Microwave frequency measurement method and device, computer device and storage medium

Abstract

A microwave frequency measurement method, device, computer equipment and storage medium are provided. The method includes obtaining an estimated frequency range of a to-be-measured microwave signal. The frequency range is estimated by using a first measurement structure and a first amplitude comparison equation. The method further includes constructing a model curve of a second amplitude comparison equation based on a second measurement structure, and constructing a model curve of a third amplitude comparison equation based on a third measurement structure. The method further includes splicing a part of the model curve of the second amplitude comparison equation, in which the slope is greater than a predetermined threshold, and a part of the model curve of the third amplitude comparison equation, in which the slope is greater than the predetermined threshold, to obtain a spliced model curve, within a measurement bandwidth of the first measurement structure. The method further includes determining a frequency of the to-be-measured microwave signal based on the spliced model curve and the estimated frequency range.

Description

Technical Field

[0001] This disclosure relates to the field of photonics, and more particularly to the fields of integrated photonic chips and microwave photonics, specifically to a microwave frequency measurement method, apparatus, computer equipment, computer-readable storage medium, and computer program product. Background Technology

[0002] Microwave photonics technology has attracted widespread attention for its advantages, such as large bandwidth, low loss, and insensitivity to electromagnetic interference, in measuring microwave frequencies. Microwave frequency measurement using microwave photonics technology is generally achieved through a "frequency-energy" mapping method. The basic principle is to convert the frequency information of the microwave signal into the energy information of the microwave or optical signal. Then, using a pre-established frequency-energy equation (usually called an amplitude comparison equation), the corresponding frequency information is deduced given the known energy information. Summary of the Invention

[0003] This disclosure provides a microwave frequency measurement method, apparatus, computer equipment, computer-readable storage medium, and computer program product.

[0004] According to one aspect of this disclosure, a microwave frequency measurement method is provided. The method includes obtaining an estimated frequency range of a microwave signal under test. The estimated frequency range is obtained by measuring the microwave signal under test using a first measurement structure. The first measurement structure determines a measurement bandwidth, which is associated with a model curve of a first amplitude comparison equation constructed based on the first measurement structure. The method also includes constructing a model curve of a second amplitude comparison equation based on a second measurement structure, and constructing a model curve of a third amplitude comparison equation based on a third measurement structure. Each of the first, second, and third measurement structures is constructed by programming on a programmable optical network. The method further includes, within the measurement bandwidth of the first measurement structure, splicing the portion of the model curve of the second amplitude comparison equation with a slope greater than a predetermined threshold with the portion of the model curve of the third amplitude comparison equation with a slope greater than a predetermined threshold to obtain a spliced ​​model curve. The method also includes determining the frequency of the microwave signal under test based on the spliced ​​model curve and the estimated frequency range.

[0005] According to another aspect of this disclosure, a microwave frequency measurement apparatus is provided. The apparatus includes an estimated frequency acquisition unit configured to acquire an estimated frequency range of a microwave signal under test. The estimated frequency range is obtained by measuring the microwave signal under test using a first measurement structure. The first measurement structure determines a measurement bandwidth, which is associated with a model curve of a first amplitude comparison equation constructed based on the first measurement structure. The apparatus also includes a model curve construction unit configured to construct a model curve of a second amplitude comparison equation based on a second measurement structure, and a model curve of a third amplitude comparison equation based on a third measurement structure. Each of the second and third measurement structures is constructed by programming on a programmable optical network. The apparatus further includes a model curve splicing unit configured to splice a portion of the model curve of the second amplitude comparison equation with a slope greater than a predetermined threshold within the measurement bandwidth of the first measurement structure, and a portion of the model curve of the third amplitude comparison equation with a slope greater than a predetermined threshold, to obtain a spliced ​​model curve. The apparatus also includes a frequency determination unit configured to determine the frequency of the microwave signal under test based on the spliced ​​model curve and the estimated frequency range.

[0006] According to one aspect of this disclosure, a computer device is provided, comprising: at least one processor; and at least one memory having a computer program stored thereon, wherein the computer program, when executed by the processor, causes the processor to perform the method as described above.

[0007] According to one aspect of this disclosure, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, causes the processor to perform the method described above.

[0008] According to one aspect of this disclosure, a computer program product is provided, including a computer program that, when executed by a processor, causes the processor to perform the method described above.

[0009] According to one or more embodiments of this disclosure, high-bandwidth, high-precision microwave frequency measurement can be achieved.

[0010] These and other aspects of this disclosure will be clear from the embodiments described below, and will be elucidated with reference to the embodiments described below. Attached Figure Description

[0011] Further details, features, and advantages of this disclosure are disclosed in the following description of exemplary embodiments in conjunction with the accompanying drawings, in which:

[0012] Figure 1 A flowchart is shown for a microwave frequency measurement method according to an embodiment of the present disclosure;

[0013] Figure 2A schematic diagram of a first measurement system according to an embodiment of the present disclosure is shown;

[0014] Figure 3 A schematic diagram of a first measurement structure constructed on a programmable optical network according to an embodiment of the present disclosure is shown;

[0015] Figure 4 A schematic diagram of the complementary power response according to an embodiment of the present disclosure is shown;

[0016] Figure 5 A schematic diagram showing the model curve of the first amplitude comparison equation according to an embodiment of the present disclosure;

[0017] Figure 6 A schematic diagram illustrating an example of a second measurement system according to an embodiment of the present disclosure;

[0018] Figure 7 A schematic diagram of a second measurement structure constructed on a programmable optical network according to an embodiment of the present disclosure is shown;

[0019] Figure 8 A schematic diagram of the complementary power response according to another embodiment of the present disclosure is shown;

[0020] Figure 9 A schematic diagram showing a spliced ​​model curve according to an embodiment of the present disclosure;

[0021] Figure 10 A schematic block diagram of a microwave frequency measuring apparatus according to an embodiment of the present disclosure is shown; and

[0022] Figure 11 An example configuration of a computer device that can be used to implement the methods described in this disclosure is shown. Detailed Implementation

[0023] It will be understood that although the terms first, second, third, etc., may be used herein to describe various elements, components, areas, layers, and / or parts, these elements, components, areas, layers, and / or parts should not be limited by these terms. These terms are used only to distinguish one element, component, area, layer, or part from another. Therefore, the first element, component, area, layer, or part discussed below may be referred to as the second element, component, area, layer, or part without departing from the teachings of this disclosure.

