Time domain characterization and modeling method for S parameter model of microwave photonic device, medium and device

Abstract

The invention provides a time domain characterization and modeling method of an S parameter model of a microwave photonic device, a medium and a device. The method comprises the following steps: completing frequency response data interpolation of an FIR (Finite Impulse Response) digital filter based on an S parameter; designing an adaptive order FIR digital filter; time domain convolution of the input signal is completed based on an FIR digital filter; and correcting the delay amount of the output signal. Compared with an original frequency domain S parameter model, the FIR digital filter model constructed by the method directly calculates the input signal in the time domain, so that repeated time-frequency transformation in each simulation step is avoided, the simulation efficiency of the broadband microwave photon array system link time domain signal flow can be effectively improved, and the simulation efficiency of the broadband microwave photon array system link time domain signal flow is improved. Moreover, time domain signal aliasing caused by frequency domain discretization can be avoided, meanwhile, the FIR digital filter also ensures that the signals do not generate phase distortion, and compared with a traditional method, the method has obvious advantages.

Description

Technical Field

[0001] The present invention relates to the field of microwave, optics, microwave photonic modeling and simulation, and in particular to a time domain characterization and modeling method, medium and device for an S parameter model of a microwave photonic device. Background Art

[0002] The link simulation analysis of broadband microwave photonic array systems involves the full connection of antennas, microwaves, optoelectronics, digital and other parts. The performance evaluation of microwave photonic array systems is achieved based on the complex combination and parameter control of various device models. The device model is the key to determining the efficient and accurate analysis and evaluation of microwave photonic systems. In addition, it is difficult to achieve full-link analysis and evaluation of microwave photonic array systems by relying on traditional single-discipline modeling and simulation methods, because microwave photonic array systems need to implement time-domain simulation driven by signal flow, while device models constructed by disciplines such as antennas and microwaves based on three-dimensional electromagnetic field finite element analysis or frequency-domain circuit analysis cannot be directly called by system links. Therefore, it is urgent to build a microwave photonic device model that meets the time-domain signal flow simulation requirements of microwave photonic array systems.

[0003] Among many device modeling methods, the multi-port network S parameter model is a model characterization method widely used in passive devices such as microwave, optical, microwave photonics, or small signal active devices. It has the advantages of easy parameter acquisition and high computational efficiency. The device model based on measured S parameters has better simulation accuracy than the ideal device model based on formulas. Although the scattering parameter S parameter characterizes the mapping relationship between the incident voltage wave and the reflected voltage wave at the port, from the perspective of signal flow, the S parameter also reflects the frequency domain response of the device to the input signal and can be regarded as the frequency domain circuit model of the device.

[0004] If the S parameter model is directly called without processing in the simulation of the time domain signal flow of the microwave photon array system link, the input signal needs to be transformed into a time-frequency signal at each time step of the simulation: first, the input time domain signal is converted into a frequency domain signal, and then the frequency domain signal calculated by the device model is converted into a time domain signal output. However, broadband microwave photon array systems often contain a large number of devices, and frequent time-frequency transformations not only seriously restrict the efficiency of system simulation, but also may cause time domain signal aliasing due to frequency domain discretization. Summary of the invention

[0005] In view of the above-mentioned problems, the present invention provides a time domain characterization and modeling method, medium and device of the S parameter model of a microwave photonic device. The devices characterized by the S parameters are regarded as filters. The S parameters determine the expected frequency response of the filter. An FIR digital filter is constructed based on the expected frequency response, thereby realizing time domain convolution and delay correction of the input signal.

[0006] The present invention provides a method for time domain characterization and modeling of an S parameter model of a microwave photonic device, comprising the following steps:

[0007] Step 1: Complete the FIR digital filter frequency response data interpolation based on S parameters;

[0008] Step 2: Adaptive order FIR digital filter design;

[0009] Step 3: Complete the time domain convolution of the input signal based on the FIR digital filter;

[0010] Step 4: Correct output signal delay.

[0011] Furthermore, in step 1, the analog frequency of the original S parameter needs to be mapped to the digital angular frequency, and the frequency response data interpolation needs to be completed.

[0012] Further, mapping the analog frequency of the original S parameter to the digital angular frequency includes:

[0013] Assume that the sampling rate of the system simulation is f s , and the maximum frequency of the device S parameter is f max , then the device sampling rate f that prevents signal distortion and aliasing within the device operating frequency band is obtained s component for:

[0014] f s component =max{f s ,2·f max} (1)

[0015] Therefore, based on formula (2), the analog frequency f of the S parameter is mapped to the digital angular frequency of the FIR digital filter:

[0016]

[0017] Wherein, ω is the digital angular frequency of the FIR digital filter.

