Phase difference correction method, device, equipment and medium

Abstract

This invention discloses a phase difference correction method, apparatus, device, and medium applied to interferometer direction finding. The method includes: responding to acquired correction data, filtering out invalid correction data, and classifying the remaining correction data as valid correction data; processing the zero-crossing point of the phase difference output by the phase detector, and calculating the phase difference difference between adjacent points and the true phase difference; calculating the linear correlation of the sampling points and determining whether the linear correlation is valid; calculating the linear parameter through linear regression based on the valid correction data, and then recovering the phase difference at any frequency based on the linear parameter. This invention designs the correction data processing flow in a phase interferometer direction finding system, further completing phase difference data transformation, linear correlation coefficient calculation, and phase difference data reconstruction by filtering out invalid correction data.

Description

Technical Field

[0001] This invention belongs to the field of electromagnetic signal direction finding technology, and particularly relates to phase difference correction methods, devices, equipment and media. Background Technology

[0002] There are three common types of electromagnetic signal direction finding methods: spatial spectrum estimation methods, interferometric methods, and amplitude comparison methods. Interferometric methods are widely used in various direction finding systems due to their low computational complexity and high accuracy. Interferometric direction finding includes correlation interferometer algorithms and phase interferometer algorithms.

[0003] Correlation interferometer algorithms measure the signal phase from each incoming wave direction in a real-world environment to build a database. In later applications, the incoming wave direction is accurately estimated by comparing the database and employing interpolation compensation algorithms. Due to the high sampling requirements for phase difference data and the large computational workload, correlation interferometers are more suitable for narrowband direction finding applications.

[0004] Phase interferometers utilize the phase difference measurements between multiple array elements, combined with the spatial relationships of these elements, to estimate the angle of arrival (AOA) of a target signal by analyzing and calculating the phase differences between signals from different channels. Due to their relatively low computational cost and high timeliness, phase interferometers are widely used in broadband direction-finding channelization. In practical direction-finding systems, inconsistencies between channels can affect direction-finding accuracy, necessitating effective correction methods to improve performance.

[0005] For signals of different frequencies with a fixed incident angle, the phase difference in a phase interferometer algorithm changes linearly with the signal frequency. The phase output range of a typical signal phase detector is (0, 2π). When the signal frequency changes continuously, it may exceed the detection range, leading to phase ambiguity. Long and short baselines are commonly used interferometer deambiguity methods. A long baseline ensures angular measurement accuracy, while a short, unambiguous baseline resolves the angular ambiguity of the long baseline. Inconsistencies between antenna array element channels affect direction finding accuracy, requiring effective correction methods to improve direction finding performance. For broadband direction finding systems, to reduce correction time, phase difference correction can be performed on selected frequencies. Due to the phase difference... Since there is a linear relationship with the signal frequency f, the phase difference at any frequency can be corrected by the phase difference at some frequency points. Previous systems often simply used pairwise linear interpolation between frequency points to calculate the phase difference at other frequency points.

[0006] However, linear interpolation methods have the following problems:

[0007] 1) If the error of the correction frequency is large, it will directly affect the direction finding accuracy of the interpolation frequency;

[0008] 2) Lack of judgment on the validity of calibration data. When the collected calibration data samples lack a linear relationship, the calibration data should not be accepted. Interpolation methods are difficult to expose system calibration problems. Summary of the Invention

[0009] The purpose of this invention is to overcome the shortcomings of the prior art by providing a phase difference correction method, device, equipment and medium. The correction data processing flow in the phase interferometer direction finding system is designed to complete the phase difference data transformation, linear correlation coefficient calculation and phase difference data reconstruction, thereby improving the direction finding accuracy.

[0010] The objective of this invention is achieved through the following technical solution:

[0011] A phase difference correction method, characterized in that it is applied to interferometer direction finding, the method comprising:

[0012] In response to the acquired correction data, invalid correction data is filtered out, and the remaining correction data is considered valid correction data;

[0013] After processing the zero-crossing point of the phase difference output by the phase detector, calculate the phase difference difference between adjacent points and the true phase difference;

[0014] Calculate the linear correlation of the sampling points and determine whether the linear correlation is valid;

[0015] Based on the effective correction data, linear parameters are calculated through linear regression, and then the phase difference at any frequency is recovered based on the linear parameters.

