An On-line Calibration Method of SINS/Odometer Integrated Navigation System

Considering the key factors that affect the precision of strapdown inertial navigation system (SINS) and odometer integrated navigation system, an on-line calibration method based on Kalman filter aided by odometer is proposed. Dead reckoning (DR) algorithm and DR error model including odometer scale factor and odometer installation errors are given. Based on the error model, a closed-loop Kalman filter is designed to estimate odometer scale factor error, odometer installation errors, gyroscope drifts and accelerometer biases, and then improve the horizontal position precision. Finally, the simulation of SINS/odometer integrated navigation is carried out. Correlated results show that current parameters including odometer scale factor and odometer installation can be estimated on the base of former parameters, and compared with the horizontal position calculated by dead reckoning algorithm, the proposing method exerts a higher horizontal position precision, which sufficiently verifies the validity of proposing method.