CN115542275A - Radar radiation source PRI calculation method based on pulse rising edge correlation matching - Google Patents
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Abstract
The invention discloses a radar radiation source PRI calculation method based on pulse rising edge correlation matching, which utilizes the characteristics of stability and significance of the rising edge of a radar pulse signal, determines the number of sampling points included in the complete PRI by extracting the rising edge part of an intercepted radar pulse signal to perform correlation matching with the whole pulse stream signal, and finally calculates the PRI of the radar radiation source. The method comprises the following implementation steps: 1. generating a radar radiation source pulse flow intermediate frequency signal; 2. extracting the rising edge of the intermediate frequency pulse signal of the radar radiation source as a reference signal; 3. performing sliding correlation operation on the reference signal and the whole pulse stream signal; 4. determining the number of interval sampling points between adjacent pulses according to the correlation coefficient; 5. and calculating the PRI value of the radar radiation source. The invention can reduce the influence of noise on the detection amplitude, thereby improving the PRI measurement calculation precision.
Description
[ technical field ] A method for producing a semiconductor device
The invention belongs to the field of electronic countermeasure reconnaissance, and particularly relates to a radar radiation source PRI calculation method based on pulse rising edge correlation matching. The invention can be used for the precise measurement of the pulse repetition interval of the intercepted radar radiation source signal in electronic information reconnaissance, electronic support and threat warning equipment.
[ background of the invention ]
In radar countermeasure reconnaissance, the receiver is responsible for measuring the conventional parameters of the intercepted signal, including pulse arrival direction, pulse arrival time, pulse signal carrier rate, pulse width, pulse amplitude and the like. Through the analysis of the conventional parameters, the target radar can realize all-around and multi-level cognition, and further master the intention and the dynamics of the target. Therefore, accurate measurement of conventional parameters of the intercepted radar radiation source signal is significant for radar counterreconnaissance, and the Pulse Repetition Interval (PRI) is not exceptional as one of the conventional parameters.
The pulse repetition interval of the radar radiation source mainly depends on the signal arrival time and the signal amplitude to realize measurement. Under an ideal condition, the pulse envelope of the radar radiation source is rectangular, and no error exists in the signal arrival time obtained through threshold detection. However, in a practical complex and variable electromagnetic environment, the envelope of the pulse signal intercepted by the reconnaissance receiver is not normally a standard rectangle, and certain distortion is generated, which causes the measurement accuracy of the arrival time and the pulse repetition interval to be reduced. Generally, the existence of the pulse rising time is considered to be a main reason for influencing the measurement error of the pulse repetition interval, and due to the influence of environmental noise, the amplitude of the pulse envelope is distorted, the threshold detection has an error, and the measurement accuracy of the pulse repetition interval is reduced.
The application of a constant ratio triggering method in high-precision radar PRI measurement is published in modern radar 2007, namely, in 1 month, and provides a constant ratio triggering method for calculating a corresponding floating threshold value for each radar pulse in real time, so that a triggering error caused by a fixed threshold value is effectively overcome, and the measurement precision of a pulse repetition interval is improved to a certain extent. In essence, this approach does not solve well for noise-affected amplitudes and thus decision threshold time advance or delay.
One approach to PRI estimation for high pulse loss rates, published in space electronic countermeasure, focuses on PRI estimation under pulse loss conditions rather than on the accuracy of PRI measurement itself.
The 'analysis and simulation verification of factors restricting the radar PRI measurement accuracy' published in the journal of modern defense technology 2009, 2, the important analysis of the factors influencing the PRI measurement accuracy is the bandwidth of a receiver, a noise reduction method, a self-adaptive floating threshold and the like.
[ summary of the invention ]
In view of the above, it is necessary to provide a radar radiation source PRI calculation method based on pulse rising edge correlation matching to improve the measurement accuracy.
In order to solve the above problems in the prior art, the present invention provides a method for calculating a radar radiation source PRI based on pulse rising edge correlation matching.
