A digital frequency measurement method, system, storage medium and electronic device

Abstract

The application belongs to the technical field of electronic countermeasure signal reconnaissance, and particularly relates to a digital frequency measurement method and system, a storage medium and electronic equipment. Different extraction factors are used to extract an original input digital signal to obtain multiple digital signals, a single-bit Fourier transform result corresponding to each digital signal, a single-bit Fourier transform result corresponding to the original input digital signal, the amplitude-frequency characteristics of each digital signal and the amplitude-frequency characteristics of the original input digital signal, the frequency calculation value of each digital signal and the frequency calculation value of the original input digital signal. The frequency calculation value of each digital signal and the frequency calculation value of the original input digital signal are used for demodulation calculation to obtain the final frequency value of the original input digital signal. The application has high frequency measurement accuracy, short frequency measurement time and low operation complexity.

Description

Technical Field

[0001] This invention relates to the field of electronic countermeasures signal reconnaissance technology, and particularly to a digital frequency measurement method, system, storage medium, and electronic device. Background Technology

[0002] Instantaneous frequency measurement technology is an indispensable processing technique in electronic warfare applications. Early methods primarily used analog instantaneous frequency measurement. However, with the development of digital technology and the increasing bandwidth and sampling rate of digital-to-analog converter chips, digital instantaneous frequency measurement using a combination of analog-to-digital converters (ADCs) and FPGAs has gradually become the mainstream technology. Among these methods, frequency measurement based on single-bit Fourier transform (DFT) is widely used in practice because it only requires addition and subtraction to achieve spectrum analysis. However, the frequency measurement accuracy of conventional single-bit DFT is equal to the reciprocal of the signal acquisition time, making it impossible to simultaneously satisfy both high accuracy and ultra-fast speed. Summary of the Invention

[0003] The technical problem to be solved by the present invention is to address the shortcomings of the prior art by providing a digital frequency measurement method, system, storage medium and electronic device.

[0004] The technical solution of the digital frequency measurement method of the present invention is as follows: The original input digital signal is decimated according to different decimation factors to obtain multiple digital signals; Local signals are extracted from each digital signal and the original input digital signal, and a single-bit Fourier transform is performed to obtain the single-bit Fourier transform result corresponding to each digital signal and the single-bit Fourier transform result corresponding to the original input digital signal. The number of calculation points for performing a single-bit Fourier transform on any digital signal is greater than the length of the local signal extracted from that digital signal, and the number of calculation points for performing a single-bit Fourier transform on the original input digital signal is greater than the length of the local signal extracted from the original input digital signal. The magnitude of each single-bit Fourier transform result is approximated to obtain the amplitude-frequency characteristics of each digital signal and the amplitude-frequency characteristics of the original input digital signal. Based on the amplitude-frequency characteristics of any digital signal, search for the peak position of the amplitude spectrum of that digital signal, and calculate the frequency value of that digital signal based on the peak position, until the frequency value of each digital signal is obtained; based on the amplitude-frequency characteristics of the original input digital signal, search for the peak position of the amplitude spectrum of the original input digital signal, and calculate the frequency value of the original input digital signal based on the peak position. Defuzzing calculation is performed based on the frequency calculation value of each digital signal and the frequency calculation value of the original input digital signal to obtain the final frequency value of the original input digital signal.

[0005] The beneficial effects of the digital frequency measurement method of the present invention are as follows: On the one hand, the original input digital signal and each extracted digital signal are simultaneously subjected to single-bit Fourier transform, which is equivalent to combining coarse frequency measurement and fine frequency measurement. Compared with the existing technology of "only performing single-bit Fourier transform on the original output signal", the present invention requires less computation and shortens the frequency measurement time to achieve the same frequency measurement accuracy. On the other hand, higher spectrum analysis accuracy can be obtained and the frequency measurement time can be shortened, thereby realizing a digital frequency measurement method with high frequency measurement accuracy, short frequency measurement time and low computational complexity.

