CN116055262B - Communication signal carrier frequency blind estimation method, system and medium based on synchronous extrusion wavelet transformation - Google Patents
Communication signal carrier frequency blind estimation method, system and medium based on synchronous extrusion wavelet transformation Download PDFInfo
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Abstract
The invention discloses a communication signal carrier frequency blind estimation method, a system and a medium based on synchronous extrusion wavelet transformation, wherein the method comprises the following steps: truncating the input communication signal data into a beat length; performing wavelet transformation on the obtained truncated data s (t) with one beat length to obtain a signal time-frequency diagram; synchronous extrusion operation is carried out on the signal time-frequency diagram so as to refine local characteristics; judging whether the terminal point of the communication signal data is reached, if the terminal point is not reached, accumulating the signal time-frequency diagram after synchronous extrusion operation, and then skipping to intercept the input communication signal data into a beat length; otherwise, aiming at the accumulated signal time-frequency diagram, averaging according to the beat number; searching a frequency point with the maximum intensity in the time-frequency diagram of the averaged signal as a carrier frequency estimated value. The invention has the characteristics of high precision and quick calculation.
Description
Technical Field
The invention relates to the field of communication, in particular to a communication signal carrier frequency blind estimation method, a system and a medium based on synchronous extrusion wavelet transformation.
Background
The communication signal parameter blind estimation technology is to estimate the relevant parameters of the communication signal by using a modern signal processing method under the condition of not having prior information of the intercepted signal so as to be used for signal demodulation of a subsequent demodulator.
The research history of estimating the carrier frequency parameters of the non-cooperative communication signals is as follows:
in 1996, azzouz E E A proposed a frequency centering method of carrier frequency estimation, whose basic principle is to use the centering frequency in the signal spectrum as the estimated value of carrier frequency. The method has the advantages that the principle is simple and easy to realize, but the estimation principle shows that the method is only suitable for signals with symmetrical frequency spectrums, and the frequency spectrums are greatly influenced by noise under the condition of low signal to noise ratio, so that the performance of carrier frequency estimation is greatly reduced.
In 2004, YU Z proposed a carrier frequency estimation algorithm based on an autocorrelation function, and carrier frequency estimation was achieved using phase information of the autocorrelation function. The algorithm does not need to know information such as symbol rate, shaping pulse, modulation mode and the like, and experimental simulation shows that the algorithm is suitable for various modulation signals and has good anti-noise performance. But this algorithm requires that the carrier frequency must be less than 1/4 of the sampling rate and that the estimation accuracy is not high.
In 2008, shi Jianfeng estimates carrier frequencies by detecting the spectral peak positions at non-zero cyclic frequencies. The algorithm does not need prior information such as pseudo code sequences, signal parameters and the like, can realize blind estimation of spread spectrum parameters, performs two one-dimensional searches on non-zero cyclic frequency, reduces the influence of noise and interference to a great extent, is suitable for the condition of low signal-to-noise ratio, and has the algorithm effect only aiming at simulation signals.
In 2016, yang Kaili effectively suppresses noise by using cyclostationary characteristics of signals, realizes carrier frequency estimation of MPSK, and can realize 100% accurate estimation of carrier frequency at about 3dB of signal-to-noise ratio, but the algorithm is only aimed at a single-path Gaussian white noise channel, and whether an actual multipath channel and a fading channel are suitable for further research is needed.
2021, Zhang Changwen used a cyclic spectrum method for estimating carrier frequency and chip width of the signal, and verified by using the simulation signal, and performed an actual measurement test, thereby verifying the applicability of the method.
It can be seen that in recent years, many efforts have been made to study parameter estimation of common communication signals. However, most of the method only performs feasibility analysis and Matlab simulation, does not design corresponding hardware to perform experiments on actual signals and real communication environments, and engineering practicability is still to be researched; and the error of the carrier frequency estimation result is larger and the algorithm precision is not high in the research.
Disclosure of Invention
The invention aims to solve the technical problems: aiming at the problems in the prior art, the communication signal carrier frequency blind estimation method, system and medium based on synchronous extrusion wavelet transformation have the characteristics of high precision and quick calculation.
