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Method for estimating modulation frequency and starting frequency of linear frequency-modulated signal

A technology of linear frequency modulation signal and starting frequency, which is applied in the field of signal processing, and can solve problems such as limited engineering application, precision limitation, and slow operation speed.

Inactive Publication Date: 2012-09-19
SOUTHEAST UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Among them, WHT is the problem of converting the estimation of the parameters of the chirp signal into a straight line search problem in the time-frequency graph, and RAT is the problem of converting it into a straight line searched through the origin in the fuzzy graph. Both methods require complex calculations Then perform straight-line search, the operation speed is very slow, which limits its engineering application, and the RAT method loses the initial frequency information of the signal, so it is only suitable for occasions that are only interested in frequency modulation
FRFT makes full use of the aggregation characteristics of the chirp signal in the time-frequency domain, and can estimate the modulation frequency and initial frequency parameters of the signal at the same time, but this method requires a two-dimensional search for the modulation frequency and initial frequency parameters of the chirp signal, and calculates The amount is large, and the accuracy of parameter estimation is limited by the inherent resolution of FRFT

Method used

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  • Method for estimating modulation frequency and starting frequency of linear frequency-modulated signal
  • Method for estimating modulation frequency and starting frequency of linear frequency-modulated signal
  • Method for estimating modulation frequency and starting frequency of linear frequency-modulated signal

Examples

Experimental program
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Effect test

Embodiment 1

[0074] Example 1: Initialize the parameters first, set the short-time window length M=128, the short-time window moving step L=64, and the weight correction factor σ 1 =1, the maximum iteration threshold K=2000 and the precision control index ε=10 -6 , to calculate the total number of short-time windows The number of initialization window moves i=1, and the number of iterations k=1.

[0075] Then move the time window, use the Rife interpolation algorithm to estimate the instantaneous frequency estimated value of the data sequence in each short time window, and obtain the instantaneous frequency estimated value sequence f i ,i=1,2,...,20, as shown in Table 1

[0076] Table 1 The instantaneous frequency sequence estimated by Rife interpolation algorithm

[0077]

[0078] where f 3 , f 4 , f 11 , f 15 , f 18 , f 19 are outliers present in the instantaneous frequency estimate.

[0079] Finally, the iterative calculation is carried out by weighted least squares linear...

Embodiment 2

[0080] Example 2: Initialize the parameters first, set the short-time window length M=128, the short-time window moving step L=64, and the weight correction factor σ 1 =100, the maximum iteration threshold K=100 and the precision control index ε=10 -3 , to calculate the total number of short-time windows The number of initialization window moves i=1, and the number of iterations k=1.

[0081] Then move the time window, use the Rife interpolation algorithm to estimate the instantaneous frequency estimated value of the data sequence in each short time window, and obtain the instantaneous frequency estimated value sequence f i ,i=1,2,...,20;

[0082] Finally, the iterative calculation is carried out by weighted least squares linear fitting method, and the estimated value of the modulation frequency of the chirp signal is estimated The relative error is starting frequency estimate f ^ l = ...

Embodiment 3

[0083] Example 3: Initialize the parameters first, set the short-time window length M=256, the short-time window moving step L=128, and the weight correction factor σ 1 =1000000, the maximum number of iterations threshold K=100000 and the precision control index ε=10 -16 , to calculate the total number of short-time windows The number of initialization window moves i=1, and the number of iterations k=1.

[0084] Then move the time window, use the Rife interpolation algorithm to estimate the instantaneous frequency estimated value of the data sequence in each short time window, and obtain the instantaneous frequency estimated value sequence f i ,i=1,2,...,9;

[0085] Finally, the iterative calculation is carried out by weighted least squares linear fitting method, and the estimated value of the modulation frequency of the chirp signal is estimated The relative error is starting frequency estimate f ^ l ...

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Abstract

The invention discloses a method for estimating the modulation frequency and starting frequency of a linear frequency-modulated signal. The method comprises the following steps of: I, acquiring a data sequence x(n), wherein n=0, 1, 2, ellipsis , N-1; II, initializing parameters; III, calculating the power spectrum Yi(12) of a data sequence xi(m) in an ith short time window; IV, estimating the instant frequency estimated value fi of the data sequence in the short time window by adopting a Rife interpolation algorithm; V, judging whether the data sequences of all short time windows are processed, if not, returning to the step III, otherwise, turning to a step VI; VI, calculating a kth iteration weight; VII, judging whether an iteration weight least square linear fitting stop condition is met, if not, returning to the step VI, otherwise, turning to a step VIII; and VIII, calculating modulation frequency and starting frequency parameters. Due to the adoption of the method, the accuracy ofparameter estimation can be increased on the premise of ensuring rapid estimation without performing complex calculation and parameter search.

Description

technical field [0001] The invention belongs to the field of signal processing, in particular to a method for estimating the modulation frequency and initial frequency of a linear frequency modulation signal. Background technique [0002] The low peak power and large time-width-bandwidth product characteristics of the chirp signal make it have good compressibility, which makes the chirp signal widely used in sonar and radar and other fields. Initial frequency and modulation frequency are two basic parameters that characterize the frequency characteristics of LFM signals, and their estimation has always been an important research content in the field of signal processing. The chirp signal is a typical non-stationary signal, and the simple Fourier transform can only obtain the overall frequency spectrum of the signal, and it is difficult to obtain its local characteristics. Therefore, it is often necessary to use time-frequency analysis methods to estimate the parameters of L...

Claims

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Application Information

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IPC IPC(8): G01S7/28G01S7/523G01S13/32G01S15/32
Inventor 姚帅方世良王晓燕蔡敏时
Owner SOUTHEAST UNIV
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