[0024] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit this disclosure. As used herein, the singular forms “a,” “an,” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprising” and / or “including” as used in this specification designate the presence of the stated features, integrals, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components, and / or groups thereof. As used herein, the term “and / or” includes any and all combinations of one or more of the associated listed items, and the phrase “at least one of A and B” means only A, only B, or both A and B.

[0025] Unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure pertains. It will be further understood that terms such as those defined in commonly used dictionaries should be interpreted as having meanings consistent with their meanings in the relevant field and / or the context of this specification, and will not be interpreted in an idealized or overly formal sense unless expressly defined herein.

[0026] In microwave frequency measurement using microwave photonics technology, the first step is to pre-construct an amplitude comparison function (ACF) that reflects the mapping relationship between microwave frequency information and energy information using a specific measurement structure. Then, given the energy information of the microwave to be measured, the frequency information corresponding to the energy information is deduced from the amplitude comparison function, thereby obtaining the frequency of the microwave to be measured.

[0027] However, traditional methods cannot simultaneously meet the requirements of both measurement bandwidth and measurement accuracy. In particular, when using a single measurement structure, measurement bandwidth and measurement accuracy are mutually restrictive, making it difficult to meet the requirements for high precision and large bandwidth.

[0028] Therefore, according to one aspect of this disclosure, a microwave frequency measurement method is provided. Embodiments of this disclosure will now be described in detail with reference to the accompanying drawings.

[0029] Figure 1 A flowchart of a microwave frequency measurement method 100 according to an embodiment of the present disclosure is shown. Figure 1 As shown, the microwave frequency measurement method 100 includes steps S102, S104, S106 and S108.

[0030] In step S102, the estimated frequency range of the microwave signal under test is obtained. This estimated frequency range is obtained by measuring the microwave signal under test using a first measurement structure. The first measurement structure determines the measurement bandwidth, which is correlated with the model curve of a first amplitude comparison equation constructed based on the first measurement structure.

[0031] In the example, the estimated frequency range of the microwave signal under test can represent the interval in which the frequency of the microwave signal under test is most likely to fall, that is, a rough range reflecting the frequency of the microwave signal under test. Obtaining the estimated frequency range of the microwave signal under test may include first measuring the microwave signal under test using a first measurement structure to obtain a frequency estimate, and then adding a certain error tolerance (e.g., determined based on empirical values) to this frequency estimate to obtain the estimated frequency range. For example, the frequency estimate obtained by measurement may be approximately 10 GHz, and the estimated frequency range obtained based on this may be, for example, 9.9 GHz to 10.1 GHz.

[0032] In this example, before measuring the microwave signal to be measured to obtain a frequency estimate, a model curve of the first amplitude comparison equation can be constructed based on the first measurement structure. As mentioned earlier, the amplitude comparison equation reflects the mapping relationship between the frequency information and energy information of the microwave. For example, this mapping relationship between frequency information and energy information can be established by inputting several sample microwave signals with specific frequencies into the first measurement structure to obtain the corresponding energy information. Thus, a model curve of the first amplitude comparison equation can be obtained, which can contain several sample points corresponding to the several sample microwave signals with specific frequencies, each sample point reflecting the mapping relationship between a specific frequency and its corresponding energy. For example, the sample microwave signals can have a sufficiently large sample size, be random, and have a relatively uniform interval distribution. Accordingly, the measurement bandwidth of the first measurement structure can also be determined through this model curve of the first amplitude comparison equation.

[0033] In the example, the model curve of the first amplitude comparison equation can also be represented in the form of a lookup table. For example, a lookup table can construct a frequency-energy fitting curve / equation based on sample points.

[0034] In the example, the first measurement structure may include a two-port power complementary device capable of providing a relatively large measurement bandwidth. For example, the first measurement structure may include a Mach-Zehnder interferometer (MZI) or an add-drop microring resonator with a low Q value. Since the measurement bandwidth of the first measurement structure is correlated with the model curve of the first amplitude comparison equation, providing a relatively large measurement bandwidth with the first measurement structure can help increase the overall measurement bandwidth.

[0035] In step S104, a model curve for the second amplitude comparison equation is constructed based on the second measurement structure, and a model curve for the third amplitude comparison equation is constructed based on the third measurement structure. Each of the second and third measurement structures is constructed through programming on a programmable optical network.

[0036] In the example, the method of constructing the model curve of the second amplitude comparison equation based on the second measurement structure, and the method of constructing the model curve of the third amplitude comparison equation based on the third measurement structure, can be similar to the method of constructing the model curve of the first amplitude comparison equation based on the first measurement structure. In the following text, the construction of the model curve of the amplitude comparison equation can also be referred to as the modeling process.

[0037] In the example, depending on the required measurement accuracy, it is not limited to two measurement structures; instead, model curves of corresponding amplitude comparison equations can be constructed based on more measurement structures. Accordingly, in the subsequent step S106, model curves of more amplitude comparison equations can be stitched together to achieve higher measurement accuracy.

[0038] In the example, the first, second, and third measurement structures can be constructed on the same optical FPGA (Field-Programmable Gate Array) chip by switching the on / off states of tunable basic units (TBUs). This allows for the dynamic construction of desired measurement structures using the programmability and reconfigurability of programmable optical networks, facilitating rapid switching between different measurement structures. In the example, each of the second and third measurement structures may include an add-drop microring resonator or an MZI with a high extinction ratio.

[0039] In step S106, within the measurement bandwidth of the first measurement structure, the portion of the model curve of the second amplitude comparison equation with a slope greater than a predetermined threshold is spliced ​​with the portion of the model curve of the third amplitude comparison equation with a slope greater than a predetermined threshold to obtain a spliced ​​model curve.

[0040] In the example, the portion of the model curve with a larger slope in the second or third amplitude comparison equation corresponds to a portion with higher measurement accuracy. This is because a larger slope allows a relatively small step in frequency to correspond to a relatively large step in energy, thus resulting in higher measurement accuracy. Therefore, by concatenating the portion of the model curve with a slope greater than a predetermined threshold in the second amplitude comparison equation with the portion of the model curve with a slope greater than a predetermined threshold in the third amplitude comparison equation, a concatenated model curve that reflects the mapping relationship between frequency and energy information with relatively high accuracy can be obtained.

[0041] In step S108, the frequency of the microwave signal to be tested is determined based on the spliced ​​model curve and the estimated frequency range.

[0042] In the example, since the spliced ​​model curve originates from two different model curves, the spliced ​​model curve may not be monotonic, meaning that the frequency information and energy information may not be a one-to-one mapping. This implies that the same energy information may correspond to multiple different frequency information. However, since the estimated frequency range of the microwave signal under test, i.e., a rough frequency range, has been obtained in step S102, the frequency to which the energy information should correspond can be accurately determined based on this estimated frequency range.