[0018] Further, the completing the FIR digital filter frequency response data interpolation comprises:

[0019] The original S parameters are linearly interpolated to obtain the frequency response of the digital angular frequency in the range of [0,π], and then expanded according to the conjugate symmetry principle to obtain the frequency response of the digital angular frequency in the range of (π,2π], thereby obtaining the complete frequency response of the FIR digital filter.

[0020] Furthermore, with S 21 Taking the parameters as an example, the completion of the FIR digital filter frequency response data interpolation includes the following process:

[0021] In order to construct the N-order FIR digital filter based on the frequency sampling method, the number of expected frequency response sample points is required to be equal to the filter length N, and they are evenly spaced on the unit circle, and the frequency response corresponding to the sample points is about Conjugate symmetry;

[0022] The digital angular frequency ω is calculated in the range of [0,π] If the sample points to be interpolated are equal Calculated by formula (4):

[0023]

[0024] The magnitude response of the FIR digital filter corresponding to the interpolation sample point Calculated by formula (5):

[0025]

[0026] Among them, ω Interp1 ,ω Interp2 , According to formula (6), we can get:

[0027]

[0028] Linear phase response of the FIR digital filter corresponding to the interpolation sample point Calculated by formula (7):

[0029]

[0030] Based on equations (4), (5) and (7), the frequency response of the FIR digital filter in the range [0,π] is:

[0031]

[0032] According to the FIR digital filter frequency response Based on the characteristics of conjugate symmetry, the frequency response in the range of (π, 2π] is obtained as follows:

[0033]

[0034] Combining equations (8) and (9) together forms the complete frequency response of the FIR digital filter in the range of [0,2π], as shown in equation (10):

[0035]

[0036] Furthermore, in step 2, the design of the adaptive order FIR digital filter includes:

[0037] A, set an initial value for the order N of the FIR digital filter;

[0038] B, based on step 1, complete the frequency response data interpolation of the N-order FIR digital filter;

[0039] C, performing an inverse discrete Fourier transform on the frequency response of the FIR digital filter, thereby obtaining the impulse response of the FIR digital filter in the time domain, that is, the coefficient vector of the FIR digital filter;

[0040] D. Use the original S parameters to verify the accuracy of the amplitude frequency response of the designed N-order FIR digital filter. If it does not meet the expected simulation accuracy, gradually increase the order N and repeat steps A to C; if it meets the expected accuracy requirements, end.

[0041] Furthermore, the time domain convolution of the input signal based on the FIR digital filter includes: assuming that the signal stream length of each simulation step is M, after performing time domain convolution calculation with the N-order FIR digital filter, an output signal stream with a length of M+N-1 will be obtained.

[0042] Further, the output signal delay correction includes: Initially, M data points are read, and the delay amount can be corrected and the effective part of the output signal can be extracted.

[0043] The present invention also provides a computer terminal storage medium storing computer terminal executable instructions, wherein the computer terminal executable instructions are used to execute the above-mentioned time domain characterization and modeling method of the microwave photonic device S parameter model.

[0044] The present invention also provides a computing device, comprising:

[0045] At least one processor; and a memory in communication with the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can perform the time domain characterization and modeling method of the S parameter model of the microwave photonic device.

[0046] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0047] In the present invention, a FIR digital filter that meets the S parameter frequency response of the device is constructed, and then time domain convolution of the input signal is implemented based on the FIR digital filter. Compared with the original frequency domain S parameter model, the FIR digital filter model constructed by the present invention directly calculates the input signal in the time domain, avoiding repeated time-frequency transformation in each simulation step. It can not only effectively improve the simulation efficiency of the time domain signal flow of the broadband microwave photonic array system link, but also avoid the aliasing of the time domain signal caused by the discretization of the frequency domain. At the same time, the FIR digital filter also ensures that the signal will not be phase distorted, which has obvious advantages over the traditional method. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 The flowchart is a time domain characterization and modeling method of the S parameter model of a microwave photonic device in an embodiment of the present invention.

[0049] Figure 2 It is a comparison diagram of the frequency response of the FIR filter model designed by the present invention and the original S21 parameters of the low-pass filter in the embodiment.

