Abstract
The main purpose of this paper is to present a fusion approach to bridge the period of Global Positioning System (GPS) outages using two proprioceptive sensors that are the Inertial Navigation System (INS) and the odometer in order to assure a continuous localization for land vehicle in urban areas where GPS signal blockage is very often. Odometer and GPS measures are exploited to correct inertial sensor errors. In fact, during GPS availability, INS is integrated with GPS to provide accurate localization solution; whereas during GPS outages, the odometer measurements are used to correct the INS error thereby improving the positioning accuracy and assuring the continuity of navigation solution. The problem of estimation of vehicle localization is realized by Kalman Filter (KF) that merges sensor measurements. The paper thus introduces results from simulation and real data.
Highlights
Satellite navigation systems such as Global Positioning System (GPS) or Galileo are increasingly popular and used in strategic as well as public applications
The estimator uses the odometer measures in order to correct inertial sensor errors
This paper proposes a new technique for GPS/Inertial Navigation System (INS)/Odometer integration based on Kalman filter that minimizes the INS error and provides continuous estimation of vehicle position, velocity and attitude
Summary
Satellite navigation systems such as GPS or Galileo are increasingly popular and used in strategic as well as public applications. One of the solutions is to integrate the GPS with other sensors that provide a good availability such as INS and odometry. Integrated navigation systems have been used intensively in many domains such as aeronautics Their application to the automotive industry shows a big increase due to the low cost inertial measurement units (IMU). The measurements of the inertial sensors are affected by errors due to physical limitations The accumulation of these errors leads to the decrease of the accuracy of navigation solution. GPS is very often used as an aiding source to the INS, and the GPS/INS integrated system with good GPS availability provides more precise dynamic positioning than a stand-alone GPS or INS. Our proposed method is based on the use of an additional aiding source The estimation of dynamic characteristics of the vehicle is solved by a KF that fuses the measurements of each sensor to estimate position, velocity and attitude of the vehicle
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