In order to solve the technical problems, the invention adopts the following technical scheme:
a communication signal carrier frequency blind estimation method based on synchronous extrusion wavelet transformation comprises the following steps:
S1, cutting off input communication signal data into one beat length;
S2, performing wavelet transformation on the obtained truncated data S (t) with one beat length to obtain a signal time-frequency diagram;
s3, synchronous extrusion operation is carried out on the signal time-frequency diagram so as to refine local characteristics;
S4, judging whether the end point of the communication signal data is reached, if the end point is not reached, accumulating the signal time-frequency diagram after synchronous extrusion operation, and then jumping to the step S1; otherwise, jumping to the step S5;
S5, averaging according to the beat number aiming at the accumulated signal time-frequency diagram;
and S6, searching a frequency point with the maximum intensity in the time-frequency diagram of the signal after the averaging as a carrier frequency estimated value.
Further, step S2 includes:
s2.1, performing wavelet transformation on the obtained truncated data S (t) with one beat length to obtain a wavelet transformation coefficient;
and S2.2, drawing the wavelet transformation coefficients into a three-dimensional signal time-frequency diagram, wherein the abscissa of the signal time-frequency diagram is time, and the axis coordinate comprises frequency and amplitude.
Further, the functional expression of the wavelet transformation in step S2.1 is:
In the above formula, W s (a, b) is a wavelet transform coefficient, a and b are transformed scale factors and translation factors, s (t) is input truncated data with one beat length, ψ is a wavelet mother function, x represents conjugate complex number, and t is time; Representing the wavelet mother function after the scaling and translation changes.
Further, in step S3, when performing synchronous extrusion operation on the signal time-frequency diagram, the method includes the steps of determining a section where any frequency w 0 is locatedThe values in all squeeze to w 0, where Δw is the frequency squeeze width.
Further, in step S3, the function expression for performing synchronous extrusion operation on the signal time-frequency diagram is as follows:
In the above expression, T s(w0, b) is the result of the synchronous extrusion operation of the wavelet transform coefficient, W s (a, b) is the wavelet transform coefficient, W 0 is the discrete value, (Δa) i＝ai-ai-1,ai and a i-1 are the values of the scale factors a of the i-th and i-1-th items, respectively, and Δw is the frequency extrusion width.
Further, the step S4 further includes a waiting interval data length d before the step S1 is skipped.
Further, when the communication signal data input in step S1 is communication signal data modulated by 2fsk, and the frequency point with the maximum intensity in the averaged signal time-frequency diagram is searched as the carrier frequency estimation value in step S6, the frequency point with the maximum intensity and the next largest frequency point in the averaged signal time-frequency diagram is searched as the carrier frequency estimation value.
Further, when the frequency point with the maximum intensity and the second largest in the time-frequency diagram of the signal after the average is searched as the carrier frequency estimated value, the synchronous extrusion wavelet transformation result corresponding to each frequency point is extracted, the results are compared, and the frequency corresponding to the point with the maximum intensity and the second largest in the synchronous extrusion wavelet transformation result is the carrier frequency estimated value.
The invention also provides a communication signal carrier frequency blind estimation system based on the synchronous extrusion wavelet transformation, which comprises a microprocessor and a memory which are connected with each other, wherein the microprocessor is programmed or configured to execute any communication signal carrier frequency blind estimation method based on the synchronous extrusion wavelet transformation.
The invention also proposes a computer readable storage medium having stored therein a computer program for programming or configuring by a microprocessor to perform any one of the synchronous extrusion wavelet transform based blind estimation methods of communication signal carrier frequencies.
Compared with the prior art, the invention has the following advantages:
1. and the carrier frequency blind estimation is carried out on the non-cooperative communication signals by introducing the synchronous extrusion wavelet transformation method, so that the accuracy is greatly improved compared with the conventional carrier frequency blind estimation method for the communication signals.
2. In order to meet the actual application scene of synchronous extrusion wavelet transformation in the communication field, the calculation amount of an algorithm is reduced by using a multi-snapshot averaging method, and the calculation speed is greatly improved on the premise of ensuring the accuracy.
