CN115166650A - Radar signal identification and parameter estimation method and system - Google Patents
Radar signal identification and parameter estimation method and system Download PDFInfo
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- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
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- G01S7/28—Details of pulse systems
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- G01S7/292—Extracting wanted echo-signals
- G01S7/2923—Extracting wanted echo-signals based on data belonging to a number of consecutive radar periods
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Abstract
The application provides a radar signal identification and parameter estimation method and system, and belongs to the field of radar signal processing research. The method comprises the following steps: the traditional reverse order correlation accumulation method is improved, an intra-pulse discrete frequency coding modulation identification method based on time-frequency ridge line characteristics and a characteristic correlation analysis technology is designed, and the problem of accurate positioning of signal frequency mutation positions under the condition of short time slot and high code elements is solved by introducing wavelet transformation with automatically adjustable scale coefficients. According to the technical scheme, an effective and high-practicability analysis method is provided for detection, modulation recognition and parameter estimation of the frequency coding radar signal.
Description
Technical Field
The application belongs to the field of radar signal processing research, and particularly relates to a method and a system for radar signal identification and parameter estimation.
Background
With the complexity of modern electromagnetic environment, the radar needs to have stronger anti-interception and anti-identification capabilities, so that the waveform with more complex intra-pulse modulation mode is more and more emphasized. The discrete frequency coding signal is an intra-pulse modulation mode with high dimensional complexity, the signal is characterized in that discrete frequency coding is provided in a pulse, and a code element sequence is similar to a pseudo-random shape. Compared with a linear frequency modulation signal, the code has a more ideal 'picture pin-shaped' fuzzy function and has excellent resolution capability on a moving target during observation. The radar working waveform modulated by the intra-pulse discrete frequency coding is adopted, a group of discrete frequency coding sequence sets which are orthogonal coding waveform sequence sets with good autocorrelation cross correlation are formed, and researches show that the coded radar signals are used for a gateway radar monitoring system, so that self-interference and detection confusion in a mesh radar system can be effectively avoided. By utilizing the characteristics that any waveform in the intra-pulse frequency coding waveform set has positive correlation similar to an impact function and no cross correlation exists between any two waveforms, the mesh radar system can switch among single base, double base and multiple bases according to real-time requirements, so that the target searching capability, tracking and identifying capability are stronger than those of the traditional radar system.
At present, discrete frequency coding signals appear in working waveforms of a space radar system, accurate modulation recognition and frequency coding parameter measurement are carried out on the space signals received by an earth signal station, and the method is of great importance for analyzing and measuring working modes and technical performance of space radar loads and mastering the capability threat level of the space radar.
Currently, relatively much research is being conducted on the design of discrete frequency encoded signal waveforms, and relatively little research is being conducted on extracting discrete frequency encoded signal parameters. It is known that the research on the extraction of discrete frequency coded signal parameters by the team related to the university of electronic technology of west ampere provides a better solution. The main difficulty of discrete frequency coded signal parameter extraction lies in the following 2 aspects: firstly, the correlation accumulation effect of the signals is weaker than that of the traditional Linear Frequency Modulation (LFM) signals, and the signal detection rate under low signal-to-noise ratio is influenced; secondly, in a very short pulse time width, a higher number of code elements are designed, and a time slot chip of each code element is very short, so that the situation that time-frequency ridge transition points are wrongly identified often occurs when modulation identification based on time-frequency ridge characteristics and discrete frequency coding signal parameter measurement are carried out, and the identification accuracy and the parameter estimation precision of the frequency coding signals are influenced. This is especially true when the received signal has a low signal-to-noise ratio.
The main problems of the existing discrete frequency coding signal parameter extraction are that the signal detection rate under low signal-to-noise ratio is low due to the relevant accumulation effect of the signals, and when the parameter extraction is carried out based on the time-frequency ridge line characteristics, the jump characteristic extraction of the time-frequency base line is easy to generate errors under the condition that the time slot of a chip is small, so that the modulation identification and the estimation of the chip frequency and the coding parameter are wrong.
In view of the foregoing problems, the present application provides a method and system for radar signal identification and parameter estimation.
Disclosure of Invention
In order to solve the deficiencies of the prior art, the present application provides a method and a system for radar signal identification and parameter estimation to solve the above technical problems.
The invention discloses a radar signal identification and parameter estimation method in a first aspect, which comprises the following steps:
s1, improving a traditional reverse order correlation accumulation recurrence formula by a method of endowing different weights to each accumulated sampling point, and finishing estimation of a pulse rising edge and a pulse falling edge of a radar signal so as to realize pulse detection;
s2, carrying out Wigner-Ville conversion on the radar signal subjected to pulse detection to obtain a two-dimensional function of amplitude with respect to time and frequency, and further obtaining a time-frequency diagram of the radar signal;
s3, extracting time-frequency ridge lines according to the time-frequency graph;
s4, calculating the frequency variation trend of the time-frequency ridge in the pulse by using the time-frequency ridge, and identifying the frequency variation trend as intra-pulse frequency coding modulation when the frequency variation trend is random;
s5, performing wavelet transformation on the time-frequency ridge to obtain a wavelet coefficient, calculating the maximum value of the wavelet coefficient corresponding to each moment, setting a threshold on the maximum value of the wavelet coefficient and detecting a peak value, wherein the moment corresponding to the peak value of the wavelet coefficient is an estimated value of a jump moment, and further obtaining the jump moment and a jump period;
and S6, positioning to obtain the position of each code element in each pulse through the hopping moment and the hopping period, and performing fast Fourier transform on each code element in each pulse respectively to obtain the frequency hopping frequency estimation value of each code element, so that the hopping period, the hopping moment and the frequency hopping frequency estimation value of the frequency hopping signal in each pulse are obtained, and accurate estimation of the frequency coding parameters is realized.
