Multi-parameter GNSS Spoofing Interference Detection Based on CS-C-SVM

‍ ‍Spoofing makes the receiver calculate the wrong position， speed and time by transmitting false global navigation satellite system （GNSS） signals， which is extremely harmful， so it is very necessary to detect spoofing interference. The traditional method with using a single parameter to detect spoofing interference has certain limitations， but spoofing process makes a series of parameters change. A detection method with comprehensively using multiple parameters was proposed in this paper， which multiple parameters were used as C-support vector machines （C-SVM） feature input and constructed a classifier for detecting spoofing interference. The C-SVM algorithm optimized by the traditional grid search （GS-C-SVM） is easy to fall into the local optimum， decreasing the performance of the classifier. The paper proposed to use the cuckoo search algorithm to optimize the C-SVM （CS-C-SVM）. Simulation result shows that this method can further improve the classification accuracy and reduce the false alarm rate.