Drawings
FIG. 1 is a flow chart of an embodiment of the present invention.
Fig. 2 is a schematic diagram of performing multi-snapshot averaging.
Fig. 3 is a time-frequency diagram of a signal obtained by performing wavelet transform on a beat-length signal in an embodiment of the present invention.
Fig. 4 is a signal time-frequency diagram of the synchronized extrusion wavelet transform result after averaging in the embodiment of the present invention.
Detailed Description
The invention is further described below in connection with the drawings and the specific preferred embodiments, but the scope of protection of the invention is not limited thereby.
The invention researches the problems of inaccurate parameter estimation and unknown engineering practice in the blind estimation research of the carrier frequency of the communication signal, and provides accurate priori knowledge for the subsequent demodulation and decoding of the communication signal.
In the embodiment, lake-sea test data are used as non-cooperative communication signals, in order to accurately estimate carrier frequency blindness of the lake-sea test data, wavelet transformation is considered to be carried out on the non-cooperative communication signals so as to analyze time-frequency characteristics, and the change condition of frequency along with time is obtained through a time-frequency diagram. Because the time-frequency analysis graph result of the wavelet transformation is not accurate, the synchronous extrusion method is applied to the wavelet transformation to refine the time-frequency analysis graph in order to further improve the signal frequency blind estimation result. The time-frequency analysis chart after the synchronous extrusion wavelet transformation has prominent and obvious local characteristics, and can extract and obtain the carrier frequency estimated value with higher accuracy. Meanwhile, in order to overcome the problem that the internal memory is insufficient easily when the actual lake-sea test data are directly subjected to synchronous extrusion wavelet transformation, the algorithm structure is improved by adopting a method of carrying out multi-snapshot averaging on the data, and the required internal memory and calculated amount are effectively reduced while the estimation accuracy is ensured.
Based on the above concept, this embodiment proposes a communication signal carrier frequency blind estimation method based on synchronous extrusion wavelet transform, as shown in fig. 1, including the following steps:
S1, cutting off input communication signal data into one beat length;
S2, performing wavelet transformation on the obtained truncated data S (t) with one beat length to obtain a signal time-frequency diagram;
s3, synchronous extrusion operation is carried out on the signal time-frequency diagram so as to refine local characteristics;
S4, judging whether the end point of the communication signal data is reached, if the end point is not reached, accumulating the signal time-frequency diagram after synchronous extrusion operation, and then jumping to the step S1; otherwise, jumping to the step S5;
S5, averaging according to the beat number aiming at the accumulated signal time-frequency diagram;
and S6, searching a frequency point with the maximum intensity in the time-frequency diagram of the signal after the averaging as a carrier frequency estimated value.
In this embodiment, in order to effectively reduce the required memory and the calculation amount, the steps S1 to S4 are performed iteratively, as shown in fig. 2, the lake-sea test data are intercepted by one beat length L at each time by the interval data length d, the synchronous extrusion wavelet transform is performed on the lake-sea test data, and then the transform results are accumulated, so that the required memory and the calculation amount are significantly reduced compared with the direct synchronous extrusion wavelet transform of the lake-sea test data.
In this embodiment, step S2 specifically includes:
S2.1, performing wavelet transformation on the obtained truncated data S (t) with one beat length to obtain wavelet transformation coefficients, wherein the function expression for performing the wavelet transformation is as follows:
In the above formula, W s (a, b) is a wavelet transform coefficient, a and b are transformed scale factors and translation factors, s (t) is input truncated data with one beat length, ψ is a wavelet mother function, * represents conjugate complex number, and t is time; Representing the wavelet mother function after the scaling and translation changes.
S2.2, the wavelet transformation coefficients are plotted into a three-dimensional signal time-Frequency diagram, the abscissa of the signal time-Frequency diagram is time (time/S), and the axis coordinates comprise Frequency (Frequency/kHZ) and amplitude (Magnitude).