[0043] The above Figure 1 In the microwave frequency measurement method 100, according to one example, the frequency can first be coarsely measured using a first measurement structure such as an MZI to pinpoint a rough frequency range. This first measurement structure can have, for example, a measurement bandwidth of 0–15.5 GHz and a measurement accuracy (e.g., measurement root mean square error) of approximately 110 MHz. Then, the frequency can be precisely measured using a second and third measurement structure, such as a microring resonator. By constructing a stitched model curve, the measurement accuracy can be reduced to 56 MHz. That is, the final measurement bandwidth can be increased to 15.5 GHz, while the measurement accuracy can be reduced to 56 MHz, thereby simultaneously achieving the measurement requirements for both high accuracy and large bandwidth.

[0044] Therefore, the microwave frequency measurement method according to the embodiments of this disclosure can achieve high-bandwidth and high-precision microwave frequency measurement, breaking through the constraint between measurement bandwidth and measurement accuracy in microwave frequency measurement. Furthermore, thanks to the programmability and reconfigurability of programmable optical networks, the measurement structure required for measurement can be dynamically constructed. Compared to customized chips, this can significantly shorten the time required for device fabrication, thereby improving overall measurement efficiency.

[0045] Figure 2 A schematic diagram of a first measurement system 200 according to an embodiment of the present disclosure is shown.

[0046] In the example, the first measurement system 200 can be used for, on the one hand, as... Figure 1 Step S102, as shown, is used to construct the model curve of the first amplitude comparison equation (i.e., the modeling process), and on the other hand, it can be used to obtain the estimated frequency range of the microwave signal under test (i.e., the coarse measurement process). As mentioned earlier, the modeling process may involve establishing a mapping relationship between frequency information and energy information, while the coarse measurement process may involve, given the energy information, back-calculating the frequency estimate of the microwave signal under test based on the model curve of the amplitude comparison equation, and obtaining the estimated frequency range based on this frequency estimate.

[0047] In the example, as Figure 1 The estimated frequency range of the microwave signal under test obtained in step S102 can be obtained based on a coarse measurement process of the first measurement system 200. Therefore, a modeling process can be performed in advance by the first measurement system 200 before this coarse measurement process.

[0048] like Figure 2 As shown, the first measurement system 200 may include a laser diode (LD) 201, a Mach-Zehnder modulator (MZM) 202, a first measurement structure 203, a photodetector (PD) 204, and a processing unit 205.

[0049] LD 201 can emit an optical signal S1, and the optical signal S1 can be input to MZM 202. The microwave signal S2 can be modulated onto the optical signal S1 through MZM 202 to generate a modulated optical signal S3. The modulated optical signal S3 can be input to the first measurement structure 203.

[0050] The first measurement structure 203 may include an input port 203-1 and output ports 203-2 and 203-3. The output ports 203-2 and 203-3 of the first measurement structure 203 may be connected to PDs 204-1 and 204-2, respectively. The modulated optical signal S3 may be input to the first measurement structure 203 via the input port 203-1 and output as optical output signals S3-1 and S3-2 via the output ports 203-2 and 203-3, respectively, to be input to the next-level corresponding PDs 204-1 and 204-2.

[0051] The optical output signals S3-1 and S3-2 can be converted into corresponding electrical signals in PDs 204-1 and 204-2, respectively, and input to the processing unit 205 for subsequent processing. In the example, for the modeling process, the processing unit 205 can output energy information corresponding to the microwave signal S2 with a specific frequency. For the coarse measurement process, the processing unit 205 can output energy information corresponding to the microwave signal S2 with the frequency to be determined.

[0052] During the modeling process, the model curve of the first amplitude comparison equation can be obtained based on several sample microwave signals with specific frequencies. Therefore, the microwave signal S2 loaded onto the MZM 202 can be a sample microwave signal with a specific frequency. In the example, the frequency of the sample microwave signal can be changed in predetermined steps using a stepping method.

[0053] During the coarse measurement process, the microwave signal S2 applied to the MZM 202 can be a microwave signal to be measured with a frequency to be determined. For example, energy information corresponding to the microwave signal to be measured can be obtained through the first measurement structure 203. Then, based on the model curve of the pre-constructed first amplitude comparison equation, the frequency estimate of the microwave signal to be measured can be inferred from the obtained energy information, and the estimated frequency range can be obtained based on the frequency estimate.

[0054] According to some embodiments, the first measurement structure 203 may be constructed by programming on a programmable optical network.

[0055] In the example, the first measurement structure 203 may include an MZI or an add-drop microring resonator with a low Q value, or other two-port power complementary devices. Figure 2 The example is shown using the first measuring structure 203 with an arm length difference of ΔL and an MZI. Figure 2 (marked as OFPGA_MZI).

[0056] By constructing the first measurement structure through programming on a programmable optical network, just like the second and third measurement structures, the programmability and reconfigurability of the programmable optical network can be used to dynamically construct the required measurement structure, enabling real-time and fast switching between different measurement structures.

[0057] According to some embodiments, the first measurement structure 203 may include two output ports 203-2 and 203-3 that provide complementary power responses, and the model curve of the first amplitude comparison equation indicates the ratio of the complementary power responses provided at the two output ports 203-2 and 203-3 at different frequencies within the measurement bandwidth.

[0058] By utilizing the complementary power responses provided at the two output ports, energy information can be easily represented by the ratio of the complementary power responses, and thus the mapping relationship between frequency information and energy information can be easily obtained.

[0059] According to some embodiments, measuring the microwave signal S2 under test using the first measurement structure 203 may include: modulating the microwave signal S2 under test onto an optical signal S1; inputting the modulated optical signal S3 into the first measurement structure 203 to obtain the ratio of complementary power responses provided at two output ports 203-2 and 203-3; and determining a frequency estimate of the microwave signal S2 under test based on the ratio of complementary power responses and a model curve of a first amplitude comparison equation. An estimated frequency range can be determined based on the frequency estimate.

[0060] This measurement method allows the frequency of the microwave signal under test to be inferred from the model curve of the first amplitude comparison equation and the energy information (i.e., represented by the ratio of complementary power responses).

[0061] In the example, an error margin (e.g., determined empirically) can be included in the frequency estimate to obtain the estimated frequency range. Given that the first measurement structure is a single structure, the frequency measured by it may not be accurate. Therefore, including an error margin can help to pinpoint the range within which the frequency of the microwave signal under test is most likely to fall.