According to the method of the first aspect of the present invention, in step S1, the method for completing the estimation of the rising edge and the falling edge of the pulse of the radar signal by improving the conventional reverse order correlation accumulation recurrence formula through the method of assigning different weights to the sampling points accumulated each time includes:
carrying out initial measurement on data of the radar signals after coherent accumulation to determine a preset detection range of the radar signals;
and performing reverse order correlation accumulation on the delay conjugate multiplication output signals in the preset detection range by using an improved correlation accumulation recursion formula, so that data points with larger accumulated values have higher accumulated weight values, thereby detecting inflection points and finishing the estimation of pulse rising edges and pulse falling edges of the radar signals.
According to the method of the first aspect of the present invention, in the step S1, the improved correlation accumulation recurrence formula is:
wherein y (m) is the conjugate multiplication output signal of the tiny delay mT, n represents the n time, r w (n) is the initial accumulated value at time n, y (n + 1) is the conjugate multiplication output signal at time n +1, r w (n + 1) is the accumulated value at time n +1, and T is the sampling interval.
According to the method of the first aspect of the present invention, in step S3, the method for extracting time-frequency ridges according to the time-frequency diagram includes:
and extracting the frequency corresponding to the maximum amplitude of the PWVD at each moment, namely extracting the maximum module value on the frequency axis of each moment or the frequency value corresponding to the maximum module value along the time axis of the time-frequency graph to form a time-frequency ridge line.
According to the method of the first aspect of the present invention, in step S4, before the calculating the frequency variation trend of the time-frequency ridge in the pulse by using the time-frequency ridge, the method further includes:
and performing linear fitting on the time-frequency ridge line in the pulse, and then calculating correlation factors of the linear fitting result and the time-frequency ridge line in the pulse, thereby eliminating the possibility that the time-frequency ridge line in the pulse is linearly changed.
According to the method of the first aspect of the present invention, in step S4, the method for calculating the frequency variation trend of the time-frequency ridge in the pulse by using the time-frequency ridge includes:
and calculating the jumping times, the upper jumping times and the lower jumping times of the time-frequency ridge line, and calculating the frequency change trend of the time-frequency ridge line in the pulse by utilizing the jumping times, the upper jumping times and the lower jumping times.
According to the method of the first aspect of the present invention, in the step S5, the method further comprises:
when the signal noise of the radar signal is low, a hopping period is obtained by conjecturing according to the obtained hopping time, and then the hopping time which cannot be positioned is obtained by conjecturing according to the hopping period, which specifically comprises the following steps: firstly, calculating a first-order difference of a hopping moment, and after eliminating a minimum value of the first-order difference, taking the remaining first-order difference result as an integral multiple of a hopping period; setting the range with the most occurrence of the first-order difference result as a first range of a hopping period, screening out the first-order difference values in the first range and calculating the mean value of the first-order difference values, thereby obtaining a first estimation value of the hopping period; then, counting a range with the maximum occurrence probability of the hopping period according to a distribution histogram of the first estimation value of the hopping period, defining the range as a second range, and averaging the hopping period in the second range to obtain a hopping period estimation value; and finally, estimating to obtain estimated values of all the jumping moments according to the known jumping moment and the jumping period estimated value.
The second aspect of the invention discloses a radar signal identification and parameter estimation system, which comprises:
the first processing module is configured to improve a traditional reverse order correlation accumulation recurrence formula by a method of endowing different weights to sampling points accumulated each time, complete estimation of pulse rising edges and pulse falling edges of radar signals, and accordingly realize pulse detection;
the second processing module is configured to obtain a two-dimensional function of amplitude with respect to time and frequency after the pulse-detected radar signal is subjected to Wigner-Ville conversion, and further obtain a time-frequency diagram of the radar signal;
the third processing module is configured to extract time-frequency ridge lines according to the time-frequency graph;
the fourth processing module is configured to calculate the frequency variation trend of the time-frequency ridge line in the pulse by using the time-frequency ridge line, and when the frequency variation trend is random, the frequency variation trend is identified as intra-pulse frequency coding modulation;
the fifth processing module is configured to perform wavelet transformation on the time-frequency ridge line to obtain a wavelet coefficient, calculate a maximum value of the wavelet coefficient corresponding to each moment, set a threshold for the maximum value of the wavelet coefficient and detect a peak value, wherein the moment corresponding to the peak value of the wavelet coefficient is an estimated value of a jump moment, and further obtain the jump moment and a jump period;
and the sixth processing module is configured to obtain the position of each code element in each pulse through the hopping time and the hopping period by positioning, and perform fast fourier transform on each code element in each pulse respectively to obtain a frequency hopping frequency estimation value of each code element, so as to obtain the hopping period, the hopping time and the frequency hopping frequency estimation value of the frequency hopping signal in each pulse, thereby realizing accurate estimation of the frequency coding parameters.
According to the system of the second aspect of the present invention, the first processing module is configured to improve the conventional reverse order correlation accumulation recurrence formula by assigning different weights to each accumulated sampling point, and the estimation of the rising edge and the falling edge of the pulse of the radar signal comprises:
carrying out initial measurement on data of the radar signals after coherent accumulation to determine a preset detection range of the radar signals;
and performing reverse order correlation accumulation on the delay conjugate multiplication output signals in the preset detection range by using an improved correlation accumulation recursion formula, so that data points with larger accumulated values have higher accumulated weight values, thereby detecting inflection points and finishing the estimation of pulse rising edges and pulse falling edges of the radar signals.
