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The traditional fault detection method of redundant IMU in navigation system is difficult to realize real-time fault detection due to its too complex mathematical model, large calculation and large delay. However, PCA is only applied to fault detection and isolation in static situation. Aiming at the disadvantage that PCA is not able to detect redundant IMU in dynamic situation, a fault detection method based on parity space is proposed This method uses even and odd vectors to isolate the dynamic variables of vehicles, so as to eliminate the influence of dynamic variables on fault detection. Then PCA method is used to detect the data to realize the real-time detection of vehicle sensor information. By transposing the original data set to the feature plane to form a pattern, the normal and fault modes of IMU sensors are realized accurately Separation improves the accuracy and reliability of fault detection results of redundant IMU. The experimental results show that this method can detect the faults of redundant IMU in dynamic state, improve the performance of PCA, and effectively eliminate the negative effects of navigation system motion.