[0062] According to some embodiments, modulating the microwave signal S2 to be tested onto the optical signal S1 may include carrier-suppressed double-sideband modulation or carrier-suppressed single-sideband modulation.

[0063] In the example, the MZM 202 can be operated at the minimum bias point to achieve carrier-suppressed double-sideband modulation. Only odd-order optical sidebands can be retained. Under small-signal conditions, the amplitudes of higher-order odd-order sidebands are small and can be ignored. Therefore, the modulated optical sidebands after MZM 202 modulation have only ±1 order optical sidebands.

[0064] In the example, the MZM 202 can be operated under carrier-suppressed single-sideband (CSSB) conditions, retaining only the +1 or -1 order optical sidebands under small signal conditions to achieve carrier-suppressed CSSB modulation.

[0065] By using the above modulation method, the ±1-order optical sideband, or +1 or -1-order optical sideband required in the measurement process can be obtained to modulate the microwave signal S2 to be measured onto the optical signal S1.

[0066] According to some embodiments, the first measurement structure 203 can be adjusted such that the resonant wavelength of the first measurement structure 203 is consistent with the center wavelength of the optical signal S1.

[0067] In the example, the first measurement structure 203 includes an MZI (Mechanical Zig-Insulation) array programmed onto a programmable optical network. Figure 2 Taking OFPGA_MZI as an example, the phase control unit in the MZI can be adjusted so that the resonant wavelength of the MZI matches the center wavelength of the optical signal S1 emitted by the LD 201. For example, the phase control unit can be a TBU in a programmable optical network that can achieve dual-arm heating (in addition to heating, the TBU can also be adjusted based on thermo-optical effect, electro-optical effect, piezoelectric effect, etc.). Alternatively, the center wavelength of the optical signal S1 emitted by the LD 201 can also be adjusted to match the resonant wavelength of the MZI.

[0068] By adjusting the first measurement structure 203 so that its resonant wavelength is consistent with the center wavelength of the optical signal S1, it is convenient to represent the spectrum of the modulated optical signal S3 in a symmetrical manner on the coordinate axis with the optical signal S1 as the reference (i.e., the spectrum represented by the complementary power response of the two optical output signals S3-1 and S3-2).

[0069] According to some embodiments, the model curve of the first amplitude comparison equation is monotonic.

[0070] In the example, the monotonic interval can be within the rising / falling edge range of the spectrum represented by the complementary power responses of the two optical output signals S3-1 and S3-2.

[0071] Since the frequency estimate of the microwave signal S2 to be measured can be derived from the model curve of the first amplitude comparison equation, this monotonicity of the model curve of the first amplitude comparison equation makes it easy to deduce the frequency information from the energy information based on the one-to-one mapping relationship.

[0072] Figure 3 A schematic diagram of a first measurement structure 300 constructed on a programmable optical network according to an embodiment of the present disclosure is shown.

[0073] like Figure 3 The first measuring structure 300 shown can be as follows: Figure 2 The example shown is of the first measurement structure 203, where, for example, MZI can be constructed on a programmable optical network by controlling the switching state of the TBU. The input port 301-1 of the first measurement structure 300 can correspond to, for example,... Figure 2 The input port 203-1 shown, and the two output ports 301-2 and 301-3 can correspond to, as shown in the figure. Figure 2 The two output ports shown are 203-2 and 203-3. TBU 302 can achieve dual-arm heating as a phase control unit, while the other TBUs can achieve single-arm heating.

[0074] Figure 4 A schematic diagram of a complementary power response 400 according to an embodiment of the present disclosure is shown.

[0075] like Figure 4 As shown, the complementary power response 400 may include a first power response 410 and a second power response 420 having complementary characteristics. The first power response 410 may be as follows: Figure 2 The second power response 420 is generated at the output port 203-2 shown, and can be generated at the output port 203-2 shown. Figure 2 This is generated at output port 203-3 as shown. Accordingly, the complementary power response 400 can be represented as follows: Figure 2 The spectrum generated by the modulated optical signal S3 through the first measurement structure 203 is shown, where the frequency coordinate axis is represented with reference to the optical signal S1, and f0 represents the center wavelength of the optical signal S1.

[0076] like Figure 4 As shown, the method of suppressing double-sideband by carrier at ±f is also illustrated. uk (f ukThe ±1st order optical sidebands generated at the frequency of the microwave under test. Figure 2 The resonant wavelength of the first measurement structure 203 shown is consistent with the center wavelength f0 of the optical signal S1, and the complementary power response 400 can be represented in a symmetrical manner.

[0077] Figure 5 A schematic diagram showing a model curve 500 of a first amplitude comparison equation according to an embodiment of the present disclosure is provided.

[0078] like Figure 5 As shown, the model curve 500 of the first amplitude comparison equation is monotonic. In the example, the model curve 500 of the first amplitude comparison equation can be based on, for example... Figure 2 The first measurement structure 203 shown is constructed from this. The model curve 500 of the first amplitude comparison equation may also include information about the measurement bandwidth of the first measurement structure 203, for example, in Figure 5 The frequency range spanned by the model curve 500 is represented by the x-axis f. RF This indicates the frequency of the microwave signal.

[0079] Figure 6 A schematic diagram of a second measurement system 600 according to an embodiment of the present disclosure is shown.

[0080] In the example, the second measurement system 600 can be used for, on the one hand, as... Figure 1 The step S104 shown is used to construct the model curves of the second amplitude comparison equation and the third amplitude comparison equation (i.e., the modeling process). On the other hand, it can be used for, for example... Figure 1 The step S108 shown is used to determine the frequency of the microwave signal to be measured (i.e., the precise measurement process).

[0081] With Figure 2 Similar to the first measurement system 200 shown, the second measurement system 600 may include a laser diode (LD) 601, a Mach-Zehnder modulator (MZM) 602, a second measurement structure 603, a photodetector (PD) 604, and a processing unit 605.

[0082] LD 601 can emit an optical signal S1, and the optical signal S1 can be input to MZM 602. The microwave signal S2 can be modulated onto the optical signal S1 through MZM 602 to generate a modulated optical signal S3. The modulated optical signal S3 can be input to the second measurement structure 603.

[0083] The second measurement structure 603 may include an input port 603-1 and output ports 603-2 and 603-3. The output ports 603-2 and 603-3 of the second measurement structure 603 can be connected to PDs 604-1 and 604-2, respectively. The modulated optical signal S3 can be input to the second measurement structure 603 via the input port 603-1 and output as two optical output signals S3-1 and S3-2 via the output ports 603-2 and 603-3, respectively, to be input to the corresponding PDs 604-1 and 604-2 at the next stage.

