CN107561498B - Linear frequency modulation signal rapid identification method based on multi-path preset convolver - Google Patents
Linear frequency modulation signal rapid identification method based on multi-path preset convolver Download PDFInfo
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Abstract
The method is applied to the field of radar signal intra-pulse analysis and identification. The invention quickly identifies the linear frequency modulation signal by a method of presetting a convolver in a plurality of paths. Firstly, screening pulses in a frequency and pulse width parameter range which accord with prior information, secondly, generating a conjugate signal by utilizing frequency modulation slope, pulse width and frequency information to serve as a preset convolver, calculating the ratio of a main lobe energy value to total energy after the autocorrelation of the signal of the preset convolver, then convolving the conjugate signal with a signal to be identified, detecting the peak position of the conjugate signal, calculating the ratio of the main lobe energy to the total energy and a first-level confidence coefficient parameter, performing autocorrelation on the signal to be identified which exceeds a first-level confidence coefficient parameter threshold, and calculating the ratio of the main lobe energy to the total energy and a second-level confidence coefficient parameter. And finally, calculating the final signal recognition confidence coefficient according to the previous two confidence coefficient parameters. The algorithm has the advantages of small calculated amount, high recognition speed, simple flow, convenient engineering realization and low requirement on the signal to noise ratio.
Description
Technical Field
The method is applied to the field of radar signal intra-pulse analysis and identification.
Background
The radar signal intra-pulse modulation characteristics are important components of radar parameters, and common radar intra-pulse modulation forms include various modulation forms such as conventional, two-phase coding, four-phase coding, linear frequency modulation and frequency coding. The chirp signal adopts a pulse compression technology, can obtain high-distance resolution, has excellent Doppler mismatch resistance compared with a phase coding signal, and is widely applied to radar signals. The linear frequency modulation pulse signal parameter estimation method mainly comprises a maximum likelihood estimation method, a de-linear frequency modulation method, a discrete polynomial phase parameter estimation method, a discrete linear Fourier transform method, various time frequency distribution analysis methods and the like. Maximum Likelihood Estimation (MLE) is a statistical method, which uses a probability model under limited observation sample conditions, without knowing prior knowledge of parameters, and uses a Likelihood function as a parameter estimator. The method needs integration and search, and the calculation amount is large. The solution chirp technology is to convert a two-dimensional search problem of the MLE into two one-dimensional problems for processing, and estimate two parameters of the initial frequency and the chirp rate of a chirp signal, so that the calculation amount is reduced compared with the MLE, but the estimation accuracy is not enough, the resolution is low, and the anti-noise performance is not good. Discrete Polynomial Phase Transform (DPT) is used to analyze Polynomial Phase signals, including LFM signals. When the LFM signal parameters are estimated, the calculation amount is small, and the estimation precision is higher under the condition of high signal-to-noise ratio. However, the DPT algorithm has poor estimation performance under low signal-to-noise ratio, and needs to be further researched. The time-frequency analysis method is to describe the relation of the frequency of the signal changing along with the time by using the joint function of the time and the frequency of the signal so as to analyze the characteristics of the signal. The linear frequency modulation pulse signal is in a dorsal fin shape on a time-frequency plane and has better energy aggregation, so a series of methods for extracting the initial frequency and the frequency modulation slope parameter of the LFM in the time-frequency image by utilizing image processing appear. Such as Wigner-Hough Transform (WHT), which combines Hough Transform with Wigner-Ville Distribution (WVD), Radon-Ambiguity Transform (RAT) method, Radon-STFT Transform, Radon-wavelet Transform, etc., but the time-frequency analysis method has a large amount of calculation and poor performance when the signal-to-noise ratio is low.
The existing linear frequency modulation signal analysis method adopts a posterior identification method of estimating signal frequency and frequency modulation slope and comparing the estimated signal frequency and the frequency modulation slope with the existing parameters in a database, so the method has the defects of large calculated amount, high signal-to-noise ratio requirement and poor real-time property. The electromagnetic environment of modern battlefield is complex, the real-time requirement of electronic countermeasure on electronic reconnaissance is higher and higher, the scheme provides a linear frequency modulation signal rapid identification method based on a multipath preset convolver, and the method has the advantages of small calculated amount, high identification speed, simple flow, convenient engineering realization and low signal-to-noise ratio requirement.
Disclosure of Invention
The invention aims to provide a method for quickly identifying a linear frequency modulation signal based on a multipath preset convolver.
The technical solution for realizing the purpose of the invention is as follows: and constructing a method for convolving the signal to be detected by a preset convolver by utilizing the known frequency, pulse width and frequency modulation slope information to identify the signal. The specific method comprises the following steps: 1. and screening the pulses in the frequency and pulse width parameter ranges which accord with the prior information. 2. And generating a conjugate signal by using the frequency modulation slope, the pulse width and the frequency information as a preset convolver, and calculating the ratio of the energy value of the main lobe to the total energy after the autocorrelation of the signal of the preset convolver. 3. And (3) convolving the preset convolver signal with the signal to be identified, detecting the peak position of the signal, and calculating the ratio of the energy of the main lobe to the total energy and the first-stage confidence coefficient parameter. 4. And performing autocorrelation on the signal to be identified which exceeds the threshold of the first-level confidence coefficient parameter, and calculating the ratio of main lobe energy to total energy and the second-level confidence coefficient parameter. 5. And calculating the final signal recognition confidence coefficient according to the confidence coefficient parameters of the previous two stages.
