Phase measurement method and device for low-frequency time code signal, medium and equipment

Abstract

The invention discloses a phase measurement method and device for a low-frequency time code signal, a medium and equipment, and relates to the technical field of phase measurement. The low-frequency time code signal is easily interfered by noise in the propagation process, and the all-phase FFT performs weighted average processing on the signal, so that the influence of the noise can be better inhibited, and the phase measurement precision of the low-frequency time code signal is improved; in addition, due to the initial phase invariance of the all-phase FFT, additional phase compensation operation is not needed when low-frequency time code signal phase measurement is carried out, and the method is more suitable for the actual signal measurement condition; meanwhile, the all-phase FFT phase measurement method can realize high frequency measurement precision under the condition of asynchronous sampling, and realizes cost reduction and precision improvement.

Description

Technical Field

[0001] The present invention relates to the technical field of phase measurement, and in particular to a method, device, medium and equipment for measuring the phase of a low-frequency time code signal. Background Art

[0002] With the advancement of information technology and low-frequency time code signal timing technology, the industry and technology related to low-frequency time code signals are becoming increasingly sophisticated. Currently, a low-frequency time code signal transmitter is being built, transmitting an amplitude-modulated low-frequency time code signal with a 68.5 kHz carrier wave at 100 kW, providing standard time and frequency services to nearly 100 million users across various regions. With further development, the integration of various timing technologies to build a ground-based timing system to complement and back up the satellite timing system is on the agenda. This system will encompass low-frequency time code timing systems, long-wave timing systems, short-wave timing systems, and fiber-optic timing systems. The synergy of these technologies will effectively improve timing accuracy and reliability. As the low-frequency time code signal timing system continues to improve, the demand for signal quality monitoring is also increasing. Key areas of focus include field strength, phase, and amplitude modulation.

[0003] The phase of a low-frequency time code signal is a relative quantity and requires a reference zero point. However, since this is not readily available, the standard UTC (NTSC) 1PPS signal is used as the reference zero point for carrier phase measurement. When a standard 1PPS signal is available externally to the receiving device, the external 1PPS signal is used as the reference zero point. If no external 1PPS signal is present, the low-frequency time code signal is demodulated and the recovered 1PPS signal is used as the reference zero point to trigger signal acquisition. Phase measurement is then performed using various phase detection methods.

[0004] In the prior art, the main methods for monitoring the phase of low-frequency time code signals include zero-crossing detection, discrete Fourier transform (DFT), and quadrature phase detection. The zero-crossing detection method estimates two adjacent zero-crossing points and calculates the signal's carrier phase value from the resulting time difference Δt. However, when the signal is interfered with by harmonics or noise, the zero-crossing point will shift, resulting in inaccurate measurement results. The DFT method performs a DFT transform on the sampled signal, and the phase angle value of its fundamental frequency component in the frequency domain corresponds to the phase of the signal. This method can effectively remove harmonic interference, but the DFT method requires strict full-cycle sampling, otherwise the accuracy will be affected by spectrum leakage and the fence effect. The measurement accuracy of the quadrature phase detection method is greatly affected by frequency offset and is also greatly affected by environmental factors, requiring additional compensation and calibration.

[0005] In summary, the existing phase measurement methods for low-frequency time code signals have poor applicability and accuracy. Summary of the Invention

[0006] Based on this, it is necessary to provide a phase measurement method, device, medium and equipment for low-frequency time code signals to address the above technical problems.

[0007] The present invention adopts the following technical solutions:

[0008] The present invention provides a phase measurement method for a low-frequency time code signal, comprising:

[0009] Convolve the N-point window function with itself to obtain a convolution window, and normalize the convolution window to obtain a 2N-1-point normalized convolution window;

[0010] Acquire sampling data of the low-frequency time code signal, and perform windowing on the sampling data using a 2N-1 point normalized convolution window to obtain windowed sampling data;

[0011] The windowed sampled data is padded with zeros and split into two equal-length sequences, and the data at corresponding positions of the two equal-length sequences are sequentially added to obtain the fully phase-preprocessed sampled data;

[0012] The full-phase preprocessed sampling signal is subjected to fast Fourier transform to obtain the amplitude spectrum and phase spectrum of the sampling signal, and the phase value corresponding to the peak value of the amplitude spectrum of the sampling signal in the phase spectrum of the sampling signal is determined to obtain the phase measurement result of the low-frequency time code signal.