[0084] The optical output signals S3-1 and S3-2 can be converted into corresponding electrical signals in the two PDs 604-1 and 604-2, respectively, and input to the processing unit 605 for subsequent processing. In the example, for the modeling process, the processing unit 605 can output energy information corresponding to the microwave signal S2 with a specific frequency. For the precise measurement process, the processing unit 605 can output energy information corresponding to the microwave signal S2 with the frequency to be determined.

[0085] During the modeling process, the model curve of the second amplitude comparison equation can be obtained based on several sample microwave signals with specific frequencies. Therefore, the microwave signal S2 loaded onto the MZM 602 can be a sample microwave signal with a specific frequency. In the example, the frequency of the sample microwave signal can be changed in predetermined steps using a stepping method.

[0086] During precise measurement, the microwave signal S2 applied to the MZM 602 can be a microwave signal to be measured with a frequency to be determined. For example, energy information corresponding to the microwave signal to be measured can be obtained through the second measurement structure 603. Then, based on, as... Figure 1 The stitched model curve obtained in step S106 is used to infer the precise frequency of the microwave signal under test based on the obtained energy information. This is due to the high measurement accuracy brought about by the stitched model curve.

[0087] According to some embodiments, such as Figure 1 Each of the second and third measurement structures in step S104 shown is constructed by programming on a programmable optical network. In the example, the second measurement structure 603 may include an add-drop micro ring resonator (MRR) or an MZI with a high extinction ratio, or other dual-port power complementary devices. Figure 6 MRR is used as an example to illustrate ( Figure 2(Illustrated as OFPGA_MRR). A third measurement structure 606 can be constructed by adjusting the phase control unit in the second measurement structure 603. For example, the phase control unit could be a TBU in a programmable optical network capable of dual-arm heating. In this example, the second and third measurement structures 603 can be adjusted such that the notch point of the spectrum of the modulated optical signal S3 obtained based on the second measurement structure 603 coincides with the carrier wavelength (e.g., center wavelength) of the optical signal S1 emitted by the LD 601, while the peak point of the spectrum of the modulated optical signal S3 obtained based on the third measurement structure 606 coincides with the carrier wavelength (e.g., center wavelength) of the optical signal S1 emitted by the LD 601. That is, the spectrum obtained based on these two measurement structures has a certain phase shift.

[0088] In the example, due to, as Figure 2 The first measurement structure 203 shown can also be constructed by programming on a programmable optical network, thus allowing the measurement to be controlled by adjusting the switching state of the TBU in the programmable optical network. Figure 2 The first measurement structure 203 shown can be quickly switched to, as... Figure 6 The second measurement structure 603 shown is a prime example of how the programmability and reconfigurability of programmable optical networks enable the dynamic construction of different required measurement structures. In other words, in this way, as... Figure 2 The first measurement system 200 shown is Figure 6 The second measurement system 600 shown actually has the same system architecture, and different measurement structures can be obtained simply by changing the programming of the programmable optical network.

[0089] According to some embodiments, the second measurement structure 603 may include two output ports 603-2 and 603-3 that provide complementary power responses, and the model curve of the second amplitude comparison equation may indicate the ratio of the complementary power responses provided at the two output ports 603-2 and 603-3 at different frequencies.

[0090] The third measurement structure 606 may also include two output ports that provide complementary power responses (in...). Figure 6 (Also referred to as 603-2 and 603-3), and the model curve of the third amplitude comparison equation can indicate the ratio of the complementary power responses provided at the two output ports 603-2 and 603-3 at different frequencies.

[0091] By utilizing the complementary power responses provided at the two output ports, the energy information can be easily represented by the ratio of the complementary power responses, and thus the correspondence between frequency information and energy information can be easily obtained.

[0092] As mentioned earlier, during the modeling process, the microwave signal S2 loaded onto the MZM 602 can be a sample microwave signal with a specific frequency.

[0093] According to some embodiments, the model curve for constructing the second amplitude comparison equation based on the second measurement structure 603 may include: inputting an optical signal S3 modulated by a sample microwave signal S2 with different frequencies to the second measurement structure 603 to obtain the ratio of complementary power responses provided at the two output ports 603-2 and 603-3 of the second measurement structure 602 at different frequencies. The wavelength of the minimum power in the complementary power response may coincide with the carrier wavelength of the optical signal (i.e., aligned with the notch point).

[0094] Similarly, the model curve for constructing the second amplitude comparison equation based on the third measurement structure 606 may include: inputting an optical signal S3 modulated by sample microwave signals S2 with different frequencies to the third measurement structure 606 to obtain the amplitude comparison curve at different frequencies at the two output ports of the third measurement structure 606 (in... Figure 6 The ratio of complementary power responses provided at (also denoted as 603-2 and 603-3). The wavelength of the maximum power in the complementary power response can be aligned with the carrier wavelength of the optical signal (i.e., aligned with the peak point).

[0095] The above embodiments may involve the case of carrier-suppressed double sideband. According to some other embodiments, in the case of carrier-suppressed single sideband, it is not necessary to satisfy the requirement of carrier wavelength alignment with the dip or peak point.

[0096] By using the above method, we can obtain the model curve of the second amplitude comparison equation shifted in phase and the model curve of the second amplitude comparison equation, so as to facilitate the splicing of the model curves.

[0097] As mentioned earlier, during the precise measurement process, the microwave signal S2 applied to the MZM 602 can be the microwave signal to be measured with the frequency to be determined.

[0098] According to some embodiments, determining the frequency of the microwave signal S2 to be measured may include: modulating the microwave signal S2 to be measured onto an optical signal S1; inputting the modulated optical signal S3 to a second measurement structure 603 or a third measurement structure 606 to obtain a ratio of corresponding complementary power responses provided at the corresponding two output ports 603-2 and 603-3; and determining the frequency of the microwave signal S2 to be measured based on the ratio of complementary power responses and a portion of the estimated frequency range selected on the spliced ​​model curve.

[0099] In the example, since the stitched model curves originate from two different model curves, they may not be monotonic, meaning that frequency and energy may not be a one-to-one mapping. Therefore, when using the stitched model curves, the frequency to which the energy information should correspond can be accurately determined based on the estimated frequency range; that is, the corresponding portion of the stitched model curve can be selected based on the estimated frequency range. In this case, the precise frequency of the microwave signal S2 under test can be determined based on the ratio of complementary power responses (i.e., energy information) and the corresponding portion of the stitched model curve (the mapping relationship between frequency and energy information).

[0100] Figure 7 A schematic diagram of a second measurement structure 700 constructed on a programmable optical network according to an embodiment of the present disclosure is shown.