[0006] The technical solution of the digital frequency measurement system of the present invention is as follows: It includes an extraction module, a single-bit Fourier transform module, an approximate modulus calculation module, a first calculation module, and a second calculation module; The extraction module is used to: extract the original input digital signal according to different extraction factors to obtain multiple digital signals; The single-bit Fourier transform module is used to: extract local signals from each digital signal and the original input digital signal, and perform single-bit Fourier transform to obtain the single-bit Fourier transform result corresponding to each digital signal and the single-bit Fourier transform result corresponding to the original input digital signal. The number of calculation points for performing single-bit Fourier transform on any digital signal is greater than the length of the local signal extracted from that digital signal, and the number of calculation points for performing single-bit Fourier transform on the original input digital signal is greater than the length of the local signal extracted from the original input digital signal. The approximate modulus module is used to: approximate the modulus of each single-bit Fourier transform result to obtain the amplitude-frequency characteristics of each digital signal and the amplitude-frequency characteristics of the original input digital signal; The first calculation module is used to: search for the peak position of the amplitude spectrum of any digital signal based on the amplitude-frequency characteristics of the digital signal, calculate the frequency value of the digital signal based on the peak position of the digital signal, until the frequency value of each digital signal is obtained; search for the peak position of the amplitude spectrum of the original input digital signal based on the amplitude-frequency characteristics of the original input digital signal, and calculate the frequency value of the original input digital signal based on the peak position of the original input digital signal. The second calculation module is used to: perform defuzzification calculation based on the frequency calculation value of each digital signal and the frequency calculation value of the original input digital signal to obtain the final frequency value of the original input digital signal.

[0007] The beneficial effects of the digital frequency measurement system of the present invention are as follows: On the one hand, the original input digital signal and each extracted digital signal are simultaneously subjected to single-bit Fourier transform, which is equivalent to combining coarse frequency measurement and fine frequency measurement. Compared with the existing technology of "only performing single-bit Fourier transform on the original output signal", the present invention requires less computation and shortens the frequency measurement time to achieve the same frequency measurement accuracy. On the other hand, higher spectrum analysis accuracy can be obtained and the frequency measurement time can be shortened, thereby realizing a digital frequency measurement method with high frequency measurement accuracy, short frequency measurement time and low computational complexity.

[0008] The present invention provides a storage medium storing instructions, wherein when a computer reads the instructions, the computer executes any of the above-described digital frequency measurement methods.

[0009] An electronic device according to the present invention is characterized in that it includes a processor and the aforementioned storage medium, wherein the processor executes instructions in the storage medium. Attached Figure Description

[0010] Figure 1 This is one of the flowcharts illustrating a digital frequency measurement method according to an embodiment of the present invention; Figure 2 This is a second schematic flowchart of a digital frequency measurement method according to an embodiment of the present invention; Figure 3 The figure shows the simulation results of frequency measurement error in an embodiment of the present invention.

[0011] Figure 4 This is a schematic diagram of the structure of a digital frequency measurement system according to an embodiment of the present invention. Detailed Implementation

[0012] like Figure 1 and Figure 2 As shown, a digital frequency measurement method according to an embodiment of the present invention includes the following steps: S1. The original input digital signal is decimated according to different decimation factors to obtain multiple digital signals. The different decimation factors are not divisible by each other. Specifically: For example, according to the sampling rate based on three sampling factors f s The original input digital signal is decimated in three separate streams, with decimation factors of 1, 2, and 3 respectively. D 1. D 2. D 3, D 1. D 2. D 3 are not divisible by each other, such as D 1=17、 D 2=19 and D3 = 27. Adding this to the original input digital signal, we obtain four digital signals with different sampling rates: the original input digital signal and the three decimated digital signals. The decimation factor for each digital signal is... D i , i = 0,1,2,3, where D 0=1, which is the decimation factor of the original input digital signal.

