A radar emitter pulse repetition interval (PRI) calculation method based on pulse rising edge correlation matching

Abstract

This invention discloses a method for calculating the PRI (Primary Indicator) of a radar radiation source based on pulse rising edge correlation matching. It utilizes the stable and significant characteristics of the rising edge of a radar pulse signal. By extracting the rising edge portion of the intercepted radar pulse signal and performing correlation matching with the entire pulse stream signal, the number of sampling points included in the complete PRI is determined, and finally, the PRI of the radar radiation source is calculated. The implementation steps are: 1. Generate the intermediate frequency (IF) signal of the radar radiation source pulse stream; 2. Extract the rising edge of the IF pulse signal of the radar radiation source as a reference signal; 3. Perform a sliding correlation operation between the reference signal and the entire pulse stream signal; 4. Determine the number of sampling points between adjacent pulses based on the correlation coefficient; 5. Calculate the PRI value of the radar radiation source. This invention can reduce the influence of noise on the detection amplitude, thereby improving the accuracy of PRI measurement and calculation.

Description

[Technical Field]

[0001] This invention belongs to the field of electronic countermeasures reconnaissance, specifically a method for calculating the PRI (Primary Intensity Repetition) of radar radiation sources based on pulse rising edge correlation matching. This invention can be used in electronic intelligence reconnaissance, electronic support, and threat warning equipment for the accurate measurement of the pulse repetition interval of intercepted radar radiation source signals. [Background Technology]

[0002] In radar countermeasures and reconnaissance, the receiver is responsible for measuring the conventional parameters of the intercepted signal, including pulse direction of arrival, pulse arrival time, pulse signal load, pulse width, and pulse amplitude. Analysis of these conventional parameters allows for comprehensive and multi-layered understanding of the target radar, thereby revealing the target's intentions and dynamics. Therefore, accurate measurement of the conventional parameters of intercepted radar radiation source signals is of great significance for radar countermeasures and reconnaissance, and the Pulse Recurrence Interval (PRI), as one of these conventional parameters, is no exception.

[0003] The measurement of radar source pulse repetition interval primarily relies on signal arrival time and signal amplitude. Under ideal conditions, the radar source pulse envelope is rectangular, and the signal arrival time obtained through threshold detection is error-free. However, in real-world, complex, and variable electromagnetic environments, the pulse signal envelope intercepted by the reconnaissance receiver is usually not a standard rectangle, resulting in distortion. This leads to a decrease in the accuracy of arrival time and pulse repetition interval measurements. Generally, we consider the presence of pulse rise time to be the main cause of measurement error in repetition intervals. Due to environmental noise, pulse envelope amplitude is distorted, and threshold detection introduces errors, thus reducing the accuracy of pulse repetition interval measurements.

[0004] The article "Application of Constant Ratio Triggering Method in High-Precision Radar PRI Measurement," published in the January 2007 issue of *Modern Radar*, proposed a constant ratio triggering method to calculate the corresponding floating threshold value for each radar pulse in real time, effectively overcoming the triggering error caused by a fixed threshold value and improving the measurement accuracy of the pulse repetition interval to a certain extent. However, this method does not adequately address the impact of noise amplitude on the determination of whether the threshold time is advanced or delayed.

[0005] The paper "A PRI estimation method for high pulse loss rate" published in Aerospace Electronic Countermeasures focuses on PRI estimation under pulse loss conditions, rather than addressing the accuracy of PRI measurement itself.

[0006] The article "Analysis and Simulation Verification of Factors Limiting Radar PRI Measurement Accuracy", published in the February 2009 issue of Modern Defense Technology, focuses on analyzing the factors affecting PRI measurement accuracy, such as receiver bandwidth, noise reduction methods, and adaptive floating threshold. [Summary of the Invention]

[0007] Therefore, it is necessary to provide a radar radiation source PRI calculation method based on pulse rising edge correlation matching to address the aforementioned problems in PRI measurement and improve measurement accuracy.

[0008] To address the aforementioned problems in the prior art, this invention provides a method for calculating the PRI of radar radiation sources based on pulse rising edge correlation matching.

