Parameter estimation of chirp signal under low SNR

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Aiming at solving the problem of great difficulty and low accuracy existing in parameter estimation of chirp signal under low signal-to-noise ratio(SNR) condition, an algorithm of accurate parameter estimation of chirp signal is proposed. First, the algorithm extracts ridge frequency of chirp signal based on Short Time Fourier Transform. Second, the protruding glitch frequencies are eliminated through median filter with proper size and the smoothing frequencies are obtained corresponding to the time. Third, the frequency time frequencymodulated(FM) line is fitted coarsely by the least-square linear fitting method, and some frequency points are removed, which are far away from the FM line. Repeat the process several times until the sample correlation coefficient of the fitted line is in high degree when the optimum chirp line is fitted out, so chirp rate and initial frequency are obtained. Simulation shows that the correct rate of parameter estimation is very high. When SNR is not less than –17 d B, the correct rate is 100%, and when the SNR is –18 d B, the correct rate is still capable of up to 99%. This algorithm has a lower SNR threshold of about –17 d B. When the SNR is greater than threshold,parameter estimation accuracy is close to Cramer Rao low bound(CRLB), higher than parameter estimation based on the phase field method. Measured data experiments show that the algorithm can reasonably fit the chirp line of measured chirp signal, which better characterizes the FM features of chirp signal. Aiming at solving the problem of great difficulty and low accuracy existing in parameter estimation of chirp signal under low signal-to-noise ratio (SNR) condition, an algorithm of accurate parameter estimation of chirp signal is proposed. First, the algorithm extracts ridge frequency of chirp signal based on Short Time Fourier Transform. Second, the protruding glitch frequencies are eliminated through median filter with proper size and the smoothing frequencies are obtained to the time. Third, the frequency time frequency modulated (FM) line is fitted coarsely by the least-square linear fitting method, and some frequency points are removed, which are far away from the FM line. Repeat the process several times until the sample correlation coefficient of the fitted line is in high degree when the optimum chirp line is fitted out, so chirp rate and initial frequency are obtained. Simulation shows that the correct rate of parameter estimation is very high. When SNR is not less than -17 d B, the correct rate is 100%, and when the SNR is -18 d B, the correct rate is still capable of up to 99%. This algorithm has a lower SNR threshold of about -17 d B. When the SNR is greater than threshold, the parameter estimation accuracy is close to Cramer Rao low bound (CRLB), the higher the parameter estimation accuracy is close to Cramer Rao low bound (CRLB), the higher the parameter estimation accuracy is close to Cramer Rao low bound which better characterizes the FM features of chirp signal.
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