Mirror image distortion correction method, system and device, medium and program product

Abstract

The invention discloses a mirror image distortion correction method, system and device, a medium and a program product, which are used for eliminating mirror image distortion at a beam level and reducing hardware resources required by mirror image correction. The method comprises the following steps: determining a correction value of a first beam signal based on a predetermined beam-level mirror image distortion coefficient matrix of a beam channel where the first beam signal is located and a plurality of beam signals, the influence weights are used for representing influence weights of partial or all beam channels in mirror image distortion signals of a single beam channel; and correcting the first beam signal by using the correction value of the first beam signal to obtain a second beam signal.

Description

Technical Field

[0001] This application relates to the field of communication technology, and in particular to a method, system, device, medium and program product for correcting image distortion. Background Technology

[0002] With the continuous advancement of digital signal processing technology, zero-IF receivers have been widely used due to their advantages such as simple circuit structure, low power consumption, easy integration, small size, and low cost.

[0003] Currently, in zero-IF reception scenarios, the quadrature local oscillator frequency sources used by the in-phase (I) branch and the quadrature (Q) branch cannot guarantee absolute orthogonality, i.e. there is IQ mismatch, which will cause image distortion in the received signal.

[0004] Specifically, assuming the input signal is the initial baseband frequency w b The single-tone signal, the local oscillator signal is at frequency w c Ideally, the amplitudes and phases of the signals from the I and Q branches should be completely orthogonal to obtain the frequency point w. b +w c The transmitted signal, however, cannot actually guarantee that the amplitude and phase of the I and Q branches are completely orthogonal, resulting in IQ mismatch. Besides obtaining the frequency point w... b +w c The transmitted signal is at a frequency w that is mirror-symmetrical to the local oscillator. c -w b There is also a non-ideal signal, a phenomenon known as "mirror distortion".

[0005] In related technologies, channel-level correction is the main method to solve the image distortion problem. However, in large-scale digital beamforming arrays, channel-level correction algorithms need to be implemented in each receiving channel, which requires a lot of hardware resources. Summary of the Invention

[0006] This application provides a method, system, device, medium, and program product for correcting image distortion, which can eliminate image distortion at the beam level and reduce the hardware resources required for image correction.

[0007] In a first aspect, embodiments of this application provide a method for correcting image distortion, the method comprising:

[0008] Based on the pre-determined beam-level image distortion coefficient matrix of the beam channel where the first beam signal is located and multiple beam signals, the correction value of the first beam signal is determined. The beam-level image distortion coefficient matrix is ​​used to characterize the influence weight of some or all beam channels in the image distortion signal of a single beam channel.

[0009] The first beam signal is corrected using the correction value of the first beam signal to obtain the second beam signal.

[0010] As an optional implementation, determining the correction value of the first beam signal based on a predetermined beam-level image distortion coefficient matrix of the beam channel where the first beam signal is located and multiple beam signals includes:

[0011] Determine the reference signal corresponding to each beam signal;

[0012] The correction value of the first beam signal is determined based on the beam-level image distortion coefficient matrix of the beam channel in which the first beam signal is located and the reference signal corresponding to each beam signal.

[0013] As an optional implementation, determining the correction value of the first beam signal based on the beam-level image distortion coefficient matrix of the beam channel where the first beam signal is located and the reference signal corresponding to each beam signal includes:

[0014] The influence weight of each beam channel in the beam-level image distortion coefficient matrix of the beam channel where the first beam signal is located is multiplied by the reference signal corresponding to the beam signal in each beam channel to obtain multiple products. The multiple products are then summed to obtain the correction value of the first beam signal.

[0015] As an optional implementation, the reference signal includes a conjugate signal of the beam signal.

[0016] As an optional implementation, the beam-level image distortion coefficient matrix of the beam channel is determined in the following manner:

[0017] Obtain the beamforming weight matrix;

[0018] Based on the beamforming weight matrix, the image distortion weight matrix of the beam channel is determined. The image distortion weight matrix of the beam channel is used to characterize the influence weight of some or all beam channels in the image distortion signal of the receiving channel.

[0019] Based on the channel-level image distortion coefficient matrix and the image distortion weight matrix of the beam channel, the beam-level image distortion coefficient matrix of the beam channel is determined. The channel-level image distortion coefficient matrix is ​​an N×1 dimensional matrix that includes the image distortion coefficients of some or all of the receiving channels.

[0020] As an optional implementation, the channel-level image distortion coefficient matrix is ​​estimated during antenna calibration.

[0021] As an optional implementation, the channel-level image distortion coefficient matrix is ​​determined in the following manner:

[0022] For the target receiving channel, perform the following operations to obtain the image distortion coefficient of the target receiving channel, and then combine the image distortion coefficients of the receiving channels sequentially according to the order of the receiving channels to obtain the channel-level image distortion coefficient matrix:

[0023] During antenna calibration, the original calibration sequence signal and the calibration reference signal received by the calibration reference channel are acquired.

[0024] Based on the calibration reference signal, delay compensation and complex gain compensation are performed on the correction sequence signal received by the target receiving channel to obtain the corrected sequence signal;

[0025] Calculate the difference between the corrected sequence signal and the original corrected sequence signal to determine the error signal;

[0026] Based on the error signal and the original correction sequence signal, the mirror mismatch coefficient of the target receiving channel is calculated, wherein the target receiving channel is any one of multiple receiving channels.

[0027] As an optional implementation, determining the image distortion weight matrix of the beam channel based on the beamforming weight matrix includes:

[0028] Based on the following formula, the image distortion weight matrix of the beam channel is determined using the element values ​​in the beamforming weight matrix:

[0029]

[0030] Among them, e mn (k)=BF mn *BF kn E(k) is the image distortion weight matrix of the k-th beam channel, BF mn Let BF be the element value in the m-th row and n-th column of the beamforming weight matrix. kn Let M be the element value in the k-th row and n-th column of the beamforming weight matrix, where M is the total number of beam signals, N is the total number of receiving channels, n is the n-th receiving channel, and m is the m-th beam signal. m, n, N, and M are all positive integers.

[0031] Secondly, embodiments of this application provide a mirror distortion correction device, the device comprising:

[0032] The processing unit is used to determine the correction value of the first beam signal based on the beam-level image distortion coefficient matrix of the beam channel where the first beam signal is located and multiple beam signals. The beam-level image distortion coefficient matrix is ​​used to characterize the influence weight of some or all beam channels in the image distortion signal of a single beam channel.

[0033] The correction unit is used to correct the first beam signal using the correction value of the first beam signal to obtain the second beam signal.

[0034] As an optional implementation, the processing unit is specifically used for:

[0035] Determine the reference signal corresponding to each beam signal;

[0036] The correction value of the first beam signal is determined based on the beam-level image distortion coefficient matrix of the beam channel in which the first beam signal is located and the reference signal corresponding to each beam signal.

