A method, device, medium and equipment for optimizing amplitude modulation and phase modulation of a multi-stage amplitude-phase circuit

Abstract

The present application discloses a method for optimizing amplitude modulation and phase modulation of a multi-stage amplitude-phase circuit, including: sequentially executing a first calibration process from the nth stage attenuator to the first stage attenuator, and sequentially executing a second calibration process from the mth stage phase shifter to the first stage phase shifter; the first calibration process includes: determining the first actual state value of each stage attenuator, calibrating the first actual state value by the attenuation state correlation coefficient corresponding to the nth stage attenuator, and obtaining a first calibration state value; the second calibration process includes: determining the second actual state value of each stage phase shifter, calibrating the second actual state value by the phase shift state correlation coefficient corresponding to the mth stage phase shifter, and obtaining a second calibration state value. The present application realizes the precise optimization and closed-loop control of state values ​​between different levels. At the same time, the method realizes the linkage of attenuation and phase through the correlation coefficient, optimizes the amplitude-phase screening method, and solves a series of problems such as low accuracy and lack of correlation consideration when using traditional methods.

Description

Technical Field

[0001] The present application relates to the technical field of amplitude-phase optimization, and in particular to a method, device, medium and equipment for optimizing amplitude modulation and phase modulation of a multi-stage amplitude-phase circuit. Background Art

[0002] The amplitude-phase control system is a cluster of key components mainly used in electronic communication systems such as electronic countermeasure radar, digital mobile communication, microwave millimeter wave communication, etc. The amplitude-phase control circuit covered by the system has both amplitude modulation and phase modulation control output. The circuit also has digital attenuators and phase shifters to control amplitude adjustment and phase adjustment. The multi-channel amplitude-phase control circuit is the core unit of the phased array system. The system has been widely used in the fields of communication, radar, electronic countermeasure, and instrumentation.

[0003] In order to meet the increasingly stringent requirements for amplitude and phase control accuracy in practical application scenarios such as phased arrays, amplitude-phase control systems have gradually evolved from single-stage (one attenuator and phase shifter) to multi-stage (a combination of multiple attenuators and phase shifters with different levels of stepping rules). By implementing state adjustment for a combination of attenuators and phase shifters with different step amplitudes and gears, the demand for achieving higher-precision ideal amplitude-phase state values ​​is achieved to meet more stringent and extensive application scenarios.

[0004] Traditional amplitude-phase control optimization algorithms are mostly used in single-stage systems. When the system integration is simple and the number of attenuators or phase shifters is single, they can meet certain state screening and optimization requirements. The waterfall-style amplitude-phase control optimization algorithm does not have a closed-loop characteristic and cannot reversely prove and optimize the state judgment of the upper-level associated devices based on the lower-level attenuators or phase shifters. In addition, the algorithm does not involve the quantitative calculation and inference of the correlation factor between the two parameters of amplitude and phase. In the multi-stage amplitude-phase control system, it is impossible to avoid the deviation of the ideal value from the actual value caused by the mutual influence of the amplitude and phase indicators. The algorithm itself has certain limitations. Summary of the invention

[0005] In view of the above-mentioned shortcomings of the prior art, the purpose of the present application is to provide a multi-stage amplitude-phase circuit amplitude modulation-phase modulation optimization method, device, medium and equipment to solve at least one problem existing in the prior art.

[0006] To achieve the above-mentioned object and other related objects, the present application provides a multi-stage amplitude-phase circuit amplitude modulation-phase modulation optimization method, wherein the multi-stage amplitude-phase circuit includes 1st to nth attenuators and 1st to mth phase shifters, and the method includes:

[0007] In a spiral iteration manner, a first calibration process is sequentially performed from the nth attenuator to the first attenuator; the first calibration process includes: determining a first actual state value of each attenuator, calibrating the first actual state value by using an attenuation state correlation coefficient corresponding to the nth attenuator, and obtaining a first calibration state value;

[0008] In a spiral iteration manner, a second calibration process is sequentially performed from the m-th stage phase shifter to the first stage phase shifter; the second calibration process comprises: determining a second actual state value of each stage phase shifter, calibrating the second actual state value by a phase shift state correlation coefficient corresponding to the m-th stage phase shifter, and obtaining a second calibration state value;

[0009] Among them, the attenuation state correlation coefficient and the phase shift state correlation coefficient are both established through a pre-calibrated attenuation offset matrix and a pre-calibrated phase offset matrix, the attenuation state correlation coefficient is established based on the influence of phase shift on attenuation, and the phase shift state correlation coefficient is established based on the influence of attenuation on phase shift; the attenuation offset matrix represents the difference between the actual state value and the ideal state value of each stage of attenuator, and the phase offset matrix represents the difference between the actual state value and the ideal state value of each stage of phase shifter.

[0010] In one embodiment of the present invention, the method further includes:

[0011] For the calibrated amplitude-phase circuit, a first optimization process is sequentially performed from the first-stage attenuator to the n-stage attenuator, and a second optimization process is sequentially performed from the first-stage phase shifter to the m-stage phase shifter, so as to optimize the amplitude-phase circuit;

[0012] Among them, the first optimization process includes: optimizing the first actual state value or the first calibrated state value of each stage attenuator in an error approximation manner; the second optimization process includes: optimizing the second actual state value or the second calibrated state value of each stage phase shifter in an error approximation manner.

