Heading error of Strapdown inertial navigation system (INS) may be enlarged in some complicated road and vehicle conditions when maneuvering long time.An integrated navigation algorithm based on single INS (SINS) integrated navigation algorithm frame was presented.Integrated navigation was achieved through Kalman filter with 21 error states of the inertial measurement unit/distance transfer unit (IMU/DTU),which selected the difference between the displacement increment obtained respectively from the INS and the DTUas the observation term.Most errors of IMU/DTU integrated navigation system was canceled automatically by way of rotation and Kalman filter,which integrated information from the INS and the DTU.Precise position information and attitude information could be output without special conditions for marching vehicles.Some simulation experiments and vehicular tests were executed,which showed that the algorithm was able to achieve precise heading(attitude) and position.Potential accuracy was discovered.Rapid response capability,environmental adaptability and usability were improved greatly.

Aiming at the problem that the vehicle odometer scale factor changes in real time due to the influence of tire pressure and temperature, a method of SINS (strap down inertial navigation system)/odometer integrated navigation based on strong tracking filter is presented. The property that the residual sequences of Kalman filter are mutually orthogonal is used to adjust fading factor adaptively. The strong tracking filter has the ability to track the sudden change state. The average velocity matching method is proposed to eliminate the influence of vehicle vibration and odometer quantization error on integrated navigation. The lever arm error is adopted into the state variables to eliminate the influence of inaccurate lever arm on integrated navigation when the vehicle is turning. The SINS/odometer integrated navigation model is built. The actual vehicle integrated navigation experiment is carried out. The results show that the positioning accuracy of integrated navigation is better than 1‰D.