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.