[0013] In one embodiment of the present invention, the method further includes:

[0014] Obtaining a first code value corresponding to a first calibration state value of each stage of attenuators, and a second code value corresponding to a second calibration state value of each stage of phase shifters;

[0015] An attenuation-phase shift code is established based on the first code value and the second code value, wherein the n-th attenuator corresponds to the n-th phase shifter.

[0016] In one embodiment of the present invention, the attenuation offset matrix and the phase offset matrix are obtained;

[0017] Taking the attenuation offset matrix and the phase offset matrix as inputs and taking the attenuation state correlation coefficient matrix and the second correlation coefficient matrix as outputs, training an initial neural network to obtain an attenuation-shift correlation coefficient model;

[0018] The attenuation state correlation coefficient and the phase shift state correlation coefficient are obtained based on the attenuation-shift correlation coefficient model.

[0019] In one embodiment of the present invention, the attenuation state correlation coefficient and the phase shift state correlation coefficient are expressed by a high-order expansion, wherein each step state value of each attenuator corresponds to all step phase shift states of all phase shifters, and each step state value of each phase shifter corresponds to all step phase shift states of all attenuators.

[0020] In one embodiment of the present invention, during the training of the attenuation-shift correlation coefficient model, for the training of the attenuation state correlation coefficient or the phase shift state correlation coefficient, starting from the 1st-order expansion, all phase shift states or all attenuation states are assigned to the neural network in a random weight distribution manner by a step-by-step ascending method; an error inversion algorithm is used to correct the weight value of each factor through the error of the feedforward conclusion through the feedback link. If the weight value still cannot be approached to the threshold range after traversal, the highest order of the expansion is increased by 1, and the random weight is reallocated to perform the above training until the training result reaches the threshold range or the order setting of the high-order expansion exceeds the set upper limit, the training is stopped, and the optimal solution matrix of the state is output.

[0021] In one embodiment of the present invention, before training, the attenuation offset matrix and the phase offset matrix are converted into a one-dimensional array, and the one-dimensional array is used as input to train the attenuation-shift correlation coefficient model.

[0022] To achieve the above-mentioned purpose and other related purposes, the present application provides a multi-stage amplitude-phase circuit amplitude modulation-phase modulation optimization device, wherein the multi-stage amplitude-phase circuit includes 1st to nth attenuators and 1st to mth phase shifters, and the device includes:

[0023] A first calibration module is used to perform a first calibration process in sequence from the nth attenuator to the first attenuator in a spiral iteration manner; the first calibration process includes: determining a first actual state value of each attenuator, calibrating the first actual state value by an attenuation state correlation coefficient corresponding to the nth attenuator, and obtaining a first calibration state value;

[0024] A second calibration module is used to perform a second calibration process from the m-th stage phase shifter to the first stage phase shifter in a spiral iterative manner; the second calibration process includes: determining a second actual state value of each stage phase shifter, and calibrating the second actual state value by a phase shift state correlation coefficient corresponding to the m-th stage phase shifter to obtain a second calibration state value;

[0025] Among them, the attenuation state correlation coefficient and the phase shift state correlation coefficient are both established through a pre-calibrated attenuation offset matrix and a pre-calibrated phase offset matrix, the attenuation state correlation coefficient is established based on the influence of phase shift on attenuation, and the phase shift state correlation coefficient is established based on the influence of attenuation on phase shift; the attenuation offset matrix represents the difference between the actual state value and the ideal state value of each stage of attenuator, and the phase offset matrix represents the difference between the actual state value and the ideal state value of each stage of phase shifter.

[0026] To achieve the above-mentioned purpose and other related purposes, the present application provides a multi-stage amplitude-phase circuit amplitude modulation-phase modulation optimization device, comprising:

[0027] one or more processors; and

[0028] One or more machine-readable media having instructions stored thereon, which when executed by the one or more processors, cause the processors to perform one or more of the described methods.

[0029] To achieve the above objectives and other related objectives, the present application provides one or more machine-readable media having instructions stored thereon, which, when executed by one or more processors, enable the processors to execute one or more of the described methods.

