Aiming at the demand of monitoring deep coupling system errors, this paper presents a method based on Principal Component Analysis (PCA) for the error monitoring according to the statistical characteristics of view measurement of deep coupling system.The normal observation data is used to construct the PCA model, and the parameters of the model is used for monitoring the observed data in the deep coupling system in real time.This method is used to detect and mitigate the errors in the deep coupling system, while the wavelet denoising is adopted to improve the performance of error detection.Finally, the result of simulation verifies the feasibility and effectiveness of the method.