Performance Analysis of Constrained Loosely Coupled GPS/INS Integration Solutions

The paper investigates approaches for loosely coupled GPS/INS integration. Error performance is calculated using a reference trajectory. A performance improvement can be obtained by exploiting additional map information (for example, a road boundary). A constrained solution has been developed and its performance compared with an unconstrained one. The case of GPS outages is also investigated showing how a Kalman filter that operates on the last received GPS position and velocity measurements provides a performance benefit. Results are obtained by means of simulation studies and real data.

[1]  Naser El-Sheimy,et al.  Improved Vehicle Navigation Using Aiding with Tightly Coupled Integration , 2008, VTC Spring 2008 - IEEE Vehicular Technology Conference.

[2]  John Weston,et al.  Strapdown Inertial Navigation Technology , 1997 .

[3]  Mark G. Petovello,et al.  Benefits of Combined GPS/GLONASS with Low-Cost MEMS IMUs for Vehicular Urban Navigation , 2012, Sensors.

[4]  Mark G. Petovello,et al.  Comparison of Vector-Based Software Receiver Implementations With Application to Ultra-Tight GPS/INS Integration , 2006 .

[5]  Claus Kaschwich,et al.  Improving GNSS Attitude Determination Using Inertial and Magnetic Field Sensors , 2022 .

[6]  J. Farrell,et al.  The global positioning system and inertial navigation , 1999 .

[7]  D. W. Allan,et al.  Statistics of atomic frequency standards , 1966 .

[8]  Bernd Eissfeller,et al.  Deep Integration of Navigation Solution and Signal Processing , 2005 .

[9]  M. Petovello Real-time integration of a tactical-grade IMU and GPS for high-accuracy positioning and navigation , 2003 .

[10]  Chan Gook Park,et al.  Covariance analysis of strapdown INS considering gyrocompass characteristics , 1995 .

[11]  Bernd Eissfeller,et al.  A KALMAN FILTER FOR THE INTEGRATION OF A LOW COST INS AND AN ATTITUDE GPS , 2002 .

[12]  Salah Sukkarieh,et al.  Low Cost, High Integrity, Aided Inertial Navigation Systems for Autonomous Land Vehicles , 2000 .

[13]  Yong Li,et al.  Low-cost tightly coupled GPS / INS integration based on a nonlinear Kalman filtering design , 2006 .

[14]  Saurabh Godha,et al.  Performance evaluation of low cost MEMS-based IMU integrated with GPS for land vehicle navigation application , 2006 .

[15]  Jinling Wang,et al.  A Novel Method to Integrate IMU and Magnetometers in Attitude and Heading Reference Systems , 2011, Journal of Navigation.

[16]  Adriano Solimeno,et al.  Low-Cost INS/GPS Data Fusion with Extended Kalman Filter for Airborne Applications , 2007 .

[17]  Richard A. Brown,et al.  Introduction to random signals and applied kalman filtering (3rd ed , 2012 .

[18]  Eun-Hwan Shin,et al.  Accuracy Improvement of Low Cost INS/GPS for Land Applications , 2002 .

[19]  Tomer Toledo,et al.  Pseudo-Measurements as Aiding to INS during GPS Outages , 2010 .

[20]  John Weston,et al.  Strapdown Inertial Navigation Technology, Second Edition , 2005 .

[21]  Peter Brooker,et al.  Radar Inaccuracies and Mid-Air Collision Risk: Part 1 A Dynamic Methodology , 2004, Journal of Navigation.