[0030] As described above, the present application provides a multi-stage amplitude-phase circuit amplitude modulation-phase modulation optimization method, device, medium and equipment, which have the following beneficial effects:

[0031] The present invention discloses a multi-stage amplitude-phase circuit amplitude modulation-phase modulation optimization method, comprising: in a spiral iterative manner, sequentially performing a first calibration process from the n-th stage attenuator to the first-stage attenuator and sequentially performing a second calibration process from the m-th stage phase shifter to the first-stage phase shifter, so as to calibrate the amplitude-phase circuit; wherein the first calibration process comprises: determining a first actual state value of each stage attenuator, calibrating the first actual state value by means of an attenuation state correlation coefficient corresponding to the n-th stage attenuator, and obtaining a first calibration state value; the second calibration process comprises: determining a second actual state value of each stage phase shifter, calibrating the first actual state value by means of an attenuation state correlation coefficient corresponding to the m-th stage attenuator, and obtaining a first calibration state value; The phase shift state correlation coefficient of the phase shifter calibrates the second actual state value to obtain a second calibrated state value; wherein the attenuation state correlation coefficient and the phase shift state correlation coefficient are both established by a pre-calibrated attenuation offset matrix and a pre-calibrated phase offset matrix, the attenuation state correlation coefficient is established based on the influence of phase shift on attenuation, and the phase shift state correlation coefficient is established based on the influence of attenuation on phase shift; the attenuation offset matrix represents the difference between the actual state value and the ideal state value of each stage of the attenuator, and the phase offset matrix represents the difference between the actual state value and the ideal state value of each stage of the phase shifter. The present invention aims at the defects of the existing multi-stage amplitude-phase state optimization algorithm, such as low precision, uncontrollability and inability to consider the mutual influence between amplitude and phase, and provides a new multi-stage amplitude-phase state optimization method based on the spiral rise algorithm architecture. The method realizes the precise optimization and closed-loop control of the state values ​​between different levels due to its structural advantages. At the same time, the method realizes the linkage of amplitude (attenuation) and phase by introducing the correlation coefficient, optimizes the amplitude-phase screening method, and solves the series of problems such as low precision and lack of correlation consideration when using traditional methods.

[0032] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the description of the embodiments of the present application will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0034] Figure 1 It is a flow chart of the prior art multi-stage amplitude-phase circuit amplitude modulation-phase modulation optimization method;

[0035] Figure 2 This is a flow chart of an exemplary multi-stage amplitude-phase circuit amplitude modulation-phase modulation optimization method of the present application;

[0036] Figure 3A block diagram of an exemplary multi-stage amplitude-phase circuit amplitude modulation-phase modulation optimization device of the present application;

[0037] Figure 4 A schematic diagram of the structure of a computer system suitable for implementing the memory of an embodiment of the present application is shown. DETAILED DESCRIPTION

[0038] The following will describe the implementation methods of the present application with reference to the accompanying drawings and preferred embodiments. Those skilled in the art can easily understand other advantages and effects of the present application from the contents disclosed in this specification. The present application can also be implemented or applied through other different specific implementation methods, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present application. It should be understood that the preferred embodiments are only for illustrating the present application, not for limiting the scope of protection of the present application.

[0039] It should be noted that the illustrations provided in the following embodiments are only schematic illustrations of the basic concept of the present application, and thus the drawings only show components related to the present application rather than being drawn according to the number, shape and size of components in actual implementation. In actual implementation, the type, quantity and proportion of each component may be changed at will, and the component layout may also be more complicated.

[0040] In the following description, a large number of details are discussed to provide a more thorough explanation of the embodiments of the present application. However, it is obvious to those skilled in the art that the embodiments of the present application can be implemented without these specific details. In other embodiments, well-known structures and devices are shown in the form of block diagrams rather than in detail to avoid making the embodiments of the present application difficult to understand.

[0041] The current mainstream multi-level amplitude and phase state optimization algorithm usually adopts a waterfall architecture, and establishes an independent top-down hierarchical optimization algorithm according to the two dimensions of amplitude control and phase control. Taking amplitude control as an example, the algorithm arranges the attenuator circuits of different levels in descending order of large step-small step, and prioritizes adjusting the large step amplitude to approach the ideal state value. Then, the small step amplitude is adjusted when the upper step value is determined, so that the state value is closer to the ideal result. After the step value and state value of each level are determined, the state value combination of multiple attenuators is output, and converted into an amplitude control code value to finally obtain the optimized amplitude code value result. Using the same method, the optimization control code of the phase state is calculated and provided together with the amplitude control code to complete the operation of the multi-level amplitude and phase control optimization algorithm. Its principle is as follows Figure 1As shown. The algorithm follows the upper-lower level non-closed-loop screening method, which makes it difficult to deal with the scenario of large amplitude or phase errors caused by uneven upper-level steps (the actual value of individual steps is smaller than the actual value of lower-level steps), and cannot achieve accurate state optimization by adjusting the lower-level steps (due to the limited adjustment range). The amplitude-phase is treated as two independent branches for separate algorithm optimization operations, without considering the two-dimensional characteristics of the amplitude-phase circuit itself, that is, the uncertain relationship between the amplitude and phase values, resulting in a large error between the theoretical optimization value and the measured value. Based on the above-mentioned defects of the prior art, the present application discloses a new multi-level amplitude-phase state optimization algorithm based on the spiral ascending algorithm architecture. Due to its structural advantages, the algorithm realizes the precise optimization and closed-loop control of state values ​​between different levels. At the same time, the algorithm realizes the linkage of amplitude (attenuation) and phase by introducing neural networks and correlation coefficient calibration, optimizes the amplitude-phase screening method, and solves a series of problems such as low accuracy and lack of correlation consideration when using traditional methods.

