A signal parameter identification method, system and device based on FPGA

Abstract

The present invention belongs to the field of signal reconnaissance, and specifically relates to a signal parameter identification method, system and device based on FPGA. The method comprises: dividing a signal to be measured into N segments, performing Fourier calculation on each segment of the signal to be measured to obtain a Fourier calculation value, and modulo-ing the Fourier calculation value to obtain a maximum subscript, i.e., an instantaneous frequency; comparing N instantaneous frequencies obtained from the N segments of the signal to obtain a maximum instantaneous frequency and a minimum instantaneous frequency, and calculating a signal bandwidth and a center frequency point; performing K-point differential on a time-frequency diagram of the signal to be measured to determine a frequency modulation mode of the signal to be measured, or performing square and fourth power calculation on the signal to be measured to obtain a quadratic spectrum and a quartic spectrum, multiplying the signal mean of the quadratic spectrum and the quartic spectrum in a sliding window by a threshold gain to obtain a judgment threshold, and comparing the threshold with the window center judgment point to determine a phase modulation modulation mode of the signal to be measured. The present application has the effect of accurately identifying the modulation mode and obtaining more accurate bandwidth and frequency point.

Description

Technical Field

[0001] The present invention belongs to the field of signal reconnaissance, and in particular relates to a signal parameter identification method, system and device based on FPGA. Background Art

[0002] Pulse system identification and parameter measurement are important concepts in signal processing and communications, particularly in radar, communications, and sonar systems. Pulse system identification involves analyzing received signals to identify the underlying pulse waveform or encoding scheme. Parameter measurement involves analyzing received signals to extract key signal-related parameters, including bandwidth and frequency. In electronic warfare, accurate information about the current electromagnetic environment is essential for accurate situational assessment and countermeasure strategies. Electronic reconnaissance equipment requires the identification of fundamental information such as the radiation source's modulation system, bandwidth, frequency, and pulse width.

[0003] In related technologies, the main techniques for signal parameter identification include: a signal generation module; a pulse formation module; an identification module, including a phase-modulated signal identification module and a frequency-modulated signal identification module; a frequency measurement module, including FFT frequency measurement and instantaneous phase difference frequency measurement; and a comprehensive discrimination module. Signal identification uses a coarse-to-fine approach, first performing coarse identification using a 3dB bandwidth, classifying signals into two categories: phase-modulated signals and frequency-modulated signals. Phase-modulated signals include BPSK, QPSK, and conventional radar signals; frequency-modulated signals include LFM, NLFM, VFM, and SFM.

[0004] Regarding the above-mentioned related technologies, the signal recognition is performed in a variety of ways, the recognition speed is slow, and the bandwidth and frequency of the signal cannot be accurately obtained. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide a signal parameter identification method, system and device based on FPGA, which can quickly and accurately identify the frequency, bandwidth and modulation mode of the signal to be measured.

[0006] A signal parameter identification method based on FPGA, comprising:

[0007] Dividing the signal to be measured into N segments, performing Fourier calculation on each segment of the signal to be measured to obtain a Fourier calculation value, taking the modulus of the Fourier calculation value to obtain a Fourier modulus value, and obtaining a maximum subscript of the Fourier modulus value, sorting the maximum subscripts to obtain a maximum subscript value and a minimum subscript value among the N Fourier modulus values, and obtaining a corresponding maximum instantaneous frequency, a minimum instantaneous frequency, and a time-frequency diagram of the signal to be measured according to the maximum subscript value and the minimum subscript value;

[0008] Calculating the signal bandwidth and the center frequency according to the maximum instantaneous frequency and the minimum instantaneous frequency;

[0009] The time-frequency diagram of the signal to be measured is used to obtain K-point differences to determine the frequency modulation mode of the signal to be measured, wherein the frequency modulation mode includes positive and negative linear frequency modulation, dual linear frequency modulation, triangle frequency modulation, sawtooth frequency modulation and sine frequency modulation, or

[0010] Squaring the signal to be measured to obtain a square signal, performing Fourier transform on the square signal to obtain a quadratic spectrum, and squaring the square signal again and performing Fourier transform on the square signal to obtain a quartic spectrum;

[0011] Set the sliding window size;

[0012] Calculating the quadratic signal average and the quartic signal average of the quadratic spectrum and the quartic spectrum within the sliding window size;

[0013] Multiplying the average value of the quadratic signal and the average value of the quartic signal by a threshold gain to obtain a decision threshold, comparing the decision threshold with the center point of the sliding window to determine the phase modulation mode of the signal to be measured, wherein the phase modulation mode includes QPSK phase modulation and BPSK phase modulation;

[0014] The signal bandwidth, center frequency, and frequency modulation or phase modulation modulation are used as parameter identification results of the signal to be measured.

