Generalized Group Delay Weighted Sparse Time–Frequency Analysis for Transient Signals

Time-frequency (TF) postprocessing methods are often used to form concentrated TF representations (TFRs) for nonstationary signals. Regrettably, most such techniques are sensitive to noise and tend to underestimate weak components when dealing with transient signals, resulting in sidelobes and low-resolution TFRs. In this work, we introduce a generalized group delay (GD) weighted sparse TF (GWSTF) analysis method exploiting sparse reconstruction theory to form sparse high-resolution TFRs. Using both numerical simulations and measured data, we show the preferable performance of the proposed method as compared to recent alternative approaches.