The most commonly used Inertial Navigation System (INS)/Global Navigation Satellite System (GNSS) integration strategy is known as the Loosely Coupled (LC) scheme in which GNSS-derived positions and velocities are integrated with INS-derived navigation information to provide robust navigation solutions. Although the LC scheme uses a simple and flexible architecture to derive navigation information, but its limitation is that the Global Position System (GPS) Kalman Filter (KF) cannot provide position and velocity updates for INS solutions if fewer than four satellites are tracked by the GNSS receiver. Another commonly used integration strategy is known as the Tightly Coupled (TC) scheme, which processes GNSS raw measurements rather than the GNSS navigation information to execute measurement updates. It performs well even if fewer than four satellites are tracked and only one (KF) is implemented in the TC scheme, which is integrated with the inertial mechanization equation and processes the accelerations and angular rates from inertial sensors as well as pseudo-range, pseudo-range rate, and carrier phase measurements from the GPS receiver. These measurements are used by the filter to estimate the navigation solutions and the inertial sensor errors, which are used to compensate for the raw measurements of inertial sensors. The present study investigates the impact of LC and TC INS/GNSS integration schemes on Directly Geo-reference (DG) technology in terms of positioning accuracy using the landbased Mobile Mapping System (MMS) van developed at the Department of Geomatics at National Cheng Kung University. Performance analysis is conducted by performing a DG operation with 70 to 80 check points from images taken kinematically with the MMS van using the positioning and orientation solutions processed with LC and TC schemes, respectively, with a variable number of visible satellites. The results are compared to precisely known coordinates for performance verification.
|Number of pages||5|
|Journal||Advanced Science Letters|
|Publication status||Published - 2012 Aug 2|
All Science Journal Classification (ASJC) codes
- Computer Science(all)
- Health(social science)
- Environmental Science(all)