[0101] like Figure 7 The second measuring structure 700 shown can be as follows: Figure 6 The example of the second measurement structure 603 shown illustrates how the MRR is constructed on a programmable optical network by controlling the switching state of the TBU. The input port 701-1 of the second measurement structure 700 can correspond to, for example... Figure 6 The input port 603-1 is shown, and the output ports 701-2 and 701-3 can correspond to, as shown in the figure. Figure 6 The output ports 603-2 and 603-3 are shown. TBU 702 can be used as a phase control unit for dual-arm heating, while the other TBUs can be used for single-arm heating.

[0102] In the example, a third measurement structure can be constructed by adjusting the TBU 702 in the second measurement structure 700 that enables dual-arm heating, so that the spectra obtained based on the two measurement structures have a certain phase shift for model curve stitching. The third measurement structure can be as follows: Figure 6 An example of the third measuring structure 606 is shown.

[0103] Figure 8 A schematic diagram of a complementary power response 800 according to another embodiment of the present disclosure is shown.

[0104] like Figure 8 As shown, the complementary power response 800 may include a first power response 810 and a second power response 820 having complementary characteristics. The first power response 810 may be as follows: Figure 6 The second power response 820 is generated at the output port 603-2 shown, and can be generated at the output port 603-2 shown. Figure 6 This is generated at output port 603-3 as shown. In the example, the complementary power response 800 can be represented as follows: Figure 6The spectrum generated by the modulated optical signal S3 through the second measurement structure 603 is shown, where the frequency coordinate axis is represented relative to the optical signal S1, and f0 represents the center wavelength of the optical signal S1. Furthermore, the ±f0 spectrum is also shown using carrier-suppressed double-sideband modulation. uk (f uk The ±1st order optical sidebands generated at the frequency of the microwave being measured. Similarly, after passing through... Figure 6 The spectrum generated by the third measurement structure 606 shown can have a certain phase shift with the complementary power response 800.

[0105] Figure 9 A schematic diagram of a spliced ​​model curve 900 according to an embodiment of the present disclosure is shown. For reference, Figure 9 The model curve 905 of the first amplitude comparison equation is also shown to represent the spliced ​​model curve 900 formed within its measurement bandwidth. Figure 9 In the middle, the x-coordinate f RF This indicates the frequency of the microwave signal.

[0106] like Figure 9 As shown, the spliced ​​portion 910 of the model curve of the second amplitude comparison equation and the spliced ​​portion 920 of the model curve of the third amplitude comparison equation together form the spliced ​​model curve 900. The spliced ​​portion 910 is the part of the model curve of the second amplitude comparison equation with a slope greater than a predetermined threshold, and the spliced ​​portion 920 is the part of the model curve of the third amplitude comparison equation with a slope greater than a predetermined threshold.

[0107] According to some embodiments, the spliced ​​model curve 900 can be obtained by replacing the portion of the model curve of the second amplitude comparison equation and the model curve of the third amplitude comparison equation whose slope is lower than or equal to a predetermined threshold with the portion of the other curve whose slope is greater than the predetermined threshold at the same frequency. For example, the spliced ​​model curve 900 can be obtained by replacing the portion 910' of the model curve of the second amplitude comparison equation whose slope is lower than or equal to the predetermined threshold with the spliced ​​portion 920.

[0108] By using the above methods, a stitched model curve with high measurement accuracy can be obtained to determine the precise frequency of the microwave signal under test.

[0109] According to another aspect of this disclosure, a microwave frequency measuring device is also provided.

[0110] Figure 10 A schematic block diagram of a microwave frequency measuring device 1000 according to an embodiment of the present disclosure is shown.

[0111] like Figure 10As shown, the microwave frequency measurement device 1000 includes an estimated frequency acquisition unit 1010, a model curve construction unit 1020, a model curve splicing unit 1030, and a frequency determination unit 1040.

[0112] The frequency acquisition unit 1010 is configured to acquire an estimated frequency range of the microwave signal under test. The estimated frequency range is obtained by measuring the microwave signal under test using a first measurement structure. The first measurement structure has a measurement bandwidth, which is correlated with a model curve of a first amplitude comparison equation constructed based on the first measurement structure.

[0113] The model curve construction unit 1020 is configured to construct a model curve for a second amplitude comparison equation based on a second measurement structure, and a model curve for a third amplitude comparison equation based on a third measurement structure. Each of the second and third measurement structures is constructed through programming on a programmable optical network.

[0114] The model curve splicing unit 1030 is configured to splice the portion of the model curve of the second amplitude comparison equation with the portion of the model curve of the third amplitude comparison equation with the portion of the model curve with the slope greater than the predetermined threshold within the measurement bandwidth of the first measurement structure, so as to obtain the spliced ​​model curve.

[0115] The frequency determination unit 1040 is configured to determine the frequency of the microwave signal under test based on the spliced ​​model curve and the estimated frequency range.

[0116] It should be understood that Figure 10 The various modules of the device 1000 shown can be used with reference to Figure 1 The steps in method 100 described correspond to each other. Therefore, the operations, features, and advantages described above for method 100 also apply to apparatus 1000 and its included modules. For the sake of brevity, some operations, features, and advantages will not be repeated here.

[0117] While specific functions have been discussed above with reference to specific modules, it should be noted that the functions of the modules discussed herein can be divided into multiple modules, and / or at least some functions of multiple modules can be combined into a single module. The specific actions performed by the modules discussed herein include the specific module itself performing the action, or alternatively, the specific module calling or otherwise accessing another component or module that performs the action (or performs the action in conjunction with the specific module). Therefore, a specific module performing an action can include the specific module performing the action itself and / or another module that performs the action, called or otherwise accessed by the specific module.

[0118] It should also be understood that this article can describe various technologies in the general context of software and hardware components or program modules. The above regarding... Figure 10The various modules described can be implemented in hardware or in hardware in combination with software and / or firmware. For example, these modules can be implemented as computer program code / instructions configured to execute in one or more processors and stored in a computer-readable storage medium. Alternatively, these modules can be implemented as hardware logic / circuit. For example, in some embodiments, one or more of the frequency estimation acquisition unit 1010, model curve construction unit 1020 and model curve stitching unit 1030, and frequency determination unit 1040 can be implemented together in a System on Chip (SoC). The SoC may include an integrated circuit chip (which includes a processor (e.g., a Central Processing Unit (CPU), microcontroller, microprocessor, digital signal processor (DSP), etc.), memory, one or more communication interfaces, and / or one or more components of other circuitry) and may optionally execute received program code and / or include embedded firmware to perform functions.