The technical problem to be solved by the invention is realized by the following technical scheme:
a radar radiation source PRI calculation method based on pulse rising edge correlation matching is characterized by comprising the following steps:
(1) According to the principle of a radar transmitter and the characteristics of a radar counterscout receiver intercepting signal waveforms, a mathematic model s of the ith intermediate frequency pulse signal of a radar radiation source pulse stream is constructed i (t) and a signal stream S comprising N pulse waveforms N (t)；
(2) Extracting said signal stream S N Envelope A of (t) N (t) and cutting A N (t) the rising phase of the first pulse envelope as a reference signal r (t);
(3) According to the calculation requirement, a reference signal r (t) and an envelope A are combined N (t) performing M sliding correlation operations according to the compartment L to obtain a correlation coefficient vector R 1×M And taking the maximum value and the corresponding address of each group of O (less than O is filled with 0) to obtain a new correlation coefficient vector R' 1×K And an address vector D 1×K Where L and O are determined according to computational accuracy requirements, M is the signal envelope length divided by L and rounded up,
(round up);
(4) Comparing correlation coefficient vector R' 1×K To determine a matching threshold Thre, holding the correlation coefficient and the corresponding address greater than Thre, and generating a matching vector R ″ 1×K And address vector D' 1×K Using the vector R ″ 1×K And D' 1×K Calculating the number of sampling points P between two adjacent pulses 1×(N-1) ；
(5) From the number P of samples 1×(N-1) And calculating the repetition interval between two adjacent pulses according to the pulse stream signal parameters.
Further, the step (1) is carried out according to the following steps:
(1a) According to the radar transmitter principle, a mathematical model s of the intercepted ith radar pulse intermediate frequency signal in a transmitting and receiving period is constructed i (t)：
Wherein, a i (t) is the envelope function of the ith pulse signal, f i (t) and
respectively the frequency and phase change rule of the ith pulse signal,
is the arrival time of the ith pulse waveform,
for the pulse width tau of the ith pulse waveform i ，
The arrival time of the (i + 1) th pulse waveform,
pulse repetition interval Tr for ith pulse waveform i N (t) is channel Gaussian white noise;
(1b) Constructing pulse signal packets according to general characteristics of pulse waveforms intercepted by radar counterscout receiversMathematical model of the collateral a i (t)：
Wherein h is 1 (t) is a mathematical model of the rise phase, h 2 (t) is a mathematical model of the descent phase,
and
i is more than or equal to 1 and less than or equal to N at the boundary point of an ascending stage and a stable stage of the intercepted ith pulse waveform respectively;
(1c) Assuming that the noise of the signal in a propagation channel is white Gaussian noise n (t), synthesizing the characteristics of a transmitting signal and a receiver intercepting signal under ideal conditions, and obtaining a radar radiation source pulse stream signal
Wherein i is more than or equal to 1 and less than or equal to N,
the expression that the former only takes the vector with the same dimension as the latter to carry out multiplication operation.
Further, the step (2) is carried out according to the following steps:
(2a) Wavelet denoising is carried out on the pulse flow signal by adopting an empirical Bayes method based on Cauchy prior, and the pulse flow signal S is updated 100 (t)；
(2b) For radar radiation source pulse stream signal S N (t) performing Hilbert transform to obtain an analytic signal thereof
And get
The absolute value of (a) yields the envelope of the radar radiation source pulse stream signal,
(2c) Cutting A by rectangular window N The rising phase of the first pulse envelope of (t) serves as the reference signal r (t).
