Interference can severely degrade the performance of the Global navigation satellite system (GNSS) receivers. Therefore it is important to detect the interference accurately and efficiently. Both the pre-correlation method and post-correlation method currently in use require certain strict pre-conditions, which limit their application. A new pre-correlation method that could be applied in most cases, called GNSS signal driven (GSD) method is proposed. The essence of the GSD method is to use classification techniques to detect the interference, based on the feature parameters extracted directly from the GNSS signals. The Support vector machine (SVM) and the Competitive agglomeration (CA) are adopted as the classification algorithms. When a classifier can be trained in advance, the SVM method is used, otherwise the CA method is adopted. Both methods show satisfying detection accuracy, especially the SVM method, whereas the robust CA method has an even wider application. The effectiveness of the proposed method is verified properly by experiments with the GPS L1 band Coarse/acquisition (C/A) signals.