According to the system of the second aspect of the present invention, the first processing module is configured to obtain the improved correlation accumulation recurrence formula as:
wherein y (m) is the conjugate multiplication output signal of the tiny delay mT, n represents the n time, r w (n) is the initial accumulated value at time n, y (n + 1) is the conjugate multiplication output signal at time n +1, r w (n + 1) is the accumulated value at time n +1, and T is the sampling interval.
According to the system of the second aspect of the present invention, the third processing module is configured to extract the time-frequency ridge line according to the time-frequency diagram, including:
and extracting the frequency corresponding to the maximum amplitude of the PWVD at each moment, namely extracting the maximum module value on the frequency axis of each moment or the frequency value corresponding to the maximum module value along the time axis of the time-frequency graph to form a time-frequency ridge line.
The system according to the second aspect of the invention, the fourth processing module, configured to,
before the calculating the frequency variation trend of the time-frequency ridge line in the pulse by using the time-frequency ridge line, the method further comprises the following steps:
and performing linear fitting on the time-frequency ridge in the pulse, and then calculating correlation factors of linear fitting results and the time-frequency ridge in the pulse, thereby eliminating the possibility that the time-frequency ridge in the pulse is linearly changed.
The system according to the second aspect of the invention, the fourth processing module, configured to,
the calculating the frequency variation trend of the time-frequency ridge line in the pulse by using the time-frequency ridge line comprises the following steps:
and calculating the jumping times, the upper jumping times and the lower jumping times of the time-frequency ridge line, and calculating the frequency change trend of the time-frequency ridge line in the pulse by utilizing the jumping times, the upper jumping times and the lower jumping times.
According to the system of the second aspect of the present invention, the fifth processing module is configured to, when the signal-to-noise ratio of the radar signal is low, infer a hopping period according to the obtained hopping time, and infer a hopping time that cannot be located according to the hopping period, and specifically include: firstly, calculating a first-order difference of a hopping moment, and after eliminating a minimum value of the first-order difference, taking the remaining first-order difference result as an integral multiple of a hopping period; setting the range with the most occurrence of the first-order difference result as a first range of a hopping period, screening out the first-order difference values in the first range and calculating the mean value of the first-order difference values, thereby obtaining a first estimation value of the hopping period; then, counting a range with the maximum occurrence probability of the hopping period according to a distribution histogram of the first estimation value of the hopping period, defining the range as a second range, and averaging the hopping periods in the second range to obtain an estimation value of the hopping period; and finally, estimating to obtain estimated values of all the jumping moments according to the known jumping moment and the jumping period estimated value.
A third aspect of the invention discloses an electronic device. The electronic device comprises a memory and a processor, the memory stores a computer program, and the processor implements the steps of a radar signal identification and parameter estimation method in any one of the first aspect of the disclosure when executing the computer program.
A fourth aspect of the invention discloses a computer-readable storage medium. The computer readable storage medium has stored thereon a computer program which, when executed by a processor, implements the steps in a method of radar signal identification and parameter estimation according to any one of the first aspect of the present disclosure.
The technical effect that this application will reach is realized through following scheme: the detection rate of the intra-pulse frequency coding modulation type radar signals can be greatly improved, a practical and effective technical method with high robustness is provided for modulation identification of the intra-pulse frequency coding modulation type radar signals, and high-precision estimation of intra-pulse discrete frequency coding parameters under narrow-pulse high-code elements is achieved.
Drawings
In order to more clearly illustrate the embodiments or prior art solutions of the present application, the drawings needed for describing the embodiments or prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments described in the present application, and that other drawings can be obtained by those skilled in the art without inventive exercise.
FIG. 1 is a flow chart of a method for radar signal identification and parameter estimation according to an embodiment of the present disclosure;
FIG. 2 is a diagram of the time and time domain of an intra-pulse frequency-coded modulation signal according to an embodiment of the present invention;
FIG. 3 illustrates an intra-pulse frequency-coded modulation signal envelope detection at low SNR according to an embodiment of the present invention;
FIG. 4 is a time-frequency diagram of a pulse signal calculated by the SPWVD algorithm according to an embodiment of the present invention;
FIG. 5 is a diagram illustrating extraction of time-frequency ridges of pulse signals according to an embodiment of the present invention;
FIG. 6 is a scale used for continuous wavelet transformation according to an embodiment of the present invention;
FIG. 7 is a diagram of wavelet transform modulus maxima of an impulse signal according to an embodiment of the present invention;
FIG. 8 is a block diagram of a radar signal identification and parameter estimation system according to an embodiment of the present invention;
fig. 9 is a block diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the technical solutions of the present application will be described in detail and completely with reference to the following embodiments and accompanying drawings. It should be apparent that the described embodiments are only a few embodiments of the present application, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
Various non-limiting embodiments of the present application are described in detail below with reference to the accompanying drawings.
In the discrete frequency coding signal, the frequency coding of the signal can be changed randomly, so that the signal reconnaissance equipment has certain analysis difficulty, can resist signal interference of various forms, and is a main waveform form of radar equipment in a future complex electromagnetic environment. The discrete frequency code number may be expressed as:
In the formula (I), the compound is shown in the specification,Mis the number of frequency chips within a pulse,T sp for the width of each frequency chip,f c for transmitting the carrier frequency of the signal, the frequency-coding sequence of the transmitted pulses is f l =a•Δf，ΔfIs the frequency interval of a frequency chip, andf=1/T sp ，a={a 1 ,…,a M is a frequency coding coefficient and is represented by the integers 0,1, …,M-1} random rearrangement.