[0015] Optionally, the step of obtaining K-point differences in the time-frequency graph of the signal to be measured to determine a frequency modulation mode of the signal to be measured, wherein the frequency modulation mode includes linear frequency modulation, triangle frequency modulation, sawtooth frequency modulation, and sine frequency modulation, and the linear frequency modulation includes positive linear frequency modulation, negative linear frequency modulation, and dual linear frequency modulation.

[0016] The time-frequency diagram of the signal to be measured is subjected to K-point differentiation to obtain a frequency point difference diagram;

[0017] Divide the frequency difference map into four intervals on average, and calculate the sum of the difference values ​​in each interval;

[0018] The frequency modulation mode of the signal to be tested is determined according to the sum of the difference values ​​and a preset frequency modulation rule.

[0019] Optionally, the preset frequency modulation rule includes:

[0020] When the sum of the differences of the four intervals is all positive or all negative, and the absolute value of the maximum or minimum value of the entire pulse differential value is close to the signal bandwidth, it is sawtooth frequency modulation;

[0021] When the sum of the differences of the four intervals is positive and does not meet the sawtooth frequency modulation condition, it is negative linear frequency modulation;

[0022] When the sum of the differences of the four intervals is negative and does not meet the sawtooth frequency modulation condition, it is positive linear frequency modulation;

[0023] When the sum of the differences in the four intervals changes to negative, positive, positive, and negative, or negative, negative, positive, and positive, and the last difference value in the second interval is close to 0, it is sinusoidal frequency modulation;

[0024] When the difference and change of the four intervals are positive, positive, negative and negative or negative, negative, positive and positive and do not meet the sinusoidal frequency modulation conditions, it is bilinear frequency modulation;

[0025] When the difference and change of the four intervals are positive, negative, positive, negative or negative, positive, negative, positive, it is triangle wave frequency modulation.

[0026] Optionally, multiplying the average value of the quadratic signal and the average value of the quartic signal by a threshold gain to obtain a decision threshold, and comparing the decision threshold with the center point of the sliding window to determine the phase modulation mode of the signal to be measured includes:

[0027] Multiplying the average value of the secondary signal and the average value of the fourth signal by the threshold gain to obtain the secondary signal decision threshold and the fourth signal decision threshold respectively;

[0028] When the center point of the secondary signal sliding window is greater than the secondary signal decision threshold and the center point of the secondary signal sliding window is a maximum value, or the center point of the quartic signal sliding window is greater than the quartic signal decision threshold and the center point of the quartic signal sliding window is a maximum value point, then a secondary signal recording point or a quartic signal recording point is obtained;

[0029] The phase modulation mode of the signal to be measured is determined according to the secondary signal recording point and / or the quaternary signal recording point.

[0030] Optionally, determining the phase modulation mode of the signal to be measured according to the secondary signal recording point and / or the quaternary signal recording point includes:

[0031] When both the secondary spectrum and the quartic spectrum of the signal to be measured exist and there is only one secondary recording point and one quartic recording point, it is determined that the phase modulation mode of the signal to be measured is BPSK;

[0032] When the signal to be measured has only one fourth-order signal recording point in the fourth-order spectrum, it is determined that the phase modulation mode of the signal to be measured is QPSK.

[0033] Optionally, the step of using the signal bandwidth, center frequency, and frequency modulation or phase modulation as parameter identification results of the signal to be measured includes:

[0034] When the frequency modulation mode of the signal to be measured is positive linear frequency modulation and negative linear frequency modulation, a FIFO is used to record the preceding signals of the first M points and the following signals of the last M points of the signal to be measured within a pulse;

[0035] Performing conjugate multiplication on the preceding signal and the succeeding signal to obtain a preceding conjugate signal and a succeeding conjugate signal;

[0036] Performing Fourier transform on the preceding conjugate signal and the succeeding conjugate signal to obtain a preceding center frequency point and a succeeding center frequency point;

[0037] Calculate a corrected center frequency and the corrected signal bandwidth according to the previous center frequency and the subsequent center frequency;

[0038] The corrected central frequency point, the corrected signal bandwidth, and the frequency modulation mode are used as modification parameter identification results of the signal to be measured.

[0039] Optionally, when the signal to be measured is in a phase modulation mode, the signal to be measured is delayed by point Z to obtain a delayed signal, the delayed signal is conjugated to obtain a conjugate delayed signal, the conjugate delayed signal is multiplied by the signal to be measured, a Fourier transform is performed at point y, and the subscript of the maximum value is obtained from the y Fourier transform results;

[0040] According to the frequency domain value corresponding to the subscript of the maximum value, the bandwidth of the signal to be measured is obtained as the correction bandwidth.

