, and international networks are available for use • Highly accurate geodetic coordinates derived in minutes or less • Popular for surveying, engineering, navigation, machine control, precision agriculture, structural health monitoring, mobile mapping, construction

  3. Real-time Networks (RTNs) RTN Base RTN Base VRS Control Center RTN Base

  4. Problem Statement • Some desire to use RTNs for establishing geodetic control on marks • Traditional guidelines like in the USA recommend lengthy static GNSS survey campaigns (e.g., NOS-NGS 58) which require sessions from 30 min. to 5 hours • To set national standards for use of RTNs, need to ensure RTN is aligned to the national reference system • Few comparative studies have been completed on the accuracy of RTNs from different equipment manufacturers

  5. Study Area • Collected both static GPS and NRTK data on 9 bench marks (brass disks or metal rods) • All bench marks at sites suitable for GNSS observation

  6. Static GPS Campaign • Observed all 9 bench marks for two to four repeat, 24-hour static GPS sessions • Added 24-hour data for each day of survey from 8 additional CORS • Post-processed in NGS software OPUS-Projects • Survey network adjusted by least squares using NGS software ADJUST • Estimated errors in adjusted coordinates were less than 0.5 cm horizontally and 0.6 cm vertically (ellipsoid height) at 95% confidence • Used adjusted coordinates from this survey as “truth” for evaluating the RTNs

  7. RTK Equipment Topcon Hyper V Leica GS18 Trimble R10 (TopNET Live) (SmartNet) (KeyNetGPS)

  8. Network RTK Campaign, Survey Steps • Visited each bench mark 6 times (3 mornings & 3 afternoons on 3 different days) from February 21 to March 7, 2018 • Every Network RTK (NRTK) Observation = 5-minute duration (300 second), fixed measurement using both GPS+GLONASS • During each visit, repeat these steps 3 times: • (1) attach the Trimble R10 antenna to tripod, wait for fix then collect NRTK shot; • (2) remove the antenna and invert it so that it loses initialization; • (3) attach the Leica GS18 antenna, wait for fix then collect NRTK observation; • (4) remove the antenna and invert it; • (5) attach the Topcon Hyper V antenna, wait for fix, then collect NRTK observation; • (6) remove the antenna and invert it.

  9. Network RTK Campaign Survey Data • 54 NRTK observations per bench mark (54 x 9 bench marks = 486 total) • 18 NRTK observations from 3 different rovers per bench mark • From each rover, collected 9 in morning & 9 in afternoon on 3 different days • Stored each observation as a vector from a physical base station to rover • ECEF vector components plus 3x3 covariance matrix • Stored other metadata, including number of satellite vehicles used, PDOP, HDOP, and VDOP

  10. Number of Satellites, PDOP, HDOP, VDOP

  11. 1. Results: NRTK minus Adjusted Static Coordinates

  12. 1. Results: NRTK minus Adjusted Static Coordinates after Correcting Base Station Coordinates • HRMSE = 2.3 cm, VRMSE = 4.5 cm (95% confidence)

  13. 2. Results: Precision of Repeat Vectors

  14. 3. Formal Error Propagation via Survey Network Least Squares Adjustment

  15. 3. Survey Networks for Least Squares Adjustment • Constructed 5 separate survey networks for data from 3 RTNs • 2 vectors per mark • 3 vectors per mark • 4 vectors per mark • 5 vectors per mark • 6 vectors per mark

  16. 3. Results: Formal Error Propagation via Survey Network Least Squares Adjustment

  17. Conclusions • All three RTNs performed similarly in terms of accuracy. Based on 486 NRTK, 5-min. duration observations on 9 bench marks using both GPS and GLONASS: • Coordinates differed from adjusted coordinates from a static GPS survey campaign by ± 2.3 cm horizontally and ± 4.5 cm in ellipsoid height at 95% confidence • Repeat vector differences were ± 2.4 cm horizontally and ± 3.4 cm in ellipsoid height at 95% confidence • By formal error propagation, 4 repeat vectors to each mark in a survey network adjustment resulted in ellipsoid heights with estimated errors less than 2 cm (95% conf.)

  18. Questions? • Daniel.Gillins@noaa.gov

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