The invention discloses a radar signal identification and parameter estimation method in a first aspect. Fig. 1 is a flowchart of a radar signal identification and parameter estimation method according to an embodiment of the present invention, as shown in fig. 1, the method includes:
s1, improving a traditional reverse order correlation accumulation recurrence formula by a method of endowing different weights to each accumulated sampling point, and finishing estimation of a pulse rising edge and a pulse falling edge of a radar signal so as to realize pulse detection;
s2, after the radar signal subjected to pulse detection is subjected to Wigner-Ville transformation, a two-dimensional function of amplitude with respect to time and frequency can be obtained, and a time-frequency graph of the radar signal is further obtained;
s3, extracting time-frequency ridge lines according to the time-frequency graph;
s4, calculating the frequency variation trend of the time-frequency ridge in the pulse by using the time-frequency ridge, and identifying the frequency variation trend as intra-pulse frequency coding modulation when the frequency variation trend is random;
s5, performing wavelet transformation on the time-frequency ridge to obtain a wavelet coefficient, calculating the maximum value of the wavelet coefficient corresponding to each moment, setting a threshold on the maximum value of the wavelet coefficient and detecting a peak value, wherein the moment corresponding to the peak value of the wavelet coefficient is an estimated value of a jump moment, and further obtaining the jump moment and a jump period;
and S6, positioning to obtain the position of each code element in each pulse through the hopping moment and the hopping period, and performing fast Fourier transform on each code element in each pulse respectively to obtain the frequency hopping frequency estimation value of each code element, so that the hopping period, the hopping moment and the frequency hopping frequency estimation value of the frequency hopping signal in each pulse are obtained, and accurate estimation of the frequency coding parameters is realized.
In step S1, the traditional reverse order correlation accumulation recurrence formula is improved by assigning different weights to each accumulated sampling point, and the estimation of the rising edge and the falling edge of the pulse of the radar signal is completed, thereby realizing pulse detection.
In some embodiments, in step S1, the method for completing the estimation of the rising edge and the falling edge of the pulse of the radar signal by improving the conventional reverse order correlation accumulation recurrence formula through a method of assigning different weights to the sampling points accumulated each time includes:
carrying out initial measurement on data of the radar signals after coherent accumulation to determine a preset detection range of the radar signals;
and performing reverse order correlation accumulation on the delay conjugate multiplication output signals in the preset detection range by applying an improved correlation accumulation recurrence formula, so that data points with larger accumulated values have higher accumulated weighted values, thereby performing inflection point detection and finishing the estimation of pulse rising edges and pulse falling edges of radar signals.
The improved correlation accumulation recurrence formula is as follows:
wherein y (m) isThe conjugate multiplication of the small delay mT outputs a signal, n denotes the time n, r w (n) is the initial accumulated value at time n, y (n + 1) is the conjugate multiplication output signal at time n + 1, r w (n + 1) is the accumulated value at time n + 1, and T is the sampling interval.
Specifically, firstly, the data of the acquired radar signal is subjected to conjugate multiplication based on time delay, the radar signal is multiplied by the micro time delay of the complex conjugate of the radar signal, and the influence of intracochet modulation is removed: for received noise-containing signalx(t)=s(t)+w(t) Sampling is performed with a sampling time interval T, and the sampled complex received signal can be represented as:
WhereinA(nT) In order to be the amplitude of the signal,f c is the carrier frequency of the intermediate frequency signal,φ(nT) The information is modulated for the wideband signal and,w(nT) Is zero mean gaussian noise. With a small delay in receptionmTAnd conjugate multiply by having
The signal part can be expressed as
Carrying out initial measurement on data of the radar signals after coherent accumulation to determine a preset detection range of the radar signals
(ii) a In the conventional reverse order correlation accumulation method, when performing coherent accumulation, in order to find the inflection point of the falling edge of a signal, the result of coherent accumulation needs to be combined with a straight linec(t)=k c , 
Make a difference in thatk c Is the slope of the line. Namely, it isk c Has a certain influence on the estimation result, andk c value of (a) is directly received by signal amplitudeA(nT) Because accurate estimation of the signal amplitude is generally difficult to guarantee in the case of low signal-to-noise ratio, the pulse detection accuracy of the conventional reverse order correlation accumulation method is directly affected.
By the method of endowing different weights to each accumulated sampling point, the method avoids the problem of adding different weights to the accumulated sampling pointsk c Making an estimate of demand and comparing the analysis with the utilization by experimentk c Compared with the traditional reverse order correlation accumulation method for pulse estimation, the processing performance is the same or even better.
Applying an improved correlation accumulation recursion formula to perform reverse order correlation accumulation (CRA) on the delayed conjugate multiplication output signal y (n) in the preset detection range,
equation 5 uses the following recursive expression:
equation 6, i.e. the difference between two adjacent sampling points is,
formula 7, effectively avoid the pairk c The estimated demand of (2). Wherein y (m) is the conjugate multiplication output signal of the tiny delay mT, n represents the n time, r w (n) is the initial accumulated value at time n, y (n + 1) is the conjugate multiplication output signal at time n + 1, r w (n + 1) is the accumulated value at time n + 1, and T is the sampling interval. By adopting the coherent accumulation method, points with larger n values have higher accumulated weight values, so that inflection point detection is facilitated, and the problem that the conventional CRA method needs to calculate is avoided
To do so
The problem of more signal to noise ratio. The discrete frequency coded signal with SNR = -5dB is processed by the above method as shown in fig. 2, and the falling edge result of the signal is detected as shown in fig. 3. Therefore, the algorithm has a good detection effect on the radar signals with low signal to noise ratio.
