KR101426863B1 - A method for recognizing radar intra-pulse modulation type using features - Google Patents

A method for recognizing radar intra-pulse modulation type using features Download PDF

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KR101426863B1
KR101426863B1 KR1020140032098A KR20140032098A KR101426863B1 KR 101426863 B1 KR101426863 B1 KR 101426863B1 KR 1020140032098 A KR1020140032098 A KR 1020140032098A KR 20140032098 A KR20140032098 A KR 20140032098A KR 101426863 B1 KR101426863 B1 KR 101426863B1
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South Korea
Prior art keywords
modulation
quadrature
shift keying
information
pulse
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KR1020140032098A
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Korean (ko)
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박병구
김영민
이동원
김종규
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국방과학연구소
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • 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
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/02—Systems using reflection of radio waves, e.g. primary radar systems; Analogous systems
    • G01S13/50—Systems of measurement based on relative movement of target
    • G01S13/52—Discriminating between fixed and moving objects or between objects moving at different speeds
    • G01S13/536—Discriminating between fixed and moving objects or between objects moving at different speeds using transmission of continuous unmodulated waves, amplitude-, frequency-, or phase-modulated waves
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • 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
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/74—Systems using reradiation of radio waves, e.g. secondary radar systems; Analogous systems
    • G01S13/76—Systems using reradiation of radio waves, e.g. secondary radar systems; Analogous systems wherein pulse-type signals are transmitted
    • G01S13/78—Systems using reradiation of radio waves, e.g. secondary radar systems; Analogous systems wherein pulse-type signals are transmitted discriminating between different kinds of targets, e.g. IFF-radar, i.e. identification of friend or foe
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • 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
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/28—Details of pulse systems

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  • Engineering & Computer Science (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Digital Transmission Methods That Use Modulated Carrier Waves (AREA)
  • Radar Systems Or Details Thereof (AREA)

Abstract

In the method of recognizing the modulated shape in the radar pulse using the feature parameter of the present invention, in order to recognize the in-pulse modulation form from the received / measured radar signal, the I / Q selected from the pulse description word (PDW) / Quadrature information and obtain the peak of Power Spectrum Density (PSD), Instantaneous Frequency and Statistical Test and use them to calculate the modulation type in pulse (NM, Non-Modulation) (FSK), Phase Shift Keying (PSK), Linear Frequency Modulation (LFM), and Nonlinear Frequency Modulation (NLFM) The modulation type can be more accurately recognized, and an important parameter that can greatly enhance the radar signal discrimination capability of the electronic warfare support system through the pulse modulation type It characterized the information is accurately obtained than.

Description

[0001] The present invention relates to a method of recognizing a radar pulse,

The present invention relates to modulation type recognition in a radar pulse, and more particularly, to a modulation type recognition method in a radar pulse using a feature factor that is robust to noise and can increase a recognition rate.

Generally, an electronic warfare support system is a system for detecting / identifying a radar signal in a high-density electromagnetic wave signal environment.

For this purpose, the electronic warfare support system for the detection / identification receives the radar signal received from all directions and measures the pulse unit parameter data in real time, and obtains the continuity, regularity and correlation of the signal in the collected pulse train data, Separate each radar signal source.

In addition, the inter-pulse and intrapulse modulation characteristics of each radar signal source pulse train should be analyzed and the radar signal should be identified by comparing with the identification library that is finally built in.

Korean Patent No. 10-1302624 (Aug. 27, 2013)

However, due to the gradual development of radar technology and the rapidly increasing trend of electronic equipment using electromagnetic signals, it becomes increasingly difficult to accurately identify each signal source.

Particularly, the in-pulse modulated form of the radar signal is an important identification parameter which can contribute to improvement of the signal detection and discrimination ability in the electronic warfare support system, and a method of being robust against noise and increasing the recognition rate is required.

In view of the above, the present invention reads I / Q (In-phase / Quadrature) information selected from a pulse description word (PDW) Power Spectrum Density), instantaneous frequency and statistical test peaks, and use these to determine the modulation form in the NM as non-modulation, FSK (Frequency Shift Keying), PSK (Phase Shift Keying), LFM Modulation, and Nonlinear Frequency Modulation (NLFM), which are important discriminative variables that can contribute to improvement of signal detection and identification ability in the electronic warfare support system. A method for recognizing a modulation type in a radar pulse using a characteristic parameter is provided.