[0041] A signal parameter identification system based on FPGA, comprising:

[0042] A first calculation module is configured to divide the signal to be measured into N segments, perform Fourier calculation on each segment of the signal to be measured to obtain a Fourier calculation value, modulo the Fourier calculation value to obtain a Fourier modulus value, obtain a maximum subscript of the Fourier modulus value, sort the maximum subscripts to obtain a maximum subscript value and a minimum subscript value among the N Fourier modulus values, and obtain a corresponding maximum instantaneous frequency value, a minimum instantaneous frequency value, and a time-frequency diagram of the signal to be measured according to the maximum subscript value and the minimum subscript value;

[0043] A second calculation module is used to calculate the signal bandwidth and the center frequency according to the maximum instantaneous frequency and the minimum instantaneous frequency;

[0044] The first determination module is used to obtain K-point differences in the time-frequency diagram of the signal to be measured to determine the frequency modulation mode of the signal to be measured, wherein the frequency modulation mode includes positive and negative linear frequency modulation, dual linear frequency modulation, triangle frequency modulation, sawtooth frequency modulation and sine frequency modulation, or

[0045] Squaring the signal to be measured to obtain a square signal, performing Fourier transform on the square signal to obtain a quadratic spectrum, and squaring the square signal again and performing Fourier transform on the square signal to obtain a quartic spectrum;

[0046] Setting module, used to set the sliding window size;

[0047] A third calculation module is used to calculate the average value of the quadratic signal and the average value of the quartic signal of the quadratic spectrum and the quartic spectrum within the sliding window size;

[0048] The second determination module is used to multiply the average value of the secondary signal and the average value of the fourth signal by the threshold gain to obtain a decision threshold, compare the decision threshold with the center point of the sliding window, and determine the phase modulation mode of the signal to be tested, where the phase modulation mode includes QPSK phase modulation and BPSK phase modulation.

[0049] A terminal device includes a memory and a processor. The memory stores a computer program that can be run on the processor. When the processor loads and executes the computer program, a signal parameter identification method based on FPGA is adopted.

[0050] A computer-readable storage medium stores a computer program. When the computer program is loaded and executed by a processor, a signal parameter identification method based on FPGA is adopted.

[0051] The beneficial effects of the present invention are:

[0052] By dividing the signal into N segments, performing Fourier calculation and finding the modulus value of each segment, the corresponding instantaneous frequency maximum value, instantaneous frequency minimum value and time-frequency diagram of the signal to be measured are obtained by subscripting the maximum modulus value of the calculated value of each segment, and then calculating the signal bandwidth and center frequency point. The signal time-frequency diagram is differentiated by K points to obtain the frequency modulation modulation mode or the signal is squared and fourth-powered to obtain the quadratic spectrum and the quartic spectrum. By finding the average value of the quadratic spectrum and the quartic spectrum under different sliding windows, multiplying it by the threshold gain and comparing it with the center maximum value of the sliding window, the phase modulation modulation mode is obtained. Compared with the traditional method, the present application can accurately identify the modulation mode and obtain more accurate bandwidth and frequency point. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 The figure is a flow chart of a signal parameter identification method based on FPGA of the present invention.

[0054] Figure 2 It is the linear frequency modulation time-frequency diagram and frequency point difference diagram of the present invention;

[0055] Figure 3 The time-frequency diagram and frequency point difference diagram of the sawtooth frequency modulation of the present invention;

[0056] Figure 4 This is the time-frequency diagram and frequency point difference diagram of the triangle wave frequency modulation of the present invention;

[0057] Figure 5 It is the dual linear frequency modulation time-frequency diagram and frequency point difference diagram of the present invention;

[0058] Figure 6 This is the time-frequency diagram and frequency point difference diagram of the sinusoidal frequency modulation of the present invention. DETAILED DESCRIPTION

[0059] A signal parameter identification method based on FPGA, such as Figure 1 As shown, the present invention includes:

[0060] S1. Divide the signal to be measured into N segments, perform Fourier calculation on each segment of the signal to be measured to obtain a Fourier calculation value, and modulus the Fourier calculation value to obtain a Fourier modulus value, and obtain the maximum subscript of the Fourier modulus value, sort the maximum subscript to obtain the maximum subscript and the minimum subscript among the N Fourier modulus values, and obtain the corresponding maximum instantaneous frequency, minimum instantaneous frequency and time-frequency diagram of the signal to be measured according to the maximum subscript and the minimum subscript.