[0013] S2. Extract local signals from each digital signal and the original input digital signal, and perform single-bit Fourier transforms to obtain the single-bit Fourier transform results for each digital signal and the original input digital signal. Specifically, the number of calculation points for the single-bit Fourier transform of any digital signal is greater than the length of the local signal extracted from that signal, and the number of calculation points for the single-bit Fourier transform of the original input digital signal is also greater than the length of the local signal extracted from the original input digital signal. Extract the four digital signals separately N i ( i = 0, 1, 2, 3 points, padded with zeros and then respectively performed M i A single-bit DFT with points, where the number of DFT calculation points is greater than the length of the truncated signal, can shorten the waiting time for the signal; considering the symmetry of the real signal spectrum, only the index [0, ... M i / 2) range of DFT results, which can save half of the computation. N 0 Corresponding to the original input digital signal, N 1 The corresponding extraction factor is D A digital signal of 1 N 2 The corresponding extraction factor is D 2 digital signal, N 3 The corresponding extraction factor is D 3 digital signal, M 0 Corresponding to the original input digital signal, M 1 The corresponding extraction factor is D A digital signal of 1 M 2 The corresponding extraction factor is D 2 digital signal, M 3 The corresponding extraction factor is D A 3-digit digital signal.

[0014] S3. Approximate the modulus of each single-bit Fourier transform result to obtain the amplitude-frequency characteristics of each digital signal and the amplitude-frequency characteristics of the original input digital signal. S4. Based on the amplitude-frequency characteristics of any digital signal, search for the peak position of the amplitude spectrum of that digital signal. Based on the peak position of that digital signal, calculate the frequency value of that digital signal, until the frequency value of each digital signal is obtained. Based on the amplitude-frequency characteristics of the original input digital signal, search for the peak position of the amplitude spectrum of the original input digital signal. Based on the peak position of the original input digital signal, calculate the frequency value of the original input digital signal. Specifically: By searching the four sets of single-bit DFT results, [0, ... M i The locations of the amplitude peak points within the range of / 2) are respectively P i , i =0,1,2,3, calculate the frequency of each digital signal: in, P 0 Corresponding to the original input digital signal, P 1 The corresponding extraction factor is D A digital signal of 1 P 2 The corresponding extraction factor is D 2 digital signal, P 3 The corresponding extraction factor is D The calculated frequency value of the original input digital signal (3). Unambiguous, but with low precision; extraction factor is D Calculated frequency value of a digital signal of 1 Extraction factor is D Calculated frequency value of a 2-digit digital signal Extraction factor is D Calculated frequency value of a 3-digit digital signal It has high accuracy, but there are two types of ambiguity: one is because the amplitude-frequency characteristics of the positive and negative frequencies of the real signal are the same, and the other is because of frequency folding caused by decimation.

[0015] S5. Perform defuzzification calculation based on the frequency calculation value of each digital signal and the frequency calculation value of the original input digital signal to obtain the final frequency value of the original input digital signal.

[0016] On the one hand, the original input digital signal and each extracted digital signal are simultaneously subjected to single-bit Fourier transform, which is equivalent to combining coarse frequency measurement and fine frequency measurement. Compared with the existing technology of "only performing single-bit Fourier transform on the original output signal", the present invention requires less computation and shortens the frequency measurement time to achieve the same frequency measurement accuracy. On the other hand, higher spectrum analysis accuracy can be obtained and the frequency measurement time can be shortened, thereby realizing a digital frequency measurement method with high frequency measurement accuracy, short frequency measurement time and low computational complexity.

[0017] Optionally, in the above technical solution, in S3, the approximate modulus calculation is performed on each single-bit Fourier transform result, including: The modulus of each single-bit Fourier transform result is approximated using Taylor expansion. Specifically: Based on the complex output of the DFT, the amplitude of the spectrum is calculated. This invention uses a Taylor expansion approximation method, assuming... V = I + jQ , then | V |≈ max {| I |,| Q |}+ min {| I |,| Q |} / 2.

[0018] Optionally, in the above technical solution, in step S5, defuzzification calculation is performed based on the frequency calculation value of each digital signal and the frequency calculation value of the original input digital signal to obtain the final frequency value of the original input digital signal, including: S51. Calculate the minimum value of the intermediate quantity W using the first formula, which is W = Where q1∈{1,2,3,4}, q2∈{1,2,3,4}, q3∈{1,2,3,4}, , , , , , Indicates to Perform floor rounding; S52. Calculate the final frequency value of the original input digital signal using the second formula. The second formula is: Among them, the intermediate quantity W takes the minimum value when it corresponds to The value of is 'a', and the intermediate quantity W takes the minimum value when it corresponds to 'a'. The value of is b, and the intermediate quantity W takes the minimum value corresponding to . The value of is c.