According to an aspect of the present invention, there is provided an information processing apparatus for reading in-phase / quadrature (I / Q) information selected from a pulse description word (PDW) (FSK) modulation, a phase shift keying (PSK), a linear frequency modulation (LFM) and a nonlinear frequency modulation (NLFM) using the number of peaks of a PSD (Power Spectrum Density) ), And NM (Non-Modulation) modulation types.

Also, the present invention performs DFT (Discrete Fourier Transform) using I / Q (In-phase / Quadrature) information, calculates a pseudo bandwidth based on the threshold TH_DB and generates a bandpass FIR filter Generate new I / Q (In-phase / Quadrature) with improved noise, calculate the instantaneous frequency using the new I / Q (In-phase / Quadrature) information, and add a median filter of length M (NLFM), non-modulation (NM), and frequency shift keying (FSK) using standard deviation and threshold (TH_STD) , And phase shift keying (PSK) modulation.

In addition, the present invention squares I / Q (In-phase / Quadrature)

Figure 112014026316692-pat00001
Lt; / RTI >
Figure 112014026316692-pat00002
And smoothing window function with odd length (L)
Figure 112014026316692-pat00003
A row vector is generated for each k,
Figure 112014026316692-pat00004
, Covariance matrix
Figure 112014026316692-pat00005
, Statistical test
Figure 112014026316692-pat00006
Lt; / RTI >
Figure 112014026316692-pat00007
(MAX_V) is obtained from the set and a peak number (PEAK_Cnt) of a new threshold value (TH_MAX_NEW) or more is obtained using the threshold value (TH_MAX), and a quadrature phase shift keying (QPSK) BPSK (Binary Phase Shift Keying), and NM (Non-Modulation) modulation.

In addition, the present invention uses I / Q (In-phase / Quadrature) information

Figure 112014026316692-pat00008
And
Figure 112014026316692-pat00009
And smoothing window function with odd length (L)
Figure 112014026316692-pat00010
A row vector is generated for each k,
Figure 112014026316692-pat00011
A covariance matrix,
Figure 112014026316692-pat00012
, Statistical test
Figure 112014026316692-pat00013
Lt; / RTI >
Figure 112014026316692-pat00014
(MAX_V2) is obtained from the set and the peak number (PEAK_Cnt2) of the new threshold value (TH_MAX_NEW2) or more is obtained using the threshold value (TH_MAX2), and the BPSK (Binary Phase Shift Keying) And NM (Non-Modulation) modulation types.

Particularly, in order to achieve the above object, a method of recognizing a modulation type in a radar pulse using a feature factor of the present invention is a method for recognizing an in-phase / quadrature (I / Q) And a complex number which is obtained by using the I / Q (In-phase / Quadrature)

Figure 112014026316692-pat00015
Is obtained,
Figure 112014026316692-pat00016
A step of estimating a PSD (Power Spectrum Density) using the received signal; A frequency shift keying (FSK) modulation mode, a non-modulation (NM) mode, and a phase shift keying (PSK) mode using a number of peaks equal to or greater than a threshold value TH1 based on the result of the PSD (Power Spectrum Density) ), LFM (Linear Frequency Modulation), and NLFM (Non Linear Frequency Modulation) modulation; Calculating an instantaneous frequency using the I / Q (In-phase / Quadrature) information; (NM), a phase shift keying (PSK) modulation type, an FM (Linear Frequency Modulation) and a NLFM (Non Linear Frequency) modulation method using the threshold value TH2. Modulation) modulation step; A statistical test is obtained by squaring the in-phase / quadrature information to check the presence or absence of cyclostationarity and the number of peaks higher than the threshold value TH3 for the statistical test is obtained Quadrature phase shift keying (QPSK) modulation, BPSK (binary phase shift keying), and NM modulation; A statistical test is performed using the I / Q information to check whether cyclostationarity exists or not. The number of peaks equal to or higher than the threshold value TH4 for Statistical Test is obtained, and Binary Phase Shift (BPSK) Keying modulation and NM (non-modulation) modulation; As shown in FIG.