In step S2, as shown in fig. 4, after the pulse-detected radar signal is subjected to Wigner-Ville transform, a two-dimensional function of amplitude with respect to time and frequency is obtained, and a time-frequency diagram of the radar signal is further obtained.
Specifically, a PWVD (Psedo-Wigner-Ville Distribution) method in Cohen time frequency analysis is adopted for time frequency analysis, the Wigner-Ville Distribution is the most important Cohen time frequency Distribution, a signal can obtain a two-dimensional function of amplitude related to time and frequency after Wigner-Ville transformation, the amplitude value is projected to a time frequency plane, then a time frequency graph of the signal can be analyzed, namely, the signal time frequency graph is subjected to multi-scale analysis, when the signal has mutation, a coefficient after wavelet transformation has a modulus maximum value, so that the time point of the mutation occurrence can be determined through detection of the modulus maximum value point, and parameters such as the frequency of a stepped frequency signal, the number of pulse stepping points, the width of sub-pulses and the like can be estimated.
The PWVD algorithm used in the algorithm, namely the pseudo Wigner _ Ville distribution, namely windowing is carried out on the WVD distribution, the inherent cross interference item influence of the WVD algorithm is inhibited, and the algorithm is defined as follows:
In the above formula, t is time, τ is time delay, f is frequency, z (t) is signal data to be processed and analyzed, and z is conjugate complex signal data of the signal.
Where l window length, W Z Is a Winger-Ville distribution.
In step S3, a time-frequency ridge is extracted according to the time-frequency diagram, as shown in fig. 5.
In some embodiments, in step S3, the method for extracting time-frequency ridges according to the time-frequency graph includes:
and extracting the frequency corresponding to the maximum amplitude of the PWVD at each moment, namely extracting the maximum module value on the frequency axis of each moment or the frequency value corresponding to the maximum module value along the time axis of the time-frequency graph to form a time-frequency ridge line.
Specifically, the method for extracting the time-frequency ridgeline from the time-frequency graph is to extract the frequency corresponding to the maximum amplitude of the PWVD at each moment, and the jumping moment of the extracted time-frequency ridgeline is the jumping moment of the frequency-hopping signal. That is, the maximum modulus value or the frequency value corresponding to the maximum modulus value on the frequency axis at each moment is extracted along the time axis to form a time-frequency ridge line, and the ridge line is changed correspondingly at the moment of frequency hopping.
In addition, in order to accurately position the jumping time of the time-frequency ridge, in this embodiment, a wavelet transform method is further adopted, the time resolution and the frequency resolution of the signal are automatically adjusted through the scale coefficient of the wavelet basis function, so that a wavelet coefficient map of a time-scale domain can be obtained), and the characteristic of the signal jumping point can be positioned by utilizing the modulus maximum value of the wavelet transform.
And S4, calculating the frequency variation trend of the time-frequency ridge line in the pulse by using the time-frequency ridge line, and identifying the frequency variation trend as intra-pulse frequency coding modulation when the frequency variation trend is random.
In some embodiments, in step S4, before the calculating the trend of frequency change of the time-frequency ridge in the pulse by using the time-frequency ridge, the method further includes:
and performing linear fitting on the time-frequency ridge in the pulse, and then calculating correlation factors of linear fitting results and the time-frequency ridge in the pulse, thereby eliminating the possibility that the time-frequency ridge in the pulse is linearly changed.
The method for calculating the frequency change trend of the time-frequency ridge in the pulse by using the time-frequency ridge comprises the following steps:
and calculating the jumping times, the upper jumping times and the lower jumping times of the time-frequency ridge line, and calculating the frequency change trend of the time-frequency ridge line in the pulse by utilizing the jumping times, the upper jumping times and the lower jumping times.
In step S5, wavelet transform is performed on the time-frequency ridge to obtain a wavelet coefficient, and a maximum value of the wavelet coefficient corresponding to each time is calculated, then a threshold is set for the maximum value of the wavelet coefficient and a peak value is detected, and the time corresponding to the peak value of the wavelet coefficient is an estimated value of a jump time, so as to obtain a jump time and a jump period.
In some embodiments, in the step S5, the method further comprises:
when the signal noise of the radar signal is low, a hopping period is obtained by conjecture according to the obtained hopping time, and then the hopping time which cannot be positioned is obtained by conjecture according to the hopping period, which specifically comprises the following steps: firstly, calculating first-order difference of a hopping moment, and after eliminating the minimum value of the first-order difference, the remaining first-order difference result is an integral multiple of a hopping period; setting the range with the most occurrence of the first-order difference result as a first range of a jump period, screening out first-order difference values in the first range and calculating the mean value of the first-order difference values, thereby obtaining a first estimation value of the jump period; then, counting a range with the maximum occurrence probability of the hopping period according to a distribution histogram of the first estimation value of the hopping period, defining the range as a second range, and averaging the hopping periods in the second range to obtain an estimation value of the hopping period; and finally, estimating to obtain estimated values of all the jumping moments according to the known jumping moment and the jumping period estimated value.