[0009] The technical problem to be solved by this invention is achieved through the following technical solution:

[0010] A method for calculating the PRI (Primary Intake) of radar radiation sources based on pulse rising edge correlation matching, characterized by the following steps:

[0011] (1) Based on the principle of radar transmitter and the characteristics of the signal waveform intercepted by radar countermeasure reconnaissance receiver, a mathematical model s of the i-th intermediate frequency pulse signal of radar radiation source pulse flow is constructed. i (t) and the signal flow S containing N pulse waveforms N (t);

[0012] (2) Extract the signal stream S N The envelope A of (t) N (t), and extract A N The rising phase of the first pulse envelope of (t) is used as the reference signal r(t);

[0013] (3) According to the calculation requirements, the reference signal r(t) and the envelope A are... N (t) Perform M sliding correlation operations according to the compartment L to obtain the correlation coefficient vector R. 1×M Then, by taking the maximum value and the corresponding address of each group of O (padded with 0 if less than O), a new correlation coefficient vector R′ is obtained. 1×K and address vector D 1×K Where L and O are determined according to the required calculation accuracy, and M is the signal envelope length divided by L and rounded up. (Round up);

[0014] (4) Compare the correlation coefficient vector R′ 1×K Based on the values ​​in the table, determine the matching threshold Thre, retain the correlation coefficients and corresponding addresses greater than Thre, and generate the matching vector R″. 1×K and address vector D′ 1×K Using vector R″ 1×K and D′ 1×K Calculate the number of sampling points P between two adjacent pulses. 1×(N-1) ;

[0015] (5) The number of sampling points P 1×(N-1)The repetition interval between two adjacent pulses is calculated using pulse flow signal parameters.

[0016] Furthermore, step (1) is performed as follows:

[0017] (1a) Based on the principle of radar transmitter, construct a mathematical model s of the intercepted i-th radar pulse intermediate frequency signal within one transmission and reception cycle. i (t):

[0018]

[0019] Among them, a i (t) is the envelope function of the i-th pulse signal, f i (t) and The frequency and phase variation patterns of the i-th pulse signal are respectively shown. Let be the arrival time of the i-th pulse waveform. The pulse width τ of the i-th pulse waveform i , Let be the arrival time of the (i+1)th pulse waveform. The pulse repetition interval Tr of the i-th pulse waveform i n(t) is the channel's white Gaussian noise;

[0020] (1b) Based on the general characteristics of the pulse waveform intercepted by the radar countermeasure reconnaissance receiver, construct a mathematical model of the pulse signal envelope. i (t):

[0021]

[0022] Where h1(t) is the mathematical model for the rising phase, and h2(t) is the mathematical model for the falling phase. and These are the dividing points between the rising and stable phases and the falling phase of the captured i-th pulse waveform, respectively, where 1≤i≤N;

[0023] (1c) Assuming the noise in the propagation channel is Gaussian white noise n(t), and considering the characteristics of the transmitted signal and the intercepted signal under ideal conditions, the radar radiation source pulse stream signal Where 1≤i≤N, This means that the former only takes the leftmost vector with the same dimension as the latter for multiplication.

[0024] Furthermore, step (2) is performed as follows:

[0025] (2a) Wavelet denoising based on the empirical Bayesian method with Cauchy prior is applied to the pulse stream signal, and the pulse stream signal S is updated. 100 (t);

[0026] (2b) Regarding the radar radiation source pulse stream signal S N The analytic signal is obtained by performing a Hilbert transform on (t). and take The absolute value is the envelope of the radar radiation source pulse stream signal.

[0027] (2c) Use a rectangular window to capture A N The rising phase of the first pulse envelope of (t) is used as the reference signal r(t).

[0028] Furthermore, step (3) is performed as follows:

[0029] (3a) In A N From the starting point of the signal, extract the envelope vector r′1(t) with the same length as r(t). Perform correlation operation on r(t) and r′1(t) to obtain the correlation coefficient γ1 between them.

[0030] (3b) Continue to cut off equal lengths of r′ at intervals of L. j (t), and r(t) are correlated with each other, and finally the vector R is generated after M sliding correlation operations. 1×M =[γ1,γ2,…,γ M ];

[0031] (3c) For the correlation coefficient vector R 1×M Perform a sliding pre-screening process, taking the maximum value and corresponding address from the M correlation coefficients in groups of O, padding each group with 0 if there are fewer than O values. This process is repeated for a total of... Group, among which This indicates rounding up to the nearest integer to form a new correlation coefficient vector. and address vector

[0032] Furthermore, step (4) is performed as follows:

[0033] (4a) Select the matching threshold Thre, for Compare and filter based on the correlation coefficients in the data; if γ j ≥Thre, retain γ j and the corresponding address, as the matching vector P 1×N The element; conversely, γ j = 0, and simultaneously set its address to zero, ultimately resulting in a new coefficient vector. and the new address vector

[0034] (4b) Based on the new coefficient vector The elements are aggregated from different peak clusters, and the interval between different clusters is 0. Detection Each cluster contains correlation coefficients, and the maximum value among them is used to form a vector r. 1×N Calculate r 1×N The original address corresponding to each maximum correlation coefficient is formed into a vector d. 1×N ;

[0035] (4c) via address vector d 1×N Determine the maximum correlation coefficient vector r 1×N The number of sampling points P between two adjacent maximum correlation coefficients 1×(N-1) :

[0036] P 1×(N-1) = [d(1,2:N)-d(1,1:N-1)]*L.