[0050] Figure 3 4 is a waveform comparison diagram of the output signal and the input signal of the low-pass filter model constructed based on the present invention in the embodiment.

[0051] Figure 4 Graph showing the power spectrum of the low-pass filter input signal in an embodiment of the present invention.

[0052] Figure 5 Graph showing the power spectrum of the output signal of the low-pass filter in an embodiment of the present invention.

[0053] Figure 6 It is a comparison diagram of the frequency response of the FIR filter model designed based on the present invention and the original S21 parameters of the low noise amplifier in the embodiment.

[0054] Figure 7 It is a waveform comparison diagram of the output signal and the input signal of the low noise amplifier model constructed based on the present invention in the embodiment.

[0055] Figure 8 This is a power spectrum diagram of the input signal of the low noise amplifier in an embodiment of the present invention.

[0056] Fig. 9 This is a power spectrum diagram of the output signal of the low noise amplifier in an embodiment of the present invention. DETAILED DESCRIPTION

[0057] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0058] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0059] Example

[0060] like Figure 1 As shown, this embodiment proposes a time domain characterization and modeling method of an S parameter model of a microwave photonic device, comprising the following steps:

[0061] Step 1: Complete FIR digital filter frequency response data interpolation based on S parameters

[0062] Since the S parameter model is usually represented by analog frequency, and the FIR digital filter is usually represented by digital angular frequency, in order to construct the FIR digital filter, it is first necessary to map the analog frequency of the original S parameter to the digital angular frequency and complete the frequency response data interpolation.

[0063] For a broadband microwave photonic array system, assuming that the sampling rate of the system simulation is f s , and the maximum frequency of the device S parameter is f max , we can get the device sampling rate f that prevents signal distortion and aliasing within the device operating frequency band. s component for:

[0064] f s component =max{f s ,2·f max} (1)

[0065] Therefore, based on equation (2), the analog frequency f of the S parameter is mapped to the digital angular frequency ω of the FIR digital filter:

[0066]

[0067] At this time, the original S parameter can be expressed as formula (3), where L is the number of ports of the device.

[0068]

[0069] In order to adapt to the arbitrary frequency response characteristics of various types of devices such as microwave, optical, and microwave photonics, the present invention constructs an FIR digital filter with an odd order N to approximate the frequency response of the original S parameter. 21 As an example, the S parameter modeling method of other dimensions of the S parameter matrix in formula (3) is the same as S 21 Consistent.

[0070] In order to construct the N-order FIR digital filter based on the frequency sampling method, the number of expected frequency response sample points is required to be equal to the filter length N, and they are evenly spaced on the unit circle, and the frequency response corresponding to the sample points is about Conjugate symmetry.

[0071] The present invention firstly based on the original S 21 The parameters are linearly interpolated to obtain the frequency response of the digital angular frequency in the range of [0,π], and then expanded according to the conjugate symmetry principle to obtain the frequency response of the digital angular frequency in the range of (π,2π], thereby obtaining the complete frequency response of the FIR digital filter.

[0072] The digital angular frequency ω is calculated in the range of [0,π] If the sample points to be interpolated are equal It can be calculated by formula (4):

[0073]

[0074] The magnitude response of the FIR digital filter corresponding to the interpolation sample point It can be calculated by formula (5):

[0075]

[0076] Among them, ω Interp1 ,ω Interp2 , According to formula (6), we can get:

[0077]

[0078] Linear phase response of the FIR digital filter corresponding to the interpolation sample point It can be calculated by formula (7):

[0079]

[0080] Based on equations (4), (5) and (7), the frequency response of the FIR digital filter in the range [0,π] can be obtained as follows:

[0081]

[0082] According to the FIR digital filter frequency response The characteristics of conjugate symmetry can be used to obtain the frequency response in the range of (π, 2π] based on equation (9):

[0083]

[0084] Combining equations (8) and (9) together forms the complete frequency response of the FIR digital filter in the range of [0,2π], as shown in equation (10):

[0085]

[0086] The above is based on S 21 Take the interpolation method as an example to illustrate that other ports S can be obtained by similar methods. ij The frequency response corresponding to the parameter.

[0087] Step 2: Adaptive order FIR digital filter design

[0088] The order of the FIR digital filter directly affects the accuracy of its approximation to the expected frequency response. Although increasing the order of the filter can effectively improve the accuracy, it will also increase the amount of calculation. Therefore, it is necessary to find the minimum filter order that meets the expected accuracy requirements.