[0042] See also Figure 2 , Figure 2 The flowchart of the multi-stage amplitude-phase circuit amplitude modulation-phase modulation optimization method according to an embodiment of the present application, wherein the multi-stage amplitude-phase circuit includes 1st to nth attenuators and 1st to mth phase shifters. Figure 2 In the multi-stage amplitude-phase circuit amplitude modulation-phase modulation optimization method, the method includes at least steps S210 to S220, which are described in detail as follows:

[0043] Step S210, performing a first calibration process in sequence from the n-th attenuator to the first-th attenuator in a spiral iteration manner; the first calibration process includes: determining a first actual state value of each attenuator, calibrating the first actual state value by using an attenuation state correlation coefficient corresponding to the n-th attenuator, and obtaining a first calibration state value;

[0044] Step S220, performing a second calibration process in sequence from the m-th stage phase shifter to the first stage phase shifter in a spiral iterative manner; the second calibration process includes: determining a second actual state value of each stage phase shifter, calibrating the second actual state value by a phase shift state correlation coefficient corresponding to the m-th stage phase shifter, and obtaining a second calibration state value;

[0045] Among them, the attenuation state correlation coefficient and the phase shift state correlation coefficient are both established through a pre-calibrated attenuation offset matrix and a pre-calibrated phase offset matrix, the attenuation state correlation coefficient is established based on the influence of phase shift on attenuation, and the phase shift state correlation coefficient is established based on the influence of attenuation on phase shift; the attenuation offset matrix represents the difference between the actual state value and the ideal state value of each stage of attenuator, and the phase offset matrix represents the difference between the actual state value and the ideal state value of each stage of phase shifter.

[0046] Each step is described in detail below.

[0047] In this embodiment, the first calibration process is executed sequentially from the n-th attenuator to the 1-th attenuator in a spiral iterative manner, that is, the first calibration process is first executed on the n-th attenuator, and after the first calibration process is completed, the first calibration process is executed on the n-1-th attenuator, and so on, until the calibration of the 1-th attenuator is completed.

[0048] In this embodiment, the second calibration process is performed sequentially from the m-th phase shifter to the 1-th phase shifter in a spiral iterative manner, that is, the first calibration process is first performed on the m-th phase shifter, and after the first calibration process is completed, the first calibration process is performed on the m-1-th phase shifter, and so on, until the calibration of the 1-th phase shifter is completed.

[0049] In this embodiment, the correlation coefficient includes an attenuation state correlation coefficient and a phase shift state correlation coefficient, the attenuation state correlation coefficient is established based on the influence of phase shift on attenuation, and the phase shift state correlation coefficient is established based on the influence of attenuation on phase shift. The attenuation state correlation coefficient and the phase shift state correlation coefficient can be established by a pre-calibrated attenuation offset matrix and a pre-calibrated phase offset matrix. The attenuation offset matrix refers to a matrix composed of the attenuation offset of each stage of attenuator as matrix elements, and the attenuation offset refers to the difference between the actual state value and the ideal state value. The phase shift offset matrix refers to a matrix composed of the phase shift offset of each stage of phase shifter as matrix elements, and the phase shift offset refers to the difference between the actual state value and the ideal state value.

[0050] In this embodiment, it is necessary to calibrate the two ideal state values ​​of amplitude and phase and the corresponding actual state value of each step, and establish an offset matrix offset-matrix to count the errors between the actual value and the ideal value. The offset matrix offset-matrix will be used as the system error to calculate the attenuation state correlation coefficient and the phase shift state correlation coefficient.

[0051] In the process of constructing the attenuation offset matrix and the phase shift offset matrix, the ideal state value of each attenuator and phase shifter is first recorded and stored in the matrix array, which is recorded as the attenuation ideal state value Att martix1 ...Att martixn (n is the number of attenuator stages) and the ideal phase state value Ps martix1 ...Ps martixm (m is the number of phase shifter stages), and then the actual state value is obtained by configuring each attenuator and phase shifter state, which is recorded as the attenuation actual state value Att' martix1 ...Att' martixn (n is the number of attenuator stages) and the actual state value of phase shift Ps' martix1 ...Ps'martixm (m is the number of phase shifter stages), and the differences between the measured state value and the ideal state value, namely, the attenuation offset and the phase offset, are calculated respectively by the following formulas.

[0052] Attenuation offset AttOffset martixn =Att' martixn -Att martixn (1)

[0053] Phase offset PsOffset martixm =Ps' martixm -Ps martixm (2)

[0054] Thus, the attenuation offset matrix AttOffset can be obtained martix1 ...AttOffset martixn and the phase shift offset matrix PsOffset martix1 ...PsOffset martixm .

[0055] After the attenuation offset matrix and the phase offset matrix are established, correlation coefficients may be obtained based on the attenuation offset matrix and the phase offset matrix, including attenuation state correlation coefficients and phase shift state correlation coefficients.