[0037] As an optional implementation, the processing unit is specifically used for:

[0038] The influence weight of each beam channel in the beam-level image distortion coefficient matrix of the beam channel where the first beam signal is located is multiplied by the reference signal corresponding to the beam signal in each beam channel to obtain multiple products. The multiple products are then summed to obtain the correction value of the first beam signal.

[0039] As an optional implementation, the reference signal includes a conjugate signal of the beam signal.

[0040] As an optional implementation, the processing unit predetermines the beam-level image distortion coefficient matrix of the beam channel in the following manner:

[0041] Obtain the beamforming weight matrix;

[0042] Based on the beamforming weight matrix, the image distortion weight matrix of the beam channel is determined. The image distortion weight matrix of the beam channel is used to characterize the influence weight of some or all beam channels in the image distortion signal of the receiving channel.

[0043] Based on the channel-level image distortion coefficient matrix and the image distortion weight matrix of the beam channel, the beam-level image distortion coefficient matrix of the beam channel is determined. The channel-level image distortion coefficient matrix is ​​an N×1 dimensional matrix that includes the image distortion coefficients of some or all of the receiving channels.

[0044] As an optional implementation, the channel-level image distortion coefficient matrix is ​​estimated during antenna calibration.

[0045] As an optional implementation, the processing unit determines the channel-level image distortion coefficient matrix in the following manner:

[0046] For the target receiving channel, perform the following operations to obtain the image distortion coefficient of the target receiving channel, and then combine the image distortion coefficients of the receiving channels sequentially according to the order of the receiving channels to obtain the channel-level image distortion coefficient matrix:

[0047] During antenna calibration, the original calibration sequence signal and the calibration reference signal received by the calibration reference channel are acquired.

[0048] Based on the calibration reference signal, delay compensation and complex gain compensation are performed on the correction sequence signal received by the target receiving channel to obtain the corrected sequence signal;

[0049] Calculate the difference between the corrected sequence signal and the original corrected sequence signal to determine the error signal;

[0050] Based on the error signal and the original correction sequence signal, the mirror mismatch coefficient of the target receiving channel is calculated, wherein the target receiving channel is any one of multiple receiving channels.

[0051] As an optional implementation, the processing unit is specifically used for:

[0052] Based on the following formula, the image distortion weight matrix of the beam channel is determined using the element values ​​in the beamforming weight matrix:

[0053]

[0054] Among them, e mn (k)=BF mn *BF kn E(k) is the image distortion weight matrix of the k-th beam channel, BF mn Let BF be the element value in the m-th row and n-th column of the beamforming weight matrix. kn Let M be the element value in the k-th row and n-th column of the beamforming weight matrix, where M is the total number of beam signals, N is the total number of receiving channels, n is the n-th receiving channel, and m is the m-th beam signal. m, n, N, and M are all positive integers.

[0055] Thirdly, embodiments of this application provide a mirror distortion correction system, comprising: a digital beamforming module, a channel-level mirror distortion coefficient matrix calculation module, a mirror distortion weight matrix calculation module, a beam-level mirror distortion coefficient matrix calculation module, and a mirror correction module, wherein...

[0056] The digital beamforming module is used to perform digital beamforming on multiple raw signals received by the receiving channel based on the beamforming weight matrix to obtain multiple beam signals, and then transmit the multiple beam signals to the mirror correction module.

[0057] The channel-level image distortion coefficient matrix calculation module is connected to some or all of the receiving channels respectively, and is used to determine the channel-level image distortion coefficient matrix;

[0058] The image distortion weight matrix calculation module is connected to the digital beamforming module and is used to determine the image distortion weight matrix of the beam channel.

[0059] The beam-level image distortion coefficient matrix calculation module is connected to the channel-level image distortion coefficient matrix calculation module and the image distortion weight matrix calculation module, and is used to determine the beam-level image distortion coefficient matrix of the beam channel based on the channel-level image distortion coefficient matrix and the image distortion weight matrix of the beam channel.

[0060] The image correction module is connected to the beam-level image distortion coefficient matrix calculation module. It is used to determine the correction value of the first beam signal based on the beam-level image distortion coefficient matrix of the beam channel where the first beam signal is located and the multiple beam signals, and to correct the first beam signal using the correction value of the first beam signal to obtain the second beam signal.

[0061] As an optional implementation, the mirror correction module is specifically used for:

[0062] Determine the reference signal corresponding to each beam signal;

[0063] The correction value of the first beam signal is determined based on the beam-level image distortion coefficient matrix of the beam channel in which the first beam signal is located and the reference signal corresponding to each beam signal.

[0064] As an optional implementation, the mirror correction module is specifically used for:

[0065] The influence weight of each beam channel in the beam-level image distortion coefficient matrix of the beam channel where the first beam signal is located is multiplied by the reference signal corresponding to the beam signal in each beam channel to obtain multiple products. The multiple products are then summed to obtain the correction value of the first beam signal.

[0066] As an optional implementation, the reference signal includes a conjugate signal of the beam signal.

[0067] As an optional implementation, the channel-level image distortion coefficient matrix is ​​an N×1 dimensional matrix, including the image distortion coefficients of some or all of the receiving channels;

[0068] The channel-level image distortion coefficient matrix calculation module specifically employs the following method to determine the channel-level image distortion coefficient matrix, and sequentially combines the image distortion coefficients of the received channels according to the order of the received channels to obtain the channel-level image distortion coefficient matrix:

[0069] For the target receiving channel, perform the following operations to obtain the image distortion coefficient of the target receiving channel:

[0070] During antenna calibration, the original calibration sequence signal and the calibration reference signal received by the calibration reference channel are acquired.

[0071] Based on the calibration reference signal, delay compensation and complex gain compensation are performed on the correction sequence signal received by the target receiving channel to obtain the corrected sequence signal;

[0072] Calculate the difference between the corrected sequence signal and the original corrected sequence signal to determine the error signal;

[0073] Based on the error signal and the original correction sequence signal, the mirror mismatch coefficient of the target receiving channel is calculated, wherein the target receiving channel is any one of multiple receiving channels.

[0074] As an optional implementation, the image distortion weight matrix of the beam channel includes the influence weights of some or all beam channels in the image distortion signal of the receiving channel.

[0075] The mirror distortion weight matrix calculation module is specifically used for:

[0076] Based on the following formula, the image distortion weight matrix of the beam channel is determined using the element values ​​in the beamforming weight matrix:

[0077]

[0078] Among them, e mn (k)=BF mn *BF kn E(k) is the image distortion weight matrix of the k-th beam channel, BF mn Let BF be the element value in the m-th row and n-th column of the beamforming weight matrix. kn Let M be the element value in the k-th row and n-th column of the beamforming weight matrix, where M is the total number of beam signals, N is the total number of receiving channels, n is the n-th receiving channel, and m is the m-th beam signal. m, n, N, and M are all positive integers.

[0079] As an optional implementation, the system further includes: multiple mixer modules and multiple analog-to-digital conversion modules;

[0080] The mixer module is connected to the receiving channel and is used to mix the original signal received by the receiving channel.