[0019] The technical effects of this invention are as follows: 1) Performing multi-channel single-bit DFT on both the original signal and the decimated signal simultaneously is equivalent to combining coarse frequency measurement with fine frequency measurement. Compared with performing single-bit DFT on only the original signal, this method requires less computation to achieve the same frequency measurement accuracy. 2) Performing single-bit DFT calculation after zero-padding the input signal can achieve higher spectrum analysis accuracy; the time for single-bit DFT of the received signal is shortened, which can shorten the frequency measurement time. 3) Based on the symmetry of the amplitude-frequency characteristics of the real signal, only half of the DFT result is calculated, reducing the computational load by 1 / 2; 4) Calculate the amplitude of the spectrum based on the complex output of the DFT. This invention uses a Taylor expansion approximation. V = I + jQ , then | V |≈ max {| I |,| Q |}+ min {| I |,| Q |} / 2; The technical effects of the digital frequency measurement method of the present invention are illustrated by the following embodiments: If the original signal frequency range is 200MHz to 2200MHz, the sampling rate... f s It is 4800MHz, and other parameters include D 1=17、 D 2=19、 D 3=27, N 0=64, N 1= N 2= N 3=32, M 0 = 256 M 1= M 2= M 3=512, the simulation signal-to-noise ratio is 10dB, and the FPGA processing clock frequency is 300MHz.

[0020] Data collection time requires max { D i N i / f s,i=0,1,2,3}=180ns; Single-bit DFT is implemented through cumulative addition and subtraction, and the single-bit DFT result can be obtained immediately after signal acquisition; Amplitude calculation is implemented by calculating the absolute value and addition, which requires 2 FPGA processing clock cycles; Peak point search is performed on half of the amplitude spectrum of the real signal through pairwise comparison in parallel processing, and the required number of FPGA processing clock cycles is max{ceil(log2( M i / 2)), i =0,1,2,3} = 8; In ambiguity resolution, the deviation calculation requires 2 clock cycles, and the minimum deviation combination search requires log24. 3 = 6 clock cycles; the final result sums and averages in 2 clock cycles; the total time required is 180 + (2 + 9 + 2 + 6) × 3.3 ≈ 250 ns, and the root mean square error of the frequency measurement is no greater than 450 kHz. Figure 3 As shown.

[0021] In the above embodiments, although the steps are numbered S1, S2, etc., they are only specific embodiments given in this application. Those skilled in the art can adjust the execution order of S1, S2, etc. according to the actual situation, which is also within the protection scope of this invention. It can be understood that in some embodiments, some or all of the above embodiments may be included.

[0022] like Figure 4 As shown, a digital frequency measurement system 200 according to an embodiment of the present invention includes an extraction module 210, a single-bit Fourier transform module 220, an approximate modulus calculation module 230, a first calculation module 240, and a second calculation module 250. The decimation module 210 is used to: decimate the original input digital signal according to different decimation factors to obtain multiple digital signals; The single-bit Fourier transform module 220 is used to: extract local signals from each digital signal and the original input digital signal, and perform single-bit Fourier transform to obtain the single-bit Fourier transform result corresponding to each digital signal and the single-bit Fourier transform result corresponding to the original input digital signal. The number of calculation points for performing single-bit Fourier transform on any digital signal is greater than the length of the local signal extracted from that digital signal, and the number of calculation points for performing single-bit Fourier transform on the original input digital signal is greater than the length of the local signal extracted from the original input digital signal. The approximate modulus module 230 is used to: approximate the modulus of each single-bit Fourier transform result to obtain the amplitude-frequency characteristics of each digital signal and the amplitude-frequency characteristics of the original input digital signal; The first calculation module 240 is used to: search for the peak position of the amplitude spectrum of any digital signal based on the amplitude-frequency characteristics of the digital signal, calculate the frequency value of the digital signal based on the peak position of the digital signal, until the frequency value of each digital signal is obtained; search for the peak position of the amplitude spectrum of the original input digital signal based on the amplitude-frequency characteristics of the original input digital signal, and calculate the frequency value of the original input digital signal based on the peak position of the original input digital signal. The second calculation module 250 is used to: perform defuzzification calculation based on the frequency calculation value of each digital signal and the frequency calculation value of the original input digital signal to obtain the final frequency value of the original input digital signal.