[0037] Furthermore, step (5) is performed as follows:

[0038] The pulse stream signal parameters are the sampling rate f of the intermediate frequency signal of the radar radiation source pulse waveform. s Then the repetition interval PRI of the radar radiation source pulse stream is P 1×(N-1) / f s .

[0039] A radar radiation source PRI calculation system based on pulse rising edge correlation matching includes a computer-readable storage medium and a processor;

[0040] The computer-readable storage medium is used to store executable instructions;

[0041] The processor is used to read executable instructions stored in the computer-readable storage medium and execute the above-described radar radiation source PRI calculation method based on pulse rising edge correlation matching.

[0042] A non-transitory computer-readable storage medium storing a computer program that, when executed by a processor, implements the aforementioned method for calculating the radar radiation source PRI based on pulse rising edge correlation matching.

[0043] The beneficial effects of this invention are:

[0044] (1) This invention utilizes the stability of the rising edge of a certain type of radar pulse signal intercepted by a reconnaissance receiver. By extracting the pulse rising edge as a reference signal and performing a sliding correlation operation with the pulse stream, the dimension of signal correlation is increased, thereby reducing the impact of noise on the detection amplitude and making it easier to determine the number of sampling points between two adjacent pulses. This achieves improved PRI measurement accuracy based on signal processing methods. Simulation results show that the average PRI calculation error of this patented method is 0.38 × 10⁻⁶ when the signal-to-noise ratio is 15 dB. -3 The results are better than other methods in μs.

[0045] (2) In this invention, the sliding step size L and the sampled value O can be adjusted according to the comprehensive consideration of calculation accuracy and complexity to meet variable requirements.

[0046] (3) This invention can be used for offline precise measurement and analysis of intercepted radar pulse signals, and can also serve as a reference for online measurement and calculation of radar pulse signal PRI values. [Attached Image Description]

[0047] Figure 1 This is a flowchart illustrating the algorithm principle of this invention.

[0048] Figure 2 The waveform before partial pulse denoising is shown.

[0049] Figure 3 This is a waveform diagram after partial pulse denoising;

[0050] Figure 4 This is a partial pulse envelope diagram;

[0051] Figure 5 This is a partial correlation coefficient curve;

[0052] Figure 6 This is a correlation coefficient curve after partially selecting the maximum value;

[0053] Figure 7 Error in the measurement and calculation results of the radar radiation source pulse current PRI;

[0054] Figure 8 This is a flowchart of one embodiment of a radar radiation source PRI calculation method based on pulse rising edge correlation matching according to the present invention.

Detailed Implementation Methods

[0055] The present invention will now be described in further detail with reference to specific embodiments and accompanying drawings.

[0056] Reference Figure 1 and Figure 8 As shown, this invention utilizes a segment of signal, including the rising edge of the pulse, extracted from the pulse stream, and performs a sliding correlation with the pulse stream. The length of the PRI is then determined by the correlation coefficient, thereby achieving the measurement of the PRI. The specific steps are as follows:

[0057] Step 1: Generate radar radiation source pulse signal stream:

[0058] Based on the principles of radar transmitters and the characteristics of radar countermeasures and reconnaissance receivers, a mathematical model s of the i-th intermediate frequency signal of the radar radiation source pulse flow is constructed. i (t):

[0059]

[0060] Among them, a i (t)=1 Frequency variation law f i (t)=f c *t+1 / 2*K*t 2 The intermediate frequency carrier frequency is f c =10MHz, bandwidth 5MHz, sampling frequency 100MHz, K = 0.5MHz / μs, initial phase Unknown, pulse width The pulse signal length is L = 1000, and the pulse repetition interval is...

[0061] Simulate the noise environment (Gaussian white noise) during the propagation of a simulated pulse signal, set the signal-to-noise ratio (SNR) to SNR, and calculate the average power P of the pulse signal. s =1 / L*∑|s i (t)| 2 The generated length is 3000 and the average power is P. n =P s / 10 SNR / 10 Gaussian white noise n(t).

[0062] Based on the general characteristics of pulse waveforms intercepted by radar countermeasures reconnaissance receivers, a mathematical model of the pulse signal envelope is constructed.

[0063]

[0064] Among them, within a repeating cycle, let h2(t) = 1, Obtain the pulse signal envelope within each repetition cycle. The dimension is 1000.