[0119] According to one aspect of this disclosure, a computer device is also provided, including a memory, a processor, and a computer program stored in the memory. The processor is configured to execute the computer program to implement the steps of any of the method embodiments described above.

[0120] According to one aspect of this disclosure, a non-transitory computer-readable storage medium is also provided, on which a computer program is stored, which, when executed by a processor, implements the steps of any of the method embodiments described above.

[0121] According to one aspect of this disclosure, a computer program product is also provided, which includes a computer program that, when executed by a processor, implements the steps of any of the method embodiments described above.

[0122] In the following text, combined with Figure 11 Illustrative examples describing such computer devices, non-transitory computer-readable storage media, and computer program products.

[0123] Figure 11 An example configuration of computer device 1100 that can be used to implement the methods described in this disclosure is shown. The microwave frequency measuring device 1000 described above can be implemented wholly or at least partially by computer device 1100 or similar devices or systems.

[0124] Computer device 1100 can be a variety of different types of devices. Examples of computer device 1100 include, but are not limited to: desktop computers, server computers, laptop or netbook computers, mobile devices (e.g., tablets, cellular or other wireless phones (e.g., smartphones), notebook computers, mobile stations), wearable devices (e.g., glasses, watches), entertainment devices (e.g., entertainment appliances, set-top boxes communicatively coupled to a display device, game consoles), televisions or other display devices, automotive computers, and so on.

[0125] Computer device 1100 may include at least one processor 1102, memory 1104, communication interfaces(s)1106, display device 1108, other input / output (I / O) devices 1110, and one or more mass storage devices 1112, capable of communicating with each other, such as via system bus 1114 or other suitable connections.

[0126] Processor 1102 may be a single processing unit or multiple processing units, and all processing units may include single or multiple computing units or multiple cores. Processor 1102 may be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, state machines, logic circuits, and / or any device that manipulates signals based on operating instructions. Among other capabilities, processor 1102 may be configured to acquire and execute computer-readable instructions stored in memory 1104, mass storage device 1112, or other computer-readable media, such as program code of operating system 1116, program code of application program 1118, program code of other program 1120, etc.

[0127] Memory 1104 and mass storage device 1112 are examples of computer-readable storage media for storing instructions executed by processor 1102 to perform the various functions described above. For example, memory 1104 may generally include both volatile and non-volatile memory (e.g., RAM, ROM, etc.). Furthermore, mass storage device 1112 may generally include hard disk drives, solid-state drives, removable media, including external and removable drives, memory cards, flash memory, floppy disks, optical disks (e.g., CDs, DVDs), storage arrays, network-attached storage, storage area networks, etc. Both memory 1104 and mass storage device 1112 may be collectively referred to herein as memory or computer-readable storage media, and may be non-transitory media capable of storing computer-readable, processor-executable program instructions as computer program code, which may be executed by processor 1102 as a specific machine configured to perform the operations and functions described in the examples herein.

[0128] Multiple programs can be stored on mass storage device 1112. These programs include operating system 1116, one or more application programs 1118, other programs 1120, and program data 1122, and they can be loaded into memory 1104 for execution. Examples of such application programs or program modules may include, for example, computer program logic (e.g., computer program code or instructions) for implementing the following components / functions: frequency estimation acquisition unit 1010, model curve construction unit 1020 and model curve stitching unit 1030 and frequency determination unit 1040 and / or other embodiments described herein.

[0129] Although Figure 11 The modules 1116, 1118, 1120, and 1122, or portions thereof, are illustrated as being stored in memory 1104 of computer device 1100, but modules 1116, 1118, 1120, and 1122, or portions thereof, may be implemented using any form of computer-readable medium accessible by computer device 1100. As used herein, “computer-readable medium” includes at least two types of computer-readable media: computer-readable storage media and communication media.

[0130] Computer-readable storage media include volatile and non-volatile, removable and non-removable media implemented by any method or technology for storing information such as computer-readable instructions, data structures, program modules, or other data. Computer-readable storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, DVD, or other optical storage devices, magnetic cassettes, magnetic tapes, disk storage devices or other magnetic storage devices, or any other non-transmission medium that can be used to store information for access by a computer device. In contrast, communication media can embody computer-readable instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms. Computer-readable storage media as defined herein do not include communication media.

[0131] One or more communication interfaces 1106 are used for exchanging data with other devices, such as via a network, direct connection, etc. Such communication interfaces can be one or more of the following: any type of network interface (e.g., a network interface card (NIC)), wired or wireless (such as IEEE 802.11 Wireless LAN (WLAN)) wireless interface, Wi-MAX interface, Ethernet interface, Universal Serial Bus (USB) interface, cellular network interface, Bluetooth. TMInterfaces, near field communication (NFC) interfaces, etc. Communication interface 1106 can facilitate communication across various network and protocol types, including wired networks (e.g., LAN, cable, etc.) and wireless networks (e.g., WLAN, cellular, satellite, etc.), the Internet, etc. Communication interface 1106 can also provide communication with external storage devices (not shown) such as storage arrays, network-attached storage, storage area networks, etc.

[0132] In some examples, a display device 1108, such as a monitor, may be included for displaying information and images to the user. Other I / O devices 1110 may be devices that receive various inputs from the user and provide various outputs to the user, and may include touch input devices, gesture input devices, cameras, keyboards, remote controls, mice, printers, audio input / output devices, and so on.

[0133] The technologies described herein can be supported by these various configurations of computer device 1100, and are not limited to specific examples of the technologies described herein. For example, the functionality can also be implemented wholly or partially on a “cloud” using a distributed system. A cloud includes and / or represents a platform for resources. The platform abstracts the underlying functionality of the cloud’s hardware (e.g., servers) and software resources. Resources may include applications and / or data that can be used when performing computational processing on a server remote from computer device 1100. Resources may also include services provided via the Internet and / or via subscriber networks such as cellular or Wi-Fi networks. The platform can abstract resources and functionality to connect computer device 1100 to other computer devices. Therefore, the implementation of the functionality described herein can be distributed throughout the cloud. For example, the functionality can be implemented partly on computer device 1100 and partly through a platform that abstracts the functionality of the cloud.