[0056] The calculation of the correlation coefficient provides the correlation conclusion of the two-dimensional parameters of amplitude (or attenuation) and phase for the final optimization result. The final optimization result of each state value of the amplitude and phase parameters needs to be dynamically adjusted by introducing the correlation coefficient relationship. The setting of the correlation coefficient is a high-order expansion (usually less than or equal to the third order). The setting of the attenuation correlation coefficient requires that each step state value of each attenuator corresponds to all step phase shift states of all phase shifters; similarly, the setting of the phase shift correlation coefficient requires that each step state value of each phase shifter corresponds to all step phase shift states of all attenuators.

[0057] In one embodiment, the calculation of the correlation coefficient includes the following steps: obtaining the attenuation offset matrix and the phase offset matrix; training the initial neural network with the attenuation offset matrix and the phase offset matrix as input and the attenuation state correlation coefficient matrix and the second correlation coefficient matrix as output to obtain an attenuation-shift correlation coefficient model; and obtaining the attenuation state correlation coefficient and the phase shift state correlation coefficient based on the attenuation-shift correlation coefficient model.

[0058] Specifically, first, the calibrated attenuation offset matrix and phase offset matrix are converted into a one-dimensional array array by dimensionality reduction. For each attenuator or phase shifter, the ideal attenuation state value Att1...Att of each step needs to be considered. nOr the ideal phase shift value Ps1...Ps m , respectively, for the attenuation ideal state value Att1 to the attenuation ideal state value Att n Calculate and summarize the ideal phase shift state value Ps1...Ps m The relationship between the correlation coefficient and the ideal phase shift value Ps1 to the ideal phase shift value Ps m By the attenuation ideal state value Att1...Att n The relationship of the correlation coefficient generated. In this embodiment, the relevant training threshold is set according to the rules. For the training of the attenuation state correlation coefficient and the phase shift state correlation coefficient, starting from the 1st order relationship, the attenuation offset matrix converted into a one-dimensional array is introduced into the neural network in the form of random weight distribution by adopting a mechanism of successive order increase. The neural network adopts an error inversion algorithm, and the weight value of each factor is corrected through the feedback link through the system error of the feedforward conclusion. If it still cannot be approached to the threshold range after the weight traversal, the training network will increase the highest order of the relationship by +1, reallocate the random weights, and perform the above training until the training result reaches the training threshold range or the order of the high-order expansion of the expansion exceeds the set upper limit, stop the training, and obtain the attenuation-shift correlation coefficient model. In determining the correlation coefficient, each training result and the correlation coefficient need to be subjected to a gradient descent normalization algorithm from the nth order to the first order. After all attenuation state and phase shift state training is completed, the final correlation coefficient is output. as well as For any attenuator, the corresponding attenuation state value Att n ,have:

[0059] Att' n =Att n +Ps1*a n1 +...+Ps m *a nm

[0060] Where m is the number of all phase shift states, n is the number of all attenuation states, Ps m is the actual phase shift state value corresponding to the m-th phase shifter, Att n is the actual attenuation state value of the nth-stage attenuator, a nm It represents the correlation coefficient of the n-th attenuator to the m-th phase shifter.

[0061] Similarly, for any phase shifter, the corresponding phase shift state value Ps m ,have:

[0062] Ps' m =Ps m +Att1*b m1 +...+Att n *bmn

[0063] b nm It represents the correlation coefficient of the n-th phase shifter on the m-th attenuator.

[0064] Finally, the decay state correlation coefficient matrix is ​​obtained and the phase-shift state correlation coefficient matrix This completes the calculation of the correlation coefficient.

[0065] After completing the calculation of the correlation coefficient, the actual state value of each stage of phase shifter or attenuator is calibrated using the correlation coefficient, that is: the first actual state value is calibrated by the attenuation state correlation coefficient corresponding to the nth stage attenuator to obtain the first calibrated state value, and the second actual state value is calibrated by the phase shift state correlation coefficient corresponding to the mth stage phase shifter to obtain the second calibrated state value.

[0066] According to the calculation conclusion of the correlation coefficient, a median operation is performed from bottom to top for each attenuator and phase shifter. For an amplitude-phase circuit with n-stage attenuators, the actual attenuation state value of the n-stage attenuator is first determined, and the first calibration state value is obtained through the correlation coefficient relationship, and then a spiral iteration is performed from the n-1 stage upward step by step until the first stage (maximum step amplitude) attenuator is reached.

[0067] Among them, Att' n =Att n +Ps1*a n1 +...+Ps m *a nm , Att' m represents the first calibration state value,

[0068] Similarly, for an amplitude-phase circuit with m-stage phase shifters, the actual phase shift state value of the m-th stage phase shifter is first determined, and the second calibration state value is obtained through the correlation coefficient relationship. Then, similar spiral iterations are performed step by step from the m-1 stage upwards until the first stage (maximum phase shift step) phase shifter is reached.

[0069] Among them, Ps' m =Ps m +Att1*b m1 +...+Att n *b mn , Ps' m Indicates the second calibration status value.

[0070] The present application achieves the purpose of minimizing the overall offset and system error caused by the uncertainty of the lower-stage attenuator (or phase shifter) by calibrating the actual attenuation state value and the actual phase shift state value, so that the interference amplitude of the selection of the upper-stage device state reaches the theoretical minimum value, the screening accuracy of the amplitude and phase state is improved, and the actual value is closer to the theoretical value.