[0065] The receiver intercepts a complete cycle of radar radiation source signal. in This means that the former only takes the leftmost vector with the same dimension as the latter for multiplication, producing a signal stream S containing 100 pulse waveforms. 100 (t), its pulse waveform diagram is referenced. Figure 2 As shown, the number of pulses is 3, and the SNR = 15dB.

[0066] Step 2: Extract the radar radiation source pulse flow envelope and reference signal:

[0067] Wavelet denoising based on an empirical Bayesian method with Cauchy prior is applied to the pulse stream signal to update the pulse stream signal S. 100 (t), its denoised pulse waveform diagram is referenced. Figure 3 As shown.

[0068] For radar radiation source pulse stream signal S 100 The analytic signal is obtained by performing a Hilbert transform on (t). and take The absolute value is the envelope of the radar radiation source pulse stream signal. Three pulse envelope diagrams can be referenced. Figure 4 As shown.

[0069] (2b) Use a rectangular window to cut out A 100 The rising phase of the first pulse envelope of (t) is used as the reference signal r(t), with a dimension of 150.

[0070] Step 3, related sliding operations:

[0071] In A 100 From the starting point of the signal, extract the envelope vector r′1(t) with the same length as r(t). Perform a correlation operation between r(t) and r′1(t) to obtain the correlation coefficient γ1 = 1.

[0072] Continue to cut equal lengths r′ with a sliding step size of 5. j (t), and r(t) are correlated with each other, and finally, after 59971 sliding correlation operations, a vector R is generated. 1×59971 Some of the correlation coefficient curves can be referenced. Figure 5 As shown, the maximum peak value of the correlation coefficient represents the position where the rising edge of each pulse waveform matches the reference signal. By determining the position of each peak value, the number of sampling points between adjacent PRI values ​​can be determined, and then the PRI value can be calculated.

[0073] To more accurately locate the position of the maximum correlation coefficient, first analyze R... 1×59971 Perform a sliding pre-screening process, taking the maximum value and corresponding label for every 10 correlation coefficients, padding with zeros if there are fewer than 10, to form a new correlation coefficient vector R′. 1×5998 and address vector D 1×5998 .

[0074] Step 4: Determine the number of sampling points between adjacent PRIs:

[0075] Selecting a matching threshold of 0.8, for R′ 1×5998 Compare and filter based on the correlation coefficients in the data; if γ j ≥0.8, retain γ j and the corresponding address; conversely, γ j =0, resulting in a new coefficient vector R″ 1×5998 and the address vector D′ corresponding to each vector element 1×5998 The new coefficient vector can be referenced. Figure 6 As shown.

[0076] According to the new coefficient vector R″ 1×5998 The elements are aggregated into different peak clusters, and the interval between different clusters is 0. The detection R″ 1×5998 Each cluster contains correlation coefficients, and the maximum value among them is used to form a vector r. 1×100 Calculate r 1×100 The original address corresponding to each maximum correlation coefficient is formed into a vector d. 1×100 r 1×100 The interval between two adjacent maximum correlation coefficients is PRI.

[0077] via address vector d 1×100 Determine the maximum correlation coefficient vector r 1×100 The number of sampling points P between two adjacent maximum correlation coefficients 1×99 :P 1×99 =[d(1,2:100)-d(1,1:99)]*5.

[0078] Step 5: Calculate the repetition interval between two adjacent pulses:

[0079] Based on the sampling rate f of the intermediate frequency signal of the radar radiation source pulse waveform s =100MHz, then the repetition interval PRI of the radar radiation source pulse stream is P 1×99 / 100, unit is μs.

[0080] Calculate the error of PRI measurement using the method of this invention: PRI err = 1 / MNum*∑|PRI-30|, where MNum is the number of Monte Carlo experiments performed in this invention, with a value of 1000. Under signal-to-noise ratio conditions of 10dB and 15dB, the average error of the PRI value (99 pulses) with 100 pulses is as follows: Figure 7 As shown. When the signal-to-noise ratio is 15dB, the average error of PRI calculation is 0.38×10. -3 The results of the method of the present invention are compared with those of the "Analysis and Simulation Verification of Factors Limiting the Accuracy of Radar PRI Measurement" (hereinafter referred to as the comparison method) published in the February 2009 issue of Modern Defense Technology. Table 1 shows that the error of the method of the present invention in calculating PRI is smaller than that of the comparison method.

[0081] Table 1

[0082]

[0083] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can 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, etc.) containing computer-usable program code.

