CN112505641B - Radar interference signal identification method based on characteristic parameter extraction - Google Patents
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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
- 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
- G01S7/36—Means for anti-jamming, e.g. ECCM, i.e. electronic counter-counter measures
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
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Abstract
The invention discloses a radar interference signal identification method based on characteristic parameter extraction, which has high automation degree and high accuracy. The radar interference signal identification method provided by the invention comprises the following steps: (10) receiving a disturbed radar signal: the radar ground equipment receives a disturbed radar signal containing interference; and (20) extracting time domain characteristic parameters: extracting time domain characteristic parameters of a disturbed radar signal, wherein the time domain characteristic parameters comprise a time domain moment skewness coefficient, a time domain moment kurtosis coefficient and a time domain kurtosis coefficient; (30) frequency domain characteristic parameter extraction: carrying out frequency domain transformation on the disturbed radar signal, and extracting frequency domain characteristic parameters of the disturbed radar signal; (40) time domain comparison: comparing the disturbed radar signal with time domain characteristic parameters of known interference radar signals; (50) frequency domain comparison: comparing the disturbed radar signal with the frequency domain characteristic parameters of the known interference radar signal; (60) discriminating the type of the interference signal: and D-S theory is adopted to judge the type of the radar interference signal.
Description
Technical Field
The invention relates to a radar interference signal identification method, in particular to a radar interference signal identification method based on characteristic parameter extraction.
Background
As radar continues to increase in role in combat, the identification of radar interference signals is becoming more and more urgent and important.
Electromagnetic interference experienced by radar systems at the receiver is dominated by jamming signals directed at the radar receiver, which can be classified in two categories in terms of operation, namely rogue interference and suppressed interference.
The deception jamming can achieve good jamming effect with very low power consumption, but information such as a working frequency point, bandwidth, pseudo code and the like of a target signal needs to be known in advance, and a military navigation signal is usually encrypted by using a more complex pseudo code different from a civil navigation signal, so that the deception jamming technology is difficult to realize.
The pressed interference is different from deception interference, the signal energy is far greater than the radar signal, and the purpose of interfering the receiver work is achieved by completely submerging the radar signal. The suppression type interference technology is a most widely used interference form because of low implementation difficulty, simple technology and low cost. Noise interference, audio interference, and impulse interference are common ways of radar interference. From the radar anti-interference flow, the high-probability correct interference type identification is the basis of the whole anti-interference process. In the present situation, the identification of the radar interference type only depends on the richness of the working experience of the radar operator, that is, the energy of the operator is consumed, and the practicability is not high.
Thus, the prior art has the following problems: the radar interference signal identification has low automation degree and low accuracy.
Disclosure of Invention
The invention aims to provide a radar interference signal identification method based on characteristic parameter extraction, which has high automation degree and high accuracy.
The technical solution for realizing the purpose of the invention is as follows:
a radar interference signal identification method based on characteristic parameter extraction comprises the following steps:
(10) Receiving a disturbed radar signal: the radar ground equipment receives a disturbed radar signal containing interference;
(20) Extracting time domain characteristic parameters: extracting time domain characteristic parameters of a disturbed radar signal, wherein the time domain characteristic parameters comprise a time domain moment skewness coefficient, a time domain moment kurtosis coefficient and a time domain kurtosis coefficient;
(30) Extracting frequency domain characteristic parameters: carrying out frequency domain transformation on the disturbed radar signal, and extracting frequency domain characteristic parameters of the disturbed radar signal, wherein the frequency domain characteristic parameters comprise frequency domain carrier factors, normalized 3dB bandwidths and normalized frequency spectrum impulse part standard deviations;
(40) And (3) time domain comparison: comparing the time domain characteristic parameters of the interfered radar signals with the time domain characteristic parameters of the known interference radar signals extracted under the known interference condition to give an interference type probability time domain result;
(50) Frequency domain comparison: comparing the frequency domain characteristic parameters of the interfered radar signals with the frequency domain characteristic parameters of the known interference radar signals extracted under the known interference condition to give an interference type probability frequency domain result;
(60) Discriminating the type of the interference signal: and according to the interference type probability time domain result and the interference type probability frequency domain result, adopting a D-S theory to judge the type of the radar interference signal.