In step (a-1), PDW (Pulse Description Word) and I / Q (In-phase / Quadrature) data of the received and measured radar signals are processed in the step of Estimation of Power Spectral Density (In-phase) information and N Q (quadrature) information are generated by (a-2) reading in-phase / quadrature data of the selected Pulse Description Word (PDW) (A-3) using each of N I (In-phase) and Q (Quadrature) information,

Figure 112014026316692-pat00017
Is obtained.

In the step of obtaining the standard deviation, (b-1)

Figure 112014026316692-pat00018
A minimum frequency, a maximum frequency and a pseudo bandwidth in which a value equal to or greater than a threshold value TH_DB exists are calculated from a discrete Fourier transform (DFT) using information; (b-2) (Finite Impulse Response) filter is designed, (b-3) a finite impulse response
Figure 112014026316692-pat00019
New and improved noise passing information
Figure 112014026316692-pat00020
And (b-4)
Figure 112014026316692-pat00021
(B-5) The standard deviation is obtained from the filtered instantaneous frequency. The instantaneous frequency is calculated from the instantaneous frequency by the median filter having the odd number M, and the standard deviation is obtained from the filtered instantaneous frequency.

In the step of separating the QPSK (Quadrature Phase Shift Keying) modulation, the BPSK (Binary Phase Shift Keying), and the NM (Non-Modulation) modulation type, (c-1)

Figure 112014026316692-pat00022
Lt; RTI ID = 0.0 >
Figure 112014026316692-pat00023
(C-2)
Figure 112014026316692-pat00024
A row vector for the integer k from < RTI ID = 0.0 >
Figure 112014026316692-pat00025
(C-3) calculating
Figure 112014026316692-pat00026
And an odd length L window function (
Figure 112014026316692-pat00027
) To a covariance matrix
Figure 112014026316692-pat00028
, (C-4)
Figure 112014026316692-pat00029
And
Figure 112014026316692-pat00030
(Statistical Test)
Figure 112014026316692-pat00031
, (C-5)
Figure 112014026316692-pat00032
After the set of < RTI ID = 0.0 >
Figure 112014026316692-pat00033
(PEAK_Cnt) of a new threshold value (TH_MAX_NEW) using the threshold value (TH_MAX_NEW), (c-6) calculating the maximum value (MAX_V) Shift Keying modulation type, BPSK (Binary Phase Shift Keying) mode, and NM (Non-Modulation) modulation mode.

In the step of distinguishing the BPSK (Modulation-Binary Phase Shift Keying) modulation mode and the NM (Non-Modulation) modulation mode, (d-1)

Figure 112014026316692-pat00034
A row vector for the integer k from < RTI ID = 0.0 >
Figure 112014026316692-pat00035
(D-2)
Figure 112014026316692-pat00036
And an odd length L window function (
Figure 112014026316692-pat00037
) To a covariance matrix
Figure 112014026316692-pat00038
(D-3)
Figure 112014026316692-pat00039
And
Figure 112014026316692-pat00040
(Statistical Test)
Figure 112014026316692-pat00041
(D-4)
Figure 112014026316692-pat00042
(PEAK_Cnt2) of a new threshold value (TH_MAX_NEW2) using the threshold value (TH_MAX_NEW2) is obtained from the peak value (PEAK_Cnt2), and the maximum value (MAX_V2) Shift Keying modulation type and the NM (Non-Modulation) modulation type.

The present invention has the effect of more accurately recognizing the in-pulse modulation form of the radar signal, which is an important identification parameter that can contribute to improvement of the signal detection and identification ability in the electronic warfare support system by utilizing the feature factor.

In addition, the present invention has the effect of significantly increasing the identification capability of the radar signal of the electronic warfare support system by more accurately deriving the in-pulse modulation type information by more accurate recognition using the feature factor.

FIG. 1 is a flowchart of a method of recognizing a modulation type in a radar pulse using a feature parameter according to the present invention. FIG. 2 is an example of a PSD (Power Spectrum Density) according to modulation in the present invention, 4 is a diagram illustrating an example of an instantaneous frequency according to a modulation type in the present invention, and Fig. 5 is a flowchart illustrating an instantaneous frequency and a standard deviation according to the present invention. (Quadrature Phase Shift Keying) modulation type and NM (Non-Modulation) mode according to presence or absence of cyclostationarity by statistical test after squaring / Q (In-phase / Quadrature) 6 is a diagram illustrating a statistical test obtained by squaring a modulated signal according to an embodiment of the present invention. FIG. 7 is a diagram illustrating an example of a BPSK (Binary Phase Shift Keying) In-phase / quadrature (Q) (BPSK) and non-modulation (NM) modulation patterns according to presence or absence of cyclostationarity through a statistical test, and Fig. 8 And a statistical test of a modulated signal according to the present invention is obtained.

Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings, which illustrate exemplary embodiments of the present invention. The present invention is not limited to these embodiments.

FIG. 1 shows a procedure of a method of recognizing a modulation type in a radar pulse using a characteristic factor according to the present embodiment.

S100 is a step of reading I / Q (In-phase / Quadrature, hereinafter referred to as I / Q) information and processes a specific radar signal by digital signal processing to obtain Pulse Description Word (PDW) I / Q data can be generated. Then, by selecting the specific PDW, the following N I (In-phase) information and N Q (Quadrature) information can be generated by reading the corresponding I / Q data.

Figure 112014026316692-pat00043

Figure 112014026316692-pat00044

By using each of the N I (In-phase) and Q (Quadrature) information,

Figure 112014026316692-pat00045
Is obtained.

Figure 112014026316692-pat00046

here

Figure 112014026316692-pat00047
Figure 112014026316692-pat00048
I (In-phase) information
Figure 112014026316692-pat00049
) And Q (Quadrature) information
Figure 112014026316692-pat00050
) Is a complex number.

In S200,

Figure 112014026316692-pat00051
The PSD estimation is performed using a non-parametric technique, a parametric technique, and a non-parametric technique. In this case, the PSD estimation is performed based on the power spectral density (PSD) and subspace (subspace) technique.

For example, the non-parametric techniques include periodogram, welch, and multitaper methods. The parametric techniques include Yule-Walker AR, Burg covariance, and modified covariance. MUSIC, eigenvector .

S300 is a step of obtaining the number of peaks equal to or greater than the threshold value TH1 based on the PSD estimation result obtained in S200. If the number of peaks is more than 2, the frequency shift keying (FSK) Modulation, and if not, it is recognized as non-modulation (NM), phase shift keying (PSK), FM (Linear Frequency Modulation (LFM) Linear Frequency Modulation (NLFM).

A PSD example according to the modulation type is illustrated in FIG. As shown, in the FSK modulation type (1-1), the PSD peaks are two or more, and in the LFM and NLFM modulation types (1-2), PSK and NM modulation types (1-3) One can know.

Referring again to FIG. 1, in step S400,

Figure 112014026316692-pat00052
Information is used to calculate an instantaneous frequency, which is performed as a specific step as shown in FIG. 3, thereby obtaining a standard deviation.

S100

Figure 112014026316692-pat00053
Information is used to perform Discrete Fourier Transform (DFT) at S410, from which a minimum frequency, a maximum frequency, and a pseudo bandwidth with a threshold TH_DB or more are calculated.

By using the minimum frequency, maximum frequency, and pseudo bandwidth of S410, a bandpass FIR (Finite Impulse Response) filter is designed in S420,

Figure 112014026316692-pat00054
New and improved noise by passing information
Figure 112014026316692-pat00055
Is generated.

New to S420 noise improvement

Figure 112014026316692-pat00056
The instantaneous frequency is calculated in step S430. In step S440, the instantaneous frequency of step S430 is filtered by a median filter having an odd size M. Then, in step S450, the filtered instantaneous frequency of step S440 is used to calculate a standard deviation Is obtained.

Referring again to FIG. 1, S500 is a step of distinguishing a modulation type from the standard deviation obtained in S400. If the standard deviation is within the threshold TH_STD, the NM and PSK modulation types are distinguished. Otherwise, FM (LFM, NLFM ) Modulation type is distinguished.

An example of the instantaneous frequency according to the modulation type is illustrated in FIG. As shown, the standard deviation of the instantaneous frequency is small in the NM, PSK modulation type 10-1 while the instantaneous frequency standard deviation of the LFM modulation type 10-2 and the NLFM modulation type 10-3 is NM, PSK modulation type (10-1).