[0016] Furthermore, the filtering out of invalid correction data specifically includes frequency filtering and amplitude filtering;

[0017] The frequency filtering includes:

[0018]

[0019] Where, f′ n Given the known true frequency of the signal source in the system, f n T is the actual frequency obtained during calibration. f The threshold representing the difference between the actual frequency and the true frequency;

[0020] The amplitude filtering includes:

[0021] The amplitude of the matrix element i satisfies PA i <T PA If the correction data is invalid, then the correction amplitude of all array elements is greater than or equal to T. PA The correction data is valid;

[0022] Where the frequency is f, and the amplitude of array element i is PA. i TPA The threshold representing the correction magnitude.

[0023] Furthermore, the method also includes determining whether the proportion of the effective correction data meets the requirements after acquiring the effective correction data, specifically including:

[0024] like Therefore, the data collected for this calibration does not meet the requirements;

[0025] like Therefore, the data collected in this calibration meets the requirements;

[0026] Among them, C invalid C represents the number of invalid correction data to be filtered. valid To effectively correct the amount of data, T C The threshold representing the proportion of invalid correction data.

[0027] Furthermore, calculating the phase difference between the adjacent points includes:

[0028]

[0029] in, and f i These are the phase difference between the i-th and (i-1)-th correction data, the measured phase difference, and the frequency, respectively.

[0030] Will The following steps were taken:

[0031]

[0032]

[0033] Calculating the true phase difference includes:

[0034]

[0035] in, This represents the true phase difference.

[0036] Furthermore, the calculation of the linear correlation of the sampling points includes based on the phase difference. and frequency f i Calculate the linear correlation:

[0037] linear correlation

[0038] Furthermore, determining whether the linear correlation is valid includes:

[0039] If |r| <T r If the linear correlation is invalid, the data collected for this correction does not meet the requirements.

[0040] If |r|≥T r If the linear correlation is valid, the data collected for this correction meets the requirements.

[0041] Among them, T r This is the threshold for the degree of linear correlation of phase difference.

[0042] Furthermore, the step of calculating the linear parameters through linear regression based on the effective correction data includes:

[0043] Assumption

[0044] Based on the collected correction data, k and b are calculated using linear regression:

[0045]

[0046] On the other hand, the present invention also provides a phase difference correction device, the device comprising:

[0047] The data filtering module, in response to the acquired correction data, filters out invalid correction data, and the remaining correction data is valid correction data;

[0048] The phase difference calculation module is used to process the zero-crossing point of the phase difference output by the phase detector and calculate the phase difference difference between adjacent points and the true phase difference.

[0049] The data judgment module is used to calculate the linear correlation of the sampling points and determine whether the corrected data is effective;

[0050] The phase difference recovery module is used to calculate linear parameters through linear regression based on the effective correction data, and then recover the phase difference of any frequency based on the linear parameters.

[0051] Optionally, the data filtering module filters out invalid correction data, specifically including frequency filtering and amplitude filtering;

[0052] The frequency filtering includes:

[0053]

[0054] Where, f′ n Given the known true frequency of the signal source in the system, f n T is the actual frequency obtained during calibration. f The threshold representing the difference between the actual frequency and the true frequency;

[0055] The amplitude filtering includes:

[0056] The amplitude of the matrix element i satisfies PA i <T PAIf the correction data is invalid, then the correction amplitude of all array elements is greater than or equal to T. PA The correction data is valid;

[0057] Where the frequency is f, and the amplitude of array element i is PA. i T PA The threshold representing the correction magnitude.

[0058] Optionally, the data filtering module is further configured to determine whether the proportion of valid correction data meets the requirements after obtaining valid correction data, specifically including:

[0059] like Therefore, the data collected for this calibration does not meet the requirements;

[0060] like Therefore, the data collected in this calibration meets the requirements;

[0061] Among them, C invalid C represents the number of invalid correction data to be filtered. valid To effectively correct the amount of data, T C The threshold representing the proportion of invalid correction data.