[0081] The analog-to-digital conversion module is connected between the mixer module and the digital beamforming module, and is used to convert the mixed analog signal into a digital signal and output it to the digital beamforming module.

[0082] Fourthly, embodiments of this application provide an image distortion correction device, the device including a processor and a memory, the memory being used to store a program executable by the processor, the processor being used to read the program in the memory and execute the steps of any of the methods described in the first aspect.

[0083] Fifthly, embodiments of this application also provide a computer storage medium having a computer program stored thereon, which, when executed by a processor, is used to implement the steps of the method described in any of the first aspects above.

[0084] In a sixth aspect, this application provides a computer program product comprising: computer program code, which, when executed on a computer, causes the computer to perform the steps of the method described in any one of the first aspects.

[0085] The beneficial effects of the embodiments of this application are as follows:

[0086] This application provides a method, system, device, medium, and program product for image distortion correction. Based on a pre-determined beam-level image distortion coefficient matrix of the beam channel where the first beam signal is located and multiple beam signals, a correction value for the first beam signal is determined. Then, the correction value of the first beam signal is used to correct the first beam signal to obtain a second beam signal. This achieves image correction of IQ mismatch at the beam level and enables joint cancellation of inter-beam image interference in multi-beam scenarios. Compared with channel-level image correction in related technologies, in large-scale digital beamforming antenna arrays, the number of beams is much smaller than the number of channels, which can significantly reduce the hardware resources required for image correction.

[0087] These or other aspects of this application will become more apparent in the following description of embodiments. Attached Figure Description

[0088] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0089] Figure 1 This is a schematic diagram illustrating the principle of image distortion signal generation provided in the embodiments of this application;

[0090] Figure 2 A schematic flowchart illustrating a method for correcting image distortion provided in an embodiment of this application;

[0091] Figure 3 A schematic flowchart illustrating the specific implementation process of a method for correcting image distortion provided in this application embodiment;

[0092] Figure 4 This is a schematic diagram of the structure of a mirror distortion correction system provided in an embodiment of this application;

[0093] Figure 5 This is a schematic diagram of the structure of a mirror correction module provided in an embodiment of this application;

[0094] Figure 6 A schematic diagram of the structure of a channel-level image distortion coefficient matrix calculation module provided in an embodiment of this application;

[0095] Figure 7 This is a schematic diagram of the structure of a mirror distortion weight matrix calculation module provided in an embodiment of this application;

[0096] Figure 8 This is a schematic diagram of the structure of a mirror distortion correction device provided in an embodiment of this application;

[0097] Figure 9 This is a schematic diagram of a mirror distortion correction device provided in an embodiment of this application. Detailed Implementation

[0098] To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0099] In the embodiments of this application, the term "and / or" describes the relationship between associated objects, indicating that three relationships can exist. For example, A and / or B can represent three cases: A alone, A and B simultaneously, and B alone. The character " / " generally indicates that the preceding and following associated objects have an "or" relationship.

[0100] The application scenarios described in this application are for the purpose of more clearly illustrating the technical solutions of this application, and do not constitute a limitation on the technical solutions provided in this application. Those skilled in the art will understand that with the emergence of new application scenarios, the technical solutions provided in this application are also applicable to similar technical problems. In the description of this application, unless otherwise stated, "multiple" means two or more.

[0101] Before introducing the image distortion correction method provided in the embodiments of this application, for ease of understanding, the technical background of the embodiments of this application will be described in detail below.

[0102] With the continuous advancement of digital signal processing technology, zero-IF receivers have been widely used due to their advantages such as simple circuit structure, low power consumption, easy integration, small size, and low cost.

[0103] Currently, in zero-IF reception scenarios, the quadrature local oscillator frequency sources used by the I and Q branches cannot guarantee absolute orthogonality, i.e., there is IQ mismatch, which will cause image distortion in the received signal.

[0104] Specifically, such as Figure 1 As shown, taking a transmitter mixer as an example, assuming the input signal X is the initial baseband frequency w b The single-tone signal, X = cosw b t+jsinw b t, the local oscillator signal is frequency w c Ideally, the amplitudes and phases of the signals from the I and Q branches are completely orthogonal. The frequency point w can then be obtained as shown in formula (1). b +w c The transmitted signal.

[0105]

[0106] However, it is impossible to guarantee that the signal amplitude and phase of the I and Q branches are completely orthogonal in practice, and there is an IQ mismatch. Assuming that amplitude distortion γ and phase distortion θ are introduced on the Q path, the expression of the frequency-shifted radio frequency signal is as shown in formula (2).

[0107]

[0108] As can be seen from the above formula (2), in addition to obtaining the frequency point w b +w c The transmitted signal is at a frequency w that is mirror-symmetrical to the local oscillator. c -w b There is also a non-ideal signal, a phenomenon called "image distortion". When the image from the receiving channel hits the user equipment, it will affect the receiving sensitivity.

[0109] In related technologies, channel-level correction is the main method to solve the image distortion problem. However, in large-scale digital beamforming arrays, channel-level correction algorithms need to be implemented in each receiving channel, which requires a lot of hardware resources and is difficult to implement.

[0110] Meanwhile, beam-level image correction faces technical obstacles. Specifically, after digital beamforming (DBF) processing, beam-level image distortion includes the aliasing of image distortion from each receiving channel. Furthermore, in multi-beam scenarios, there are other beam image components, including components in the direction of the target correction beam, making beam-level image correction difficult to achieve.

[0111] In view of this, embodiments of this application provide a method, system, device, medium, and program product for correcting image distortion, overcoming the technical obstacles of beam-level image correction and solving the problem of inter-beam image aliasing. Specifically, based on a predetermined beam-level image distortion coefficient matrix of the beam channel where the first beam signal is located and multiple beam signals, a correction value for the first beam signal is determined. Then, the correction value of the first beam signal is used to correct the first beam signal to obtain the second beam signal, thereby achieving image correction of IQ mismatch at the beam level. In multi-beam scenarios, joint cancellation of inter-beam image interference is achieved. In large-scale digital beamforming antenna arrays, the number of beams is much smaller than the number of channels, which can significantly reduce the hardware resources required for image correction and reduce the implementation difficulty.

[0112] It should be noted that the image distortion correction scheme provided in this application embodiment does not rely on external devices and can achieve real-time correction of image distortion during the normal operation of the antenna array.

[0113] After introducing the technical background of the embodiments of this application, the principle of the image distortion correction scheme provided by the embodiments of this application will be explained below.

[0114] Assuming the number of receiving channels is N and the number of beamforming channels is M, the receiving beamforming weight matrix is ​​an M*N matrix, denoted as BF. In the following embodiments of this application, BF... ij This represents the element in the i-th row and j-th column of the BF matrix.

[0115] Assume the m-th beam signal uses X m If the data is expressed as follows, then the data of the m-th beam of the n-th antenna is shown in the following formula (3):

[0116] X m (n)=X m *conj(BF mn (3)

[0117] The conj function represents taking the conjugate.

