Accurate parameters estimation of chirp signal in low SNR

Abstract

Aiming at solving the problem of great difficulty and low accuracy existing in parameters estimation of chirp signal in low SNR condition, an algorithm of accurate parameters estimation of chirp signal is proposed. Firstly, the algorithm extracts ridge frequency of chirp signal based on Short Time Fourier Transform (STFT). Secondly, the protruding glitch frequencies are eliminated through median filter with proper size and the smoothing frequencies are obtained corresponding to the time. Thirdly, the frequency-time FM (Frequency Modulated) 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 got. Monte Carlo simulation results show the effectiveness of the algorithm.

A Fast Direct Position Determination Algorithm for LFM Signal Based on Spectrum Detection

“…For the LFM signal, short-time Fourier transform (STFT) performs analysis on the signal in the time window and can intuitively reflect the trend of the frequency and the change of spectrum along with time, thus the initial frequency and chirp rate of the signal can be estimated efficiently, which has a good effect on the estimation accuracy, especially at low SNR [40][41][42][43][44][45]. The common STFT is defined as…”

“…where hðτÞ is the time window function, which is called analysis window as well. Substituting Equation ( 12) into the expression of the LFM signal [42], then the STFT for the LFM signal sðtÞ is defined as…”

Passive localization for emitter with unknown LFM signal based on signal parameter estimation

“…where the Gaussian window is chosen as the analysis window so |Γ h (f )| 2 becomes a Gaussian function, which is symmetric about the point f = 0 and obtains the maximum value at f = 0 [19]. It means that the SP of the LFM signal obtains the maximum value at f = f 0 + kt at each t. Note that the SP of the LFM signal with a time shift t is Ω LFM (t − t , f) and the maximum value is obtained at…”

“…It is a kind of linear transformation and also known by the name "windowed Fourier transform". It represents the instantaneous spectrum of the signal at the time of interest by Fourier analyzing a small segment of the signal around that time [17]- [19]. The STFT for the signal s (t) is defined as,…”