[0089] The process of designing an adaptive order FIR digital filter is as follows:

[0090] A, set an initial value for the order N of the FIR digital filter;

[0091] B, based on step 1, complete the frequency response data interpolation of the N-order FIR digital filter;

[0092] C, the FIR digital filter frequency response obtained by formula (9) is subjected to inverse discrete Fourier transform to obtain the impulse response of the FIR digital filter in the time domain, that is, the coefficient vector of the FIR digital filter, as shown in formula (11):

[0093] h=[b 0 ,b 1 ,…,b N-1 ]=IDFT[H] (i=0,1,…,N-1) (11)

[0094] D. Use the original S parameters to verify the accuracy of the amplitude frequency response of the designed N-order FIR digital filter. If it does not meet the expected simulation accuracy, gradually increase the order N and repeat steps A to C; if it meets the expected accuracy requirements, end.

[0095] Step 3: Complete the time domain convolution of the input signal based on the FIR digital filter

[0096] In each simulation step of the broadband microwave photonic array system, time domain signal stream data with a certain length is transmitted between microwave photonic devices on the link. The length of the signal stream is determined by the system sampling rate and the simulation time window.

[0097] The calculation process of the input signal and the device S parameter frequency domain model can be equivalent to the time domain convolution calculation process of the input signal and the device FIR digital filter model. Assuming that the signal stream length of each simulation step is M, after the time domain convolution calculation with the N-order FIR digital filter, an output signal stream with a length of M+N-1 will be obtained, in which each element can be calculated by formula (12):

[0098]

[0099] Step 4: Output signal delay correction

[0100] The input signal stream of length M is convolved in the time domain with the N-order FIR digital filter to obtain an output signal stream of length M+N-1, in which only the data of the same length as the input signal is the valid part of the output signal. In addition, the group delay of the N-order FIR digital filter is calculated by formula (13):

[0101]

[0102] From formula (13), we can see that the N-order FIR digital filter will produce The delay of the sampling interval is therefore Initially, M data points are read, and the delay amount can be corrected and the effective part of the output signal can be extracted.

[0103] Example: 1: A low-pass filter

[0104] The S parameter frequency range of a low-pass filter is 100MHz~18GHz, the operating frequency band is 0.1~2GHz, and the input signal is y(t)=sin(2πf 1 t)+sin(2πf 2 t), f 1 =2GHz, f 2 =14.4GHz, the system sampling rate is 36GHz, and the simulation time window is 28.4ns. It can be calculated that the length of the input signal stream for each simulation step is 1024.

[0105] Step 1: Interpolate the frequency response data of the FIR digital filter based on S parameters

[0106] According to the original S 21The parameters are linearly interpolated to obtain the frequency response of the digital angular frequency in the range of [0,π], and then the frequency response of the digital angular frequency in the range of (π,2π] is obtained according to the conjugate symmetry principle, thereby obtaining the complete frequency response of the FIR digital filter. The initial value of the order of the FIR digital filter is set to 51, and the digital angular frequency ω is divided into 25 equal parts in the range of [0,π], then the interpolation sample point [ω 0 ,ω 1 ,…,ω 25 ] can be calculated by formula (4).

[0107] Then, the amplitude response and phase response in the range of [0,π] are calculated by equations (5), (6) and (7), and the frequency response in the range of (π,2π] is obtained by equation (9), and the complete frequency response is obtained as shown in equation (10).

[0108] Step 2: Adaptive order FIR digital filter design

[0109] Set the initial value of the FIR digital filter order to 51 and the expected accuracy to 10 -2 The FIR digital filter was designed, and the accuracy of the 51-order FIR digital filter was verified using the amplitude frequency response of the original S parameters. It was found that the expected accuracy was not met, and the order was gradually increased to 101. After verification, the accuracy met expectations. The comparison results of the frequency response curves of the original S parameters and the designed 101-order FIR digital filter are shown in the figure. Figure 2 shown.

[0110] Step 3: Complete the time domain convolution of the input signal based on the FIR digital filter

[0111] Based on the FIR digital filter obtained in step 2, the input signal is convolved in time domain. The length of the signal stream in each simulation step is 1024. After time domain convolution calculation with the 101-order FIR digital filter, an output signal stream with a length of 1124 is obtained, where each element can be calculated by formula (12).