[0118] Assuming there are a total of M beam signals, the total data of the nth antenna is as shown in the following formula (4):

[0119]

[0120] The IQ mismatch in the uplink mixer introduces image distortion. Assume the complex coefficients of the image distortion in the nth receive channel are W. n Then the image distortion component of the nth channel is shown in the following formula (5):

[0121]

[0122]

[0123] Uplink beamforming using DBF is performed. For the k-th beam channel, the channel weight for beamforming is BF. kn After beamforming, the mirror image component of the k-th beam channel is shown in the following formula (6):

[0124]

[0125] By changing the order of summation in formula (6) above, we can obtain the following formula (7):

[0126]

[0127] As can be seen from the above formula (7), after uplink DBF, the image distortion received by the k-th beam channel is generated by the weighted sum of the image distortions of each beam signal, and its weight is... This is similar to a weighted summation of the image distortion coefficients at the channel level.

[0128] Let e mn (k)=BF mn *BF kn Then equation (7) can be expressed as the following formula (8):

[0129]

[0130] Simply put: X imag(k) =X * ·E(k)·W.

[0131] In this embodiment, E(k) is called the image distortion weight matrix, specifically the image distortion weight matrix of the k-th beam channel. W is called the channel-level image distortion coefficient matrix, and E(k)*W is called the beam-level image distortion coefficient matrix, specifically the beam-level image distortion coefficient matrix of the k-th beam channel. All of the above matrices are slow variables, and the beam-level image distortion coefficient matrix is ​​only related to the channel image distortion coefficient and the beamforming weight matrix BF. Therefore, the beam information and receiving channel information can be used to predetermine the image distortion correction.

[0132] Specifically, when correcting the image distortion of the first beam signal, the correction value of the first beam signal is determined based on the pre-determined beam-level image distortion coefficient matrix of the beam channel where the first beam signal is located and multiple beam signals. Then, the correction value of the first beam signal is used to correct the first beam signal to obtain the second beam signal.

[0133] After introducing the principle of the image distortion correction scheme provided in the embodiments of this application, the implementation process of the image distortion correction method provided in the embodiments of this application will be described in detail below with reference to specific embodiments.

[0134] like Figure 2 As shown, the implementation process of the image distortion correction method provided in this embodiment is as follows:

[0135] Step 201: Based on the pre-determined beam-level image distortion coefficient matrix of the beam channel where the first beam signal is located and multiple beam signals, determine the correction value of the first beam signal. The beam-level image distortion coefficient matrix is ​​used to characterize the influence weight of some or all beam channels in the image distortion signal of a single beam channel.

[0136] In practice, the original signal received by the receiving channel is mixed, converted from analog to digital and then digitally beamformed to obtain multiple beam signals. The specific mixing, conversion, and digital beamforming can be performed using methods found in related technologies, and this application does not limit the specific methods used.

[0137] In practice, when determining the correction value of the first beam signal based on the pre-determined beam-level image distortion coefficient matrix of the beam channel where the first beam signal is located and multiple beam signals, the reference signal corresponding to each beam signal is first determined. Then, based on the beam-level image distortion coefficient matrix of the beam channel where the first beam signal is located and the reference signal corresponding to each beam signal, the correction value of the first beam signal is determined. The reference signal can be a conjugate signal of the beam signal.

[0138] Specifically, when determining the correction value of the first beam signal based on the beam-level image distortion coefficient matrix of the beam channel where the first beam signal is located and the reference signal corresponding to each beam signal, the influence weight of each beam channel in the image distortion signal of the beam channel where the first beam signal is located is multiplied by the reference signal corresponding to the beam signal in each beam channel to obtain multiple products. The multiple products are then summed to obtain the correction value of the first beam signal.

[0139] In one example, assume that the beam-level image distortion coefficient matrix of the k-th beam channel is as shown in formula (9) below, and the M beam signals in the M beam channels are denoted as X1, X2, ... X M The conjugate signals of each beam signal are denoted as: X1 * X2 * ...X M * .

[0140]

[0141] The correction value for the k-th beam signal is: EW k1 ×X1 * +EW k2 ×X2 * +…+EW kM ×X M * .

[0142] Step 202: Correct the first beam signal using the correction value of the first beam signal to obtain the second beam signal.

[0143] In practice, the first beam signal is corrected using the correction value of the first beam signal, and then the corrected beam signal, which is the second beam signal, is obtained.

[0144] It should be noted that the beam-level image distortion coefficient matrix of the beam channel mentioned in the embodiments of this application is determined based on the channel-level image distortion coefficient matrix and the image distortion weight matrix of the beam channel. Specifically, it can be determined in the following way: obtain the beamforming weight matrix; based on the beamforming weight matrix, determine the image distortion weight matrix of the beam channel; the image distortion weight matrix of the beam channel is used to characterize the influence weight of some or all beam channels in the image distortion signal of the beam channel on the receiving channel; based on the channel-level image distortion coefficient matrix and the image distortion weight matrix of the beam channel, determine the beam-level image distortion coefficient matrix of the beam channel; the channel-level image distortion coefficient matrix is ​​an N×1 dimensional matrix, including the image distortion coefficients of some or all receiving channels.

[0145] It should be noted that the beamforming weight matrix can be determined using methods found in related technologies, and this application embodiment does not limit this. The channel-level image distortion coefficient matrix can be estimated during antenna calibration; in other words, this application embodiment can determine the channel-level image distortion coefficient matrix using calibration sequence signals during antenna calibration.

[0146] In specific implementation, the channel-level image distortion coefficient matrix is ​​determined as follows: For any target receiving channel among multiple receiving channels, the following operations are performed to obtain the image distortion coefficient of the target receiving channel, and the image distortion coefficients of the receiving channels are combined sequentially according to the order of the receiving channels to obtain the channel-level image distortion coefficient matrix: During the antenna calibration process, the original calibration sequence signal and the calibration reference signal received by the calibration reference channel are acquired. Based on the calibration reference signal, time delay compensation and complex gain compensation are performed on the calibration sequence signal received by the target receiving channel to obtain the calibrated sequence signal. The difference between the calibrated sequence signal and the original calibration sequence signal is calculated to determine the error signal. Based on the error signal and the original calibration sequence signal, the image mismatch coefficient of the target receiving channel is calculated.

[0147] It should be noted that when calculating the error signal, both the corrected sequence signal and the original corrected sequence signal are signals with a preset duration. The preset duration can be set based on experience, and this application embodiment does not limit it.

[0148] In one example, for a target receiving channel n, assuming the original correction sequence signal is TX, delay compensation and complex gain compensation are performed on the correction sequence signal received by the target receiving channel to obtain the corrected sequence signal RX. (n) , RX (n) The difference between TX and ERR, i.e., the error signal, is ERR. (n) Then the mirror mismatch coefficient of the target receiving channel n can be calculated using the following formula (10).

[0149]

[0150] Among them, TX * The conjugate signal of TX, (TX * )' is the transpose of the conjugate signal of TX.

