Method for optimizing S-band low noise amplifier based on HEMT (High Electron Mobility Transistor)

Abstract

The invention relates to the technical field of low-noise amplifier optimization, and discloses an HEMT-based S-band low-noise amplifier optimization method, which comprises the following steps: acquiring working parameters of a low-noise amplifier, and performing one-time performance evaluation on the amplifier by comparing the working parameters with preset standard parameters. And comparing the one-time performance score with a preset performance scoring standard, and determining whether the low-noise amplifier needs to be optimized or not. After it is confirmed that optimization needs to be carried out, relevant optimization parameters are obtained, and simulation verification is carried out through the parameters. And performing secondary performance scoring by obtaining the optimized simulation parameters and comparing the optimized simulation parameters with preset working parameters. And finally, comparing the secondary performance score with a preset performance score standard to confirm whether the low-noise amplifier completes the optimization process or not. According to the steps of key working parameters, one-time performance evaluation, simulation verification, secondary performance scoring and the like, comprehensive evaluation and optimization of the performance of the low-noise amplifier are achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of low noise amplifier optimization, and in particular to an S-band low noise amplifier optimization method based on HEMT. Background Art

[0002] As an electronic amplifier, the main function of a low noise amplifier is to amplify weak RF signals while ensuring that the signal noise does not increase significantly. This device is usually deployed at the front end of the receiver link and plays a key role in many applications such as wireless communication systems, satellite communications and radars. It aims to prevent the signal from being distorted due to noise interference during transmission, thereby effectively improving the system's signal-to-noise ratio and overall operating efficiency.

[0003] However, there are currently multiple challenges in optimizing low-noise amplifiers. The lack of systematic and automated optimization methods makes the optimization process cumbersome and time-consuming. At the same time, existing low-noise amplifier optimization methods mostly rely on the designer's personal experience and repeated manual debugging, which is not only inefficient but also difficult to ensure the consistency of the optimization results. In addition, due to the lack of a unified performance evaluation standard, it is difficult to objectively compare and evaluate different design schemes, which not only increases the difficulty of achieving optimal performance, but also leads to instability in the optimization results.

[0004] In view of this, there is an urgent need to invent a low-noise amplifier optimization technology to solve the problem that the existing technology lacks systematic and automated optimization means, making the optimization process cumbersome and taking a long time to optimize, and because of over-reliance on personal experience, resulting in large differences in optimization results and inconsistent performance evaluation standards, which in turn leads to poor optimization results. Summary of the invention

[0005] In view of this, the present invention proposes an S-band low noise amplifier optimization method based on HEMT, aiming to solve the problem in the current technology that the optimization process is cumbersome and the optimization time is long due to the lack of systematic and automated optimization means, and the optimization results are quite different due to over-reliance on personal experience and the performance evaluation standards are not unified, which leads to poor optimization results.

[0006] The present invention proposes a method for optimizing an S-band low noise amplifier based on HEMT, comprising:

[0007] Acquiring operating parameters of the low noise amplifier when it is working, wherein the operating parameters include scattering parameters, noise parameters and power gain decibels;

[0008] A performance score is performed on the low noise amplifier according to the relationship between the operating parameter and the preset operating parameter, and a relationship between the performance score and the preset performance score is used to determine whether to optimize the low noise amplifier, wherein:

[0009] When it is determined that the low noise amplifier needs to be optimized, obtaining optimization parameters of the low noise amplifier, and performing simulation verification according to the optimization parameters;

[0010] Acquire simulation parameters after simulation verification, and perform secondary performance scoring according to the relationship between the simulation parameters and the preset working parameters;

[0011] Determining whether the low noise amplifier is optimized according to the relationship between the secondary performance score and the preset performance score, wherein:

[0012] When the secondary performance score is lower than the preset performance score, it is determined that the low noise amplifier optimization is not completed, and the optimization parameters are adjusted until the secondary performance score is higher than the preset performance score.

[0013] Further, when a performance score is performed on the low noise amplifier according to the relationship between the operating parameter and the preset operating parameter, it includes:

[0014] Acquire a scattering parameter difference between the scattering parameter and a preset scattering parameter, a noise parameter difference between the noise parameter and a preset noise parameter, and a gain decibel difference between the power gain decibel and a preset power gain decibel;

[0015] A primary performance score between the scattering parameter difference, the noise parameter difference and the gain decibel difference is obtained based on a formula, wherein the formula is as follows:

[0016] Q = (z1*L) + (z2*K) + (z3*J);

[0017] In the formula, Q is the primary performance score, L is the scattering parameter difference, K is the noise parameter difference, J is the gain decibel difference, z1, z2 and z3 are weight coefficients, and the sum of z1, z2 and z3 is 1.