Further, the step (3) is carried out according to the following steps:
(3a) In A N (t) an envelope vector r 'of the same length as r (t) is taken from the start of the signal' 1 (t), mixing r (t) with r' 1 (t) performing correlation operation to obtain a correlation coefficient gamma of the two 1 ；
(3b) Continuously cutting r 'with equal length at intervals of L' j (t) performing correlation operation with R (t), and finally generating a vector R through M sliding correlations 1×M ＝[γ 1 ,γ 2 ,…,γ M ]；
(3c) For the correlation coefficient vector R 1×M Performing sliding pre-screening, taking the maximum value and corresponding address of M phase relation numbers according to each O group, and filling up less than O in each group with 0
Group of which
Representing upward integers to form a new vector of correlation coefficients
And address vector
Further, the step (4) is carried out according to the following steps:
(4a) Select a matching threshold Thre, pair
The correlation coefficient in (1) is compared and screened, if gamma is j Not less than Thre, retained gamma j And corresponding address asMatch vector P 1×N An element of (1); conversely, γ j =0, and simultaneously, the address is set to be zero, and finally, a new coefficient vector is obtained
And a new address vector
(4b) According to the new coefficient vector
The medium elements are aggregated by different peak value clusters, and the intervals between different clusters are all 0, and the detection is carried out
The correlation coefficient contained in each cluster is taken as the maximum value to form a vector r 1×N Calculating r 1×N The original address corresponding to each maximum correlation coefficient in the vector d 1×N ；
(4c) By means of an address vector d 1×N Determining a maximum correlation coefficient vector r 1×N The number P of sampling points between two adjacent maximum correlation coefficients 1×(N-1) ：
P 1×(N-1) ＝[d(1,2:N)-d(1,1:N-1)]*L。
Further, the step (5) is carried out according to the following steps:
the pulse flow signal parameter is the sampling rate f of the intermediate frequency signal of the radar radiation source pulse waveform s The repetition interval PRI = P of the radar radiation source pulse stream 1×(N-1) /f s 。
A radar radiation source PRI calculation system based on pulse rising edge correlation matching, comprising a computer readable storage medium and a processor;
the computer-readable storage medium is used for storing executable instructions;
the processor is used for reading executable instructions stored in the computer-readable storage medium and executing the method for calculating the radar radiation source PRI based on the pulse rising edge correlation matching.
A non-transitory computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, implements the above-mentioned method for calculating a pulse rising edge correlation matching-based radar radiation source PRI.
The invention has the beneficial effects that:
(1) The method has certain stability by intercepting the rising edge of a certain type of radar pulse signal by using the reconnaissance receiver, increases the dimensionality related to the signal by intercepting the rising edge containing the pulse as a reference signal and performing sliding correlation operation with the pulse stream so as to reduce the influence of noise on the detection amplitude and easily determine the number of sampling points between two adjacent pulses, thereby realizing the improvement of the PRI measurement calculation precision based on a signal processing method. The simulation result shows that when the signal-to-noise ratio is 15dB, the PRI calculation average error is 0.38 multiplied by 10 -3 μ s, the results are superior to other methods.
(2) The sliding step length L and the sampling value O can be adjusted according to the calculation precision and the complexity comprehensive measurement, and the variable requirements are met.
(3) The invention can be used for accurate offline measurement and analysis of the intercepted radar pulse signals and can also be used for calculating the PRI value of the radar pulse signals for online measurement and reference.
[ description of the drawings ]
FIG. 1 is a schematic process diagram of the algorithm of the present invention;
FIG. 2 is a waveform diagram before partial pulse denoising;
FIG. 3 is a waveform diagram after partial pulse denoising;
FIG. 4 is a partial pulse envelope diagram;
FIG. 5 is a graph of a portion of a correlation coefficient;
FIG. 6 is a graph of correlation coefficients after partial preselection of maxima;
FIG. 7 is a result error of a radar radiation source pulse stream PRI measurement calculation;
fig. 8 is a flowchart of a method for calculating a PRI of a radar radiation source based on correlation matching of rising edges of pulses according to an embodiment of the present invention.
[ detailed description ] embodiments
The invention is described in further detail below with reference to specific embodiments and the attached drawing figures.