[0084] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can 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, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0085] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0086] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0087] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for calculating the PRI of a radar radiation source based on pulse rising edge correlation matching, characterized in that, Includes the following steps: Step S1: Based on the principle of radar transmitters and the characteristics of signal waveforms intercepted by radar countermeasures and reconnaissance receivers, construct a mathematical model of the i-th intermediate frequency pulse signal of the radar radiation source pulse flow. and a signal stream containing N pulse waveforms ; Step S2: Extract the signal stream envelope and intercept The rising phase of the first pulse envelope is used as the reference signal. ; Step S3: According to the calculation requirements, the reference signal With envelope Perform M sliding correlation operations at intervals L to obtain the correlation coefficient vector. And by grouping every O values, the maximum value and its corresponding address are taken to obtain a new correlation coefficient vector. and address vector If there are fewer than 0, pad with 0. Where L and O are determined according to the required calculation accuracy, and M is the signal envelope length divided by L and rounded up. And round up; Step S4: Compare the correlation coefficient vectors Based on the values ​​in the table, determine the matching threshold Thre, retain the correlation coefficients and corresponding addresses greater than Thre, and generate a matching vector. and address vector Using vectors and Calculate the number of sampling points between two adjacent pulses ; Step S5: Based on the number of sampling points Calculate the repetition interval between two adjacent pulses using pulse flow signal parameters; Step S1 is performed as follows: S1a. Based on the principle of radar transmitters, construct a mathematical model of the intercepted i-th radar pulse intermediate frequency signal within one transmission and reception cycle. : ， in, Let be the envelope function of the i-th pulse signal. and These represent the frequency and phase variation patterns of the i-th pulse signal, respectively. Let be the arrival time of the i-th pulse waveform. The pulse width of the i-th pulse waveform , Let be the arrival time of the (i+1)th pulse waveform. The pulse repetition interval of the i-th pulse waveform , The channel is Gaussian white noise; S1b. Based on the general characteristics of pulse waveforms intercepted by radar countermeasures reconnaissance receivers, construct a mathematical model of the pulse signal envelope. : ， in, For the mathematical model of the rising phase, For the mathematical model of the descent phase, and These represent the rising and stable phases of the captured i-th pulse waveform, and the boundary point between the stable and falling phases. ; S1c, Assume the noise in the propagation channel is Gaussian white noise. Based on the characteristics of the transmitted signal and the intercepted signal under ideal conditions, the radar radiation source pulse stream signal ,in, , This means that the former only takes the leftmost vector with the same dimension as the latter for multiplication; Step S3 is performed as follows: S3a, in Extracting from the starting point of the signal and Envelope vectors of the same length ,Will and Perform correlation calculations to obtain the correlation coefficient between the two. ; S3b, continue cutting equal lengths at intervals of L. ,and Perform relevant calculations, and finally generate a related vector after M sliding operations. ; S3c, Regarding the correlation coefficient vector Perform a sliding pre-screening process, taking the maximum value and corresponding address from the M correlation coefficients, grouping them into sets of O, padding each group with zeros if there are fewer than O values, for a total of... Group, among which This indicates rounding up to the nearest integer to form a new correlation coefficient vector. and address vector ; Step S4 is performed as follows: S4a, Select the matching threshold Thre, for Compare and filter based on the correlation coefficients in the data. ,reserve and the corresponding address, as a matching vector Elements; conversely, At the same time, its address is set to zero, and finally, a new coefficient vector is obtained. and the new address vector ; S4b, Based on the new coefficient vector The elements are aggregated from different peak clusters, and the interval between different clusters is 0. Detection Each cluster contains correlation coefficients, and the maximum value among them is used to form a vector. ,calculate The original address corresponding to each maximum correlation coefficient is formed into a vector. ; S4c, via address vector Determine the vector of maximum correlation coefficients Number of sampling points between two adjacent maximum correlation coefficients : 。 2. The method according to claim 1, characterized in that, Step S5 is performed as follows: The pulse stream signal parameters are the sampling rate of the intermediate frequency signal of the radar radiation source pulse waveform. The repetition interval of the radar radiation source pulse stream .

3. A radar radiation source PRI calculation system based on pulse rising edge correlation matching, characterized in that: Includes computer-readable storage media and processors; The computer-readable storage medium is used to store executable instructions; The processor is used to read executable instructions stored in the computer-readable storage medium and execute the radar radiation source PRI calculation method based on pulse rising edge correlation matching as described in any one of claims 1-2.

4. A non-transitory computer-readable storage medium, characterized in that: It stores a computer program that, when executed by a processor, implements the radar radiation source PRI calculation method based on pulse rising edge correlation matching as described in any one of claims 1-2.

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