Specifically, the characteristic information (such as frequency hopping period, frequency hopping time and frequency) of the signal is extracted according to the change rule of the ridge line, and most of the step frequency signal parameter estimation methods of the time frequency analysis class complete parameter estimation based on the idea. The disadvantage is that cross terms exist in the multi-component signal, and the step frequency signal is the multi-component signal, which will affect the analysis of the signal if the cross terms are not processed. In this embodiment, the analysis scale used by the continuous wavelet transform, the multiple-bayesian extreme phase wavelet, DB1 (Daubechies extreme phase scaling filter), is shown in fig. 6. By adopting the method, the search accuracy of time-frequency ridge jump can be further improved, and the method is particularly suitable for short time slot accurate measurement and estimation under the conditions of narrow pulse width and high frequency coding code element number.
Wavelet transformation is performed on the time-frequency ridge line to obtain a wavelet coefficient, the maximum value of the wavelet coefficient corresponding to each moment is calculated, as shown in fig. 7, then a threshold is set for the maximum value of the wavelet coefficient and a peak value is detected, the moment corresponding to the peak value of the wavelet coefficient is an estimated value of the jump moment, and the jump moment and the jump period are further obtained.
When the signal noise of the radar signal is low, a hopping period is obtained by conjecturing according to the obtained hopping time, and then the hopping time which cannot be positioned is obtained by conjecturing according to the hopping period, which specifically comprises the following steps: firstly, calculating a first-order difference of a hopping moment, and after eliminating a minimum value of the first-order difference, taking the remaining first-order difference result as an integral multiple of a hopping period; setting the range with the most occurrence of the first-order difference result as a first range of a jump period, screening out first-order difference values in the first range and calculating the mean value of the first-order difference values, thereby obtaining a first estimation value of the jump period; then, counting a range with the maximum occurrence probability of the hopping period according to a distribution histogram of the first estimation value of the hopping period, defining the range as a second range, and averaging the hopping periods in the second range to obtain an estimation value of the hopping period; and finally, estimating to obtain estimated values of all the jumping moments according to the known jumping moment and the jumping period estimated value.
In summary, whenThe method provided by the invention is different from other analysis methods in that firstly, a new recursion relational expression is designed, the traditional reverse order correlation accumulation (CRA) method is improved, and the problem that the conventional CRA method needs to be calculated is avoided
To do so
The problem of more signal to noise ratio influence; an intra-pulse frequency coding modulation mode identification algorithm based on curve fitting and jump balance calculation is provided, so that the intra-pulse frequency coding modulation identification problem of radar signals is effectively solved; thirdly, when searching the jump point of the time-frequency ridge line, the wavelet transformation analysis with variable scale is introduced, the jump point searching precision of the time-frequency ridge line is improved, and compared with the prior art, the method has the following technical advantages:
the improved signal detection method can be adapted to the pulse signal detection under the condition of lower signal-to-noise ratio, so that the whole algorithm has better adaptability.
The existing intra-pulse frequency coding radar signal processing and analyzing means are small, and compared with the traditional method, the method provided by the scheme provides an effective and practical intra-pulse frequency coding radar signal modulation and identification method.
The algorithm designed by the scheme can further improve the searching accuracy of time-frequency ridge jump and solve the problems of accurate measurement and estimation of short time slot parameters under the conditions of narrow pulse width and high frequency coding code element number.
The method has wide applicability and flexibility for different radar signal processing application requirements, can adapt to the radar signal real-time processing analysis application requirements of rapid rough measurement, and can meet the high-precision signal processing analysis requirements of waveform design parameter analysis, working mechanism research, mode performance identification and the like of the radar signal.
The invention discloses a radar signal identification and parameter estimation system in a second aspect. FIG. 8 is a block diagram of a radar signal identification and parameter estimation system according to an embodiment of the present invention; as shown in fig. 8, the system 100 includes:
the first processing module 101 is configured to improve a traditional reverse order correlation accumulation recurrence formula by a method of giving different weights to sampling points accumulated each time, complete estimation of a pulse rising edge and a pulse falling edge of a radar signal, and accordingly achieve pulse detection;
the second processing module 102 is configured to obtain a two-dimensional function of amplitude with respect to time and frequency after the pulse-detected radar signal is subjected to Wigner-Ville transform, and then obtain a time-frequency diagram of the radar signal;
a third processing module 103 configured to extract a time-frequency ridge line according to the time-frequency diagram;
the fourth processing module 104 is configured to calculate a frequency variation trend of the time-frequency ridge line in the pulse by using the time-frequency ridge line, and when the frequency variation trend is random, identify the frequency variation trend as intra-pulse frequency coding modulation;
a fifth processing module 105, configured to perform wavelet transform on the time-frequency ridge to obtain a wavelet coefficient, calculate a maximum value of the wavelet coefficient corresponding to each time, set a threshold for the maximum value of the wavelet coefficient and detect a peak value, where a time corresponding to the peak value of the wavelet coefficient is an estimated value of a jump time, and further obtain a jump time and a jump period;
and the sixth processing module 106 is configured to obtain the position of each symbol in each pulse by positioning through the hopping time and the hopping period, and perform fast fourier transform on each symbol in each pulse respectively to obtain an estimated value of the hopping frequency of each symbol, thereby obtaining the hopping period, the hopping time, and the estimated value of the hopping frequency of the intra-pulse hopping frequency signal, and thus implementing accurate estimation of the frequency coding parameters.
According to the system of the second aspect of the present invention, the first processing module 101 is configured to improve the conventional reverse order correlation accumulation recurrence formula by assigning different weights to each accumulated sampling point, and the estimation of the rising edge and the falling edge of the pulse of the radar signal includes:
carrying out initial measurement on data of the radar signals after coherent accumulation to determine a preset detection range of the radar signals;
and performing reverse order correlation accumulation on the delay conjugate multiplication output signals in the preset detection range by using an improved correlation accumulation recursion formula, so that data points with larger accumulated values have higher accumulated weight values, thereby detecting inflection points and finishing the estimation of pulse rising edges and pulse falling edges of the radar signals.