[0151] It should be noted that the image distortion weight matrix of the beam channel includes the influence weights of some or all beam channels in the image distortion signal of the receiving channel. Specifically, when determining the image distortion weight matrix of the beam channel based on the beamforming weight matrix, the image distortion weight matrix of the beam channel is determined using the element values ​​in the beamforming weight matrix based on the following formula (11):

[0152]

[0153] Among them, e mn (k)=BF mn *BF kn E(k) is the image distortion weight matrix of the k-th beam channel, BF mn Let BF be the element value in the m-th row and n-th column of the beamforming weight matrix. kn Let M be the element value in the k-th row and n-th column of the beamforming weight matrix, where M is the total number of beam signals, N is the total number of receiving channels, n is the n-th receiving channel, and m is the m-th beam signal. m, n, N, and M are all positive integers.

[0154] The following is combined Figure 3 The specific implementation process of the image distortion correction method provided in the embodiments of this application will be described in detail, such as... Figure 3 As shown, the specific implementation process of the image distortion correction method provided in this application embodiment includes:

[0155] Step 301: Obtain the beamforming weight matrix.

[0156] Step 302: Determine the image distortion weight matrix for each beam channel based on the beamforming weight matrix.

[0157] In specific implementation, the formula (11) mentioned in the above embodiments of this application can be used for determination, which will not be repeated here.

[0158] Step 303: Based on the channel-level image distortion coefficient matrix and the image distortion weight matrix of each beam channel, determine the beam-level image distortion coefficient matrix of each beam channel.

[0159] The predetermined channel-level image distortion coefficient matrix is ​​estimated during the antenna calibration process.

[0160] Step 304: After each original signal is mixed and converted from analog to digital, digital beamforming is performed to obtain multiple beam signals.

[0161] Step 305: Calculate the conjugate signal of each beam signal.

[0162] Step 306: Multiply the influence weight of each beam channel in the beam-level image distortion coefficient matrix of the beam channel where the first beam signal is located by the reference signal corresponding to the beam signal in each beam channel to obtain multiple products, and sum the multiple products to obtain the correction value of the first beam signal.

[0163] Step 307: Correct the first beam signal using the correction value of the first beam signal to obtain the second beam signal.

[0164] It should be noted that in practical applications, steps 301-303 can be performed once during each calibration, or multiple beam signals can be calibrated after one calibration, or they can be performed periodically. This application embodiment does not limit this.

[0165] Based on the same inventive concept, such as Figure 4 As shown, this application embodiment also provides a mirror distortion correction system, including: a digital beamforming module 41, a channel-level mirror distortion coefficient matrix calculation module 42, a mirror distortion weight matrix calculation module 43, a beam-level mirror distortion coefficient matrix calculation module 44, and a mirror correction module 45.

[0166] The digital beamforming module 41 is used to perform digital beamforming on multiple original signals received by the receiving channel based on the beamforming weight matrix, to obtain multiple beam signals, and to transmit the multiple beam signals to the mirror correction module 45.

[0167] The channel-level image distortion coefficient matrix calculation module 42 is connected to some or all of the receiving channels and is used to determine the channel-level image distortion coefficient matrix.

[0168] The mirror distortion weight matrix calculation module 43 is connected to the digital beamforming module and is used to determine the mirror distortion weight matrix of the beam channel.

[0169] The beam-level image distortion coefficient matrix calculation module 44 is connected to the channel-level image distortion coefficient matrix calculation module 42 and the image distortion weight matrix calculation module 43. It is used to determine the beam-level image distortion coefficient matrix of the beam channel based on the channel-level image distortion coefficient matrix and the image distortion weight matrix of the beam channel.

[0170] The image correction module 45 is connected to the beam-level image distortion coefficient matrix calculation module 44. It is used to determine the correction value of the first beam signal based on the beam-level image distortion coefficient matrix of the beam channel where the first beam signal is located and multiple beam signals, and to correct the first beam signal using the correction value of the first beam signal to obtain the second beam signal.

[0171] In practice, the system also includes multiple mixer modules 46 and multiple analog-to-digital conversion modules 47.

[0172] Mixer module 46 is connected to the receiving channel and is used to mix the original signal received by the receiving channel.

[0173] The analog-to-digital conversion module 47 is connected between the mixer module 46 and the digital beamforming module 41, and is used to convert the mixed analog signal into a digital signal and output it to the digital beamforming module 41.

[0174] Specifically, when correcting the image distortion of each beam signal, such as Figure 4 As shown, N receiving channels receive the raw signals from M beams. After passing through mixer module 46, analog-to-digital converter module 47, and digital beamforming module 41, M beam signals are obtained. Channel-level image distortion coefficient matrix calculation module 42 is used to calculate the channel-level image distortion coefficient matrix W; image distortion weight matrix calculation module 43 is used to calculate the image distortion weight matrix E of the beam channel; and beam-level image distortion coefficient matrix calculation module 44 is used to calculate the beam-level image distortion coefficient matrix E*W of the beam channel.

[0175] The mirror correction module 45 determines the correction value of the first beam signal based on the pre-calculated beam-level mirror distortion coefficient matrix E*W of the beam channel where the first beam signal is located and multiple beam signals. Then, it uses the correction value of the first beam signal to correct the first beam signal and obtain the corrected beam signal, which is the second beam signal.

[0176] In specific implementation, the mirror correction module 45 is specifically used to: determine the reference signal corresponding to each beam signal respectively;

[0177] The correction value for the first beam signal is determined based on the beam-level image distortion coefficient matrix of the beam channel in which the first beam signal is located and the reference signals corresponding to each beam signal. The reference signals include the conjugate signals of the beam signals.

[0178] The mirror correction module 45 is specifically used to: multiply the influence weight of each beam channel in the beam-level mirror distortion coefficient matrix of the beam channel where the first beam signal is located by the reference signal corresponding to the beam signal in each beam channel to obtain multiple products, and sum the multiple products to obtain the correction value of the first beam signal.

[0179] In practical implementation, we still assume that the M beam signals in the M beam channels are denoted as X1, X2, ... X M The conjugate signals of each beam signal are denoted as: X1 * X2 * ...X M * The beam-level image distortion coefficient matrix of the k-th beam channel is shown in the above formula (9).

[0180] The architecture of the mirror correction module 45, such as Figure 5 As shown, it includes M*M multipliers and M adders. For the first beam signal, i.e., k=1, it calculates EW using M multipliers and 1 adder. 11 ×X1 * +EW 12 ×X2 * +…+EW1M ×X M * The correction value for the first beam signal is obtained. For the second beam signal, i.e., k=2, the correction value is calculated using M multipliers and 1 adder: EW 21 ×X1 * +EW 22 ×X2 * +…+EW 2M ×X M * The correction value for the second beam signal is obtained, and so on. For the Mth beam signal, i.e., k = M, the correction value is calculated using M multipliers and 1 adder: EW M1 ×X1 * +EW M2 ×X2 * +…+EW MM ×X M * The correction value of the Mth beam signal is obtained.