[0071] At this point, the calibration of the multi-stage amplitude-phase circuit is completed, and the first amplitude-phase circuit is obtained.

[0072] In one embodiment, the method further comprises:

[0073] For the first amplitude-phase circuit, a first optimization process is sequentially performed from the 1st attenuator to the nth attenuator, and a second optimization process is sequentially performed from the 1st phase shifter to the mth phase shifter, so as to optimize the amplitude-phase circuit; wherein the first optimization process includes: optimizing the first actual state value or the first calibration state value of each attenuator in an error approximation manner; and the second optimization process includes: optimizing the second actual state value or the second calibration state value of each phase shifter in an error approximation manner.

[0074] In one embodiment, the method also includes: obtaining a first code value corresponding to a first calibration state value of each attenuator stage, and a second code value corresponding to a second calibration state value of each phase shifter stage; establishing an attenuation-phase shift code based on the first code value and the second code value, wherein the nth attenuator stage corresponds to the nth phase shifter stage.

[0075] After the amplitude and phase circuit has been calibrated with the reference state, the confidence and stability of the median value of the next state can be ensured. Finally, according to the adjusted attenuation (or phase shift) state, error approximation optimization is performed from the 1st level to the nth level (assuming that the attenuator has n levels in total) and from the 1st level to the mth level (assuming that the phase shifter has m levels in total), so that the state value is close to the median state value of each level of attenuator or phase shifter, and then the attenuation-phase shift code is obtained step by step and state by state. The conclusion is output after summarizing to complete the amplitude modulation-phase modulation optimization.

[0076] In summary, the present invention considers two different dimensional parameter factors of amplitude modulation and phase modulation, adopts a spiral ascending architecture, implements an optimization method from the lower-level attenuator-controller to the upper-level device step by step, and then further corrects and optimizes the state of the lower-level device through the upper-lower level backtracking method, which is more conducive to the calibration and optimization of the ideal state value of the amplitude and phase devices; in addition, the present invention adopts a correlation factor algorithm based on neural network technology to solve the two parameter quantization problems of amplitude and phase, realizes dynamic and associated optimization operations in the screening optimization of each amplitude and phase state, improves the index accuracy, and makes up for the defects of the traditional algorithm. It has the following main advantages:

[0077] (1) High precision: The amplitude and phase devices optimized by the algorithm of the present invention have fine control of both amplitude and phase dimensions. Under normal circumstances, the error of the first-stage 6-bit (64-state) attenuator is controlled within ±0.2dBm, and the error of the first-stage 6-bit (64-state) phase shifter is controlled within ±0.5°.

[0078] (2) Small system error: The median calibration method can effectively avoid the situation where the system error offset is caused by uneven step amplitude of the downstream devices.

[0079] (3) Dynamic association and strong scalability: Attenuators and phase shifters of different levels and different steps achieve quantitative influence on each other through dynamic association, and the influence factor can be calibrated. For example, if you want to achieve skip-level (not step-by-step screening) state calibration, you only need to import amplitude and phase data on the basis of the original network and retrain it.

[0080] (4) The algorithm structure is traceable and highly customizable: The spiral ascending and step-by-step optimization method adopted by the present invention can trace the optimization method and the correlation coefficient through the correlation coefficient or the ideal state. For states with special requirements, a specific optimization method can be implemented by intervening in the stepping of a certain level of devices.

[0081] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0082] Figure 3 FIG. 1 is a block diagram of a multi-stage amplitude-phase circuit amplitude modulation-phase modulation optimization device shown in an exemplary embodiment of the present application. Figure 3 As shown, a multi-stage amplitude-phase circuit amplitude modulation-phase modulation optimization device, the multi-stage amplitude-phase circuit includes 1st to nth attenuators and 1st to mth phase shifters, the device includes:

[0083] The first calibration module 310 is used to perform a first calibration process from the nth attenuator to the first attenuator in a spiral iteration manner; the first calibration process includes: determining a first actual state value of each attenuator, calibrating the first actual state value by using an attenuation state correlation coefficient corresponding to the nth attenuator, and obtaining a first calibration state value;

[0084] The second calibration module 320 is used to perform a second calibration process from the m-th stage phase shifter to the first stage phase shifter in a spiral iteration manner; the second calibration process includes: determining a second actual state value of each stage phase shifter, and calibrating the second actual state value by a phase shift state correlation coefficient corresponding to the m-th stage phase shifter to obtain a second calibration state value;

[0085] Among them, the attenuation state correlation coefficient and the phase shift state correlation coefficient are both established through a pre-calibrated attenuation offset matrix and a pre-calibrated phase offset matrix, the attenuation state correlation coefficient is established based on the influence of phase shift on attenuation, and the phase shift state correlation coefficient is established based on the influence of attenuation on phase shift; the attenuation offset matrix represents the difference between the actual state value and the ideal state value of each stage of attenuator, and the phase offset matrix represents the difference between the actual state value and the ideal state value of each stage of phase shifter.

