Correlation time delay estimation method based on emd reconstruction

Abstract

The invention discloses a related delay estimation method based on EMD reconstruction, wherein the related delay estimation method comprises the following steps: 1) obtaining sampling sequences y1(n) and y2(n), and extracting preamble background noise sequences b1(n) and b2(n); 2) obtaining a cepstrum sequence (the formula is shown in the specification) of the sampling sequence y1(n), ad obtaining the cepstrum sequence (the formula is shown in the specification) of the preamble background noise sequence b1(n); 3) obtaining the sound channel response (the formula is shown in the specification) of the (the formula is shown in the specification) and the sound channel response (the formula is shown in the specification) of the (the formula is shown in the specification); obtaining the spectral envelope (the formula is shown in the specification) of the (the formula is shown in the specification) and the spectral envelope (the formula is shown in the specification) of the (the formula is shown in the specification); obtaining a spectral difference curve D1(omega) to obtain a normalized difference curve (the formula is shown in the specification); 4) obtaining a frequency band area with amplitude of (the formula is shown in the specification) larger than a threshold T1; 5) obtaining m basic mode components; 6) obtaining the power spectrum distribution curve of each group of components, calculating a ratio eta 1, and obtaining reconstruction signals of a target signal; and 7) detecting the peak value of a secondary related sequence (the formula is shown in the specification) of the reconstruction signals C1(n) and C2(n) of the target signal to obtain an estimated delay value (the formula is shown in the specification). The method is used for improving the accuracy and the stability of the delay estimation result under the condition of a low signal to noise ratio.

Description

technical field [0001] The present invention relates to an array signal processing technology, in particular to a correlation time delay estimation method based on EMD (Empirical Mode Decomposition, Empirical Mode Decomposition, EMD for short) reconstruction. Background technique [0002] As a key technology of sound source location, sonar delay estimation has always been a hot topic in the field of array signal processing, and has been applied to underwater target tracking and location, satellite interference source location, intelligent robots and other occasions. [0003] Traditional time delay estimation methods include: generalized cross-correlation method, adaptive mean square filter estimation method, mean square error function method, etc. [0004] For generalized cross-correlation method, please refer to: "C.H.Knapp and C.G.Carter.The generalized correlation method for estimation of time delay[J].IEEE Trans,Acoustics,Speech and Signal Processing,1976,21(2),pp.320-32...

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Problems solved by technology

[0004] For generalized cross-correlation method, please refer to: "C.H.Knapp and C.G.Carter.The generalized correlation method for estimation of time delay[J].IEEE Trans,Acoustics,Speech and Signal Processing,1976,21(2),pp.320-327 .”, the time delay can be accurately estimated when the signal-to-noise ratio is high, but the required weighting function cannot be pre-determined in the actual application of reverberation noise, and can only be replaced by an estimated value, which makes the generalized cross-correlation method actually have a low signal The measurement accuracy is poor and unstable under the noise ratio

[0005] For adaptive mean square filter estimation method, please refer to: "F.A.Reed,P.L.Feintuch andN.J.Bershad.Time delay estimation using the LMS adaptive filter–behavior[J].IEEE Transactions on Acoustics,Speech and Signal Processing.1981, 29(3), pp.561-571.", estimate the time delay by setting the iterative initial value, parameters and adaptive learning, but this method needs to assume that the background noise between channels is uncorrelated Gaussian white noise, in practice Estimation accuracy drops in noisy environment

[0006] Mean square error function method, can refer to: "G.Jacovitti and G.Scarano.Discrete TimeTechniques for Time Delay Estimation[J].IEEE Transactions on Signal Processing,1993,41(2),pp.525-533.", in no The best estimation can be achieved under the influence of noise, but the estimation accuracy is greatly reduced when there is actual noise, and the poor ability to resist variable noise interference is its biggest problem

[0007] In the case of low signal-to-noise ratio, the above methods are not very effective in practical applications at this stage. In practical applications, a robust time delay estimation method with good anti-noise performance is urgently needed

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