[0013] Optionally, the window function is a Hanning window:

[0014]

[0015] Where w(n) is the value of the Hanning window function at point n, N is the number of Hanning window points, and n is the sequence number of the Hanning window function.

[0016] Optionally, convolving the N-point window function with itself to obtain a convolution window specifically includes:

[0017] The 2N-1 point convolution window is obtained by convolving the N-point window function with itself using the following formula:

[0018] win2(m)=conv(win(n),win(n)), m=0,1,…,2N-1;

[0019] Among them, win2(m) is the convolution window function value at point m, win(n) is the window function value at point n, and conv() represents the convolution operation.

[0020] Optionally, normalizing the convolution window to obtain a 2N-1 point normalized convolution window specifically includes:

[0021] Sum the convolution window function values at each point, and divide the convolution window function value at each point by the summation result using the following formula to obtain the normalized convolution window:

[0022]

[0023] Among them, win3(m) is the normalized convolution window function value at point m, win2(i) is the convolution window function value at point i, and sum() represents the summation operation.

[0024] Optionally, determining a phase value corresponding to a peak value of the amplitude spectrum of the sampled signal in the phase spectrum of the sampled signal to obtain a phase measurement result of the low-frequency time code signal specifically includes:

[0025] Determine the phase radian value corresponding to the peak of the amplitude spectrum of the sampling signal in the phase spectrum of the sampling signal, convert the corresponding phase radian value into an angle, convert the angle into a time offset, and use the time offset as the result of the initial phase measurement of the low-frequency time code signal.

[0026] The present invention provides a phase measurement device for a low-frequency time code signal, comprising:

[0027] Convolution normalization module, used to convolve the N-point window function with itself to obtain a convolution window, and normalize the convolution window to obtain a 2N-1 point normalized convolution window;

[0028] A windowing module is used to obtain the sampling data of the low-frequency time code signal, and to window the sampling data through a 2N-1 point normalized convolution window to obtain the windowed sampling data;

[0029] A superposition module is used to fill the windowed sampled data with zeros and split it into two equal-length sequences, and to sequentially add the data at corresponding positions of the two equal-length sequences to obtain the fully phase-preprocessed sampled data;

[0030] The measurement module is used to perform fast Fourier transform on the fully phase preprocessed sampling signal to obtain the amplitude spectrum and phase spectrum of the sampling signal, determine the phase value corresponding to the peak value of the amplitude spectrum of the sampling signal in the phase spectrum of the sampling signal, and obtain the phase measurement result of the low-frequency time code signal.

[0031] The present invention provides a computer-readable storage medium, wherein the storage medium stores a computer program, and when the computer program is executed by a processor, the phase measurement method of the low-frequency time code signal is implemented.

[0032] The present invention provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the above-mentioned method for measuring the phase of a low-frequency time code signal is implemented.

[0033] At least one of the above technical solutions adopted by the present invention can achieve the following beneficial effects:

[0034] Low-frequency time code signals are mainly used to provide standard time and frequency signals. China's BPC broadcasts signals at 68.5 kHz and is easily affected by noise during transmission. The full-phase FFT of the present invention performs weighted averaging on the signal, which can better suppress the influence of noise and improve the phase measurement accuracy of the low-frequency time code signal.

[0035] In addition, phase offset will occur during signal propagation. The traditional orthogonal phase detection method is greatly affected by frequency offset and requires additional compensation and calibration. However, the initial phase invariance of the full-phase FFT of the present invention makes it unnecessary to perform additional phase compensation operations when measuring the phase of low-frequency time code signals, which is more suitable for actual signal measurement conditions.