[0062] Optionally, the phase difference calculation module calculates the phase difference value between the adjacent points by:

[0063]

[0064] in, and f i These are the phase difference between the i-th and (i-1)-th correction data, the measured phase difference, and the frequency, respectively.

[0065] Will The following steps were taken:

[0066]

[0067]

[0068] Calculating the true phase difference includes:

[0069]

[0070] in, This represents the true phase difference.

[0071] Optionally, the data judgment module calculates the linear correlation of the sampling points by considering the phase difference. and frequency f i Calculate the linear correlation:

[0072] linear correlation

[0073] Optionally, the data judgment module determines whether the linear correlation is valid by including:

[0074] If |r| <T r If the linear correlation is invalid, the data collected for this correction does not meet the requirements.

[0075] If |r|≥T r If the linear correlation is valid, the data collected for this correction meets the requirements.

[0076] Among them, T r This is the threshold for the degree of linear correlation of phase difference.

[0077] Optionally, the phase difference recovery module calculates the linear parameters based on the effective correction data using linear regression, including:

[0078] Assumption

[0079] Based on the collected correction data, k and b are calculated using linear regression:

[0080]

[0081] On the other hand, the present invention also provides a computer device, the computer device including a processor and a memory, the memory storing a computer program, the computer program being loaded and executed by the processor to implement any of the phase difference correction methods described above.

[0082] On the other hand, the present invention also provides a computer-readable storage medium storing a computer program, which is loaded and executed by a processor to implement any of the phase difference correction methods described above.

[0083] The beneficial effects of this invention are as follows:

[0084] This invention implements a phase difference data reconstruction method, which designs the correction data processing flow in a phase interferometer direction finding system. By filtering invalid correction data, it further completes phase difference data transformation, linear correlation coefficient calculation, and phase difference data reconstruction. Compared with traditional methods, the processing results can determine the validity of correction data and thus indicate system errors, facilitating problem location and modification. Based on finite correction data, linear regression can calculate the phase difference at a fixed correction incident angle at any frequency point, which not only reduces correction time and improves correction efficiency but also reduces the impact of correction errors and improves direction finding accuracy. Attached Figure Description

[0085] Figure 1This is a schematic flowchart of a phase difference correction method provided in an embodiment of the present invention;

[0086] Figure 2 This is a phase difference / frequency relationship diagram of the phase detector output in an embodiment of the present invention;

[0087] Figure 3 This is a phase difference / frequency relationship diagram after transformation according to an embodiment of the present invention;

[0088] Figure 4 This is a block diagram illustrating a typical four-baseline phase interferometer direction finding system according to an embodiment of the present invention.

[0089] Figure 5 This is a structural block diagram of a phase difference correction device provided in an embodiment of the present invention. Detailed Implementation

[0090] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that, unless otherwise specified, the following embodiments and features described therein can be combined with each other.

[0091] Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0092] Due to phase difference Since there is a linear relationship with the signal frequency f, the phase difference at any frequency can be corrected by the phase difference at some frequency points. Previous systems often simply used pairwise linear interpolation between frequency points to calculate the phase difference at other frequency points.

[0093] However, linear interpolation methods have the following problems:

[0094] 1) If the error of the correction frequency is large, it will directly affect the direction finding accuracy of the interpolation frequency;

[0095] 2) Lack of judgment on the validity of calibration data. When the collected calibration data samples lack a linear relationship, the calibration data should not be accepted. Interpolation methods are difficult to expose system calibration problems.

[0096] To address the aforementioned technical problems, the following embodiments of the phase difference correction method, apparatus, device, and medium of the present invention are proposed.

[0097] Example 1

[0098] Reference Figure 1 ,like Figure 1 The diagram shown is a schematic flowchart of a phase difference correction method provided in this embodiment. The method specifically includes the following steps:

[0099] Step S100: In response to the acquired correction data, invalid correction data is filtered out, and the remaining correction data is valid correction data.

