Augmenting Kalman Filtering With Parallel Cascade Identification for Improved 2D Land Vehicle Navigation
Land vehicle positioning relies mostly on satellite navigation systems such as the Global Positioning System (GPS). However, GPS signals may be degraded or suffer from blockage in urban canyons and tunnels, and the positioning information provided is interrupted. One solution for such a problem is to integrate GPS with an Inertial Measurement Unit (IMU) and the navigation solution is achieved using an estimation technique which is traditionally based on a Kalman Filter (KF). In order to have a low cost navigation solution for land vehicles, MEMS-based inertial sensors are used. To further reduce the cost a Reduced Inertial Sensor System (RISS) which consists of only one gyroscope and a speed sensor is integrated with GPS.