As shown in fig. 3, after wavelet transformation is performed on the data with one beat length L of the lake-sea test data, frequency hopping phenomenon exists in the signal, which accords with FSK signal characteristics, but local time-frequency characteristics are not obvious, and a specific value of frequency at a certain moment cannot be determined, so that the display effect of local time-frequency characteristics of the signal needs to be enhanced by compressing wavelet transformation time-frequency distribution along the direction of a frequency axis by using a synchronous extrusion wavelet transformation technology in step S3.
In step S3 of the present embodiment, when performing synchronous extrusion operation on the signal time-frequency diagram, the method includes the steps ofThe values in all squeeze to w 0, where Δw is the frequency squeeze width, resulting in the squeeze wavelet transform coefficient, T s(w0, b) being:
In the above expression, T s(w0, b) is the result of the synchronous extrusion operation of the wavelet transform coefficient, W s (a, b) is the wavelet transform coefficient, W 0 is the discrete value, and (Δa) i＝ai-ai-1,ai and a i-1 are the values of scale factor a of the i-th and i-1-th terms, respectively. a e R, b e R, is a series of values with calculation rules specified by the designer, Δw is the frequency squeeze width.
The step S4 of the present embodiment further includes a waiting interval data length d before the step S1 is skipped. And (3) repeating the steps S1 to S4, performing synchronous extrusion wavelet transformation on the intercepted data each time, and accumulating the calculation results each time until the last data is reached. Next, in step S5, the number of data interception, that is, the beat number, is calculated, the accumulated results are averaged according to the interception number, the averaged synchronous extrusion wavelet transformation results are drawn into a three-dimensional time-frequency analysis chart, as shown in fig. 4, the time-frequency analysis chart after synchronous compression refines the local characteristics of the signal, the local characteristics of the time-frequency of the signal are obvious, and the carrier frequency of the signal can be obtained by using the time-frequency chart.
In fig. 4, the frequency point with the largest synchronous extrusion wavelet transformation result is the carrier frequency estimation value (some types of communication signals have multiple carrier frequencies, multiple synchronous extrusion wavelet transformation maximum points will appear, and the frequency points corresponding to these maximum points are the carrier frequency estimation values). Because errors exist in the artificial finding of the frequency points in the image, the invention adopts an automatic searching method to determine the frequency points. Taking 2fsk as an example, the specific method of automatic searching is as follows: and extracting a synchronous extrusion wavelet transformation result corresponding to each frequency point, comparing the results, and obtaining the frequency corresponding to the point with the maximum and the next largest synchronous extrusion wavelet transformation result as the carrier frequency estimated value. Therefore, when searching for the frequency point with the greatest intensity in the averaged signal time-frequency diagram as the carrier frequency estimation value in step S6, the frequency point with the greatest intensity and the next greatest intensity in the averaged signal time-frequency diagram is searched for as the carrier frequency estimation value.
The embodiment also provides a communication signal carrier frequency blind estimation system based on synchronous extrusion wavelet transformation, which comprises a microprocessor and a memory which are connected with each other, wherein the microprocessor is programmed or configured to execute the communication signal carrier frequency blind estimation method based on synchronous extrusion wavelet transformation.
The present embodiment also proposes a computer readable storage medium having stored therein a computer program for being programmed or configured by a microprocessor to perform the communication signal carrier frequency blind estimation method based on synchronous extrusion wavelet transform according to the present embodiment.
In summary, the present invention innovatively applies the synchronous wavelet transform to the communication signal parameter blind estimation technique. The invention innovatively adopts a multi-snapshot averaging method to reduce the computer operation memory and the calculated amount required by realizing synchronous extrusion wavelet transformation. It has been verified that: the method can realize that the carrier frequency estimation error is less than 1Hz for the computer simulation 2FSK radio communication signal and the center carrier frequency estimation error is less than 0.25% for the underwater sound OFDM communication signal collected by the lake-sea test.
The foregoing is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. While the invention has been described with reference to preferred embodiments, it is not intended to be limiting. Therefore, any simple modification, equivalent variation and modification of the above embodiments according to the technical substance of the present invention shall fall within the scope of the technical solution of the present invention.