[0100] Specifically, filtering out invalid correction data includes frequency filtering and amplitude filtering;

[0101] Frequency filtering includes:

[0102]

[0103] Where, f′ n Given the known true frequency of the signal source in the system, f n T is the actual frequency obtained during calibration. f The threshold representing the difference between the actual frequency and the true frequency;

[0104] Amplitude filtering includes:

[0105] The amplitude of the matrix element i satisfies PA i <T PA If the correction data is invalid, then the correction amplitude of all array elements is greater than or equal to T. PA The correction data is valid;

[0106] Where the frequency is f, and the amplitude of array element i is PA. i T PA The threshold representing the correction magnitude.

[0107] As one implementation method, the method further includes determining whether the proportion of valid correction data meets the requirements after acquiring valid correction data, specifically including:

[0108] like Therefore, the data collected for this calibration does not meet the requirements;

[0109] like Therefore, the data collected in this calibration meets the requirements;

[0110] Among them, C invalid C represents the number of invalid correction data to be filtered. valid To effectively correct the amount of data, T C The threshold representing the proportion of invalid correction data.

[0111] Step S200: After processing the zero-crossing point of the phase difference output by the phase detector, calculate the phase difference difference between adjacent points and the true phase difference.

[0112] according to It can be seen that when the incident angle is fixed, the phase difference is linearly related to the frequency. However, since the phase output value of the signal phase detector is in the range of (0, 2π), the measured phase difference may flip when the frequency changes continuously, resulting in the measured phase difference not completely satisfying the linear relationship with the frequency.

[0113] Reference Figure 2 ,like Figure 2 The diagram shown is a phase difference / frequency relationship graph output by the phase detector in this embodiment. Due to the presence of a zero-crossing point in the phase difference, the measured phase difference does not perfectly match... Therefore, zero-point processing is required.

[0114] Reference Figure 3 ,like Figure 3 The diagram shown is the phase difference / frequency relationship after transformation in this embodiment. After zero-crossing processing, the result is... Figure 3 The transformed phase difference / frequency relationship diagram is derived from... Figure 3 It can be seen that the phase difference has a linear relationship with the frequency. and f i These are the phase difference and frequency measured for the i-th correction data, respectively.

[0115] Calculating the phase difference between adjacent points specifically includes:

[0116]

[0117] Because there is a zero-crossing point in the phase difference, Perform the following processing

[0118]

[0119]

[0120] in, and f i These are the phase difference and frequency measured for the i-th correction data, respectively.

[0121] Calculate the true phase difference Specifically, it includes:

[0122]

[0123] Step S300: Calculate the linear correlation of the sampling points and determine whether the linear correlation is valid.

[0124] Due to phase difference and frequency f i Theoretically, the linear relationship is linear. Therefore, the linear correlation of the sampling points can be calculated to determine whether the correction data is effective. If the linear correlation is poor, the correction data can be considered invalid, and the error will be reported to the system.

[0125] The formula for calculating the linear correlation coefficient r is as follows:

[0126]

[0127] It can be proven that |r|≤1, the closer |r| is to 1, the stronger the linear correlation; the closer |r| is to 0, the weaker the linear correlation. r A threshold representing the degree of linear correlation of phase differences.

[0128] If |r|≥T r Then proceed to the next phase difference reconstruction operation;

[0129] If |r| <T r If the collected data for this calibration does not meet the requirements, an error will be reported to the system, and the process will end.

[0130] It should be noted that when |r|>0.6, it indicates a strong correlation, generally T r It should be greater than 0.6.

[0131] Step S400: Based on the effective correction data, calculate the linear parameters through linear regression, and then recover the phase difference of any frequency based on the linear parameters.

[0132] Due to phase difference and frequency f i Linear correlation, assuming Based on the collected calibration data, k and b can be calculated using linear regression.

[0133]

[0134] Given k and b, the phase difference of any frequency can be recovered.