[0061] Specifically, FPGAs, as highly flexible and programmable electronic devices, offer advantages over traditional CPUs in algorithm processing, including large capacity, low latency, high reliability, and pipeline processing. FPGAs offer a higher detection limit for high-bandwidth, low-frequency, high-speed radar and communication signals.

[0062] The signal to be measured is a radar signal or a communication signal.

[0063] Specifically, assuming the signal to be measured has 10,240 points and N = 10, the signal is divided into 10 segments, each with 1,024 points. Each segment is subjected to Fourier transformation and modulo calculation to obtain the Fourier modulus value. Each segment is then assigned a maximum subscript. The maximum subscripts are sorted, representing the instantaneous frequencies of the current 1,024 points, for a total of 10 instantaneous frequencies. These 10 instantaneous frequencies are sorted to obtain the maximum and minimum instantaneous frequencies, as well as a time-frequency plot of the signal to be measured, consisting of the 10 instantaneous frequencies over time.

[0064] When Fourier transform is performed on each signal segment, the signal to be measured is converted from a time-frequency signal to a frequency domain signal. The subscript is the subscript of the different frequency signals, and different frequency domains correspond to different frequencies.

[0065] S2. Calculate the signal bandwidth and center frequency based on the maximum and minimum instantaneous frequency.

[0066] Specifically, signal bandwidth = maximum instantaneous frequency - minimum instantaneous frequency, and center frequency = (maximum instantaneous frequency + minimum instantaneous frequency) / 2.

[0067] S3. Calculate the K-point difference of the time-frequency diagram of the signal to be measured to determine the frequency modulation mode of the signal to be measured. The frequency modulation modes include positive and negative linear frequency modulation, dual linear frequency modulation, triangle frequency modulation, sawtooth frequency modulation, and sine frequency modulation.

[0068] Specifically, the frequency value sequence obtained from the center frequency and bandwidth measurement is used to calculate the k-point differential of the sequence. k can be set to k = 2 * N / Bw. By summarizing the patterns of the differential sequence, the modulation type can be derived. N is the number of FFT points, and Bw is the signal bandwidth.

[0069] Positive and negative linear frequency modulation includes positive linear frequency modulation and negative linear frequency modulation.

[0070] The time-frequency diagram of the signal to be measured is differentiated at K points to determine the frequency modulation mode of the signal to be measured, including:

[0071] S31. Calculate K-point differences in the time-frequency diagram of the signal to be measured to obtain a frequency point difference diagram.

[0072] Specifically, the K-point difference of the time-frequency diagram of the signal to be measured is obtained by performing differential calculation on the signal to be measured to obtain a frequency point difference diagram.

[0073] S32. Divide the frequency difference graph into four intervals on average, and calculate the sum of the difference values ​​in each interval.

[0074] Specifically, the frequency point difference graph is evenly divided into four intervals according to time, and the frequency point difference values ​​in each interval are added together to obtain the sum of the difference values.

[0075] S33. Determine the frequency modulation mode of the signal to be tested according to the sum of the differential values ​​and a preset frequency modulation rule.

[0076] The preset frequency modulation rules include:

[0077] When the sum of the differences of the four intervals is all positive or all negative, and the absolute value of the maximum or minimum value of the entire pulse differential value is close to the signal bandwidth, it is sawtooth frequency modulation.

[0078] When the sum of the differences of the four intervals is positive and does not meet the sawtooth frequency modulation condition, it is negative linear frequency modulation.

[0079] When the sum of the differences of the four intervals is negative and does not meet the sawtooth frequency modulation condition, it is positive linear frequency modulation.

[0080] When the difference sum of the four intervals changes to negative, positive, positive and negative or negative, negative, positive and positive, and the last difference value of the second interval is close to 0, it is sinusoidal frequency modulation.

[0081] When the difference and change of the four intervals are positive, positive, negative and negative or negative, negative, positive and positive and do not meet the sinusoidal frequency modulation condition, it is bilinear frequency modulation.

[0082] When the difference and change of the four intervals are positive, negative, positive, negative or negative, positive, negative, positive, it is triangle wave frequency modulation.

[0083] Specifically, Figures 2 to 5 These are the FM time-frequency diagrams and frequency difference diagrams for different FM modulation methods.

[0084] S4. Square the signal to be measured to obtain a square signal, perform Fourier transform on the square signal to obtain a quadratic spectrum, square the square signal again and perform Fourier transform on the square signal to obtain a quartic spectrum.

[0085] S5. Set the sliding window size.

[0086] Specifically, the signal comes in continuously, and the sliding window size is the length of the signal that can be collected in one window at the same time.