The invention utilizes frequency, pulse width and FM slope to construct a preset convolver, can identify the linear FM signal through convolution operation and other simple operations, and has the advantages of small calculated amount, high identification speed, simple flow and low requirement on the signal to noise ratio compared with other algorithms.
Drawings
Fig. 1 is a flow chart of a chirp signal fast identification method based on a multipath preset convolver.
Detailed Description
Firstly, a main lobe energy ratio calculation method of a correlation convolution result of a linear frequency modulation signal is given:
in the formula, the signal bandwidth is B, the pulse width is T, and the peak position is TdThe width of the main lobe is 1/B, fm (t) is the correlation convolution result, the numerator part on the right side of the equation is the main lobe energy, the denominator part is the total energy, and P is the ratio of the main lobe energy to the total energy.
The method comprises the following specific implementation steps:
a. and pre-screening the signal to be identified according to the frequency and pulse width information of the signal pulse, and screening out the signal with the frequency and pulse width close to those of the multi-path preset convolver.
b. Generating a conjugate signal as a constructed preset convolver signal according to known frequency modulation slope, frequency and pulse width parameters, and calculating the ratio P of the autocorrelation main lobe energy of the preset convolver signal to the total energyST；
c. Carrying out mutual convolution on the preset convolver signal and the pulse to be identified, and calculating the ratio P of the main lobe energy to the total energy of the mutual convolution resultXYComputing a first level from the convolution resultConfidence coefficient parameter lambda1And carrying out threshold judgment according to the first-level confidence coefficient parameter, wherein the first-level confidence coefficient parameter is calculated by the following formula:
d. and if the threshold is not exceeded, the recognition is considered to be failed, and the recognition is finished. Carrying out autocorrelation on the signal to be identified with the first-level confidence coefficient parameter threshold, and calculating the ratio P of the energy of the main lobe of the autocorrelation result to the total energyXXAnd calculating the confidence coefficient lambda of the second-stage signal identification2Calculated by the following formula:
e. and calculating a final confidence coefficient parameter lambda according to the first-level confidence coefficient parameter and the second-level confidence coefficient parameter in a weighting manner, and outputting a signal recognition confidence coefficient result, wherein the calculation manner is as follows:
λ＝aλ1λ2+b (4)
in the above formula, a and b are confidence coefficient weighting coefficients, wherein a is a ratio correction coefficient, and b is an offset correction coefficient, and dynamic adjustment is performed according to the actual signal-to-noise ratio of the electromagnetic environment.
Claims (2)
1. A method for quickly identifying linear frequency modulation signals based on a multipath preset convolver is characterized by comprising the following specific steps:
a. pre-screening the signal to be identified according to the frequency and pulse width information of the signal pulse, and screening out the signal with the frequency and pulse width close to those of the multi-path preset convolver;
b. generating a conjugate signal as a constructed preset convolver signal according to known frequency modulation slope, frequency and pulse width parameters, and calculating the ratio P of the autocorrelation main lobe energy of the preset convolver signal to the total energyST；
c. Carrying out mutual convolution on the preset convolver signal and the pulse to be identified, and calculating the ratio P of the main lobe energy to the total energy of the mutual convolution resultXYCalculating a first level confidence coefficient parameter lambda according to the convolution result1And performing threshold judgment according to the first-level confidence coefficient parameter;
d. if the identification fails, the identification is considered to be failed, and the identification is finished; carrying out autocorrelation on the signal to be identified with the first-level confidence coefficient parameter threshold, and calculating the ratio P of the energy of the main lobe of the autocorrelation result to the total energyXXAnd calculating the confidence coefficient lambda of the second-stage signal identification2；
e. And calculating a final confidence coefficient parameter lambda according to the first-level confidence coefficient parameter and the second-level confidence coefficient parameter in a weighting manner, and outputting a signal identification confidence coefficient result, wherein lambda is calculated by the following formula:
λ＝aλ1λ2+b (3)
in the formula, PXYRatio of main lobe energy to total energy, P, of cross-correlation resultSTFor presetting the ratio of the energy of the autocorrelation main lobe of the convolver signal to the total energy, PXXAnd dynamically adjusting the ratio of the main lobe energy to the total energy of the signal to be identified autocorrelation result, wherein a is a ratio correction coefficient, and b is a bias correction coefficient according to the actual electromagnetic environment signal-to-noise ratio.
2. The method for rapidly identifying the chirp signal based on the multiple preset convolvers of claim 1, wherein the ratio of the energy of the main lobe to the total energy is calculated by the following formula:
in the formula, the signal bandwidth is B, the pulse width is T, and the peak position is TdThe width of the main lobe is 1/B, fm (t) is the convolution productAs a result or an autocorrelation result, the numerator part on the right side of the equation is the main lobe energy, the denominator part is the total energy, and P is the ratio of the main lobe energy to the total energy.
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