[0181] It should be noted that the channel-level image distortion coefficient matrix is ​​an N×1 dimensional matrix, which includes the image distortion coefficients of some or all of the receiving channels.

[0182] In practical implementation, the architecture of the channel-level image distortion coefficient matrix calculation module 42 is as follows: Figure 6 As shown, the system includes a multiplexer 61, a time delay compensation module 62, and a complex gain compensation module 63. Specifically, the channel-level image distortion coefficient matrix is ​​determined as follows: After N receiving channels receive the original calibration sequence signal, they are output to the multiplexer 62 through down-conversion and analog-to-digital conversion. The multiplexer 62 selects any one target receiving channel from the multiple receiving channels and performs the following operations to obtain the image distortion coefficient of the target receiving channel: During antenna calibration, the original calibration sequence signal and the calibration reference signal received by the calibration reference channel are acquired; based on the calibration reference signal, the time delay compensation module 61 and the complex gain compensation module 63 respectively perform time delay compensation and complex gain compensation on the calibration sequence signal received by the target receiving channel to obtain the calibrated sequence signal; the difference between the calibrated sequence signal and the original calibration sequence signal is calculated to determine the error signal; based on the error signal and the original calibration sequence signal, the image mismatch coefficient of the target receiving channel is calculated. After obtaining the image mismatch coefficients of each receiving channel, the image distortion coefficients of each receiving channel can be combined sequentially according to the order of the receiving channels to obtain the channel-level image distortion coefficient matrix.

[0183] It should be noted that the image distortion weight matrix of the beam channel includes the influence weights of some or all beam channels in the image distortion signal of the receiving channel.

[0184] In specific implementation, the mirror distortion weight matrix calculation module 43 determines the mirror distortion weight matrix of the beam channel based on the following formula (12) and the element values ​​in the beamforming weight matrix.

[0185]

[0186] Among them, e mn (k)=BF mn *BF kn E(k) is the image distortion weight matrix of the k-th beam channel, BF mn Let BF be the element value in the m-th row and n-th column of the beamforming weight matrix. kn Let M be the element value in the k-th row and n-th column of the beamforming weight matrix, where M is the total number of beam signals, N is the total number of receiving channels, n is the n-th receiving channel, and m is the m-th beam signal. m, n, N, and M are all positive integers.

[0187] In specific implementation, the structure of the mirror distortion weight matrix calculation module 43 is as follows: Figure 7 As shown, it includes two multiplexers, which select the corresponding element values ​​from the beamforming weight matrix and multiply them to obtain the mirror distortion weight matrix of the beam channel through selection control.

[0188] The image distortion correction system provided in this application, when correcting image distortion of beam signals, only requires real-time calculation by the image correction module. All other calculations (channel-level image distortion coefficient matrix, beam channel image distortion weight matrix, and beam channel beam-level image distortion coefficient matrix) can be implemented with minimal hardware resources through time-division multiplexing. The system requires M*M multipliers (M being the number of beams), compared to N multipliers (N being the number of channels) required for channel-level image correction in the prior art. In large-scale digital beamforming antenna arrays, if N is much larger than M, this application significantly reduces the hardware resources required for image distortion correction while also reducing power consumption.

[0189] Additionally, it should be noted that the descriptions of "partial or complete" in the embodiments of this application are all based on the example of completeness. For example, partial or complete beam channels are described using the example of complete beam channels, and partial or complete receiving channels are described using the example of complete receiving channels. In practical applications, if only partial beam channels or receiving channels are used to implement the image distortion correction method provided in the embodiments of this application, the image distortion signal can still be corrected. The principle is the same, but the correction effect is weaker than when all beam channels or all receiving channels are used.

[0190] Based on the same inventive concept, such as Figure 8 As shown in the illustration, this application embodiment also provides a mirror distortion correction device, comprising:

[0191] The processing unit 81 is used to determine the correction value of the first beam signal based on the beam-level image distortion coefficient matrix of the beam channel where the first beam signal is located and multiple beam signals. The beam-level image distortion coefficient matrix is ​​used to characterize the influence weight of some or all beam channels in the image distortion signal of a single beam channel.

[0192] The correction unit 82 is used to correct the first beam signal using the correction value of the first beam signal to obtain the second beam signal.

[0193] As an optional implementation, the processing unit 81 is specifically used for:

[0194] Determine the reference signal corresponding to each beam signal;

[0195] The correction value of the first beam signal is determined based on the beam-level image distortion coefficient matrix of the beam channel in which the first beam signal is located and the reference signal corresponding to each beam signal.

[0196] As an optional implementation, the processing unit 81 is specifically used for:

[0197] The influence weights of each beam channel in the beam-level image distortion coefficient matrix of the beam channel where the first beam signal is located are multiplied by the reference signals corresponding to the beam signals in each beam channel to obtain multiple products. The multiple products are then summed to obtain the correction value of the first beam signal.

[0198] As an optional implementation, the reference signal includes the conjugate signal of the beam signal.

[0199] As an optional implementation, the processing unit 81 predetermines the beam-level image distortion coefficient matrix of the beam channel in the following manner:

[0200] Obtain the beamforming weight matrix;

[0201] Based on the beamforming weight matrix, the image distortion weight matrix of the beam channel is determined. The image distortion weight matrix of the beam channel is used to characterize the influence weight of some or all beam channels in the image distortion signal of the receiving channel.

[0202] Based on the channel-level image distortion coefficient matrix and the beam channel's image distortion weight matrix, the beam-level image distortion coefficient matrix of the beam channel is determined. The channel-level image distortion coefficient matrix is ​​an N×1 dimensional matrix that includes the image distortion coefficients of some or all of the receiving channels.

[0203] As an optional implementation, the channel-level image distortion coefficient matrix is ​​estimated during antenna calibration.

[0204] As an optional implementation, the processing unit 81 determines the channel-level image distortion coefficient matrix in the following manner:

[0205] For the target receiving channel, perform the following operations to obtain the image distortion coefficients of the target receiving channel, and then combine the image distortion coefficients of the receiving channels in order to obtain the channel-level image distortion coefficient matrix:

[0206] During antenna calibration, the original calibration sequence signal and the calibration reference signal received by the calibration reference channel are acquired.

[0207] Based on the calibration reference signal, delay compensation and complex gain compensation are performed on the correction sequence signal received by the target receiving channel to obtain the corrected sequence signal;

[0208] Calculate the difference between the corrected sequence signal and the original corrected sequence signal to determine the error signal;

[0209] Based on the error signal and the original correction sequence signal, the image mismatch coefficient of the target receiving channel is calculated, where the target receiving channel is any one of multiple receiving channels.