[0135] The phase difference correction method provided in this embodiment is designed for the correction data processing flow in a phase interferometer direction finding system. By filtering invalid correction data, it further completes phase difference data transformation, linear correlation coefficient calculation, and phase difference data reconstruction. Compared with traditional methods, the processing results can determine the validity of the correction data and thus indicate system errors, facilitating problem location and modification. Based on finite correction data, linear regression can be performed to calculate the phase difference at any frequency point with a fixed correction incident angle. This not only reduces correction time and improves correction efficiency but also reduces the impact of correction errors and improves direction finding accuracy.

[0136] Example 2

[0137] This embodiment uses a typical 4-baseline phase interferometer direction finding system for illustration.

[0138] Reference Figure 4 ,like Figure 4The diagram shown is a typical block diagram of a 4-baseline phase interferometer direction finding system in this embodiment.

[0139] The calibration data between channels A and B are shown in the table below.

[0140]

[0141]

[0142] The meanings of the symbols in the table are as follows:

[0143] Phi AB Phase difference between antenna elements A and B;

[0144] Pa A The amplitude of antenna element A;

[0145] Pa B : Amplitude of antenna element B;

[0146] Pa C The amplitude of antenna array element C;

[0147] Pa D The amplitude of antenna element D;

[0148] Phi′ AB Phase difference between A and B after transformation;

[0149] Set a threshold T for the difference between the actual frequency and the true frequency. f The frequency is 3MHz, and the correction amplitude threshold T PA The threshold T for the proportion of invalid corrected data is 30. C The threshold for the linear correlation coefficient is 30%. r It is 0.7. According to... The filtering rules are used to filter out invalid data:

[0150] 1) The actual frequency of the 1360MHz calibration frequency in the table above is 1355MHz, which does not meet the requirements and is invalid data;

[0151] 2) The amplitudes of each channel at the correction frequencies of 1660MHz and 1900MHz in the table above do not meet the requirements and are invalid data.

[0152] Number of invalid data points C invalid =3, number of valid data points C valid =14, which meets the requirements, as shown below:

[0153]

[0154] After removing invalid data, phase difference transformation is performed, as shown in the table below.

[0155]

[0156]

[0157]

[0158] Calculate f using MATLAB i and Phi′ AB The linear correlation coefficient r = 0.99 > T r It meets the requirements for linear correlation.

[0159] according to Calculate k and b, k = 0.008788, b = -7.662411. The phase difference Phi′ between array elements A and B. AB The functional relationship between frequencies f is shown below.

[0160] Phi′ AB =0.008788*f-7.662411

[0161] According to the above formula, the phase difference data at any frequency point can be recovered. In this example, the minimum frequency step used by the receiver for correction is 20MHz. The 20MHz step phase difference between 1300MHz and 2000MHz is reconstructed as shown in the table below.

[0162]

[0163]

[0164]

[0165]

[0166] As shown in the table above, the phase difference at any frequency point can be recovered after processing the correction data using this method. Increasing the frequency step can significantly improve the correction rate. The processing in this example meets the correction data requirements of a digital receiver.

[0167] Example 3

[0168] Reference Figure 5 ,like Figure 5 The diagram shown is a structural block diagram of a phase difference correction device provided in this embodiment. The device specifically includes:

[0169] The data filtering module 10, in response to the acquired correction data, filters out invalid correction data, and the remaining correction data is valid correction data;

[0170] The phase difference calculation module 20 is used to calculate the phase difference difference between adjacent points and the true phase difference after processing the zero-crossing point of the phase difference output by the phase detector;

[0171] The data judgment module 30 is used to calculate the linear correlation of the sampling points and determine whether the correction data is effective;

[0172] The phase difference recovery module 40 is used to calculate the linear parameters through linear regression based on the effective correction data, and then recover the phase difference of any frequency based on the linear parameters.

[0173] As one implementation method, the data filtering module 10 filters out invalid correction data, specifically including frequency filtering and amplitude filtering;

[0174] Frequency filtering includes:

[0175]

[0176] Where, f′ n Given the known true frequency of the signal source in the system, f n T is the actual frequency obtained during calibration. f The threshold representing the difference between the actual frequency and the true frequency;

[0177] Amplitude filtering includes:

[0178] The amplitude of the matrix element i satisfies PA i <T PA If the correction data is invalid, then the correction amplitude of all array elements is greater than or equal to T. PA The correction data is valid;

[0179] Where the frequency is f, and the amplitude of array element i is PA. i T PA The threshold representing the correction magnitude.