Referring to fig. 1 and 8, the invention uses a segment of signal including pulse rising edge intercepted from pulse stream to make sliding correlation with pulse stream, and then determines the length of PRI by correlation coefficient, thereby realizing the measurement of PRI. The method comprises the following specific steps:
step one, generating a radar radiation source pulse signal flow:
according to the principle of a radar transmitter and the characteristics of a radar counterscout receiver, a mathematical model s of the ith intermediate frequency signal of a radar radiation source pulse stream is constructed i (t)：
Wherein, a i (t) =1 frequency variation law f i (t)＝f c *t+1/2*K*t 2 The carrier frequency of the intermediate frequency is f c =10MHz, bandwidth 5MHz, sampling frequency 100mhz, k =0.5mhz/μ s, initial phase
Unknown, pulse width
Pulse signal length L =1000, pulse repetition interval
Simulating the noise environment (white Gaussian noise) of the pulse signal in the propagation process, setting the signal-to-noise ratio as SNR, and calculating the average power P of the pulse signal s ＝1/L*∑|s i (t)| 2 Generating a length of 3000, average power of P n ＝P s /10 SNR/10 White gaussian noise n (t).
Mathematics for constructing an envelope of a pulse signal based on general characteristics of the pulse waveform captured by a radar anti-reconnaissance receiverModel (model)
Wherein the order is within a repetition period
h 2 (t)＝1，
Obtaining the envelope of the pulse signal in each repetition period
The dimension is 1000.
One complete cycle radar radiation source signal intercepted by receiver
Wherein
The expression that the former only takes the vector with the same dimension as the latter to carry out multiplication operation, and a signal flow S containing 100 pulse waveforms is generated 100 (t) the pulse waveform diagram thereof is shown with reference to fig. 2, and the number of pulses is 3,snr =15db.
Step two, extracting the radar radiation source pulse flow envelope and the reference signal:
wavelet denoising is carried out on the pulse flow signal by adopting an empirical Bayes method based on Cauchy prior, and a new pulse flow signal S is followed 100 (t), a waveform diagram of the pulse after noise reduction thereof is shown with reference to fig. 3.
For radar radiation source pulse stream signal S 100 (t) performing Hilbert transform to obtain an analytic signal thereof
And get
The absolute value of (a) yields the envelope of the radar radiation source pulse stream signal,
of which 3 pulse envelope diagrams are shown with reference to figure 4.
(2b) Cutting out A by rectangular window 100 The rising phase of the first pulse envelope of (t) serves as the reference signal r (t) with a dimension of 150.
Step three, sliding correlation operation:
in A 100 (t) an envelope vector r 'of the same length as r (t) is taken from the start of the signal' 1 (t), mixing r (t) and r' 1 (t) performing correlation operation to obtain a correlation coefficient gamma of the two 1 ＝1。
Continuously cutting r 'with equal length by taking the sliding step length as 5' j (t), performing correlation operation with R (t), and finally generating a vector R through 59971 sliding correlations 1×59971 In the partial relationship curve, as shown in fig. 5, the maximum peak of the correlation coefficient indicates the position where the rising edge of each pulse waveform matches the reference signal, and the number of sampling points between adjacent PRIs can be determined by determining the position of each peak, so as to calculate the PRI value.
In order to more accurately find the position of the maximum value of the correlation coefficient, R is firstly aligned 1×59971 Performing sliding pre-screening, taking the maximum value and the corresponding label of each 10 correlation coefficients, and filling zero in less than 10 correlation coefficients to form a new correlation coefficient vector R' 1×5998 And an address vector D 1×5998 。
Step four, determining the number of sampling points between adjacent PRIs:
selecting a matching threshold of 0.8, to R' 1×5998 Is compared with the correlation coefficient ofComparison of screening, if γ j Not less than 0.8, retaining gamma j And a corresponding address; conversely, γ j =0, resulting in a new coefficient vector R ″ 1×5998 An address vector D 'corresponding to each vector element' 1×5998 Wherein the new coefficient vector may be as shown with reference to fig. 6.