[0134] Although this disclosure has been described and illustrated in detail in the accompanying drawings and the foregoing description, such description and illustration should be considered illustrative and suggestive, not restrictive; this disclosure is not limited to the disclosed embodiments. By studying the drawings, the disclosure, and the appended claims, those skilled in the art will be able to understand and implement variations of the disclosed embodiments in practice with respect to the claimed subject matter. In the claims, the word "comprising" does not exclude other elements or steps not listed, the indefinite article "a" or "an" does not exclude a plurality, the term "a plurality" means two or more, and the term "based on" should be interpreted as "at least partially based on". The mere fact that certain measures are recited in mutually different dependent claims does not indicate that a combination of these measures cannot be beneficial.

Claims

1. A microwave frequency measurement method, comprising: An estimated frequency range of a microwave signal to be measured is obtained, wherein the estimated frequency range is obtained by measuring the microwave signal to be measured using a first measurement structure, the first measurement structure determining the measurement bandwidth, and the measurement bandwidth being associated with a model curve of a first amplitude comparison equation constructed based on the first measurement structure. A model curve for constructing a second amplitude comparison equation based on a second measurement structure different from the first measurement structure, and a model curve for constructing a third amplitude comparison equation based on a third measurement structure different from the first and second measurement structures, wherein each of the second and third measurement structures is constructed by programming on a programmable optical network; Within the measurement bandwidth of the first measurement structure, the portion of the model curve of the second amplitude comparison equation with a slope greater than a predetermined threshold is spliced ​​with the portion of the model curve of the third amplitude comparison equation with a slope greater than the predetermined threshold to obtain a spliced ​​model curve; and Based on the spliced ​​model curve and the estimated frequency range, the frequency of the microwave signal to be measured is determined.

2. The method according to claim 1, wherein, The first measurement structure is constructed by programming on the programmable optical network.

3. The method according to claim 1 or 2, wherein, The first measurement structure includes two output ports that provide complementary power responses, and the model curve of the first amplitude comparison equation indicates the ratio of the complementary power responses provided at the two output ports at different frequencies within the measurement bandwidth.

4. The method according to claim 3, wherein, The measurement of the microwave signal under test using the first measurement structure includes: The microwave signal to be tested is modulated onto an optical signal; The modulated optical signal is input to the first measurement structure to obtain the ratio of the complementary power responses provided at the two output ports; and Based on the ratio of complementary power responses and the model curve of the first amplitude comparison equation, the frequency estimate of the microwave signal under test is determined. The estimated frequency range is determined based on the frequency estimate.

5. The method according to claim 4, wherein, The modulation includes carrier-suppressed double-sideband modulation or carrier-suppressed single-sideband modulation.

6. The method according to claim 4 or 5, wherein, The first measuring structure is adjusted such that the resonant wavelength of the first measuring structure is consistent with the center wavelength of the optical signal.

7. The method according to claim 1 or 2, wherein, The model curve of the first amplitude comparison equation is monotonic.

8. The method according to claim 1 or 2, wherein, Each of the second and third measurement structures includes two output ports that provide complementary power responses, and each of the model curves of the second and third amplitude comparison equations indicates the ratio of the corresponding complementary power responses provided at the corresponding two output ports at different frequencies.

9. The method according to claim 8, wherein, The model curve for constructing the second amplitude comparison equation based on the second measurement structure includes: inputting an optical signal modulated by carrier-suppressed double-sideband using sample microwave signals with the different frequencies to the second measurement structure to obtain the ratio of the complementary power responses provided at the two output ports of the second measurement structure at the different frequencies, wherein the wavelength of the minimum power value in the complementary power response coincides with the carrier wavelength of the optical signal, and The model curve for constructing the third amplitude comparison equation based on the third measurement structure includes: inputting the optical signal, which is a carrier-suppressed double-sideband modulated sample microwave signal with the different frequencies, into the third measurement structure to obtain the ratio of the complementary power responses provided at the two output ports of the third measurement structure at the different frequencies, wherein the wavelength of the maximum power in the complementary power response is consistent with the carrier wavelength of the optical signal.

10. The method according to claim 8, wherein, Determining the frequency of the microwave signal to be measured includes: The microwave signal to be tested is modulated onto an optical signal; The modulated optical signal is input to the second or third measurement structure to obtain the ratio of the corresponding complementary power responses provided at the respective two output ports; and The frequency of the microwave signal under test is determined based on the ratio of the complementary power responses and the portion of the estimated frequency range selected on the spliced ​​model curve.

11. The method according to claim 1 or 2, wherein, The step of concatenating the portion of the model curve of the second amplitude comparison equation with the portion of the model curve of the third amplitude comparison equation with the slope greater than the predetermined threshold includes: The portion of the model curve of the second amplitude comparison equation and the model curve of the third amplitude comparison equation with a slope lower than or equal to the predetermined threshold is replaced with the portion of the other at the same frequency with a slope greater than the predetermined threshold.

12. The method according to claim 1 or 2, wherein, Each of the first measurement structure, the second measurement structure, and the third measurement structure includes a two-port power complementary device, wherein the two-port power complementary device includes a Mach-Zehnder interferometer or a microring resonator.

13. The method according to claim 1 or 2, wherein, The third measurement structure is obtained by adjusting the phase-shifting unit in the second measurement structure to perform phase shifting, or by programming the programmable optical network to reconstruct a new optical mesh structure.

14. A microwave frequency measuring device, comprising: The frequency estimation acquisition unit is configured to acquire an estimated frequency range of a microwave signal under test, wherein the estimated frequency range is obtained by measuring the microwave signal under test using a first measurement structure, the first measurement structure determining the measurement bandwidth, and the measurement bandwidth being associated with a model curve of a first amplitude comparison equation constructed based on the first measurement structure. The model curve construction unit is configured to construct a model curve of a second amplitude comparison equation based on a second measurement structure different from the first measurement structure, and to construct a model curve of a third amplitude comparison equation based on a third measurement structure different from the first measurement structure and the second measurement structure, wherein each of the second measurement structure and the third measurement structure is constructed by programming on a programmable optical network; A model curve stitching unit is configured to stitch together, within the measurement bandwidth of the first measurement structure, the portion of the model curve of the second amplitude comparison equation with a slope greater than a predetermined threshold and the portion of the model curve of the third amplitude comparison equation with a slope greater than the predetermined threshold, to obtain a stitched model curve; and The frequency determination unit is configured to determine the frequency of the microwave signal under test based on the spliced ​​model curve and the estimated frequency range.

15. A computer device, comprising: At least one processor; as well as At least one memory on which a computer program is stored, When the computer program is executed by the at least one processor, it causes the at least one processor to perform the method according to any one of claims 1 to 13.

16. A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, causes the processor to perform the method according to any one of claims 1 to 13.

17. A computer program product comprising a computer program that, when executed by a processor, causes the processor to perform the method according to any one of claims 1 to 13.

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