UrbanRTK-INS-OutlierOpt is an open-source framework that integrates Real-Time Kinematic (RTK) Global Navigation Satellite Systems (GNSS) with Inertial Navigation Systems (INS), utilizing a diagonal-form of Risk-Averse Performance-Specified (RAPS) Optimization approach. The diagonal-form RAPS is an efficient (solved in polynomial time complexity) and elegant method, well-suited for real-time navigation. This repository is designed to provide robust outlier accommodation in urban environments, where GNSS signals are often compromised due to obstacles like buildings and bridges.
@_@ Under review
- IMU nonlinear time propagation using Quaternion. see
imu/insTimePropagation.m. - Parser to Observation and Ephemeris RINEX files, see
parser/parserGnssObs.mandparser/parserGnssEph.m. For more information refer to RINEX 3.03 - Implementation of Precise Point Positioning (PPP) corrections, such as the IGGtrop model (
corr/IGGtropSH_bl.m, provided by IGGtrop paper author Dr. Wei Li, liwei@whigg.ac.cn) and SSR VTEC model (corr/ssrVtecComputation.m)
MATLAB (tested in version R2023a, certain toolboxes, such as Optimization Toolbox, may be required.)
Python (tested in Python 3.9. For generating KML file using results/createTrajKml.py)
Uncompress data\univOfTexas\univOfTexas.7z.
The main file to run is titled multiGnssMain.m.
The default setting is to perform GNSS-RTK-Aided INS using RAPS for outlier recommendation.
To switch between RTK and DGNSS (code measurement-based): p.post_mode = p.mode_rtkfloat; for RTK float; p.post_mode = p.mode_dgnss; for DGNSS.
To change estimation mode: p.est_mode = p.raps_ned_est; for RAPS; p.est_mode = p.map_est; for Extended Kalman Filter (EKF); p.est_mode = p.td_est; for Threshold Decision (TD).
The results for EKF-INS-RTK, TD-INS-RTK, and RAPS-INS-RTK were previously computed and saved in results/. To see the analysis of the results, run results/figure_plot_dgnss.m.
Google Earth 3D View uses a KML file generated by results/createTrajKml.py where it reads the experimental results from MATLAB .mat data file.
Detailed Solution to RAPS Optimization (Sec. 6 Solutions to DiagRAPS)
The open-source TEX-CUP dataset (2019May09) is used. The experimental route traversing areas within the west campus of The University of Texas at Austin and downtown Austin, contains viaducts, high-rise buildings, and dense foliage. Results are estimated through forward (real-time) processing.
The RTK-GNSS/INS integration utilizes single-frequency measurements from a Septentrio receiver GPS L1, GLONASS L1, GALILEO E1, and Beidou B1. The inertial measurements are provided by the LORD MicroStrain 3DM GX5-25 IMU with a sampling rate of 100 Hz.
Left panels: near the Dell Medical School buildings.
Right panels: near Sailboat Building (multiple skyscrapers surround the site)
Some results (red points) present positioning errors over 100 meters.
3D View from Google Earth (For the right panel above)