[0210] As an optional implementation, the processing unit 81 is specifically used for:

[0211] Based on the following formula, the image distortion weight matrix of the beamforming channel is determined using the element values ​​in the beamforming weight matrix:

[0212]

[0213] Among them, e mn (k)=BF mn *BF kn E(k) is the image distortion weight matrix of the k-th beam channel, BF mn Let BF be the element value in the m-th row and n-th column of the beamforming weight matrix. kn Let M be the element value in the k-th row and n-th column of the beamforming weight matrix, where M is the total number of beam signals, N is the total number of receiving channels, n is the n-th receiving channel, and m is the m-th beam signal. m, n, N, and M are all positive integers.

[0214] Based on the same inventive concept, such as Figure 9 As shown in the illustration, this application also provides a mirror distortion correction device, which includes a processor 900 and a memory 901. The memory 901 is used to store programs executable by the processor 900, and the processor 900 is used to read and execute the programs in the memory 901.

[0215] Based on the pre-determined beam-level image distortion coefficient matrix of the beam channel where the first beam signal is located and multiple beam signals, the correction value of the first beam signal is determined. The beam-level image distortion coefficient matrix is ​​used to characterize the influence weight of some or all beam channels in the image distortion signal of a single beam channel.

[0216] The first beam signal is corrected using the correction value of the first beam signal to obtain the second beam signal.

[0217] As an optional implementation, the processor 900 is specifically configured to execute:

[0218] Determine the reference signal corresponding to each beam signal;

[0219] The correction value of the first beam signal is determined based on the beam-level image distortion coefficient matrix of the beam channel in which the first beam signal is located and the reference signal corresponding to each beam signal.

[0220] As an optional implementation, the processor 900 is specifically configured to execute:

[0221] The influence weights of each beam channel in the beam-level image distortion coefficient matrix of the beam channel where the first beam signal is located are multiplied by the reference signals corresponding to the beam signals in each beam channel to obtain multiple products. The multiple products are then summed to obtain the correction value of the first beam signal.

[0222] As an optional implementation, the reference signal includes the conjugate signal of the beam signal.

[0223] As an optional implementation, the processor 900 is specifically configured to predetermine the beam-level image distortion coefficient matrix of the beam channel in the following manner:

[0224] Obtain the beamforming weight matrix;

[0225] Based on the beamforming weight matrix, the image distortion weight matrix of the beam channel is determined. The image distortion weight matrix of the beam channel is used to characterize the influence weight of some or all beam channels in the image distortion signal of the receiving channel.

[0226] Based on the channel-level image distortion coefficient matrix and the beam channel's image distortion weight matrix, the beam-level image distortion coefficient matrix of the beam channel is determined. The channel-level image distortion coefficient matrix is ​​an N×1 dimensional matrix that includes the image distortion coefficients of some or all of the receiving channels.

[0227] As an optional implementation, the channel-level image distortion coefficient matrix is ​​estimated during antenna calibration.

[0228] As an optional implementation, the processor 900 is specifically configured to determine the channel-level image distortion coefficient matrix in the following manner:

[0229] For the target receiving channel, perform the following operations to obtain the image distortion coefficients of the target receiving channel, and then combine the image distortion coefficients of the receiving channels in order to obtain the channel-level image distortion coefficient matrix:

[0230] During antenna calibration, the original calibration sequence signal and the calibration reference signal received by the calibration reference channel are acquired.

[0231] Based on the calibration reference signal, delay compensation and complex gain compensation are performed on the correction sequence signal received by the target receiving channel to obtain the corrected sequence signal;

[0232] Calculate the difference between the corrected sequence signal and the original corrected sequence signal to determine the error signal;

[0233] Based on the error signal and the original correction sequence signal, the image mismatch coefficient of the target receiving channel is calculated, where the target receiving channel is any one of multiple receiving channels.

[0234] As an optional implementation, the processor 900 is specifically configured as follows:

[0235] Based on the following formula, the image distortion weight matrix of the beamforming channel is determined using the element values ​​in the beamforming weight matrix:

[0236]

[0237] Among them, e mn (k)=BF mn *BF kn E(k) is the image distortion weight matrix of the k-th beam channel, BF mn Let BF be the element value in the m-th row and n-th column of the beamforming weight matrix. kn Let M be the element value in the k-th row and n-th column of the beamforming weight matrix, where M is the total number of beam signals, N is the total number of receiving channels, n is the n-th receiving channel, and m is the m-th beam signal. m, n, N, and M are all positive integers.

[0238] Based on the same inventive concept, this disclosure provides a computer storage medium comprising: computer program code, which, when executed on a computer, causes the computer to perform any of the image distortion correction methods discussed above. Since the principle by which the computer storage medium solves the problem is similar to that of the image distortion correction methods, the implementation of the computer storage medium can be referred to the implementation of the method, and repeated details will not be elaborated further.

[0239] In specific implementation, computer storage media can include: Universal Serial Bus Flash Drive (USB), portable hard drive, Read-Only Memory (ROM), Random Access Memory (RAM), magnetic disk or optical disk, and other storage media that can store program code.

[0240] Based on the same inventive concept, this disclosure also provides a computer program product, which includes computer program code that, when executed on a computer, causes the computer to perform any of the image distortion correction methods discussed above. Since the principle by which the above-described computer program product solves the problem is similar to that of the image distortion correction method, the implementation of the above-described computer program product can be referred to the implementation of the method, and repeated details will not be elaborated further.

[0241] Computer program products may employ any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may 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 readable storage media include: electrical connections having one or more wires, portable disks, hard disks, 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 devices, magnetic storage devices, or any suitable combination thereof.

[0242] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage and optical storage) containing computer-usable program code.

[0243] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 Devices that specify the functions in one or more boxes.

[0244] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including an instruction device, which is implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0245] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0246] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A method for correcting image distortion, characterized in that, The method includes: Based on the pre-determined beam-level image distortion coefficient matrix of the beam channel where the first beam signal is located and multiple beam signals, the correction value of the first beam signal is determined. The beam-level image distortion coefficient matrix is ​​used to characterize the influence weight of some or all beam channels in the image distortion signal of a single beam channel. The first beam signal is corrected using the correction value of the first beam signal to obtain the second beam signal.

2. The method according to claim 1, characterized in that, The step of determining the correction value of the first beam signal based on the pre-determined beam-level image distortion coefficient matrix of the beam channel where the first beam signal is located and multiple beam signals includes: Determine the reference signal corresponding to each beam signal; The correction value of the first beam signal is determined based on the beam-level image distortion coefficient matrix of the beam channel in which the first beam signal is located and the reference signal corresponding to each beam signal.

3. The method according to claim 2, characterized in that, The step of determining the correction value of the first beam signal based on the beam-level image distortion coefficient matrix of the beam channel where the first beam signal is located and the reference signal corresponding to each beam signal includes: The influence weight of each beam channel in the beam-level image distortion coefficient matrix of the beam channel where the first beam signal is located is multiplied by the reference signal corresponding to the beam signal in each beam channel to obtain multiple products. The multiple products are then summed to obtain the correction value of the first beam signal.

4. The method according to claim 2, characterized in that, The reference signal includes the conjugate signal of the beam signal.