According to the system of the second aspect of the present invention, the first processing module 101 is configured to obtain the improved correlation accumulation recurrence formula as follows:
wherein y (m) is the conjugate multiplication output signal of the tiny delay mT, n represents the n time, r w (n) is the initial accumulated value at time n, y (n + 1) is the conjugate multiplication output signal at time n + 1, r w (n + 1) is the accumulated value at time n + 1, and T is the sampling interval.
According to the system of the second aspect of the present invention, the third processing module 103 is configured to extract a time-frequency ridge line according to the time-frequency graph, and the extracting includes:
and extracting the frequency corresponding to the maximum amplitude of the PWVD at each moment, namely extracting the maximum module value on the frequency axis of each moment or the frequency value corresponding to the maximum module value along the time axis of the time-frequency graph to form a time-frequency ridge line.
The system according to the second aspect of the present invention, the fourth processing module 104, is configured to,
before the calculating the frequency variation trend of the time-frequency ridge line in the pulse by using the time-frequency ridge line, the method further comprises the following steps:
and performing linear fitting on the time-frequency ridge in the pulse, and then calculating correlation factors of linear fitting results and the time-frequency ridge in the pulse, thereby eliminating the possibility that the time-frequency ridge in the pulse is linearly changed.
The system according to the second aspect of the present invention, said fourth processing module 104, is configured to,
the calculating the frequency variation trend of the time-frequency ridge line in the pulse by using the time-frequency ridge line comprises the following steps:
and calculating the jumping times, the upper jumping times and the lower jumping times of the time-frequency ridge line, and calculating the frequency change trend of the time-frequency ridge line in the pulse by utilizing the jumping times, the upper jumping times and the lower jumping times.
According to the system of the second aspect of the present invention, the fifth processing module 105 is configured to, when the signal-to-noise ratio of the radar signal is low, obtain a hopping period according to the obtained hopping time, and obtain a hopping time that cannot be located according to the hopping period, specifically, the method includes: firstly, calculating a first-order difference of a hopping moment, and after eliminating a minimum value of the first-order difference, taking the remaining first-order difference result as an integral multiple of a hopping period; setting the range with the most occurrence of the first-order difference result as a first range of a jump period, screening out first-order difference values in the first range and calculating the mean value of the first-order difference values, thereby obtaining a first estimation value of the jump period; then, counting a range with the maximum occurrence probability of the hopping period according to a distribution histogram of the first estimation value of the hopping period, defining the range as a second range, and averaging the hopping periods in the second range to obtain an estimation value of the hopping period; and finally, estimating to obtain estimated values of all the jumping moments according to the known jumping moment and the jumping period estimated value.
A third aspect of the invention discloses an electronic device. The electronic device comprises a memory and a processor, the memory stores a computer program, and the processor executes the computer program to realize the steps of the radar signal identification and parameter estimation method in any one of the first aspect of the disclosure.
Fig. 9 is a block diagram of an electronic device according to an embodiment of the present invention, and as shown in fig. 9, the electronic device includes a processor, a memory, a network interface, a display screen, and an input device, which are connected by a system bus. Wherein the processor of the electronic device is configured to provide computing and control capabilities. The memory of the electronic equipment comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The network interface of the electronic device is used for carrying out wired or wireless communication with an external terminal, and the wireless communication can be realized through WIFI, an operator network, near Field Communication (NFC) or other technologies. The display screen of the electronic equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the electronic equipment can be a touch layer covered on the display screen, a key, a track ball or a touch pad arranged on the shell of the electronic equipment, an external keyboard, a touch pad or a mouse and the like.
It will be understood by those skilled in the art that the structure shown in fig. 9 is only a partial block diagram related to the technical solution of the present disclosure, and does not constitute a limitation of the electronic device to which the solution of the present application is applied, and a specific electronic device may include more or less components than those shown in the drawings, or combine some components, or have a different arrangement of components.
A fourth aspect of the invention discloses a computer-readable storage medium. The computer readable storage medium has stored thereon a computer program which, when executed by a processor, implements the steps of a method for radar signal identification and parameter estimation according to any one of the first aspect of the present disclosure.
It should be noted that the technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, however, as long as there is no contradiction between the combinations of the technical features, the scope of the present description should be considered. The above examples only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A method for radar signal identification and parameter estimation, the method comprising:
s1, improving a traditional reverse order correlation accumulation recurrence formula by a method of endowing different weights to each accumulated sampling point, and finishing estimation of a pulse rising edge and a pulse falling edge of a radar signal so as to realize pulse detection;
s2, performing Wigner-Ville transformation on the radar signal subjected to pulse detection to obtain a two-dimensional function of amplitude with respect to time and frequency, and further obtaining a time-frequency graph of the radar signal;
s3, extracting time-frequency ridge lines according to the time-frequency graph;
s4, calculating the frequency variation trend of the time-frequency ridge in the pulse by using the time-frequency ridge, and identifying the frequency variation trend as intra-pulse frequency coding modulation when the frequency variation trend is random;
s5, performing wavelet transformation on the time-frequency ridge line to obtain a wavelet coefficient, calculating the maximum value of the wavelet coefficient corresponding to each moment, setting a threshold for the maximum value of the wavelet coefficient and detecting a peak value, wherein the moment corresponding to the peak value of the wavelet coefficient is an estimated value of a jump moment, and further obtaining the jump moment and a jump period;
and S6, positioning to obtain the position of each code element in each pulse through the hopping moment and the hopping period, and performing fast Fourier transform on each code element in each pulse respectively to obtain the frequency hopping frequency estimation value of each code element, so that the hopping period, the hopping moment and the frequency hopping frequency estimation value of the frequency hopping signal in each pulse are obtained, and accurate estimation of the frequency coding parameters is realized.