Referring again to FIG. 1, in S600,

Figure 112014026316692-pat00057
(QPSK) modulation and BPSK (Binary Phase Shift Keying) modulation are performed by performing a statistical test to check whether a cyclostationarity exists or not. Then, a quadrature phase shift keying (QPSK) , And the NM modulation type is divided, and this is performed in concrete steps as shown in FIG.

S100

Figure 112014026316692-pat00058
Information is used, in S610, a new input signal
Figure 112014026316692-pat00059
The following formula is applied.

Figure 112014026316692-pat00060

like this

Figure 112014026316692-pat00061
Lt; RTI ID = 0.0 >
Figure 112014026316692-pat00062
Is generated.

S610

Figure 112014026316692-pat00063
In S620, a row vector is calculated by using the following equation.

Figure 112014026316692-pat00064

Thus, the row vector for the integer k

Figure 112014026316692-pat00065
Is calculated.

Next, at S630, a covariance matrix is calculated, and the following formula is applied to this.

Figure 112014026316692-pat00066

Figure 112014026316692-pat00067

Figure 112014026316692-pat00068

Thus,

Figure 112014026316692-pat00069
And an odd length L window function (
Figure 112014026316692-pat00070
), A covariance matrix is obtained,
Figure 112014026316692-pat00071
Is calculated. At this time,
Figure 112014026316692-pat00072
Can be a smoothing window, a kaiser window function, etc., and n has an odd length L value.

Then, in S640, a statistical test is calculated, and the following formula is applied to this.

Figure 112014026316692-pat00073

As described above,

Figure 112014026316692-pat00074
And S630
Figure 112014026316692-pat00075
(Statistical Test)
Figure 112014026316692-pat00076
Is calculated.

Then, in S650,

Figure 112014026316692-pat00077
By repeating the processes for S620, S630, and S640
Figure 112014026316692-pat00078
In S660, TH_MAX_NEW = MAX_V / TH_MAX is used to calculate the set of S650
Figure 112014026316692-pat00079
(MAX_V) is obtained from the set and the peak number (PEAK_Cnt) of the new threshold value (TH_MAX_NEW) or more is obtained by using the threshold value (TH_MAX).

In step S670, the QPSK modulation type, the BPSK and the NM modulation type are distinguished from each other using the peak number (PEAK_Cnt) of S660. If the peak number (PEAK_Cnt) is 2 or more, NM modulation type.

FIG.

Figure 112014026316692-pat00080
And the presence or absence of cyclostationarity is checked through a statistical test. The result of S600 in which QPSK modulation, BPSK and NM modulation types are distinguished is shown.

As shown, the square of the BPSK signal with 180 degree phase inversion is equal to the square of the NM modulation signal. However, since QPSK has a phase shift of 90 degrees, the form of QPSK is different from the square of BPSK and NM modulation signal even if the signal is squared, and it can be seen that cyclostationarity occurs due to periodic change of symbol for QPSK generation in QPSK modulation signal have. Therefore, if the number of peaks is two or more from the statistical test result, it can be judged that cyclostationarity has occurred.

Referring back to FIG. 1, at S700,

Figure 112014026316692-pat00081
The presence or absence of cyclostationarity is checked from the statistical test using the BPSK modulation and the NM modulation type.

This is performed in the concrete steps as shown in FIG.

S100's

Figure 112014026316692-pat00082
The row vector is calculated from the following equation at S710.

Figure 112014026316692-pat00083

Figure 112014026316692-pat00084

Figure 112014026316692-pat00085

Figure 112014026316692-pat00086

As described above, a row vector is generated for the integer k,

Figure 112014026316692-pat00087
Is calculated.

Next, at S720, a covariance matrix is calculated, and the following formula is applied to this.

Figure 112014026316692-pat00088

Figure 112014026316692-pat00089

Figure 112014026316692-pat00090

Thus,

Figure 112014026316692-pat00091
And an odd length L window function (
Figure 112014026316692-pat00092
) Is used to calculate the covariance matrix
Figure 112014026316692-pat00093
Is calculated. At this time,
Figure 112014026316692-pat00094
Can be a smoothing window, a kaiser window function, etc., and n has an odd length L value.

Then, in S730, a statistical test is calculated, and the following formula is applied to this.