[0087] S6. Calculate the average quadratic signal and the average quartic signal of the quadratic spectrum and the quartic spectrum within the sliding window size.

[0088] S7. Multiply the average of the secondary signal and the average of the fourth signal by the threshold gain to obtain a decision threshold. Compare the decision threshold with the center point of the sliding window to determine the phase modulation mode of the signal to be tested. The phase modulation modulation mode includes QPSK phase modulation and BPSK phase modulation.

[0089] Specifically, at different times, the signal within the sliding window size is different, so there will be many quadratic signal averages and quartic signal averages of the quadratic spectrum and the quartic spectrum.

[0090] The decision threshold is obtained by multiplying the average of the quadratic signal and the average of the quartic signal by the threshold gain. The decision threshold is compared with the center point of the sliding window to determine the phase modulation mode of the signal to be tested, including:

[0091] S71. Multiply the average value of the secondary signal and the average value of the fourth signal by the threshold gain to obtain the secondary signal decision threshold and the fourth signal decision threshold respectively.

[0092] Specifically, the threshold gain is related to factors such as noise and filter characteristics.

[0093] S72. When the center point of the secondary signal sliding window is greater than the secondary signal decision threshold and the center point of the secondary signal sliding window is a maximum value, or the center point of the fourth signal sliding window is greater than the fourth signal decision threshold and the center point of the fourth signal sliding window is a maximum value point, a secondary signal recording point or a fourth signal recording point is obtained.

[0094] Specifically, whether the center point of the sliding window is a maximum value needs to be confirmed by determining whether the center point of the sliding window meets the maximum value condition.

[0095] S73. Determine the phase modulation mode of the signal to be measured according to the secondary signal recording point and / or the quaternary signal recording point.

[0096] Determining the phase modulation mode of the signal to be measured based on the secondary signal recording point and / or the quaternary signal recording point includes:

[0097] S731. When both the secondary spectrum and the quartic spectrum of the signal to be measured exist and there is only one secondary recording point and one quartic recording point, it is determined that the phase modulation mode of the signal to be measured is BPSK.

[0098] S732: When the signal to be measured has only one fourth-order signal recording point in the fourth-order spectrum, it is determined that the phase modulation mode of the signal to be measured is QPSK.

[0099] S8. Using the signal bandwidth, center frequency, and frequency modulation or phase modulation as parameter identification results of the signal to be measured.

[0100] The signal bandwidth, center frequency, and frequency modulation or phase modulation modulation are used as parameter identification results of the signal to be measured, including:

[0101] S81. When the frequency modulation mode of the signal to be measured is positive linear frequency modulation and negative linear frequency modulation, use FIFO to record the preceding signals of the first M points and the following signals of the last M points of the signal to be measured within a pulse.

[0102] Specifically, when the frequency modulation mode used is positive linear frequency modulation and negative linear frequency modulation, the traditional method of calculating the bandwidth and center frequency has poor accuracy. Therefore, when the frequency modulation mode is positive linear frequency modulation and negative linear frequency modulation, different calculation methods need to be used.

[0103] S82. Perform conjugate multiplication on the preceding signal and the succeeding signal to obtain a preceding conjugate signal and a succeeding conjugate signal.

[0104] S83. Perform Fourier transform on the front conjugate signal and the rear conjugate signal to obtain a front center frequency point and a rear center frequency point.

[0105] S84. Calculate a corrected center frequency point based on the previous center frequency point and the subsequent center frequency point.

[0106] S85. Use the corrected center frequency, the corrected signal bandwidth, and the frequency modulation mode as a result of identifying the modified parameters of the signal to be measured.

[0107] Specifically, use FIFO to cache the first M points and the last M points of a pulse, take the conjugate and multiply it with the original signal and send it to FFT (Fourier transform), respectively find the maximum subscript of the FFT result, that is, the frequency point F1 (at the front center frequency point) and F2 (at the back center frequency point). At this time, F1 and F2 are twice the center frequency of the linear frequency modulation signal at the first M points and the last M points. Therefore, the center frequency is and The complete bandwidth cannot be obtained. It is necessary to calculate the slope and then compensate the bandwidth value of N points:

[0108]

[0109] S86. When the signal to be measured is phase-modulated, the signal to be measured is delayed by point Z to obtain a delayed signal, the delayed signal is conjugated to obtain a conjugate delayed signal, the conjugate delayed signal is multiplied by the signal to be measured, and Fourier transform is performed at point y, and the subscript of the maximum value is obtained from the y Fourier transform results.

