Abstract
Periodic frequency-modulated (FM) interference signals, commonly employed by jammers and radars, may lead to the performance degradation or even failure of global navigation satellite systems and wireless communications. Time–frequency (TF) representations play an essential role in FM signal analysis and instantaneous frequency (IF) estimation, which is the basis of many nonstationary interference suppression algorithms. This article provides a TF representation approach for signals with multiple periodic FM components in the presence of sample loss. The proposed approach utilizes the periodicity and the sparsity of signal components in the TF domain to suppress cross-terms and artifacts. We reconstruct TF distributions of each component by time-averaging Wigner–Ville distribution. Then, the residual artifacts are eliminated by a low-complexity sparse-based adaptive directional TF filtering method. Simulation results confirm that the proposed approach provides an outstanding suppression of cross-terms and artifacts. The proposed TF representation approach can effectively improve the accuracy of the IF estimation of each signal component.
Published Version
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