[0036] At the same time, the synchronous sampling of the low-frequency time code signal receiver is relatively complicated. The full-phase FFT phase measurement method of the present invention can achieve higher frequency measurement accuracy under asynchronous sampling, thereby reducing costs and improving accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0038] Figure 1 A schematic diagram of the principle of an orthogonal phase detection method provided by the present invention;

[0039] Figure 2 A schematic flow chart of a phase measurement method for a low-frequency time code signal provided by the present invention;

[0040] Figure 3 A schematic diagram of a full-phase FFT phase measurement process provided by the present invention;

[0041] Figure 4 A schematic diagram of a signal preprocessing process provided by the present invention;

[0042] Figure 5 A schematic diagram of a full-phase FFT transformation result provided by the present invention;

[0043] Figure 6 A schematic diagram of the core steps of full-phase FFT spectrum analysis provided by the present invention;

[0044] Figure 7 A schematic diagram of a phase measurement device for a low-frequency time code signal provided by the present invention;

[0045] Figure 8A schematic diagram of a computer device for implementing a phase measurement method for a low-frequency time code signal provided by the present invention. DETAILED DESCRIPTION

[0046] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with specific embodiments of the present invention and corresponding drawings. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0047] At present, the phase measurement technology of low-frequency time code signals has high requirements for accuracy. The existing phase measurement methods mainly include zero-crossing detection method, discrete Fourier transform method and orthogonal phase detection method.

[0048] Take the orthogonal phase detection method as an example to illustrate. Figure 1 A schematic diagram of the principle of an orthogonal phase detection method in the present invention is shown in FIG. Figure 1 As can be seen, the two basic components of the quadrature phase detection method are the multiplier and the low-pass filter. The multiplier is used to modulate the two signals, and the narrowband low-pass filter is used to eliminate various noises and harmonics mixed in the signals.

[0049] Figure 1 In the two phase comparisons, each has two input signals: one input signal is S(t)=Acos(ω s t+θ); the other is a reference signal generated by a voltage-controlled oscillator with the same frequency but different phase as the input signal. The reference signals R(t) and R'(t) are strictly orthogonal, so they can be expressed as R(t) = Acosω s t, R'(t)=Asinω s t.

[0050] The two input signals first pass through the multiplier and are multiplied by two orthogonal reference signals respectively to obtain two frequency components:

[0051]

[0052] The first multiplier outputs a frequency component that is the double frequency signal of the input signal cos(2ω s t+θ), the other frequency component is a DC signal. After the signal is processed using a low-pass filter, the double frequency component in the signal is filtered out, leaving only the DC component That is, its output voltage is The corresponding output of another multiplier is the double frequency signal sin(2ω s t+θ), the DC frequency component is After low-pass filtering, we get The phase difference can be obtained by the inverse tangent function

[0053] Zero-crossing detection introduces significant noise during low-frequency time code signal transmission, which can cause zero-crossing offsets. This offset can lead to significant errors in phase measurement. Discrete Fourier transforms, on the other hand, impose strict signal sampling requirements, requiring sampling at exact integer cycles. Accuracy is lower when sampling at non-integer cycles, making implementation difficult. Quadrature phase detection, however, significantly impacts measurement accuracy due to frequency offsets and environmental factors, requiring additional compensation and calibration.

[0054] The present invention uses a full-phase FFT to effectively suppress noise while preventing spectrum leakage. The full-phase FFT maintains its initial phase, resulting in superior phase measurement accuracy compared to previous methods. It also requires no additional frequency compensation or calibration, making it suitable for measuring the phase of low-frequency time code signals. The full-phase FFT method, when measuring the phase of low-frequency time code signals, exhibits strong noise immunity and can acquire effective phase information in the presence of asynchronous sampling and noise interference. Furthermore, even in the case of asynchronous sampling, it can obtain unbiased initial phase information with sufficient accuracy without requiring frequency correction.

[0055] The technical solutions provided by various embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0056] Figure 2 The figure is a flow chart of a phase measurement method of a low-frequency time code signal in the present invention, which specifically includes the following steps:

[0057] S101: Convolve the N-point window function with itself to obtain a convolution window, and normalize the convolution window to obtain a 2N-1-point normalized convolution window.