2. The method of claim 1, wherein in step S1, the conventional reverse order correlation accumulation recurrence formula is improved by assigning different weights to each accumulated sample point, and the method for estimating the rising edge and the falling edge of the pulse of the radar signal comprises:
carrying out initial measurement on data of the radar signals after coherent accumulation to determine a preset detection range of the radar signals;
and performing reverse order correlation accumulation on the delay conjugate multiplication output signals in the preset detection range by using an improved correlation accumulation recursion formula, so that data points with larger accumulated values have higher accumulated weight values, thereby detecting inflection points and finishing the estimation of pulse rising edges and pulse falling edges of the radar signals.
3. The method of claim 2, wherein in step S1, the improved correlation accumulation recursion formula is:
wherein y (m) is the conjugate multiplication output signal of the tiny delay mT, n represents the n time, r w (n) is the initial accumulated value at time n, y (n + 1) is the conjugate multiplication output signal at time n +1, r w (n + 1) is the accumulated value at time n +1, and T is the sampling interval.
4. The method of claim 1, wherein in step S3, the method of extracting time-frequency ridges from the time-frequency graph comprises:
and extracting the frequency corresponding to the maximum amplitude of the PWVD at each moment, namely extracting the maximum modulus value on the frequency axis of each moment or the frequency value corresponding to the maximum modulus value along the time axis of the time-frequency graph to form a time-frequency ridge line.
5. The method of claim 1, wherein before calculating the frequency variation trend of the time-frequency ridge in the pulse by using the time-frequency ridge in step S4, the method further comprises:
and performing linear fitting on the time-frequency ridge in the pulse, and then calculating correlation factors of linear fitting results and the time-frequency ridge in the pulse, thereby eliminating the possibility that the time-frequency ridge in the pulse is linearly changed.
6. The method of claim 5, wherein in step S4, the method of calculating the frequency variation trend of the time-frequency ridge within the pulse by using the time-frequency ridge comprises:
and calculating the jumping times, the upper jumping times and the lower jumping times of the time-frequency ridge line, and calculating the frequency change trend of the time-frequency ridge line in the pulse by utilizing the jumping times, the upper jumping times and the lower jumping times.
7. The radar signal identification and parameter estimation method according to claim 1, wherein in the step S5, the method further comprises:
when the signal noise of the radar signal is low, a hopping period is obtained by conjecturing according to the obtained hopping time, and then the hopping time which cannot be positioned is obtained by conjecturing according to the hopping period, which specifically comprises the following steps: firstly, calculating a first-order difference of a hopping moment, and after eliminating a minimum value of the first-order difference, taking the remaining first-order difference result as an integral multiple of a hopping period; setting the range with the most occurrence of the first-order difference result as a first range of a hopping period, screening out the first-order difference values in the first range and calculating the mean value of the first-order difference values, thereby obtaining a first estimation value of the hopping period; then, counting a range with the maximum occurrence probability of the hopping period according to a distribution histogram of the first estimation value of the hopping period, defining the range as a second range, and averaging the hopping period in the second range to obtain a hopping period estimation value; and finally, estimating to obtain estimated values of all the jumping moments according to the known jumping moment and the jumping period estimated value.
8. A system for radar signal identification and parameter estimation, the system comprising:
the first processing module is configured to improve a traditional reverse order correlation accumulation recurrence formula by a method of endowing different weights to sampling points accumulated each time, complete estimation of pulse rising edges and pulse falling edges of radar signals, and accordingly realize pulse detection;
the second processing module is configured to obtain a two-dimensional function of amplitude with respect to time and frequency after the pulse-detected radar signal is subjected to Wigner-Ville conversion, and further obtain a time-frequency diagram of the radar signal;
the third processing module is configured to extract time-frequency ridge lines according to the time-frequency graph;
the fourth processing module is configured to calculate the frequency variation trend of the time-frequency ridge line in the pulse by using the time-frequency ridge line, and when the frequency variation trend is random, the frequency variation trend is identified as intra-pulse frequency coding modulation;
the fifth processing module is configured to perform wavelet transformation on the time-frequency ridge line to obtain a wavelet coefficient, calculate the maximum value of the wavelet coefficient corresponding to each moment, set a threshold on the maximum value of the wavelet coefficient and detect a peak value, wherein the moment corresponding to the peak value of the wavelet coefficient is an estimated value of a jump moment, and further obtain the jump moment and a jump period;
and the sixth processing module is configured to obtain the position of each code element in each pulse through the hopping time and the hopping period by positioning, and perform fast fourier transform on each code element in each pulse respectively to obtain a frequency hopping frequency estimation value of each code element, so as to obtain the hopping period, the hopping time and the frequency hopping frequency estimation value of the frequency hopping signal in each pulse, thereby realizing accurate estimation of the frequency coding parameters.
9. An electronic device, comprising a memory storing a computer program and a processor, wherein the processor, when executing the computer program, implements the steps of a method for radar signal identification and parameter estimation according to any one of claims 1 to 7.
10. A computer-readable storage medium, having stored thereon a computer program which, when executed by a processor, carries out the steps of a method of radar signal identification and parameter estimation according to any one of claims 1 to 7.
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