According to the new coefficient vector R ″ 1×5998 The middle elements are aggregated by different peak value clusters, the intervals between different clusters are all 0, and R is detected 1×5998 The correlation coefficient contained in each cluster is taken as the maximum value to form a vector r 1×100 Calculating r 1×100 The original address corresponding to each maximum correlation coefficient in the vector d 1×100 ，r 1×100 The interval between two adjacent maximum correlation coefficients is PRI.
By means of address vectors d 1×100 Determining a maximum correlation coefficient vector r 1×100 The number P of sampling points between two adjacent maximum correlation coefficients 1×99 ：P 1×99 ＝[d(1,2:100)-d(1,1:99)]*5。
Step five, calculating the repetition interval between two adjacent pulses:
according to the sampling rate f of the intermediate frequency signal of the radar radiation source pulse waveform s =100MHz, the repetition interval PRI = P of the radar radiation source pulse stream 1×99 Per 100, units are in μ s.
Error in PRI measurement for the method of the invention was calculated: PRI err Where MNum is the number of monte carlo experiments performed in the present invention, and the value is 1000, the average error of the result of measuring the PRI value (99) with the pulse number of 100 under the conditions of the signal-to-noise ratio of 10dB and 15dB is shown in fig. 7. When the SNR is 15dB, the average error of PRI calculation is 0.38X 10 -3 μ s, and the comparison of the results of "analysis of the measurement precision factor and simulation verification of the radar-limited PRI" (hereinafter referred to as a comparison method) published in the modern defense technology, 2 nd month in 2009, with respect to the results shown in table 1, the error of the PRI calculated by the method of the present invention is smaller than that of the comparison method.
TABLE 1
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: although the present invention has been described in detail with reference to the above embodiments, it should be understood by those skilled in the art that: modifications and equivalents may be made to the embodiments of the invention without departing from the spirit and scope of the invention, which is to be covered by the claims.
Claims (8)
1. A radar radiation source PRI calculation method based on pulse rising edge correlation matching is characterized by comprising the following steps:
(1) According to the principle of a radar transmitter and the characteristics of a radar counterscout receiver intercepting signal waveforms, a mathematic model s of the ith intermediate frequency pulse signal of a radar radiation source pulse stream is constructed i (t) and a signal stream S comprising N pulse waveforms N (t)；
(2) Extracting said signal stream S N Envelope A of (t) N (t) and cutting A N (t) the rising phase of the first pulse envelope as a reference signal r (t);
(3) According to the calculation requirement, a reference signal r (t) and an envelope A are combined N (t) performing M sliding correlation operations according to the compartment L to obtain a correlation coefficient vector R 1×M And taking the maximum value and the corresponding address in each group of O (less than O is filled with 0) to obtain a new correlation coefficient vector R ′ 1×K And an address vector D 1×K Where L and O are determined according to computational accuracy requirements, M is the signal envelope length divided by L and rounded up,
(round up);
(4) Comparing correlation coefficient vector R' 1×K Determining a matching threshold Thre, reserving the correlation coefficient and the corresponding address which are greater than Thre, and generating a matching vector R ″ 1×K And address vector D' 1×K Using the vector R ″) 1×K And D' 1×K Calculating the number of sampling points P between two adjacent pulses 1×(N-1) ；
(5) From the number P of samples 1×(N-1) And calculating the repetition interval between two adjacent pulses according to the pulse stream signal parameters.
