Abstract
It is quite challenging for the quadratic time-frequency distribution (QTFD) to analyze the multi-component linear frequency modulation (MC-LFM) signals due to its inevitable cross-term issue, particularly in the case of simultaneous strong components and weak components involved in the MC-LFM signals. This paper proposes a novel signal-dependent QTFD based on regional radially Gaussian kernel (RRGK) to improve the time-frequency representations (TFR) of the MC-LFM signals with distinguishing component amplitudes. The model of MC-LFM signals is firstly introduced, and the detrended Radon transform of ambiguity domain (RTA) technique is combined with energy distribution feature in the ambiguity domain analysis for the detection of potential auto-terms concentrated along lines passing through the origin of the Doppler-lag plane. The combined two-step signal detection method can be easily extended to other signal-dependent QTFDs. Then the Doppler-lag distribution area of each detected auto-term is automatically selected with stronger components peeled to restrict the searching area of RGK. Afterwards, a novel iterative regional RGK-based TFD (IRRGD) is developed to resolve strong and weak components under a proper trade-off between auto-term resolution and cross-term suppression in the TFD. Finally, filtering is performed in (t, f) domain to further improve the TFD results. Also, a quantitative indicator is proposed to measure weak signal preservation. Both simulation and experimental results have verified the superiorities of the proposed method over other existing state-of-the-art algorithms.
Published Version
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