5. The method according to claim 1, characterized in that, The beam-level image distortion coefficient matrix of the beam channel is determined in the following manner: Obtain the beamforming weight matrix; Based on the beamforming weight matrix, the image distortion weight matrix of the beam channel is determined. The image distortion weight matrix of the beam channel is used to characterize the influence weight of some or all beam channels in the image distortion signal of the receiving channel. Based on the channel-level image distortion coefficient matrix and the image distortion weight matrix of the beam channel, the beam-level image distortion coefficient matrix of the beam channel is determined. The channel-level image distortion coefficient matrix is ​​an N×1 dimensional matrix that includes the image distortion coefficients of some or all of the receiving channels.

6. The method according to claim 5, characterized in that, The channel-level image distortion coefficient matrix is ​​estimated during antenna calibration.

7. The method according to claim 6, characterized in that, The channel-level image distortion coefficient matrix is ​​determined in the following manner: For the target receiving channel, perform the following operations to obtain the image distortion coefficient of the target receiving channel, and then combine the image distortion coefficients of the receiving channels sequentially according to the order of the receiving channels to obtain the channel-level image distortion coefficient matrix: During antenna calibration, the original calibration sequence signal and the calibration reference signal received by the calibration reference channel are acquired. Based on the calibration reference signal, delay compensation and complex gain compensation are performed on the correction sequence signal received by the target receiving channel to obtain the corrected sequence signal; Calculate the difference between the corrected sequence signal and the original corrected sequence signal to determine the error signal; Based on the error signal and the original correction sequence signal, the mirror mismatch coefficient of the target receiving channel is calculated, wherein the target receiving channel is any one of multiple receiving channels.

8. The method according to claim 5, characterized in that, The step of determining the image distortion weight matrix of the beam channel based on the beamforming weight matrix includes: Based on the following formula, the image distortion weight matrix of the beam channel is determined using the element values ​​in the beamforming weight matrix: Among them, e mn (k)=BF mn *BF kn E(k) is the image distortion weight matrix of the k-th beam channel, BF mn Let BF be the element value in the m-th row and n-th column of the beamforming weight matrix. kn Let M be the element value in the k-th row and n-th column of the beamforming weight matrix, where M is the total number of beam signals, N is the total number of receiving channels, n is the n-th receiving channel, and m is the m-th beam signal. m, n, N, and M are all positive integers.

9. A system for correcting image distortion, characterized in that, include: The system includes a digital beamforming module, a channel-level image distortion coefficient matrix calculation module, an image distortion weight matrix calculation module, a beam-level image distortion coefficient matrix calculation module, and an image correction module. The digital beamforming module is used to perform digital beamforming on multiple raw signals received by the receiving channel based on the beamforming weight matrix to obtain multiple beam signals, and then transmit the multiple beam signals to the mirror correction module. The channel-level image distortion coefficient matrix calculation module is connected to some or all of the receiving channels respectively, and is used to determine the channel-level image distortion coefficient matrix; The image distortion weight matrix calculation module is connected to the digital beamforming module and is used to determine the image distortion weight matrix of the beam channel. The beam-level image distortion coefficient matrix calculation module is connected to the channel-level image distortion coefficient matrix calculation module and the image distortion weight matrix calculation module, and is used to determine the beam-level image distortion coefficient matrix of the beam channel based on the channel-level image distortion coefficient matrix and the image distortion weight matrix of the beam channel. The image correction module is connected to the beam-level image distortion coefficient matrix calculation module. It is used to determine the correction value of the first beam signal based on the beam-level image distortion coefficient matrix of the beam channel where the first beam signal is located and the multiple beam signals, and to correct the first beam signal using the correction value of the first beam signal to obtain the second beam signal.

10. The system according to claim 9, characterized in that, The mirror correction module is specifically used for: Determine the reference signal corresponding to each beam signal; The correction value of the first beam signal is determined based on the beam-level image distortion coefficient matrix of the beam channel in which the first beam signal is located and the reference signal corresponding to each beam signal.

11. The system according to claim 10, characterized in that, The mirror correction module is specifically used for: The influence weight of each beam channel in the beam-level image distortion coefficient matrix of the beam channel where the first beam signal is located is multiplied by the reference signal corresponding to the beam signal in each beam channel to obtain multiple products. The multiple products are then summed to obtain the correction value of the first beam signal.

12. The system according to claim 10, characterized in that, The reference signal includes the conjugate signal of the beam signal.

13. The system according to claim 9, characterized in that, The channel-level image distortion coefficient matrix is ​​an N×1 dimensional matrix, which includes the image distortion coefficients of some or all of the receiving channels. The channel-level image distortion coefficient matrix calculation module specifically uses the following method to determine the channel-level image distortion coefficient matrix, and sequentially combines the image distortion coefficients of the received channels according to the order of the received channels to obtain the channel-level image distortion coefficient matrix: For the target receiving channel, perform the following operations to obtain the image distortion coefficient of the target receiving channel: During antenna calibration, the original calibration sequence signal and the calibration reference signal received by the calibration reference channel are acquired. Based on the calibration reference signal, delay compensation and complex gain compensation are performed on the correction sequence signal received by the target receiving channel to obtain the corrected sequence signal; Calculate the difference between the corrected sequence signal and the original corrected sequence signal to determine the error signal; Based on the error signal and the original correction sequence signal, the mirror mismatch coefficient of the target receiving channel is calculated, wherein the target receiving channel is any one of multiple receiving channels.

14. The system according to claim 9, characterized in that, The image distortion weight matrix of the beam channel includes the influence weights of some or all beam channels in the image distortion signal of the receiving channel. The mirror distortion weight matrix calculation module is specifically used for: Based on the following formula, the image distortion weight matrix of the beam channel is determined using the element values ​​in the beamforming weight matrix: Among them, e mn (k)=BF mn *BF kn E(k) is the image distortion weight matrix of the k-th beam channel, BF mn Let BF be the element value in the m-th row and n-th column of the beamforming weight matrix. kn Let M be the element value in the k-th row and n-th column of the beamforming weight matrix, where M is the total number of beam signals, N is the total number of receiving channels, n is the n-th receiving channel, and m is the m-th beam signal. m, n, N, and M are all positive integers.

15. The system according to claim 9, characterized in that, The system also includes: multiple mixer modules and multiple analog-to-digital conversion modules; The mixer module is connected to the receiving channel and is used to mix the original signal received by the receiving channel. The analog-to-digital conversion module is connected between the mixer module and the digital beamforming module, and is used to convert the mixed analog signal into a digital signal and output it to the digital beamforming module.

16. A device for correcting image distortion, characterized in that, The device includes a processor and a memory for storing a program executable by the processor, and the processor for reading the program in the memory and performing the steps of the method according to any one of claims 1-8.

17. A computer storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps of the method as described in any one of claims 1 to 8.

18. A computer program product, characterized in that, The computer program product includes: computer program code, which, when run on a computer, causes the computer to perform the steps of the method as described in any one of claims 1 to 8.

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