[0112] Step 4: Output signal delay correction

[0113] The length of the input signal stream is 1024, and the order of the matched FIR digital filter is 101. After time domain convolution, the output signal stream with a length of 1124 is obtained. The group delay of the 101-order FIR digital filter is calculated by formula (13) to be 50, that is, the 101-order FIR digital filter will produce a delay of 50 sampling intervals for the input signal. Therefore, starting from the 51st in the output signal stream with a length of 1124, reading 1024 data points can realize the correction of the delay and extract the effective part of the output signal. The waveform comparison of the output signal and the input signal is as follows: Figure 3 shown. Figure 4 , Figure 5 The power spectrum shown shows that the high-frequency signal components in the output signal are effectively filtered.

[0114] Example 2: A low noise amplifier

[0115] The S parameter frequency range of a low noise amplifier is 1000MHz~26.5GHz, the operating frequency band is 0.7~5GHz, and the input signal is y(t)=sin(2πf 1 t)+sin(2πf 2 t), f 1 =3GHz, f 2 =9GHz, the system sampling rate is 53GHz, and the simulation time window is 19.3ns. It can be calculated that the length of the input signal stream for each simulation step is 1024.

[0116] Step 1: Interpolate the frequency response data of the FIR digital filter based on S parameters

[0117] According to the original S 21 The parameters are linearly interpolated to obtain the frequency response of the digital angular frequency in the range of [0,π], and then the frequency response of the digital angular frequency in the range of (π,2π] is obtained according to the conjugate symmetry principle, thereby obtaining the complete frequency response of the FIR digital filter. The initial value of the order of the FIR digital filter is set to 51, and the digital angular frequency ω is divided into 25 equal parts in the range of [0,π], then the interpolation sample point [ω 0 ,ω 1 ,…,ω 25 ] can be calculated by formula (4).

[0118] Then, the amplitude response and phase response in the range of [0,π] are calculated by equations (5), (6) and (7), and the frequency response in the range of (π,2π] is obtained by equation (9), and the complete frequency response is obtained as shown in equation (10).

[0119] Step 2: Adaptive order FIR digital filter design

[0120] Set the initial value of the FIR digital filter order to 51 and the expected accuracy to 10 -2 The digital filter was designed, and the accuracy of the 51-order FIR digital filter was verified using the amplitude frequency response of the original S parameters. It was found that the expected accuracy was not met, and the order was gradually increased to 201. After verification, the accuracy met expectations. The comparison results of the frequency response curves of the original S parameters and the designed 201-order FIR digital filter are shown in the figure. Figure 6 shown.

[0121] Step 3: Complete the time domain convolution of the input signal based on the FIR digital filter

[0122] Based on the FIR digital filter obtained in step 2, the input signal is convolved in time domain. The length of the signal stream in each simulation step is 1024. After time domain convolution calculation with the 201-order FIR digital filter, an output signal stream with a length of 1224 is obtained, where each element can be calculated by formula (12).

[0123] Step 4: Output signal delay correction

[0124] The length of the input signal stream is 1024, and the order of the matched FIR digital filter is 201. After time domain convolution, the output signal stream with a length of 1224 is obtained. The group delay of the 201-order FIR digital filter is calculated by formula (13) to be 100, that is, the 201-order FIR digital filter will produce a delay of 100 sampling intervals for the input signal. Therefore, starting from the 101th in the output signal stream with a length of 1224, reading 1024 data points can realize the correction of the delay and extract the effective part of the output signal. The waveform comparison of the output signal and the input signal is as follows: Figure 7 shown. Figure 8 , Fig. 9 The power spectrum shown shows that there is a clear difference between the amplification factor within the operating frequency band and the amplification factor outside the operating frequency band.

[0125] In addition, in some embodiments, a computer terminal storage medium is provided, which stores computer terminal executable instructions, and the computer terminal executable instructions are used to execute the time domain characterization and modeling method of the microwave photonic device S parameter model as described in the above embodiments. Examples of computer storage media include magnetic storage media (e.g., floppy disks, hard disks, etc.), optical recording media (e.g., CD-ROMs, DVDs, etc.), or memories, such as memory cards, ROMs, or RAMs, etc. Computer storage media can also be distributed on network-connected computer systems, such as application stores.

[0126] In addition, in some embodiments, a computing device is proposed, comprising: at least one processor; and a memory connected to the at least one processor in communication; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can perform the time domain characterization and modeling method of the microwave photonic device S parameter model as described in the above embodiments. Examples of computing devices include PCs, tablet computers, smart phones, or PDAs.

