Data Integration from GPS and Inertial Navigation Systems for Pedestrians in Urban Area

Abstract

The GPS system is widely used in navigation and the GPS receiver can offer long-term stable absolute positioning information. The overall system performance depends largely on the signal environments. The position obtained from GPS is often degraded due to obstruction and multipath effect caused by buildings, city infrastructure and vegetation, whereas, the current performance achieved by inertial navigation systems (INS) is still relatively poor due to the large inertial sensor errors. The complementary features of GPS and INS are the main reasons why integrated GPS/INS systems are becoming increasingly popular. GPS/INS systems offer a high data rate, high accuracy position and orientation that can work in all environments, particularly those where satellite availability is restricted. In the paper integration algorithm of GPS and INS systems data for pedestrians in urban area is presented. For data integration an Extended Kalman Filter (EKF) algorithm is proposed. Complementary characteristics of GPS and INS with EKF can overcome the problem of huge INS drifts, GPS outages, dense multipath effect and other individual problems associated with these sensors.

Keywords

• Inertial Measurement Unit (IMU)
• Urban Area
• Inertial Navigation System
• Global Positioning System (GPS)
• Extended Kalman Filter (EKF)
• Pedestrian Trajectory
• Micro Electro Mechanical Systems (MEMS)
• Integration of Navigation