Jamming Signal Detection Based on TSVD Method
Yang Xu, An-Ping Li, Meiying Wei, Xiaofei Zhang, Sixue Lu, Wen Wang · 2020
As rapid development of the communication technology, jamming signal detection has been a challenging subject. There are various studies of jamming signal detection but little of which could detect jamming signals from high dimensional spectral data. We propose jamming signal detection method based on truncated singular value decomposition (TSVD). We compress the spectral matrix to multiple characteristic components and reconstruct the raw spectral matrix. We propose jamming-detection-score based on the reconstruction error to calculate the loss. Jamming signal detection of high dimensional data is realized by the increased lossy of jamming case. We conduct experiments with high dimensional spectral matrix and the results prove that our method is reasonable and accurate.