[0023] Optionally, in the above technical solution, different extraction factors are not divisible by each other.

[0024] Optionally, in the above technical solution, the approximate modulus calculation module 230 is specifically used for: Taylor expansion is used to approximate the modulus of each single-bit Fourier transform result.

[0025] Optionally, in the above technical solution, the second computing module 250 is specifically used for: The minimum value of the intermediate quantity W is calculated using the first formula, which is W = Where q1∈{1,2,3,4}, q2∈{1,2,3,4}, q3∈{1,2,3,4}, , , , , , Indicates to Perform floor rounding; The final frequency value of the original input digital signal is calculated using the second formula. The second formula is: Among them, the intermediate quantity W takes the minimum value when it corresponds to The value of is 'a', and the intermediate quantity W takes the minimum value when it corresponds to 'a'. The value of is b, and the intermediate quantity W takes the minimum value corresponding to . The value of is c. The parameters and steps for implementing the corresponding functions of each unit module in the digital frequency measurement system 200 of the present invention described above can be found in the embodiments of the digital frequency measurement method above, and will not be repeated here.

[0026] An embodiment of the present invention provides a storage medium storing instructions, which, when read by a computer, cause the computer to execute any of the above-mentioned digital frequency measurement methods.

[0027] An electronic device according to an embodiment of the present invention includes a processor and the aforementioned storage medium. The processor executes instructions in the storage medium. The electronic device may be a computer, a mobile phone, or the like.

[0028] Those skilled in the art will know that this invention can be implemented as a system, method, or computer program product.

[0029] Therefore, this disclosure can be implemented in the following forms: it can be entirely hardware, entirely software (including firmware, resident software, microcode, etc.), or a combination of hardware and software, generally referred to herein as a "circuit," "module," or "system." Furthermore, in some embodiments, the invention can also be implemented as a computer program product in one or more computer-readable media containing computer-readable program code.

[0030] Any combination of one or more computer-readable media may be used. A computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in connection with an instruction execution system, apparatus, or device.

[0031] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A digital frequency measurement method, characterized in that, include: The original input digital signal is decimated according to different decimation factors to obtain multiple digital signals; Local signals are extracted from each digital signal and the original input digital signal, and a single-bit Fourier transform is performed to obtain the single-bit Fourier transform result corresponding to each digital signal and the single-bit Fourier transform result corresponding to the original input digital signal. The number of calculation points for performing a single-bit Fourier transform on any digital signal is greater than the length of the local signal extracted from that digital signal, and the number of calculation points for performing a single-bit Fourier transform on the original input digital signal is greater than the length of the local signal extracted from the original input digital signal. The magnitude of each single-bit Fourier transform result is approximated to obtain the amplitude-frequency characteristics of each digital signal and the amplitude-frequency characteristics of the original input digital signal. Based on the amplitude-frequency characteristics of any digital signal, search for the peak position of the amplitude spectrum of that digital signal, and calculate the frequency value of that digital signal based on the peak position, until the frequency value of each digital signal is obtained; based on the amplitude-frequency characteristics of the original input digital signal, search for the peak position of the amplitude spectrum of the original input digital signal, and calculate the frequency value of the original input digital signal based on the peak position. Defuzzing calculation is performed based on the frequency calculation value of each digital signal and the frequency calculation value of the original input digital signal to obtain the final frequency value of the original input digital signal; Defuzzing calculations are performed based on the frequency calculation values ​​of each digital signal and the original input digital signal to obtain the final frequency value of the original input digital signal, including: The minimum value of the intermediate quantity W is calculated using the first formula, which is W = Where q1∈{1,2,3,4}, q2∈{1,2,3,4}, q3∈{1,2,3,4}, , , , , , Indicates to Perform floor rounding; These correspond to the candidate indices of the 1st, 2nd, and 3rd extracted signals, respectively. Indicates the first The initial frequency calculation value of the extracted digital signal is obtained. Indicates the first Fuzzy integer of the path-decompressed signal, This represents the sampling rate of the original input digital signal. Indicates the first The decimation factor of the decimated signal. This represents a rough frequency calculation value of the original input digital signal; The final frequency value of the original input digital signal is calculated using the second formula. The second formula is: Wherein, the intermediate quantity W takes its minimum value. The value of is a, and the intermediate quantity W takes the minimum value corresponding to . The value of is b, and the intermediate quantity W takes the minimum value corresponding to . The value of is c.