[0110] S87. Obtain the bandwidth of the signal to be measured as a correction bandwidth according to the frequency domain value corresponding to the subscript of the maximum value.

[0111] Specifically, the phase modulated signal is delayed by z points, and its conjugate is multiplied with the original signal. The result is processed by y-point FFT. The maximum subscript value except zero frequency is obtained by traversing the result. Twice the frequency domain value corresponding to the subscript is the bandwidth of the phase encoding, where Z can be taken as the ratio of the FFT point number y to the coarse measurement bandwidth Bw.

[0112] A signal parameter identification system based on FPGA, comprising:

[0113] A first calculation module is used to divide the signal to be measured into N segments, perform Fourier calculation on each segment of the signal to be measured to obtain a Fourier calculation value, modulus the Fourier calculation value to obtain a Fourier modulus value, and obtain a maximum subscript of the Fourier modulus value, sort the maximum subscripts to obtain a maximum subscript and a minimum subscript among the N Fourier modulus values, and obtain a corresponding maximum instantaneous frequency, a minimum instantaneous frequency, and a time-frequency diagram of the signal to be measured according to the maximum subscript and the minimum subscript;

[0114] The second calculation module is used to calculate the signal bandwidth and the center frequency according to the maximum instantaneous frequency and the minimum instantaneous frequency;

[0115] The first determination module is used to obtain K-point differences in the time-frequency diagram of the signal to be measured to determine the frequency modulation mode of the signal to be measured, where the frequency modulation modes include positive and negative linear frequency modulation, dual linear frequency modulation, triangle frequency modulation, sawtooth frequency modulation, and sine frequency modulation, or

[0116] The signal to be measured is squared to obtain a square signal, the square signal is Fourier transformed to obtain a quadratic spectrum, the square signal is squared again and Fourier transformed to obtain a quartic spectrum;

[0117] Setting module, used to set the sliding window size;

[0118] A third calculation module is used to calculate the average value of the quadratic signal and the average value of the quartic signal of the quadratic spectrum and the quartic spectrum within the sliding window size;

[0119] The second determination module is used to multiply the average value of the secondary signal and the average value of the fourth signal by the threshold gain to obtain a decision threshold, compare the decision threshold with the center point of the sliding window, and determine the phase modulation mode of the signal to be tested. The phase modulation modulation mode includes QPSK phase modulation and BPSK phase modulation.

[0120] An embodiment of the present application also discloses a terminal device, including a memory and a processor. The memory stores a computer program that can be run on the processor. When the processor loads and executes the computer program, a signal parameter identification method based on FPGA is adopted.

[0121] Among them, the terminal device can be a computer device such as a desktop computer, a laptop computer or a cloud server, and the terminal device includes but is not limited to a processor and a memory. For example, the terminal device can also include input and output devices, network access devices and buses, etc.

[0122] Among them, the processor can adopt a central processing unit (CPU). Of course, according to actual usage, other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. can also be adopted. The general-purpose processor can adopt a microprocessor or any conventional processor, etc., and this application does not impose any restrictions on this.

[0123] Among them, the memory can be an internal storage unit of the terminal device, such as the hard disk or memory of the terminal device, or it can be an external storage device of the terminal device, such as a plug-in hard disk, smart memory card (SMC), secure digital card (SD) or flash memory card (FC) equipped on the terminal device, etc., and the memory can also be a combination of the internal storage unit and the external storage device of the terminal device. The memory is used to store computer programs and other programs and data required by the terminal device. The memory can also be used to temporarily store data that has been output or is to be output. This application does not impose any restrictions on this.

[0124] Among them, through this terminal device, a signal parameter identification method based on FPGA in the above embodiment is stored in the memory of the terminal device, and is loaded and executed on the processor of the terminal device for easy use.

[0125] An embodiment of the present application further discloses a computer-readable storage medium, and the computer-readable storage medium stores a computer program, wherein when the computer program is executed by a processor, an FPGA-based signal parameter identification method in the above embodiment is adopted.

[0126] Among them, the computer program can be stored in a computer-readable medium, the computer program includes computer program code, the computer program code can be in the form of source code, object code, executable file or certain middleware, etc. The computer-readable medium includes any entity or device that can carry computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal and software distribution medium, etc. It should be noted that computer-readable medium includes but is not limited to the above-mentioned components.

[0127] Among them, through this computer-readable storage medium, a signal parameter identification method based on FPGA in the above embodiment is stored in a computer-readable storage medium, and is loaded and executed on a processor to facilitate the storage and application of the above method.

