Evaluation of time frequency tools for multi-component chirp signals
Evaluation of time frequency tools for multi-component chirp signals
- Author(s): J. Sharma ; V. Thakur ; S.D. Sharma
- DOI: 10.1049/cp.2016.1454
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- Author(s): J. Sharma ; V. Thakur ; S.D. Sharma Source: International Conference on Signal Processing (ICSP 2016), 2016 page ()
- Conference: International Conference on Signal Processing (ICSP 2016)
- DOI: 10.1049/cp.2016.1454
- ISBN: 978-1-78561-783-6
- Location: Vidisha, India
- Conference date: 7-9 Nov. 2016
- Format: PDF
Chirp signals are non stationary signals which have continuously increasing or decreasing frequency. If the frequency of signal increases from lowest to the highest values then it is called an up-chirp and if it decreases from highest to the lowest values then the chirp is called a down-chirp. Multi-component signals are those which contain more than one frequency component. The multi-component chirp signals play an important role in RADAR signal processing, micro-seismic signals analysis, micro-Doppler signal detection, and instantaneous frequency estimation etc. Therefore, to extract the information at a particular time instant corresponding to a particular frequency, time frequency tools have been used. These time-frequency tools are Short time Fourier transform (STFT), Wavelet transform (WT), Chirplet transform (CT), Polynomial chirplet transform (PCT), and S-transform (ST). In this paper, we have studied the existing time-frequency methods for the processing of chirp signals and multicomponent signals. Further our contributory work has also been discussed and results are compared using MATLAB.
Inspec keywords: polynomials; Fourier transforms; time-frequency analysis; signal processing; wavelet transforms
Subjects: Mathematical analysis; Integral transforms; Signal processing and detection; Algebra; Integral transforms; Algebra; Mathematical analysis; Signal processing theory; Other topics in statistics
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