[0086] It should be noted that the multi-stage amplitude-phase circuit amplitude modulation-phase modulation optimization device provided in the above embodiment and the multi-stage amplitude-phase circuit amplitude modulation-phase modulation optimization method provided in the above embodiment belong to the same concept, wherein the specific manner in which each module and unit performs the operation has been described in detail in the method embodiment, and will not be repeated here. In practical applications provided in the above embodiment, the above functions can be allocated to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above, and this is not limited here.

[0087] An embodiment of the present application also provides a multi-stage amplitude-phase circuit amplitude modulation-phase modulation optimization device, comprising: one or more processors; a storage device for storing one or more programs, and when the one or more programs are executed by the one or more processors, the memory implements the multi-stage amplitude-phase circuit amplitude modulation-phase modulation optimization method provided in the above-mentioned embodiments.

[0088] Figure 4 The schematic diagram of the structure of a computer system suitable for implementing the memory of the embodiment of the present application is shown. It should be noted that: Figure 4 The computer system of the memory shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0089] like Figure 4 As shown, the computer system includes a central processing unit (CPU), which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) or the program loaded from the storage part to the random access memory (RAM), such as executing the method described in the above embodiment. In the RAM, various programs and data required for system operation are also stored. The CPU, ROM and RAM are connected to each other through a bus. The input / output (I / O) interface is also connected to the bus.

[0090] The following components are connected to the I / O interface: an input part including a keyboard, a mouse, etc.; an output part including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker; a storage part including a hard disk, etc.; and a communication part including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication part performs communication processing via a network such as the Internet. A drive is also connected to the I / O interface as needed. Removable media, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., are installed on the drive as needed so that a computer program read therefrom is installed into the storage part as needed.

[0091] In particular, according to an embodiment of the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product, which includes a computer program carried on a computer readable medium, the computer program including a computer program for executing the process. Figure 1 A computer program for the multi-stage amplitude-phase circuit amplitude modulation-phase modulation optimization method shown. In such an embodiment, the computer program can be downloaded and installed from a network through a communication part, and / or installed from a removable medium. When the computer program is executed by a central processing unit (CPU), various functions defined in the system of the present application are executed.

[0092] It should be noted that the computer-readable medium shown in the embodiment of the present application can be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium can be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media can include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, wherein a computer-readable computer program is carried. This propagated data signal can take a variety of forms, including but not limited to an electromagnetic signal, an optical signal, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. A computer program contained on a computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0093] The flowchart and block diagram in the accompanying drawings illustrate the possible architecture, functions and operations of the system, method and computer program product according to various embodiments of the present application. Wherein, each box in the flowchart or block diagram can represent a module, a program segment, or a part of the code, and the above-mentioned module, program segment, or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0094] The units involved in the embodiments described in this application may be implemented by software or hardware, and the units described may also be set in a processor. The names of these units do not, in some cases, constitute limitations on the units themselves.

[0095] Another aspect of the present application further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor of a computer, enables the computer to execute the multi-stage amplitude-phase circuit amplitude modulation-phase modulation optimization method for cloud tourism scenarios as described above. The computer-readable storage medium may be included in the memory described in the above embodiment, or may exist independently without being assembled into the memory.

[0096] Another aspect of the present application also provides a computer program product or a computer program, the computer program product or the computer program includes computer instructions, the computer instructions are stored in a computer-readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the multi-stage amplitude-phase circuit amplitude modulation-phase modulation optimization method provided in each of the above embodiments.

[0097] The above embodiments are merely illustrative of the principles and effects of the present application, and are not intended to limit the present application. Anyone familiar with the technology may modify or change the above embodiments without violating the spirit and scope of the present application. Therefore, all equivalent modifications or changes made by a person of ordinary skill in the art without departing from the spirit and technical ideas disclosed in the present application shall still be covered by the claims of the present application.

Claims

1. A method for optimizing amplitude modulation and phase modulation of a multi-stage amplitude-phase circuit, wherein the multi-stage amplitude-phase circuit comprises attenuators of the first to nth stages and phase shifters of the first to mth stages, characterized in that: The method comprises: In a spiral iteration manner, a first calibration process is sequentially performed from the nth attenuator to the first attenuator; the first calibration process includes: determining a first actual state value of each attenuator, calibrating the first actual state value by using an attenuation state correlation coefficient corresponding to the nth attenuator, and obtaining a first calibration state value; In a spiral iteration manner, a second calibration process is sequentially performed from the m-th stage phase shifter to the first stage phase shifter; the second calibration process comprises: determining a second actual state value of each stage phase shifter, calibrating the second actual state value by a phase shift state correlation coefficient corresponding to the m-th stage phase shifter, and obtaining a second calibration state value; Among them, the attenuation state correlation coefficient and the phase shift state correlation coefficient are both established through a pre-calibrated attenuation offset matrix and a pre-calibrated phase offset matrix, the attenuation state correlation coefficient is established based on the influence of phase shift on attenuation, and the phase shift state correlation coefficient is established based on the influence of attenuation on phase shift; the attenuation offset matrix represents the difference between the actual state value and the ideal state value of each stage of attenuator, and the phase offset matrix represents the difference between the actual state value and the ideal state value of each stage of phase shifter.