2. The digital frequency measurement method according to claim 1, characterized in that, Different extraction factors are not divisible by each other.

3. The digital frequency measurement method according to claim 1, characterized in that, Approximate modulus calculation is performed on each single-bit Fourier transform result, including: Taylor expansion is used to approximate the modulus of each single-bit Fourier transform result.

4. A digital frequency measurement system, characterized in that, It includes an extraction module, a single-bit Fourier transform module, an approximate modulus calculation module, a first calculation module, and a second calculation module; The extraction module is used to: extract the original input digital signal according to different extraction factors to obtain multiple digital signals; The single-bit Fourier transform module is used to: extract local signals from each digital signal and the original input digital signal, and perform single-bit Fourier transform to obtain the single-bit Fourier transform result corresponding to each digital signal and the single-bit Fourier transform result corresponding to the original input digital signal. The number of calculation points for performing single-bit Fourier transform on any digital signal is greater than the length of the local signal extracted from that digital signal, and the number of calculation points for performing single-bit Fourier transform on the original input digital signal is greater than the length of the local signal extracted from the original input digital signal. The approximate modulus module is used to: approximate the modulus of each single-bit Fourier transform result to obtain the amplitude-frequency characteristics of each digital signal and the amplitude-frequency characteristics of the original input digital signal; The first calculation module is used to: search for the peak position of the amplitude spectrum of any digital signal based on its amplitude-frequency characteristics; calculate the frequency value of the digital signal based on the peak position of the digital signal, until the frequency value of each digital signal is obtained; and search for the peak position of the amplitude spectrum of the original input digital signal based on its amplitude-frequency characteristics; calculate the frequency value of the original input digital signal based on the peak position of the original input digital signal. The second calculation module is used to: perform defuzzification calculation based on the frequency calculation value of each digital signal and the frequency calculation value of the original input digital signal to obtain the final frequency value of the original input digital signal; The second calculation module is specifically used for: The minimum value of the intermediate quantity W is calculated using the first formula, which is W = Where q1∈{1,2,3,4}, q2∈{1,2,3,4}, q3∈{1,2,3,4}, , , , , , Indicates to Perform floor rounding; These correspond to the candidate indices of the 1st, 2nd, and 3rd extracted signals, respectively. Indicates the first The initial frequency calculation value of the extracted digital signal is obtained. Indicates the first Fuzzy integer of the path-decompressed signal, This represents the sampling rate of the original input digital signal. Indicates the first The decimation factor of the decimated signal. This represents a rough frequency calculation value of the original input digital signal; The final frequency value of the original input digital signal is calculated using the second formula. The second formula is: Wherein, the intermediate quantity W takes its minimum value. The value of is a, and the intermediate quantity W takes the minimum value corresponding to . The value of is b, and the intermediate quantity W takes the minimum value corresponding to . The value of is c.

5. A digital frequency measurement system according to claim 4, characterized in that, Different extraction factors are not divisible by each other.

6. A digital frequency measurement system according to claim 4, characterized in that, The approximate modulus calculation module is specifically used for: Taylor expansion is used to approximate the modulus of each single-bit Fourier transform result.

7. A storage medium, characterized in that, The storage medium stores instructions that, when read by a computer, cause the computer to execute a digital frequency measurement method as described in any one of claims 1 to 3.

8. An electronic device, characterized in that, It includes a processor and the storage medium of claim 7, wherein the processor executes instructions in the storage medium.

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