[0180] As one implementation method, the data filtering module 10 is also used to determine whether the proportion of valid correction data meets the requirements after acquiring valid correction data, specifically including:

[0181] like Therefore, the data collected for this calibration does not meet the requirements;

[0182] like Therefore, the data collected in this calibration meets the requirements;

[0183] Among them, C invalid C represents the number of invalid correction data to be filtered. valid To effectively correct the amount of data, T C The threshold representing the proportion of invalid correction data.

[0184] As one implementation method, the phase difference calculation module 20 calculates the phase difference between adjacent points by including:

[0185]

[0186] in, and f i These are the phase difference between the i-th and (i-1)-th correction data, the measured phase difference, and the frequency, respectively.

[0187] Will The following steps were taken:

[0188]

[0189]

[0190] Calculating the true phase difference includes:

[0191]

[0192] in, This represents the true phase difference.

[0193] As one implementation method, the data judgment module 30 calculates the linear correlation of the sampling points, including based on the phase difference. and frequency f i Calculate the linear correlation:

[0194] linear correlation

[0195] As one implementation method, the data judgment module 30 determines whether the linear correlation is valid by including:

[0196] If |r| <T r If the linear correlation is invalid, the data collected for this correction does not meet the requirements.

[0197] If |r|≥T r If the linear correlation is valid, the data collected for this correction meets the requirements.

[0198] Among them, T r This is the threshold for the degree of linear correlation of phase difference.

[0199] As one implementation method, the phase difference recovery module 40 calculates linear parameters based on the effective correction data using linear regression, including:

[0200] Assumption

[0201] Based on the collected correction data, k and b are calculated using linear regression:

[0202]

[0203] The phase difference correction device provided in this embodiment is designed for the correction data processing flow in a phase interferometer direction finding system. By filtering invalid correction data, it further completes phase difference data transformation, linear correlation coefficient calculation, and phase difference data reconstruction. Compared with traditional methods, the processing results can determine the validity of the correction data and thus indicate system errors, facilitating problem location and modification. Based on finite correction data, linear regression can calculate the phase difference at any frequency point with a fixed correction incident angle, which not only reduces correction time and improves correction efficiency but also reduces the impact of correction errors and improves direction finding accuracy.

[0204] Example 4

[0205] This preferred embodiment provides a computer device that can implement the steps of any embodiment of the phase difference correction method provided in this application. Therefore, it can achieve the beneficial effects of the phase difference correction method provided in this application. For details, please refer to the previous embodiments, which will not be repeated here.

[0206] Example 5

[0207] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by instructions, or by instructions controlling related hardware. These instructions can be stored in a computer-readable storage medium and loaded and executed by a processor. Therefore, embodiments of the present invention provide a storage medium storing multiple instructions that can be loaded by a processor to execute the steps of any embodiment of the phase difference correction method provided by the present invention.

[0208] The storage medium may include: read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.

[0209] Since the instructions stored in the storage medium can execute the steps in any phase difference correction method embodiment provided by the present invention, the beneficial effects that any phase difference correction method provided by the present invention can achieve can be realized, as detailed in the preceding embodiments, and will not be repeated here.