Compared with the prior art, the invention has the remarkable advantages that:
the method is a method for identifying interference by extracting the characteristic parameters of the time domain and the frequency domain of the disturbed radar signal, the fluctuation characteristic, the distribution characteristic and the autocorrelation characteristic of the amplitude of the time domain of the disturbed radar signal are analyzed and extracted, the spectral distribution, the power spectrum characteristic and the amplitude-frequency distribution characteristic of the frequency domain are combined for extraction and analysis, and the discrimination basis of the interference type is obtained by combining experimental experience parameter comparison. The method has high degree of automation of parameter extraction, scientificalness of interference judgment, and ensures the accuracy of interference judgment on the basis of saving manpower.
The invention is described in further detail below with reference to the drawings and the detailed description.
Drawings
Fig. 1 is a main flow chart of a radar interference signal identification method based on characteristic parameter extraction.
Fig. 2 is a flowchart of the time domain feature parameter extraction step in fig. 1.
Fig. 3 is a flowchart of the frequency characteristic parameter extraction step in fig. 1.
Fig. 4 is a flowchart of the D-S evidence fusion theory integrating two judgment probabilities.
Detailed Description
As shown in fig. 1, the radar interference signal identification method based on characteristic parameter extraction of the invention comprises the following steps:
(10) Receiving a disturbed radar signal: the radar ground equipment receives a disturbed radar signal containing interference;
in the step of receiving the disturbed radar signal (10), the radar ground device receives the disturbed radar signal containing the interference, and obtains an N-point discretization sequence x (N) = { x after sampling meeting the nyquist law 1 ,x 2 ,x 3 ,……,x N N is the number of sampling points, and x (N) is the discrete signal obtained after sampling.
(20) Extracting time domain characteristic parameters: extracting time domain characteristic parameters of a disturbed radar signal, wherein the time domain characteristic parameters comprise a time domain moment skewness coefficient, a time domain moment kurtosis coefficient and a time domain kurtosis coefficient;
as shown in fig. 2, the step of extracting (20) the time domain feature parameter includes:
(21) And (3) basic probability statistical calculation: the basic probability statistical calculation of the mean value mu and the standard deviation sigma is carried out on the N-point signal sequence
(22) Calculating time domain characteristic parameters: and (5) taking the mean value mu and the standard deviation sigma into a calculation formula of a time domain moment skewness coefficient, a time domain moment kurtosis coefficient and a time domain kurtosis coefficient to calculate a time domain characteristic parameter.
Specifically defined as
Time domain moment skewness coefficient
Time domain moment kurtosis coefficient
Time domain kurtosis coefficient
(30) Extracting frequency domain characteristic parameters: carrying out frequency domain transformation on the disturbed radar signal, and extracting frequency domain characteristic parameters of the disturbed radar signal, wherein the frequency domain characteristic parameters comprise frequency domain carrier factors, normalized 3dB bandwidths and normalized frequency spectrum impulse part standard deviations;
as shown in fig. 3, the step of extracting (30) the frequency domain characteristic parameter includes:
(31) Fast fourier transform: performing fast fourier transform on the N-point discretized sequence x (N) to obtain a frequency domain signal F (k), wherein k=0, 1,2,3 … N-1;
(32) And (3) basic probability statistical calculation: performing basic probability statistical calculation of a mean value mu and a standard deviation sigma on a discrete frequency domain signal F (k);
(33) Calculating frequency domain characteristic parameters: and (3) bringing the mean value mu and the standard deviation sigma into a calculation formula of frequency domain carrier factors, normalized 3dB bandwidth and normalized frequency spectrum impulse part standard deviation to calculate frequency domain characteristic parameters.
