A Dead-Reckoning Based Local Positioning System for Intelligent Vehicles

This paper presents a local positioning system based on vehicle motion model. The system is designed by 2D dead reckoning principle, which uses previous state information, speed and heading outputs of vehicle sensors to estimate real-time pose information. A Kalman filter based on speed-acceleration model is introduced to eliminate error of the odometer. And a linear error model is introduced to compensate the accumulative error of gyroscope. By preprocessing the speed and heading outputs, the precision of local positioning system is improved.