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Accurate estimation of the slip ratio for tractor driving wheels is of great significance to improve the working efficiency and safety of tractors and realize the antiskid control of tractors.A multi-innovation parallel extended Kalman filter algorithm was proposed, then through online statistics of multi-sensor innovations, D-S evidence theory was introduced to make decisions and correct the measurement noise matrix, which fused the information of multiple sensors, including machine vision, and then realized the accurate estimation of tractor driving wheels’ slip ratio.The simulation results showed that compared with the common Kalman filter algorithm, the proposed fusion algorithm had higher accuracy in estimating the slip ratio, the root mean square error of the estimated slip ratio was reduced from 2.34% to 1.45%, and the proposed algorithm was insensitive to interference signals. The test results showed that under two different working conditions, the average absolute error and root mean square error of the proposed multi-sensor information fusion algorithm were lower than those of single vision method or radar method. It was verified that the proposed algorithm can accurately estimate the slip ratio for tractor drive wheels, and then provide research help for the follow-up realization of tractor drive anti-skid control.