Suppressive Interference Suppression for Frequency Modulated Continuous Wave Radar Based on Singular Spectrum Entropy

In complex electromagnetic environments, Frequency Modulated Continuous Wave (FMCW) radar faces various types of interference, particularly jamming interference. To effectively suppress these interferences, an interference suppression algorithm based on Singular Value Decomposition (SVD), Principal Component Analysis (PCA), and Singular Spectrum Entropy (SSE) is proposed in this paper. Firstly, SVD is used to whiten the interfered Linear Frequency Modulation (LFM) signal, resulting in a whitening matrix. Secondly, PCA is applied to extract feature vectors and eigenvalues from the whitened signal, which are then sorted to compute the principal components, thus achieving blind source separation of the signals. Finally, to further differentiate between the signal and interference, Singular Spectrum Entropy is introduced as a feature to assess the nature of the principal components and distinguish between interference and useful signals. Simulation results indicate that the proposed method can effectively separate signals and interference in complex electromagnetic environments, demonstrating higher accuracy and robustness compared to Independent Component Analysis (ICA), Eigen Value Decomposition (EVD), Least Mean Square Adaptive Filter (LMS), and the standalone SVD approach.