[0058] S102: Acquire sampling data of a low-frequency time code signal, and perform windowing on the sampling data using a 2N-1 point normalized convolution window to obtain windowed sampling data.

[0059] S103: Filling the windowed sampled data with zeros and splitting it into two equal-length sequences, and sequentially adding the data at corresponding positions of the two equal-length sequences to obtain full-phase preprocessed sampled data.

[0060] S104: Perform fast Fourier transform on the fully phase preprocessed sampling signal to obtain an amplitude spectrum and a phase spectrum of the sampling signal, and determine the phase value corresponding to the peak value of the amplitude spectrum of the sampling signal in the phase spectrum of the sampling signal to obtain a phase measurement result of the low-frequency time code signal.

[0061] For the sake of convenience, the following description will only be based on the server as the execution subject. The server mentioned in the present invention can be a server set up on a business platform, or a device such as a desktop computer or a laptop computer that can execute the solution of the present invention.

[0062] The core of the present invention is to perform full-phase FFT transformation on the input discrete signal to measure the phase of the low-frequency time code signal. The main processing flow includes signal interception, windowing, convolution to enhance the spectrum effect, FFT transformation on the signal and calculation of the phase result, etc. Figure 3 As shown, Figure 3 This is a schematic diagram of a full-phase FFT phase measurement process in the present invention.

[0063] Compared to DFT, full-phase FFT includes data preprocessing, such as Figure 4 As shown, Figure 4 This is a schematic diagram of a signal preprocessing process in the present invention.

[0064] refer to Figure 4 The server may first construct an N-point window function: In one or more embodiments of the present invention, a Hanning window function may be used, such as:

[0065] Where w(n) is the Hanning window function value at point n, N is the number of Hanning window points, and n is the Hanning window function index. Compared to rectangular windows, the Hanning window has faster sidelobe attenuation, effectively suppressing spectral leakage. Furthermore, compared to more complex window functions such as the Blackman window and the Kaiser window, the Hanning window, whose mathematical form is a cosine-squared function, is simpler to implement, more computationally efficient, and offers better overall performance, making it highly valuable for engineering applications in phase measurement of low-frequency time-code signals.

[0066] During the preprocessing of the full-phase FFT transform, a variety of window functions are available. In addition to the Hanning window mentioned above, other window functions can be used for preprocessing the full-phase FFT transform, such as the Hamming window, Blackman window, Kaiser window, and rectangular window. The differences in the choice of each window function lie primarily in the requirements for sidelobe suppression, mainlobe width, phase characteristics, and computational complexity.

[0067] Afterwards, the server can convolve the window function: convolve the N-point window function with itself to obtain a 2N-1-point convolution window using the following formula: win2(m)=conv(win(n),win(n)), m=0,1,…,2N-1.

[0068] Where win2(m) is the convolution window function value at point m, win(n) is the window function value at point n, and conv() represents the convolution operation.

[0069] Then sum the convolution window: calculate the sum of all elements of the convolution window at 2N-1 points

[0070] The convolution window is then normalized: the convolution window function value at each point is divided by the summation result using the following formula to obtain the normalized convolution window:

[0071] Where win3(m) is the normalized convolution window function value at point m, win2(i) is the convolution window function value at point i, and sum() represents the summation operation.

[0072] Then perform data windowing: obtain the sampling data of the low-frequency time code signal, multiply the 1:2N-1 items of the sampling data by the normalized convolution window, and obtain the windowed 2N-1 items of sampling data y(m)=s(m)·win3(m).

[0073] Where y(m) represents the windowed sampling data at point m, and s(m) represents the sampling data at point m.

[0074] Then, data superposition is performed: zeros are added to the front of the windowed sampled data, and the data is split into two N-item sequences of equal length. The first item and the N+1 item, the second item and the N+2 item, …, the N-1 item and the 2N-1 item of the windowed sampled data are added together. The Nth item of the windowed sampled data is equivalent to being added to the padded zeros, thus obtaining an N-point sequence that has undergone full-phase preprocessing.

[0075] The above steps complete the preprocessing of the full-phase FFT transform, and then perform FFT transform on the preprocessed data, and then convert the data to obtain the phase measurement result.