Figure 112014026316692-pat00095

As described above,

Figure 112014026316692-pat00096
And S720
Figure 112014026316692-pat00097
(Statistical Test)
Figure 112014026316692-pat00098
Is calculated.

Then, in S740,

Figure 112014026316692-pat00099
By repeating the processes of S710, S720, and S730
Figure 112014026316692-pat00100
In S750, TH_MAX_NEW2 = MAX_V2 / TH_MAX2 is used to calculate the set of S740
Figure 112014026316692-pat00101
(MAX_V2) is obtained from the set and the peak number (PEAK_Cnt2) of the new threshold value (TH_MAX_NEW2) or more is obtained by using the threshold value (TH_MAX2).

Then, in S760, the BPSK modulation type and the NM modulation type are distinguished by using the peak number (PEAK_Cnt2) of S750, and if the number of peaks (PEAK_Cnt2) is 2 or more, they are classified into BPSK modulation type, Respectively.

Fig.

Figure 112014026316692-pat00102
The presence of Cyclostationarity is checked through Statistical Test, and the result of S700 which distinguishes BPSK modulation and NM modulation type is shown.

As shown, the BPSK signal having 180-degree phase inversion is different from the NM-modulated signal having no phase inversion, and the cyclostationarity occurs in the BPSK modulation signal due to the periodic change of the symbol for BPSK generation. Therefore, if the number of peaks is two or more from the statistical test result, it can be judged that cyclostationarity has occurred.

As described above, in the radar pulse modulation type recognizing method using the feature parameter according to the present embodiment, the I / Q information selected from the PDW to be analyzed is read from the received / measured radar signal and the PSD, The in-pulse modulation form can be more accurately recognized from the characteristic factor by dividing the in-pulse modulation form into NM, FSK, PSK, LFM and NLFM by obtaining the peak of the instantaneous frequency and the statistical test (Statistical Test) It is possible to more accurately derive the modulation type information in the pulse, which is an important discriminant variable that can greatly enhance the radar signal discrimination capability of the electronic warfare support system.

1-1, 1-2, 1-3: 1st, 2nd, 3rd PSD (Power Spectrum Density)
10-1, 10-2, 10-3: 1st, 2nd and 3rd instantaneous frequencies

Claims (5)