[0127] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A time domain characterization and modeling method for an S parameter model of a microwave photonic device, characterized in that: The steps include: Step 1: Complete the FIR digital filter frequency response data interpolation based on S parameters; Step 2: Adaptive order FIR digital filter design; Step 3: Complete the time domain convolution of the input signal based on the FIR digital filter; Step 4: Output signal delay correction.

2. The method for time domain characterization and modeling of the S parameter model of a microwave photonic device according to claim 1, characterized in that: In step 1, the analog frequency of the original S parameter needs to be mapped to the digital angular frequency and the frequency response data interpolation needs to be completed.

3. The method for time domain characterization and modeling of the S parameter model of a microwave photonic device according to claim 2, characterized in that: Mapping the analog frequency of the original S parameter to the digital angular frequency includes: Assume that the sampling rate of the system simulation is f s , and the maximum frequency of the device S parameter is f max , then the device sampling rate f that prevents signal distortion and aliasing within the device operating frequency band is obtained s component for: f s component =max{f s ,2·f max } (1) Therefore, based on formula (2), the analog frequency f of the S parameter is mapped to the digital angular frequency of the FIR digital filter: Wherein, ω is the digital angular frequency of the FIR digital filter.

4. The method for time domain characterization and modeling of the S parameter model of a microwave photonic device according to claim 3, characterized in that: The method of completing the FIR digital filter frequency response data interpolation comprises: The original S parameters are linearly interpolated to obtain the frequency response of the digital angular frequency in the range of [0,π], and then expanded according to the conjugate symmetry principle to obtain the frequency response of the digital angular frequency in the range of (π,2π], thereby obtaining the complete frequency response of the FIR digital filter.

5. The method for time domain characterization and modeling of the S parameter model of a microwave photonic device according to claim 4, characterized in that: S 21 Taking the parameters as an example, the completion of the FIR digital filter frequency response data interpolation includes the following process: In order to construct the N-order FIR digital filter based on the frequency sampling method, the number of expected frequency response sample points is required to be equal to the filter length N, and they are evenly spaced on the unit circle, and the frequency response corresponding to the sample points is about Conjugate symmetry; The digital angular frequency ω is calculated in the range of [0,π] If the sample points to be interpolated are equal Calculated by formula (4): The magnitude response of the FIR digital filter corresponding to the interpolation sample point Calculated by formula (5): Among them, ω Interp1 ,ω Interp2 , According to formula (6), we can get: Linear phase response of the FIR digital filter corresponding to the interpolation sample point Calculated by formula (7): Based on equations (4), (5) and (7), the frequency response of the FIR digital filter in the range [0,π] is: According to the FIR digital filter frequency response Based on the characteristics of conjugate symmetry, the frequency response in the range of (π, 2π] is obtained as follows: Combining equations (8) and (9) together forms the complete frequency response of the FIR digital filter in the range of [0,2π], as shown in equation (10):

6. The method for time domain characterization and modeling of the S parameter model of a microwave photonic device according to claim 1, characterized in that: In step 2, the adaptive order FIR digital filter design includes: A, set an initial value for the order N of the FIR digital filter; B, based on step 1, complete the frequency response data interpolation of the N-order FIR digital filter; C, performing an inverse discrete Fourier transform on the frequency response of the FIR digital filter, thereby obtaining the impulse response of the FIR digital filter in the time domain, that is, the coefficient vector of the FIR digital filter; D. Use the original S parameters to verify the accuracy of the amplitude frequency response of the designed N-order FIR digital filter. If it does not meet the expected simulation accuracy, gradually increase the order N and repeat steps A to C; if it meets the expected accuracy requirements, end.

7. The method for time domain characterization and modeling of the S parameter model of a microwave photonic device according to claim 5, characterized in that: The time domain convolution of the input signal based on the FIR digital filter includes: assuming that the signal stream length of each simulation step is M, after performing time domain convolution calculation with the N-order FIR digital filter, an output signal stream with a length of M+N-1 will be obtained.

8. The method for time domain characterization and modeling of the S parameter model of a microwave photonic device according to claim 7, characterized in that: The output signal delay correction comprises: Initially, M data points are read, and the delay amount can be corrected and the effective part of the output signal can be extracted.

9. A computer terminal storage medium storing computer terminal executable instructions, characterized in that: The computer terminal executable instructions are used to execute the time domain characterization and modeling method of the S parameter model of a microwave photonic device as described in any one of claims 1-8.

10. A computing device, characterized in that: include: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the time domain characterization and modeling method of the S parameter model of a microwave photonic device as described in any one of claims 1 to 8.

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