[0076] Specifically, in one or more embodiments of the present invention, the server may perform a fast Fourier transform on the fully phase preprocessed sampling signal to obtain the amplitude spectrum and phase spectrum of the sampling signal, determine the phase radian value (unit: rad) corresponding to the peak value of the amplitude spectrum of the sampling signal in the phase spectrum of the sampling signal, convert the corresponding phase radian value into an angle (unit: °), and convert the angle into a time offset (unit: us). The theoretical time offset of the low-frequency time code signal should be 0us, so the time offset can be used as the result of the initial phase measurement of the low-frequency time code signal.

[0077] When the input signal is a modulated low-frequency time code signal (China BPC station, a sinusoidal signal with a carrier frequency of 68.5 kHz and amplitude modulation), N is selected as 4096 points for FFT transformation. After a series of preprocessing and calculations, the spectrum peak is finally obtained at point 3073, and the corresponding initial phase is 1e-10 microseconds. Figure 5 This is a schematic diagram of a full-phase FFT transformation result in the present invention.

[0078] The core steps of full-phase FFT spectrum analysis are as follows Figure 6 As shown, taking N=4 as an example, the data of full phase spectrum analysis comes from a point x(0) in the time series. When this point is determined, there are only N N-dimensional vectors containing this point:

[0079] x0=[x(0),x(1),…,x(N-1)] T

[0080] x1=[x(-1),x(0),…,x(N-2)] T

[0081] …

[0082] x N-1 =[x(-N+1),x(-N+2),…,x(0)] T

[0083] After cyclically shifting each vector and moving the sample point x(0) to the first position, we can obtain another N N-dimensional vectors:

[0084] x'0=[x(0),x(1),…,x(N-1)] T

[0085] x'1=[x(0),x(1),…,x(-1)] T

[0086] …

[0087] x' N-1 =[x(0),x(-N+1),…,x(-1)] T

[0088] Adding the alignment x(0) gives the full phase data vector:

[0089]

[0090] According to the shift property of DFT, the above x' i After discrete Fourier transform, we get X' i (k) and x i The discrete Fourier transform result X i (k) There is a clear relationship between:

[0091]

[0092] The above x i The average value obtained by summing over i is the output of the full-phase FFT:

[0093]

[0094]

[0095] The above formula shows that the full-phase FFT spectrum amplitude of the sequence is the square of the traditional FFT spectrum amplitude. The square relationship here applies to all spectral lines, which means that the ratio of the side spectral lines to the main spectral line will also attenuate according to this square relationship, making the main spectral line more prominent. Therefore, the full-phase FFT has better spectrum leakage suppression capabilities. At the same time, the above formula also shows that there is a close relationship between the phase values of each spectral line in the traditional FFT and the corresponding spectrum offset value mk; the phase value θ0 of the full-phase FFT spectrum is the theoretical phase value of x(0). From this, we can find another advantage of the full-phase FFT, namely, initial phase invariance.

[0096] based on Figure 2 The phase measurement method of the low-frequency time code signal shown in the figure is mainly used to provide a standard time and frequency signal. China's BPC broadcasts signals at 68.5KHz and is easily affected by noise during the propagation process. The full-phase FFT of the present invention performs weighted averaging on the signal, which can better suppress the influence of noise and improve the phase measurement accuracy of the low-frequency time code signal. In addition, phase offset will be generated during the signal propagation process. The traditional orthogonal phase detection method is greatly affected by frequency offset and requires additional compensation and calibration. The initial phase invariance of the full-phase FFT of the present invention makes it unnecessary to perform additional phase compensation operations when measuring the phase of the low-frequency time code signal, which is more suitable for actual signal measurement conditions. At the same time, the synchronous sampling of the low-frequency time code signal receiver is relatively complex. The full-phase FFT phase measurement method of the present invention can achieve higher frequency measurement accuracy under asynchronous sampling, thereby reducing costs and improving accuracy.