Specifically defined as
Carrier factor R cw : defining the ratio of the highest amplitude to the next highest amplitude of F (k) as a carrier factor, denoted R cw . When the value is larger than a certain threshold, the interference signal can be judged to be a carrier signal, and the range of the value of the interference signal of different types is also different.
Normalized 3dB bandwidth: the normalized 3dB bandwidth may be used as a characteristic parameter for determining whether the signal belongs to narrowband interference or kunka interference. The signal spectrum is subjected to linear normalization, and the normalized spectrum of the signal is as follows:
where S (n) is the spectrum of the processed signal. 3dB bandwidth of signalIn->S th =0.5, n is the data amount.
Normalized spectral impulse partial standard deviation: first to the received signalThe normalized frequency spectrum is subjected to windowing smoothing treatment to obtain a flat part of the normalized frequency spectrum, and the flat part of the normalized frequency spectrum is subtracted by the normalized frequency spectrum to obtain an impulse part of the normalized frequency spectrumL is the flat portion data amount; standard deviation of impulse spectrum of signal
(40) And (3) time domain comparison: comparing the time domain characteristic parameters of the interfered radar signals with the time domain characteristic parameters of the known interference radar signals extracted under the known interference condition to give an interference type probability time domain result;
in the step of time domain comparison, the time domain characteristic parameters of the known interference radar signals extracted under the known interference condition are the time domain characteristic parameters of the known interference radar signals extracted under the condition that the interference signal ratio is gradually increased, wherein the time domain characteristic parameters of the known interference radar signals extracted under the condition that the radar receiver is subjected to specific interference under the laboratory environment;
the specific interference modes comprise radio frequency noise interference, amplitude modulation noise interference, noise frequency modulation interference, comb spectrum interference, continuous wave interference and pulse interference.
According to the simulation, experience data are obtained: a of radio frequency noise interference and frequency modulation noise interference 3 > 0, noise amplitude modulation disturbance a 3 ＜0。
According to the simulation, experience data are obtained: noise amplitude modulation interference and frequency modulation noise interference 4 < 3, radio frequency noise interference a 4 ＞3。
According to the simulation, experience data are obtained: impulse interference is an impulse function in the time domain that has burstiness and periodicity, and can be distinguished thereby.
(50) Frequency domain comparison: comparing the frequency domain characteristic parameters of the interfered radar signals with the frequency domain characteristic parameters of the known interference radar signals extracted under the known interference condition to give an interference type probability frequency domain result;
in the step of comparing the frequency domains, the frequency domain characteristic parameters of the known interference radar signals extracted under the known interference condition are the frequency domain characteristic parameters of the known interference radar signals extracted under the condition that the interference signal ratio is gradually increased, wherein the frequency domain characteristic parameters of the known interference radar signals extracted under the condition that the radar receiver is subjected to specific interference under the laboratory environment;
the specific interference modes comprise radio frequency noise interference, amplitude modulation noise interference, noise frequency modulation interference, comb spectrum interference, continuous wave interference and pulse interference.
According to the simulation, experience data are obtained: r of noise amplitude modulation interference cw R of radio frequency noise interference with a value between 1.4 and 1.5 cw R with value about 1.1 and noise frequency modulation interference cw The value is about 1.8.
According to the simulation, experience data are obtained: continuous wave interferenceAbout 0, interference of dressing spectrum +.>The value is between 0.1 and 0.2, pulse interference +.>The value is between 0.2 and 0.5.
And (3) according to simulation, obtaining experience data: delta of pulse disturbance spn Delta of very low, comb spectrum interference spn Significantly higher than other disturbances and thus distinguishable.
(60) Discriminating the type of the interference signal: and according to the interference type probability time domain result and the interference type probability frequency domain result, adopting a D-S theory to judge the type of the radar interference signal.