[0210] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A phase difference correction method characterized by, The method is applied to interferometer direction finding, and the method comprises the following steps: In response to the obtained correction data, invalid correction data is screened out, and the remaining correction data is valid correction data; wherein the screening out of the invalid correction data specifically comprises frequency screening and amplitude screening; The frequency screening comprises: where f n ′ f is the true frequency of the signal source known to the system n T is the actual frequency acquired at the time of correction f δ represents the threshold value of the difference between the actual frequency and the true frequency The amplitude screening comprises: The amplitude of the matrix element i satisfies PA i <T PA If the correction data is invalid, then the correction amplitude of all array elements is greater than or equal to T. PA The correction data is valid; wherein the frequency f, the amplitude of the element i is PA i , T PA denotes a threshold value for the correction amplitude; The phase difference over-zero point output by the phase discriminator is processed, and the phase difference difference value and the real phase difference of adjacent correction data points are calculated, comprising: wherein, and f i respectively the phase difference difference value of the i-th correction data and the (i-1)-th correction data, the measured phase difference and the frequency; The following The following treatments were applied: The calculation of the real phase difference comprises: wherein represents the true phase difference; Based on the real phase difference and the frequency, the linear correlation degree of the sampling point is calculated, and whether the linear correlation degree is valid is judged, wherein: The computing the linear correlation of the sampling points comprises calculating the linear correlation according to the phase difference and the frequency f i computing the linear correlation: Linear correlation The judgment of whether the linear correlation degree is valid comprises: If |r| < T r Then, it is determined that the linear correlation is invalid, and the current correction data acquisition does not meet the requirements. If |r| ≥ T r Then, the linear correlation is determined to be valid, and the current calibration data acquisition meets the requirements. wherein T r is a threshold value for the degree of linear correlation of the phase difference; When the linear correlation degree is valid, the linear parameter is calculated through linear regression according to the valid correction data, and the phase difference of any frequency is recovered according to the linear parameter.

2. The phase difference correction method according to claim 1, wherein The method further comprises judging whether the proportion of the valid correction data meets the requirements after obtaining the valid correction data, specifically comprising: If then the current calibration acquisition data does not meet the requirements; If then the current calibration data acquisition meets the requirements; where C invalid is the number of invalid correction data for screening, C valid is the number of valid correction data, T C is the threshold value indicating the proportion of invalid correction data.

3. The phase difference correction method according to claim 1, wherein The calculation of the linear parameter through linear regression according to the valid correction data comprises: Assume According to the collected correction data, k and b are calculated through linear regression:

4. A phase difference correction device characterized by comprising: The device comprises: A data screening module, in response to the obtained correction data, invalid correction data is screened out, and the remaining correction data is valid correction data; wherein the screening out of the invalid correction data specifically comprises frequency screening and amplitude screening; The frequency screening comprises: where f n ′ f is the true frequency of the signal source known to the system n T is the actual frequency acquired at the time of correction f T is the threshold value representing the difference between the actual frequency and the true frequency The amplitude screening comprises: The amplitude of the matrix element i satisfies PA i <T PA If the correction data is invalid, then the correction amplitude of all array elements is greater than or equal to T. PA The correction data is valid; wherein the frequency f, the amplitude of the element i is PA i , T PA denotes a threshold value for the correction amplitude; A phase difference calculation module for processing the phase difference over-zero point output by the phase discriminator, calculating the phase difference difference value and the real phase difference of adjacent correction data points, comprising: wherein, and f i respectively the phase difference difference value of the i-th correction data and the (i-1)-th correction data, the measured phase difference and the frequency; The following The following treatments were applied: The calculation of the real phase difference comprises: wherein represents the true phase difference; A data judgment module for calculating the linear correlation degree of the sampling point based on the real phase difference and the frequency, and judging whether the correction data is valid, wherein: The computing the linear correlation of the sampling points comprises calculating the linear correlation according to the phase difference and the frequency f i computing the linear correlation: Linear correlation The judgment of whether the linear correlation degree is valid comprises: If |r| < T r Then, it is determined that the linear correlation is invalid, and the current calibration data does not meet the requirements. If |r| ≥ T r Then, the linear correlation is determined to be valid, and the current calibration data acquisition meets the requirements. wherein T r is a threshold value for the degree of linear correlation of the phase difference; A phase difference recovery module, when the linear correlation degree is valid, for calculating the linear parameter through linear regression according to the valid correction data, and recovering the phase difference of any frequency according to the linear parameter.

5. A computer device, comprising: The computer device comprises a processor and a memory, the memory stores a computer program, the computer program is loaded and executed by the processor to realize the phase difference correction method according to any one of claims 1-3.

6. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, the computer program is loaded and executed by the processor to realize the phase difference correction method according to any one of claims 1-3.

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