In-phase / quadrature (I / Q) information is read from the received and measured radar signals for in-pulse modulation type recognition, and a complex number using the in-phase / quadrature
Figure 112014056278096-pat00103
Is obtained,
Figure 112014056278096-pat00104
A step of estimating a PSD (Power Spectrum Density) using the received signal;
A frequency shift keying (FSK) modulation mode, a non-modulation (NM) mode, and a phase shift keying (PSK) mode using a number of peaks equal to or greater than a threshold value TH1 based on the result of the PSD (Power Spectrum Density) ), LFM (Linear Frequency Modulation), and NLFM (Non Linear Frequency Modulation) modulation;
Calculating an instantaneous frequency using the I / Q (In-phase / Quadrature) information;
(NM), a phase shift keying (PSK) modulation type and an LFM (Linear Frequency Modulation), an NLFM (Linear Frequency Modulation) modulation method using the instantaneous frequency to obtain a standard deviation and determining whether the standard deviation is within a threshold TH_STD. (Non Linear Frequency Modulation) modulation mode;
A statistical test is obtained by squaring the in-phase / quadrature information, and the presence or absence of cyclostationarity is confirmed. The number of peaks equal to or higher than the threshold value TH3 for the statistical test is obtained A step of separating a QPSK (Quadrature Phase Shift Keying) modulation, a BPSK (Binary Phase Shift Keying) and an NM (Non-Modulation) modulation type;
A statistical test is obtained by using the I / Q information to check the presence or absence of cyclostationarity. The number of peaks equal to or higher than the threshold value TH4 for the statistical test is obtained, (Binary Phase Shift Keying) modulation and NM (Non-Modulation) modulation;
Wherein the modulated shape recognition is performed in the radar pulse using the feature parameter.
The method of claim 1, wherein the step (a-1) of calculating the power spectral density (PSD) comprises the steps of: (a-1) / Quadrature) data of the selected PDW ((a-2)) and reads the in-phase / quadrature data of the selected PDW (Pulse Description Word) Quadrature information is generated, and (a-3) each N I (In-phase) and Q (Quadrature) information is used
Figure 112014026316692-pat00105
Of the radar pulse is obtained.
The method according to claim 1, wherein, in the step of obtaining the standard deviation,
(b-1)
Figure 112014026316692-pat00106
A minimum frequency, a maximum frequency and a pseudo bandwidth in which a value equal to or greater than a threshold value TH_DB exists are calculated from a discrete Fourier transform (DFT) using information; (b-2) (Finite Impulse Response) filter is designed, (b-3) a finite impulse response
Figure 112014026316692-pat00107
New and improved noise passing information
Figure 112014026316692-pat00108
And (b-4)
Figure 112014026316692-pat00109
(B-5) calculating the standard deviation from the filtered instantaneous frequency, and calculating the instantaneous frequency from the radar pulse using the characteristic factor Modulation type recognition method.
2. The method of claim 1, wherein in the step of separating the QPSK (Quadrature Phase Shift Keying) modulation, the BPSK (Binary Phase Shift Keying) and the NM (Non-Modulation)
(c-1)
Figure 112014026316692-pat00110
Lt; RTI ID = 0.0 >
Figure 112014026316692-pat00111
(C-2)
Figure 112014026316692-pat00112
A row vector for the integer k from < RTI ID = 0.0 >
Figure 112014026316692-pat00113
(C-3) calculating
Figure 112014026316692-pat00114
And an odd length L window function (
Figure 112014026316692-pat00115
) To a covariance matrix
Figure 112014026316692-pat00116
, (C-4)
Figure 112014026316692-pat00117
And
Figure 112014026316692-pat00118
(Statistical Test)
Figure 112014026316692-pat00119
, (C-5)
Figure 112014026316692-pat00120
After the set of < RTI ID = 0.0 >
Figure 112014026316692-pat00121
(PEAK_Cnt) of a new threshold value (TH_MAX_NEW) using the threshold value (TH_MAX), (c-6) calculating the maximum value (MAX_V) of the set from the peak number (PEAK_Cnt) The BPSK, and the NM modulation type are distinguished from each other.
[2] The method of claim 1, wherein the BPSK (Modulation Phase Shift Keying) modulation mode and the NM (Non-Modulation)
(d-1)
Figure 112014026316692-pat00122
A row vector for the integer k from < RTI ID = 0.0 >
Figure 112014026316692-pat00123
(D-2)
Figure 112014026316692-pat00124
And an odd length L window function (
Figure 112014026316692-pat00125
) To a covariance matrix
Figure 112014026316692-pat00126
(D-3)
Figure 112014026316692-pat00127
And
Figure 112014026316692-pat00128
(Statistical Test)
Figure 112014026316692-pat00129
(D-4)
Figure 112014026316692-pat00130
(PEAK_Cnt2) of a new threshold value (TH_MAX_NEW2) by using the threshold value (TH_MAX_NEW2), (d-5) calculating the maximum value (MAX_V2) Shift Keying modulation type and the NM (Non-Modulation) modulation type are distinguished from each other.
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CN108181617A (en) * 2017-12-29 2018-06-19 北京理工大学 A kind of filtering method of the nonlinear frequency modulation system based on the transformation of tensor product model
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CN117289236A (en) * 2023-11-27 2023-12-26 成都立思方信息技术有限公司 Short-time radar signal intra-pulse modulation type identification method, device, equipment and medium

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Publication number Priority date Publication date Assignee Title
KR101722505B1 (en) * 2016-03-03 2017-04-18 국방과학연구소 Method and apparatus for recognizing modulation type of input signal
CN108181617A (en) * 2017-12-29 2018-06-19 北京理工大学 A kind of filtering method of the nonlinear frequency modulation system based on the transformation of tensor product model
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CN111060878A (en) * 2019-12-30 2020-04-24 南京东科优信网络安全技术研究院有限公司 LFM radar working mode real-time classification method and device suitable for single pulse
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CN117289236A (en) * 2023-11-27 2023-12-26 成都立思方信息技术有限公司 Short-time radar signal intra-pulse modulation type identification method, device, equipment and medium
CN117289236B (en) * 2023-11-27 2024-02-09 成都立思方信息技术有限公司 Short-time radar signal intra-pulse modulation type identification method, device, equipment and medium

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