Jamming Detection in Broadband Frequency Hopping Systems Based on Multi-Segment Signals Spectrum Clustering

Accurate jamming detection in the broadband frequency hopping (FH) systems plays a vital role in improving the anti-jamming performance of the communication systems. The traditional jamming detection algorithms are prone to misjudge FH communication signals as jamming signals, leading to inaccurate jamming detection. Therefore, this paper proposes a jamming detection algorithm for broadband FH systems based on multi-segment signals spectrum clustering (MSSC). According to the difference in the time-frequency characteristics between FH signals and jamming signals, the proposed algorithm accurately detects the jamming by clustering the spectral components of signals in multiple periods. In addition, a jamming detector suitable for broadband FH systems is designed and the theoretical solution to the threshold factor of signal detection based on the Welch spectrum is also given in this paper. The simulation results show that the MSSC-based jamming detection algorithm proposed in this paper can reduce the jamming false detection probability and significantly improve the estimation accuracy of jamming parameters, effectively overcoming the defects of the traditional FFT-based energy detection and the multi-hop accumulation algorithms whose detection accuracy is sensitive to FH signals.