[0128] Those skilled in the art should understand that the discussion of any of the above embodiments is merely illustrative and is not intended to imply that the scope of protection of the present application is limited to these examples. In line with the present application, the technical features in the above embodiments or different embodiments may be combined, the steps may be implemented in any order, and there are many other variations of different aspects of one or more embodiments of the present application as described above, which are not provided in detail for the sake of simplicity.

[0129] The one or more embodiments of this application are intended to encompass all such substitutions, modifications, and variations that fall within the broad scope of this application. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of one or more embodiments of this application should be included in the scope of protection of this application.

Claims

1. A signal parameter identification method based on FPGA, characterized in that: include: Dividing the signal to be measured into N segments, performing Fourier calculation on each segment of the signal to be measured to obtain a Fourier calculation value, taking the modulus of the Fourier calculation value to obtain a Fourier modulus value, and obtaining a maximum subscript of the Fourier modulus value, sorting the maximum subscripts to obtain a maximum subscript value and a minimum subscript value among the N Fourier modulus values, and obtaining a corresponding maximum instantaneous frequency, a minimum instantaneous frequency, and a time-frequency diagram of the signal to be measured according to the maximum subscript value and the minimum subscript value; Calculating the signal bandwidth and the center frequency according to the maximum instantaneous frequency and the minimum instantaneous frequency; The time-frequency diagram of the signal to be measured is differentiated at K points to determine the frequency modulation mode of the signal to be measured, wherein the frequency modulation mode includes positive and negative linear frequency modulation, bilinear frequency modulation, triangle frequency modulation, sawtooth frequency modulation and sine frequency modulation, or Squaring the signal to be measured to obtain a square signal, performing Fourier transform on the square signal to obtain a quadratic spectrum, and squaring the square signal again and performing Fourier transform on the square signal to obtain a quartic spectrum; Set the sliding window size; Calculating the quadratic signal average and the quartic signal average of the quadratic spectrum and the quartic spectrum within the sliding window size; Multiplying the average value of the quadratic signal and the average value of the quartic signal by a threshold gain to obtain a decision threshold, comparing the decision threshold with the center point of the sliding window to determine a phase modulation mode of the signal to be measured, wherein the phase modulation mode includes QPSK phase modulation and BPSK phase modulation; The signal bandwidth, center frequency, and frequency modulation or phase modulation modulation are used as parameter identification results of the signal to be measured.

2. The FPGA-based signal parameter identification method according to claim 1, wherein: The K-point difference of the time-frequency diagram of the signal to be measured is obtained to determine the frequency modulation mode of the signal to be measured, wherein the frequency modulation mode includes linear frequency modulation, triangle frequency modulation, sawtooth frequency modulation and sine frequency modulation, and the linear frequency modulation includes positive linear frequency modulation, negative linear frequency modulation and dual linear frequency modulation. The time-frequency diagram of the signal to be measured is subjected to K-point differentiation to obtain a frequency point difference diagram; Divide the frequency difference map into four intervals on average, and calculate the sum of the difference values ​​in each interval; The frequency modulation mode of the signal to be tested is determined according to the sum of the difference values ​​and a preset frequency modulation rule.

3. The FPGA-based signal parameter identification method according to claim 2, wherein: The preset frequency modulation rules include: When the sum of the differences of the four intervals is all positive or all negative, and the absolute value of the maximum or minimum value of the entire pulse differential value is close to the signal bandwidth, it is sawtooth frequency modulation; When the sum of the differences of the four intervals is positive and does not meet the sawtooth frequency modulation condition, it is negative linear frequency modulation; When the sum of the differences of the four intervals is negative and does not meet the sawtooth frequency modulation condition, it is positive linear frequency modulation; When the sum of the differences in the four intervals changes to negative, positive, positive, and negative, or negative, negative, positive, and positive, and the last difference value in the second interval is close to 0, it is sinusoidal frequency modulation; When the difference and change of the four intervals are positive, positive, negative and negative or negative, negative, positive and positive and do not meet the sinusoidal frequency modulation conditions, it is bilinear frequency modulation; When the difference and change of the four intervals are positive, negative, positive, negative or negative, positive, negative, positive, it is triangle wave frequency modulation.

4. The FPGA-based signal parameter identification method according to claim 1, wherein: The step of multiplying the average value of the quadratic signal and the average value of the quartic signal by a threshold gain to obtain a decision threshold, and comparing the decision threshold with the center point of the sliding window to determine the phase modulation mode of the signal to be measured includes: Multiplying the average value of the secondary signal and the average value of the fourth signal by the threshold gain to obtain the secondary signal decision threshold and the fourth signal decision threshold respectively; When the center point of the secondary signal sliding window is greater than the secondary signal decision threshold and the center point of the secondary signal sliding window is a maximum value, or the center point of the quartic signal sliding window is greater than the quartic signal decision threshold and the center point of the quartic signal sliding window is a maximum value point, then a secondary signal recording point or a quartic signal recording point is obtained; The phase modulation mode of the signal to be measured is determined according to the secondary signal recording point and / or the quaternary signal recording point.

