Fast estimating method of lfm signal parameters with low signal-to-noise ratio based on frft

Abstract

The invention discloses an FRFT-based fast estimation method for LFM signal parameters with low signal-to-noise ratio, and relates to the technical field of signal processing methods. The method determines the initial interval of the rotation order by judging the positive or negative of the frequency modulation slope; then applies high-efficiency FRFT to obtain the initial rotation order; finally uses the fourth-order origin moment of the fractional order spectrum to further determine the search interval and step size to achieve accurate Search, so as to meet the requirements of parameter accuracy. Experimental results show that this method is especially suitable for LFM signal detection and parameter estimation under low signal-to-noise ratio, and the calculation load is relatively low.

Description

technical field [0001] The invention relates to the technical field of signal processing methods, in particular to an FRFT-based method for quickly estimating parameters of an LFM signal with a low signal-to-noise ratio. Background technique [0002] Linear Frequency Modulation (LFM) signal is a signal whose frequency changes linearly with time. It is widely used in communication, radar, sonar and other fields. Its parameter estimation and signal detection are one of the research hotspots. At present, the processing methods for LFM signals mainly include short-time Fourier transform and Wigner-Ville distribution. Among them, the short-time Fourier transform cannot take into account the better time-domain resolution and frequency-domain resolution at the same time, and the estimation effect is not good in the case of low signal-to-noise ratio; while the Wigner-Ville distribution needs to analyze multiple components of the signal In the case of processing, the problem of cros...

AI Technical Summary

Problems solved by technology

Using this feature, FRFT can be used to detect and estimate the parameters of chirp signals, but because it needs to use two-dimensional search to determine the optimal rotation angle, the calculation is relatively large

[0003] To solve this problem, the existing technology proposes an undersampling fast detection algorithm, which improves the operation speed of FRFT by reducing the number of sampling points, but this algorithm cannot realize the correct estimation of signal parameters when the signal-to-noise ratio is low

The existing technology also proposes a search method based on the golden section of the fractional domain, although it can reduce the calculation cost, it is not suitable for the case of low signal-to-noise ratio

There is also an existing high-efficiency FRFT algorithm based on modified power spectrum smoothing filtering. Although this algorithm can quickly realize the detection and estimation of LFM signals, the estimation effect of signal parameters with a signal-to-noise ratio less than -3dB is not good.

Based on the transformation law between the fractional power spectrum amplitude and the rotation angle, a targeting search method is proposed. Although the optimal rotation angle can be quickly searched, when the signal-to-noise ratio is low, there is a local optimum problem, which is still a problem. The estimation accuracy of the parameters cannot be guaranteed

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