A method for post-mission velocity and orientation estimation based on data fusion from MEMS-IMU and GNSS

INS and GNSS integrated systems have become widespread as a result of low-cost MEMS inertial sensor technology. However, the accuracy of computed velocity and orientation is not sufficient for some applications, e.g. performance and technique monitoring and evaluation in sports. Significant accuracy improvements can be made by post-mission data processing. The approach is based on fixed-lag Rauch-Tung-Striebel smoothing algorithm and provides a simple and effective solution to misalignment correction. The potential velocity accuracy is about 0.02 m/s and pitch/roll accuracy is about 0.02 deg. This algorithm was tested for walking and running. The proposed approach could also be used for accurate velocity and orientation estimation in other applications including different sports, e.g. rowing, paddling, cross-country and downhill skiing, ski jump etc.

[1]  I. Bar-Itzhack,et al.  Azimuth Observability Enhancement During Inertial Navigation System In-Flight Alignment , 1980 .

[2]  O.A. Stepanov,et al.  Nonlinear filtering methods application in INS alignment , 1997, IEEE Transactions on Aerospace and Electronic Systems.

[3]  Chris Hide,et al.  GPS and Low Cost INS Integration for Positioning in the Urban Environment , 2005 .

[4]  Jay A. Farrell,et al.  Centimeter-Accuracy Smoothed Vehicle Trajectory Estimation , 2013, IEEE Intelligent Transportation Systems Magazine.

[5]  Jiancheng Fang,et al.  Application of unscented R–T–S smoothing based on novel mathematical model in SINS/GPS integrated system post processing , 2014 .

[6]  Eun-Hwan Shin,et al.  Optimizing Smoothing Computation for Near Real-Time GPS Measurement Gap Filling in INS/GPS Systems , 2002 .

[7]  Gérard Lachapelle,et al.  Low Cost INS/GPS Integration: Concepts and Testing , 2000 .

[8]  R. Piché Automatic numerical differentiation by maximum likelihood estimation of state-space model , 2016, 1610.04397.

[9]  Rong Zhang,et al.  Application of unscented R–T–S smoothing on INS/GPS integration system post processing for airborne earth observation☆ , 2013 .

[10]  Pau Closas,et al.  Tight GNSS/INS integration as a constrained least-squares problem , 2009, 2009 17th European Signal Processing Conference.

[11]  A. H. Mohamed,et al.  Adaptive Kalman Filtering for INS/GPS , 1999 .

[12]  Sandy Kennedy,et al.  GPS/INS Integration in Real-time and Post- processing with NovAtel's SPAN System , 2007 .

[13]  Feng Zhu,et al.  New optimal smoothing scheme for improving relative and absolute accuracy of tightly coupled GNSS/SINS integration , 2017, GPS Solutions.

[14]  Naser El-Sheimy,et al.  Accurate Pipeline Surveying Using Two-Filter Optimal Smoothing of Inertial Navigation Data Augmented with Velocity and Coordinate Updates , 2010 .