Claims (8)
1. A communication signal carrier frequency blind estimation method based on synchronous extrusion wavelet transformation is characterized by comprising the following steps:
S1, cutting off input communication signal data into one beat length;
S2, performing wavelet transformation on the obtained truncated data S (t) with one beat length to obtain a signal time-frequency diagram;
S3, performing synchronous extrusion operation on the signal time-frequency diagram to refine local characteristics, wherein the synchronous extrusion operation on the signal time-frequency diagram comprises the steps of The internal values are extruded to the position w 0, wherein Deltaw is the frequency extrusion width, and the function expression for synchronously extruding the signal time-frequency diagram is as follows:
In the above formula, T s(w0, b) is the synchronous extrusion operation result of the wavelet transform coefficient, W s (a, b) is the wavelet transform coefficient, W 0 is the discrete value, (Δa) i＝ai-ai-1,ai and a i-1 are the values of scale factors a of the i-th and i-1-th items respectively, and Δw is the frequency extrusion width;
S4, judging whether the end point of the communication signal data is reached, if the end point is not reached, accumulating the signal time-frequency diagram after synchronous extrusion operation, and then jumping to the step S1; otherwise, jumping to the step S5;
S5, averaging according to the beat number aiming at the accumulated signal time-frequency diagram;
and S6, searching a frequency point with the maximum intensity in the time-frequency diagram of the signal after the averaging as a carrier frequency estimated value.
2. The method for blind estimation of carrier frequencies of communication signals based on synchronous extrusion wavelet transform according to claim 1, wherein step S2 comprises:
s2.1, performing wavelet transformation on the obtained truncated data S (t) with one beat length to obtain a wavelet transformation coefficient;
and S2.2, drawing the wavelet transformation coefficients into a three-dimensional signal time-frequency diagram, wherein the abscissa of the signal time-frequency diagram is time, and the axis coordinate comprises frequency and amplitude.
3. The blind estimation method of carrier frequency of communication signal based on synchronous extrusion wavelet transform according to claim 2, wherein the functional expression of wavelet transform in step S2.1 is:
In the above formula, W s (a, b) is a wavelet transform coefficient, a and b are transformed scale factors and translation factors, s (t) is input truncated data with one beat length, ψ is a wavelet mother function, x represents conjugate complex number, and t is time; Representing the wavelet mother function after the scaling and translation changes.
4. The method for blind estimation of carrier frequency of a communication signal based on synchronous extrusion wavelet transform according to claim 1, wherein the step S4 further comprises waiting for an interval data length d before the step S1 is skipped.
5. The blind estimation method of carrier frequency of communication signal based on synchronous extrusion wavelet transform according to claim 1, wherein the communication signal data inputted in step S1 is communication signal data modulated by 2fsk, and when searching the frequency point with the largest intensity in the averaged signal time-frequency diagram as the carrier frequency estimation value in step S6, the method comprises searching the frequency point with the largest intensity and the next largest frequency point in the averaged signal time-frequency diagram as the carrier frequency estimation value.
6. The method for blind estimation of carrier frequency of communication signal based on synchronous extrusion wavelet transform according to claim 5, wherein when searching the frequency point with maximum intensity and second largest in the time-frequency diagram of the averaged signal as the carrier frequency estimation value, extracting the synchronous extrusion wavelet transform result corresponding to each frequency point, comparing the results, and the frequency corresponding to the point with maximum intensity and second largest in the synchronous extrusion wavelet transform result is the carrier frequency estimation value.
7. A communication signal carrier frequency blind estimation system based on synchronous extrusion wavelet transform, comprising a microprocessor and a memory connected to each other, characterized in that the microprocessor is programmed or configured to perform the communication signal carrier frequency blind estimation method based on synchronous extrusion wavelet transform according to any one of claims 1-6.
8. A computer readable storage medium having a computer program stored therein, wherein the computer program is for being programmed or configured by a microprocessor to perform the synchronous extrusion wavelet transform based communication signal carrier frequency blind estimation method of any one of claims 1-6.
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