As shown in fig. 4, the step of discriminating (60) the type of the interference signal specifically includes:
and according to the interference type probability time domain result and the interference type probability frequency domain result, carrying out radar interference signal type discrimination by adopting a D-S theory, extracting the fused interference type probability result, and carrying out interference signal identification.
(61) And (3) time domain judgment: and according to the judgment of the time domain characteristic parameters, a judgment result is given.
Comparing the time domain characteristic parameters obtained in the step (40) with time domain characteristic parameter experience data extracted under the conditions of radio frequency noise interference, amplitude modulation noise interference, noise frequency modulation interference, comb spectrum interference, continuous wave interference and pulse interference in an experimental environment, wherein the comparison method adopts threshold value comparison and characteristic curve similarity comparison to give an interference type probability result;
(62) Judging a frequency domain: and according to the judgment of the time domain characteristic parameters, a judgment result is given.
Comparing the frequency domain characteristic parameters obtained in the step (50) with frequency domain characteristic parameter experience data extracted under the conditions of radio frequency noise interference, amplitude modulation noise interference, noise frequency modulation interference, comb spectrum interference, continuous wave interference and pulse interference in an experimental environment, wherein the comparison method adopts threshold value comparison and characteristic curve similarity comparison to give an interference type probability result;
(63) Normalization of time domain probability: and normalizing the probability result of the interference type obtained in the time domain.
And judging the interference type probability under the time domain condition: radio frequency noise interference, amplitude modulation noise interference, noise frequency modulation interference, comb spectrum interference, continuous wave interference, impulse interference are noted as t= { T1, T2, T3, T4, T5, T6}, and t1+t2+t3+t4+t5+t6=1.
(64) Frequency domain probability normalization: and normalizing the probability result of the interference type obtained by the frequency domain.
And judging the interference type probability under the frequency domain condition: radio frequency noise interference, amplitude modulated noise interference, noise frequency modulated interference, continuous wave interference, impulse interference are noted as f= { F1, F2, F3, F4, F5, F6}, and f1+f2+f3+f4+f5+f6=1.
(65) Calculating a conflict coefficient: calculating a conflict coefficient k value according to a formula of the D-S evidence fusion theory: the k value is a conflict coefficient and is used for representing the conflict degree judged by two methods and is expressed as
(66) Calculating a D-S probability function: calculating a D-S judgment probability function according to the conflict coefficient k value obtained in the step (65), the time domain normalization probability function obtained in the step (63) and the frequency domain normalization probability function obtained in the step (62);
the union Y=TU F is used as a probability set of D-S evidence fusion, and the situation that the interference type cannot be distinguished is eliminated, and because the probability type in the set is normalized probability, the probability set is:
(67) Judging the interference type: and according to the final D-S judgment probability function, arranging the probabilities of various possible interference types from large to small, and identifying the interference types. That is, the fused result is obtained according to m (Y i ) The probability of the interference type with the largest probability is the probability of the interference type with the largest probability.
The method for extracting the time domain characteristic parameters and the frequency domain characteristic parameters is used for identifying radar interference to be detected, can realize rapid and simple extraction of fluctuation characteristics, correlation characteristics and power spectrum distribution characteristics of interference data, and is suitable for being used in environments requiring rapid interference determination under missile-borne environments and the like.