[0097] The present invention implements a full-phase FFT measurement method for phase measurement of low-frequency time code signals, which is innovative in this type of measurement method for low-frequency time code signals. By performing phase measurement on low-frequency time code signals through the present invention, the anti-interference capability of the entire phase measurement part can be improved, and the adaptability of the entire system to complex electromagnetic environments can be greatly improved. One feature of the present invention is that the frequency offset of the low-frequency time code signal to be measured will not affect the final phase measurement result, and measurement errors and phase compensation caused by frequency offset can be avoided. Another feature of the present invention is that the phase measurement accuracy of the low-frequency time code signal is improved by 7 orders of magnitude under ideal conditions, and by 30% when noise is included.

[0098] Compared with the orthogonal phase detection method, the measurement accuracy can be improved by 7 orders of magnitude under ideal signal conditions. In the case of noise interference, the measurement accuracy is also 30% higher than the orthogonal phase detection method. Low-frequency time code signals are typical weak signals in the low-frequency band and are easily affected by propagation noise. Compared with the orthogonal phase detection method, the full-phase FTT has stronger anti-noise ability when measuring low-frequency time code signals, and has good suppression effect on various interference noises. The full-phase FFT phase measurement method has the characteristic of unchanged initial phase, so there is no need to consider the influence of frequency offset and frequency compensation for initial phase measurement.

[0099] In addition, the present invention also provides a comparative embodiment of the method provided by the present invention and the orthogonal phase detection method. The phase error calculated by the full-phase FFT transform and the orthogonal phase detection method under different signal-to-noise ratios is compared to obtain the following Table 1:

[0100] Table 1 Phase error comparison

[0101]

[0102] By comparing the measurement errors under different signal-to-noise ratios, it can be found that under ideal signal-to-noise ratio conditions, the full-phase FFT phase measurement can be 7 orders of magnitude better than the orthogonal phase detection method; when the signal-to-noise ratio is 40dB, the error is also 1 / 9 of the orthogonal phase detection method; when the signal-to-noise ratio is 10dB, the error is also 2 / 3 of the orthogonal phase detection method. Under the selected signal-to-noise ratio, the phase error of the low-frequency time code signal measured by the full-phase FFT is smaller than that of the orthogonal phase detection method.

[0103] The above is a phase measurement method of a low-frequency time code signal provided by one or more embodiments of the present invention. Based on the same idea, the present invention also provides a corresponding phase measurement device of a low-frequency time code signal, such as Figure 7 shown.

[0104] Figure 7 A schematic diagram of a phase measurement device for a low-frequency time code signal provided by the present invention, comprising:

[0105] A convolution normalization module 201 is configured to convolve an N-point window function with itself to obtain a convolution window, and normalize the convolution window to obtain a 2N-1-point normalized convolution window;

[0106] A windowing module 202 is configured to obtain sampled data of the low-frequency time code signal and perform windowing on the sampled data using a 2N-1 point normalized convolution window to obtain windowed sampled data.

[0107] The superposition module 203 is used to fill the windowed sample data with zeros and split it into two equal-length sequences, and sequentially add the data at corresponding positions of the two equal-length sequences to obtain the fully phase-preprocessed sample data;

[0108] The measurement module 204 is used to perform a fast Fourier transform on the fully phase preprocessed sampling signal to obtain the amplitude spectrum and phase spectrum of the sampling signal, determine the phase value corresponding to the peak value of the amplitude spectrum of the sampling signal in the phase spectrum of the sampling signal, and obtain the phase measurement result of the low-frequency time code signal.

[0109] The specific limitations of the low-frequency time code signal phase measurement device can be found in the limitations of the low-frequency time code signal phase measurement method described above and will not be further elaborated here. Each module in the aforementioned low-frequency time code signal phase measurement device can be implemented in whole or in part via software, hardware, or a combination thereof. Each module can be embedded in or independent of a processor within a computer device in hardware form, or stored in a computer device memory in software form, allowing the processor to call and execute the corresponding operations of each module.

[0110] The present invention also provides a computer-readable storage medium, which stores a computer program, which can be used to execute the above Figure 2 A phase measurement method for low-frequency time code signals is provided.