2. The multi-stage amplitude-phase circuit amplitude modulation-phase modulation optimization method according to claim 1, characterized in that: The method further comprises: For the calibrated amplitude-phase circuit, a first optimization process is sequentially performed from the first-stage attenuator to the n-stage attenuator, and a second optimization process is sequentially performed from the first-stage phase shifter to the m-stage phase shifter, so as to optimize the amplitude-phase circuit; Among them, the first optimization process includes: optimizing the first actual state value or the first calibrated state value of each stage attenuator in an error approximation manner; the second optimization process includes: optimizing the second actual state value or the second calibrated state value of each stage phase shifter in an error approximation manner.

3. The multi-stage amplitude-phase circuit amplitude modulation-phase modulation optimization method according to claim 1 or 2, characterized in that: The method further comprises: Obtaining a first code value corresponding to a first calibration state value of each stage of attenuators, and a second code value corresponding to a second calibration state value of each stage of phase shifters; An attenuation-phase shift code is established based on the first code value and the second code value, wherein the n-th attenuator corresponds to the n-th phase shifter.

4. The multi-stage amplitude-phase circuit amplitude modulation-phase modulation optimization method according to claim 1, characterized in that: Acquire the attenuation offset matrix and the phase offset matrix; The attenuation offset matrix and the phase offset matrix are used as inputs, and the attenuation state correlation coefficient matrix and the phase shift state correlation coefficient matrix are used as outputs to train the initial neural network to obtain an attenuation-shift correlation coefficient model; The attenuation state correlation coefficient and the phase shift state correlation coefficient are obtained based on the attenuation-shift correlation coefficient model.

5. The multi-stage amplitude-phase circuit amplitude modulation-phase modulation optimization method according to claim 4, characterized in that: The attenuation state correlation coefficient and the phase shift state correlation coefficient are expressed by a high-order expansion, wherein each step state value of each attenuator corresponds to all step phase shift states of all phase shifters, and each step state value of each phase shifter corresponds to all step phase shift states of all attenuators.

6. The multi-stage amplitude-phase circuit amplitude modulation-phase modulation optimization method according to claim 4, characterized in that: In the process of training the attenuation-shift correlation coefficient model, for the training of the attenuation state correlation coefficient or the phase shift state correlation coefficient, starting from the 1st-order expansion, all phase shift states or all attenuation states are assigned to the neural network in the form of random weight distribution by gradually increasing the order; the error inversion algorithm is used to correct the weight value of each factor through the feedback link through the error of the feedforward conclusion. If it still cannot be approximated to the threshold range after the weight value traversal, the highest order of the expansion is increased by 1, and the random weights are reallocated to perform the above training until the training result reaches the threshold range or the order setting of the high-order expansion exceeds the set upper limit, the training is stopped to obtain the attenuation-shift correlation coefficient model.

7. The multi-stage amplitude-phase circuit amplitude modulation-phase modulation optimization method according to claim 4, characterized in that: Before training, the attenuation offset matrix and the phase offset matrix are converted into a one-dimensional array, and the one-dimensional array is used as input to train the attenuation-shift correlation coefficient model.

8. A multi-stage amplitude-phase circuit amplitude modulation-phase modulation optimization device, wherein the multi-stage amplitude-phase circuit comprises 1st to nth attenuators and 1st to mth phase shifters, characterized in that: The device comprises: A first calibration module is used to perform a first calibration process in sequence from the nth attenuator to the first attenuator in a spiral iteration manner; the first calibration process includes: determining a first actual state value of each attenuator, calibrating the first actual state value by an attenuation state correlation coefficient corresponding to the nth attenuator, and obtaining a first calibration state value; A second calibration module is used to perform a second calibration process from the m-th stage phase shifter to the first stage phase shifter in a spiral iterative manner; the second calibration process includes: determining a second actual state value of each stage phase shifter, and calibrating the second actual state value by a phase shift state correlation coefficient corresponding to the m-th stage phase shifter to obtain a second calibration state value; Among them, the attenuation state correlation coefficient and the phase shift state correlation coefficient are both established through a pre-calibrated attenuation offset matrix and a pre-calibrated phase offset matrix, the attenuation state correlation coefficient is established based on the influence of phase shift on attenuation, and the phase shift state correlation coefficient is established based on the influence of attenuation on phase shift; the attenuation offset matrix represents the difference between the actual state value and the ideal state value of each stage of attenuator, and the phase offset matrix represents the difference between the actual state value and the ideal state value of each stage of phase shifter.

9. A multi-stage amplitude-phase circuit amplitude modulation-phase modulation optimization device, characterized in that: include: one or more processors; and One or more machine-readable media having instructions stored thereon, which when executed by the one or more processors, cause the processors to perform the method as recited in one or more of claims 1-7.

10. One or more machine-readable media, characterized in that Instructions are stored thereon, which, when executed by one or more processors, cause the processors to perform the method as claimed in one or more of claims 1-7.

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