A high-resolution quadratic time-frequency distribution for multicomponent signals analysis

• Published in: IEEE transactions on signal processing Vol. 49; no. 10; pp. 2232 - 2239
• Main Authors: Barkat, B., Boashash, B.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.10.2001; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Additive noise; Applied sciences; Design engineering; Exact sciences and technology; Frequency estimation; Gaussian; Gaussian noise; Information, signal and communications theory; Kernel; Kernels; Mean square error methods; Noise; Signal analysis; Signal and communications theory; Signal design; Signal processing; Signal representation. Spectral analysis; Signal resolution; Signal, noise; Spectrogram; Spectrograms; Stepped; Telecommunications and information theory; Time frequency analysis; Additive noise; Performance evaluation; Parameter estimation; High resolution; Multicomponent analysis; Gaussian noise; Time frequency domain method; Instantaneous frequency; Signal analysis; Wigner distribution; Mean square error; Quadratic function
• ISSN: 1053-587X; 1941-0476
• DOI: 10.1109/78.950779

The paper introduces a new kernel for the design of a high resolution time-frequency distribution (TFD). We show that this distribution can solve problems that the Wigner-Ville distribution (WVD) or the spectrogram cannot. In particular, the proposed distribution can resolve two close signals in the time-frequency domain that the two other distributions cannot. Moreover, we show that the proposed distribution is more accurate than the WVD and the spectrogram in the estimation of the instantaneous frequency of a stepped FM signal embedded in additive Gaussian noise. Synthetic and real data collected from real-world applications are shown to validate the proposed distribution.