Claims (7)
1. The radar interference signal identification method based on characteristic parameter extraction is characterized by comprising the following steps:
(10) Receiving a disturbed radar signal: the radar ground equipment receives a disturbed radar signal containing interference;
(20) Extracting time domain characteristic parameters: extracting time domain characteristic parameters of a disturbed radar signal, wherein the time domain characteristic parameters comprise a time domain moment skewness coefficient, a time domain moment kurtosis coefficient and a time domain kurtosis coefficient;
(30) Extracting frequency domain characteristic parameters: carrying out frequency domain transformation on the disturbed radar signal, and extracting frequency domain characteristic parameters of the disturbed radar signal, wherein the frequency domain characteristic parameters comprise frequency domain carrier factors, normalized 3dB bandwidths and normalized frequency spectrum impulse part standard deviations;
(40) And (3) time domain comparison: comparing the time domain characteristic parameters of the interfered radar signals with the time domain characteristic parameters of the known interference radar signals extracted under the known interference condition to give an interference type probability time domain result;
(50) Frequency domain comparison: comparing the frequency domain characteristic parameters of the interfered radar signals with the frequency domain characteristic parameters of the known interference radar signals extracted under the known interference condition to give an interference type probability frequency domain result;
(60) Discriminating the type of the interference signal: and according to the interference type probability time domain result and the interference type probability frequency domain result, adopting a D-S theory to judge the type of the radar interference signal.
2. The radar signal identification method of claim 1, wherein:
in the step of receiving the disturbed radar signal (10), the radar ground device receives the disturbed radar signal containing the interference, and obtains an N-point discretization sequence x (N) = { x after sampling meeting the nyquist law 1 ,x 2 ,x 3 ,……,x N N is the number of sampling points, and x (N) is the discrete signal obtained after sampling.
3. The radar signal identification method according to claim 2, wherein the (20) time domain feature parameter extraction step includes:
(21) And (3) basic probability statistical calculation: the basic probability statistical calculation of the mean value mu and the standard deviation sigma is carried out on the N-point signal sequence
(22) Calculating time domain characteristic parameters: and (5) taking the mean value mu and the standard deviation sigma into a calculation formula of a time domain moment skewness coefficient, a time domain moment kurtosis coefficient and a time domain kurtosis coefficient to calculate a time domain characteristic parameter.
4. The radar signal identification method according to claim 1, wherein the (30) frequency domain feature parameter extraction step includes:
(31) Fast fourier transform: performing fast fourier transform on the N-point discretized sequence x (N) to obtain a frequency domain signal F (k), wherein k=0, 1,2,3 … N-1;
(32) And (3) basic probability statistical calculation: performing basic probability statistical calculation of a mean value mu and a standard deviation sigma on a discrete frequency domain signal F (k);
(33) Calculating time domain characteristic parameters: and (3) bringing the mean value mu and the standard deviation sigma into a calculation formula of frequency domain carrier factors, normalized 3dB bandwidth and normalized frequency spectrum impulse part standard deviation to calculate time domain characteristic parameters.
5. The radar signal identification method of claim 1, wherein:
in the step of time domain comparison, the time domain characteristic parameters of the known interference radar signals extracted under the known interference condition are the time domain characteristic parameters of the known interference radar signals extracted under the condition that the interference signal ratio is gradually increased, wherein the time domain characteristic parameters of the known interference radar signals extracted under the condition that the radar receiver is subjected to specific interference under the laboratory environment;
the specific interference modes comprise radio frequency noise interference, amplitude modulation noise interference, noise frequency modulation interference, comb spectrum interference, continuous wave interference and pulse interference.
6. The radar signal identification method of claim 1, wherein:
in the step of comparing the frequency domains, the frequency domain characteristic parameters of the known interference radar signals extracted under the known interference condition are the frequency domain characteristic parameters of the known interference radar signals extracted under the condition that the interference signal ratio is gradually increased, wherein the frequency domain characteristic parameters of the known interference radar signals extracted under the condition that the radar receiver is subjected to specific interference under the laboratory environment;
the specific interference modes comprise radio frequency noise interference, amplitude modulation noise interference, noise frequency modulation interference, comb spectrum interference, continuous wave interference and pulse interference.
7. The radar interference signal identification method according to claim 1, wherein the step of (60) discriminating the type of the interference signal is specifically:
and according to the interference type probability time domain result and the interference type probability frequency domain result, carrying out radar interference signal type discrimination by adopting a D-S theory, extracting the fused interference type probability result, and carrying out interference signal identification.
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