[0111] The present invention also provides Figure 8 The structural diagram of the computer equipment shown in FIG. Figure 8 As shown in the figure, at the hardware level, the computer device includes a processor, an internal bus, a network interface, a memory, and a non-volatile memory. Of course, it may also include other hardware required for the business. The processor reads the corresponding computer program from the non-volatile memory into the memory and then runs it to achieve the above Figure 2 A phase measurement method for low-frequency time code signals is provided.

[0112] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided by the present invention can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory or optical memory, etc. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0113] The technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of the present invention.

Claims

1. A method for measuring the phase of a low-frequency time code signal, characterized in that: include: Convolve the N-point window function with itself to obtain a convolution window, and normalize the convolution window to obtain a 2N-1-point normalized convolution window; Acquire sampling data of the low-frequency time code signal, and perform windowing on the sampling data using a 2N-1 point normalized convolution window to obtain windowed sampling data; The windowed sampled data is padded with zeros and split into two equal-length sequences, and the data at corresponding positions of the two equal-length sequences are sequentially added to obtain the fully phase-preprocessed sampled data; The full-phase preprocessed sampling signal is subjected to fast Fourier transform to obtain the amplitude spectrum and phase spectrum of the sampling signal, and the phase value corresponding to the peak value of the amplitude spectrum of the sampling signal in the phase spectrum of the sampling signal is determined to obtain the phase measurement result of the low-frequency time code signal.

2. The method for measuring the phase of a low-frequency time code signal according to claim 1, wherein: The window function is a Hanning window: Where w(n) is the value of the Hanning window function at point n, N is the number of Hanning window points, and n is the sequence number of the Hanning window function.

3. The method for measuring the phase of a low-frequency time code signal according to claim 1, wherein: The convolution window is obtained by convolving the N-point window function with itself, specifically comprising: The 2N-1 point convolution window is obtained by convolving the N-point window function with itself using the following formula: win2(m)=conv(win(n),win(n)), m=0,1,…,2N-1; Among them, win2(m) is the convolution window function value at point m, win(n) is the window function value at point n, and conv() represents the convolution operation.

4. The method for measuring the phase of a low-frequency time code signal according to claim 1, wherein: Normalizing the convolution window to obtain a 2N-1 point normalized convolution window specifically includes: Sum the convolution window function values at each point, and divide the convolution window function value at each point by the summation result using the following formula to obtain the normalized convolution window: Among them, win3(m) is the normalized convolution window function value at point m, win2(i) is the convolution window function value at point i, and sum() represents the summation operation.

5. The method for measuring the phase of a low-frequency time code signal according to claim 1, wherein: Determining the phase value corresponding to the peak value of the amplitude spectrum of the sampling signal in the phase spectrum of the sampling signal to obtain the phase measurement result of the low-frequency time code signal specifically includes: Determine the phase radian value corresponding to the peak of the amplitude spectrum of the sampling signal in the phase spectrum of the sampling signal, convert the corresponding phase radian value into an angle, convert the angle into a time offset, and use the time offset as the result of the initial phase measurement of the low-frequency time code signal.

6. A phase measurement device for a low-frequency time code signal, characterized in that: include: Convolution normalization module, used to convolve the N-point window function with itself to obtain a convolution window, and normalize the convolution window to obtain a 2N-1 point normalized convolution window; A windowing module is used to obtain the sampling data of the low-frequency time code signal, and to window the sampling data through a 2N-1 point normalized convolution window to obtain the windowed sampling data; A superposition module is used to fill the windowed sampled data with zeros and split it into two equal-length sequences, and to sequentially add the data at corresponding positions of the two equal-length sequences to obtain the fully phase-preprocessed sampled data; The measurement module is used to perform fast Fourier transform on the fully phase preprocessed sampling signal to obtain the amplitude spectrum and phase spectrum of the sampling signal, determine the phase value corresponding to the peak value of the amplitude spectrum of the sampling signal in the phase spectrum of the sampling signal, and obtain the phase measurement result of the low-frequency time code signal.

7. A computer-readable storage medium, characterized in that The storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 5 is implemented.

8. A computer device, characterized in that: The method comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method according to any one of claims 1 to 5 when executing the program.

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