2. The method of claim 1, wherein step (1) is performed by:
(1a) According to the radar transmitter principle, a mathematical model s of the intercepted ith radar pulse intermediate frequency signal in a transmitting and receiving period is constructed i (t)：
Wherein, a i (t) is the envelope function of the ith pulse signal, f i (t) and
respectively the frequency and phase change rule of the ith pulse signal,
is the arrival time of the ith pulse waveform,
for the pulse width tau of the ith pulse waveform i ，
The arrival time of the (i + 1) th pulse waveform,
pulse repetition interval Tr for ith pulse waveform i N (t) is channel Gaussian white noise;
(1b) Reconnaissance receiver based on radar countermeasuresGeneral characteristics of intercepted pulse waveform, and constructing mathematical model a of pulse signal envelope i (t)：
Wherein h is 1 (t) is a mathematical model of the rise phase, h 2 (t) is a mathematical model of the descent phase,
and
i is more than or equal to 1 and less than or equal to N at the boundary point of an ascending stage and a stable stage of the intercepted ith pulse waveform respectively;
(1c) Assuming that the noise of the signal in a propagation channel is white Gaussian noise n (t), synthesizing the characteristics of a transmitting signal and a receiver intercepting signal under ideal conditions, and obtaining a radar radiation source pulse stream signal
Wherein i is more than or equal to 1 and less than or equal to N,
the expression that the former only takes the vector with the same dimension as the latter to carry out multiplication operation.
3. The method of claim 1, wherein step (2) is performed by:
(2a) Wavelet denoising is carried out on the pulse flow signal by adopting an empirical Bayes method based on Cauchy prior, and the pulse flow signal S is updated 100 (t)；
(2b) For radar radiation source pulse stream signal S N (t) performing Hilbert transform to obtain an analytic signal thereof
And get
The absolute value of (a) yields the envelope of the radar radiation source pulse stream signal,
(2c) Cutting A by rectangular window N The rising phase of the first pulse envelope of (t) serves as the reference signal r (t).
4. The method of claim 1, wherein step (3) is performed by:
(3a) At A N (t) an envelope vector r 'of the same length as r (t) is taken from the start of the signal' 1 (t), mixing r (t) with r' 1 (t) performing correlation operation to obtain a correlation coefficient gamma of the two 1 ；
(3b) Continuously cutting r 'with equal length at intervals of L' j (t) performing correlation operation with R (t), and finally generating a vector R through M sliding correlations 1×M ＝[γ 1 ,γ 2 ,…,γ M ]；
(3c) For the correlation coefficient vector R 1×M Performing sliding pre-screening, taking the maximum value and corresponding address of M phase relation numbers according to each O group, and supplementing less than O numbers in each group with 0 to obtain a total
Group (b) of
Representing upward integers to form a new vector of correlation coefficients
And address vector
5. The method of claim 1, wherein the step (4) is performed by:
(4a) Select a matching threshold Thre, pair
The correlation coefficient in (1) is compared and screened, if gamma is j Not less than Thre, retained gamma j And corresponding address as a matching vector P 1×N An element of (1); conversely, γ j =0, while setting its address to zero, and finally obtaining a new coefficient vector
And a new address vector
(4b) According to the new coefficient vector
The medium elements are aggregated by different peak value clusters, and the intervals between different clusters are all 0, and the detection is carried out
The correlation coefficient contained in each cluster is taken as the maximum value to form a vector r 1×N Calculating r 1×N The original address corresponding to each maximum correlation coefficient in the vector d 1×N ；
(4c) By means of address vectors d 1×N Determining a maximum correlation coefficient vector r 1×N The number P of sampling points between two adjacent maximum correlation coefficients 1×(N-1) ：
P 1×(N-1) ＝[d(1,2:N)-d(1,1:N-1)]*L。
6. The method of claim 1, wherein step (5) is performed by:
the pulse flow signal parameter is the sampling rate f of the intermediate frequency signal of the radar radiation source pulse waveform s The repetition interval PRI = P of the radar radiation source pulse stream 1×(N-1) /f s 。
7. A radar radiation source PRI calculation system based on pulse rising edge correlation matching, characterized by: including computer-readable storage media and processors;
the computer-readable storage medium is used for storing executable instructions;
the processor is configured to read executable instructions stored in the computer-readable storage medium, and execute the method for calculating the PRI of the radar radiation source based on the pulse rising edge correlation matching according to any one of claims 1 to 6.
8. A non-transitory computer-readable storage medium characterized in that: stored thereon a computer program which, when being executed by a processor, carries out the method for calculating a pulse rising edge correlation matching based radar radiation source PRI according to any one of claims 1 to 6.
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