5. The FPGA-based signal parameter identification method according to claim 4, wherein: Determining the phase modulation mode of the signal to be measured according to the secondary signal recording point and / or the quaternary signal recording point includes: When both the secondary spectrum and the quartic spectrum of the signal to be measured exist and there is only one secondary recording point and one quartic recording point, it is determined that the phase modulation mode of the signal to be measured is BPSK; When the signal to be measured has only one fourth-order signal recording point in the fourth-order spectrum, it is determined that the phase modulation mode of the signal to be measured is QPSK.

6. The FPGA-based signal parameter identification method according to claim 1, wherein: The method further comprises: taking the signal bandwidth, the center frequency, and the frequency modulation mode or the phase modulation mode as the parameter identification result of the signal to be measured; When the frequency modulation mode of the signal to be measured is positive linear frequency modulation and negative linear frequency modulation, a FIFO is used to record the preceding signals of the first M points and the following signals of the last M points of the signal to be measured within a pulse; Performing conjugate multiplication on the preceding signal and the succeeding signal to obtain a preceding conjugate signal and a succeeding conjugate signal; Performing Fourier transform on the preceding conjugate signal and the succeeding conjugate signal to obtain a preceding center frequency point and a succeeding center frequency point; Calculate a corrected center frequency and a corrected signal bandwidth according to the previous center frequency and the subsequent center frequency; The corrected central frequency point, the corrected signal bandwidth, and the frequency modulation mode are used as modification parameter identification results of the signal to be measured.

7. The FPGA-based signal parameter identification method according to claim 6, comprising: When the signal to be measured is phase-modulated, the signal to be measured is delayed by point Z to obtain a delayed signal, the delayed signal is conjugated to obtain a conjugate delayed signal, the conjugate delayed signal is multiplied by the signal to be measured, a Fourier transform is performed at point y, and the subscript of the maximum value is obtained from the y Fourier transform results; According to the frequency domain value corresponding to the subscript of the maximum value, the bandwidth of the signal to be measured is obtained as the correction bandwidth.

8. A signal parameter identification system based on FPGA, characterized in that: include: A first calculation module is configured to divide the signal to be measured into N segments, perform Fourier calculation on each segment of the signal to be measured to obtain a Fourier calculation value, modulo the Fourier calculation value to obtain a Fourier modulus value, obtain a maximum subscript of the Fourier modulus value, sort the maximum subscripts to obtain a maximum subscript value and a minimum subscript value among the N Fourier modulus values, and obtain a corresponding maximum instantaneous frequency value, a minimum instantaneous frequency value, and a time-frequency diagram of the signal to be measured according to the maximum subscript value and the minimum subscript value; A second calculation module is used to calculate the signal bandwidth and the center frequency according to the maximum instantaneous frequency and the minimum instantaneous frequency; The first determination module is used to obtain K-point differences in the time-frequency diagram of the signal to be measured to determine the frequency modulation mode of the signal to be measured, where the frequency modulation mode includes positive and negative linear frequency modulation, bilinear frequency modulation, triangle frequency modulation, sawtooth frequency modulation and sine frequency modulation, or Squaring the signal to be measured to obtain a square signal, performing Fourier transform on the square signal to obtain a quadratic spectrum, and squaring the square signal again and performing Fourier transform on the square signal to obtain a quartic spectrum; Setting module, used to set the sliding window size; A third calculation module is used to calculate the average value of the quadratic signal and the average value of the quartic signal of the quadratic spectrum and the quartic spectrum within the sliding window size; A second determination module is configured to multiply the average value of the secondary signal and the average value of the fourth signal by a threshold gain to obtain a decision threshold, compare the decision threshold with the center point of the sliding window, and determine a phase modulation mode of the signal to be measured, where the phase modulation mode includes QPSK phase modulation and BPSK phase modulation; The identification module is used to use the signal bandwidth, center frequency, and frequency modulation modulation mode or phase modulation modulation mode as parameter identification results of the signal to be measured.

9. A terminal device comprising a memory and a processor, characterized in that: The memory stores a computer program that can be run on the processor. When the processor loads and executes the computer program, the method according to any one of claims 1 to 7 is adopted.

10. A computer-readable storage medium storing a computer program, wherein: When the computer program is loaded and executed by a processor, the method according to any one of claims 1 to 7 is adopted.

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