[0018] Further, when it is determined that the low noise amplifier needs to be optimized, the optimization parameters of the low noise amplifier are obtained, and simulation verification is performed according to the optimization parameters, including:

[0019] The scattering parameter difference, noise parameter difference and gain decibel difference are obtained respectively and compared with zero, and the optimization scheme of the low noise amplifier is determined according to the comparison results, wherein:

[0020] When the scattering parameter difference is greater than zero, and the noise parameter difference and the gain decibel difference are both less than zero, it is determined that the gate size and gate index of the high electron mobility transistor of the low noise amplifier need to be adjusted;

[0021] When the noise parameter difference is greater than zero, and the scattering parameter difference and the gain decibel difference are both less than zero, it is determined that the input matching network performance of the low noise amplifier needs to be adjusted;

[0022] When the gain decibel difference is greater than zero, and the scattering parameter difference and the noise parameter difference are both less than zero, it is determined that the output matching network performance of the low noise amplifier needs to be adjusted;

[0023] When the scattering parameter difference, the noise parameter difference and the gain decibel difference are all less than zero, it is determined that the gate size and gate index of the high electron mobility transistor of the low noise amplifier and the input matching network performance and the output matching network performance need to be adjusted.

[0024] Further, when it is determined that the gate size and gate index of the high electron mobility transistor of the low noise amplifier need to be adjusted, it includes:

[0025] Determining a gate width of the high electron mobility transistor according to a placement volume of the high electron mobility transistor inside the low noise amplifier, and acquiring a transistor virtual model between the gate width and each gate length;

[0026] Obtaining scattering parameter differences under each of the transistor virtual models, and removing the transistor virtual models whose scattering parameter differences are greater than zero;

[0027] Obtaining the scattering parameter differences of the transistor virtual models remaining after removing the scattering parameter differences greater than zero, and ranking them in descending order;

[0028] A transistor virtual model corresponding to the scattering parameter difference value ranked first is obtained, and a gate length and a gate width of the transistor virtual model are defined as the adjusted gate size of the high electron mobility transistor.

[0029] Furthermore, when determining the adjusted gate size of the high electron mobility transistor, it includes:

[0030] Acquiring a size difference between the adjusted gate size and the gate size, and determining an adjustment coefficient of the adjusted gate index of the high electron mobility transistor according to a relationship between the size difference and a preset size difference;

[0031] Wherein, a first preset size difference and a second preset size difference are preset, and the first preset size difference is smaller than the second preset size difference;

[0032] When the size difference is less than or equal to the first preset size difference, determining the adjustment coefficient of the adjusted gate index of the high electron mobility transistor to be M3;

[0033] When the size difference is greater than the first preset size difference, and the size difference is less than or equal to the second preset size difference, determining the adjustment coefficient of the adjusted gate index of the high electron mobility transistor to be M2;

[0034] When the size difference is greater than the second preset size difference, determining the adjustment coefficient of the adjusted gate index of the high electron mobility transistor to be M1;

[0035] And M1<M2<M3.

[0036] Further, when it is determined that the input matching network performance of the low noise amplifier needs to be adjusted, it includes:

[0037] Presetting a first preset noise parameter difference and a second preset noise parameter difference, wherein the first preset noise parameter difference is smaller than the second preset noise parameter difference;

[0038] Determining, according to the relationship between the noise parameter difference and each preset noise parameter difference, an adjustment coefficient when adjusting the performance of the input matching network;

[0039] When the noise parameter difference is less than or equal to the first preset noise parameter difference, determining that the adjustment coefficient for adjusting the input matching network performance is N3;

[0040] When the noise parameter difference is greater than the first preset noise parameter difference, and the noise parameter difference is less than or equal to the first preset noise parameter difference, determining that the adjustment coefficient for adjusting the input matching network performance is N2;

[0041] When the noise parameter difference is greater than the second preset noise parameter difference, the adjustment coefficient when the input matching network performance is adjusted is determined to be N1;

[0042] And N1<N2<N3.

[0043] Further, when it is determined that the output matching network performance of the low noise amplifier needs to be adjusted, it includes:

[0044] Presetting a first preset gain decibel difference and a second preset gain decibel difference, wherein the first preset gain decibel difference is smaller than the second preset gain decibel difference;

[0045] Determining a correction coefficient for adjusting the performance of the output matching network according to a relationship between the gain decibel difference and each preset gain decibel difference;

[0046] When the gain decibel difference is less than or equal to the first preset gain decibel difference, the correction coefficient for adjusting the output matching network performance is determined to be B3;

[0047] When the gain decibel difference is greater than the first preset gain decibel difference, and the gain decibel difference is less than or equal to the second preset gain decibel difference, the correction coefficient for adjusting the output matching network performance is determined to be B2;

[0048] When the gain decibel difference is greater than the second preset gain decibel difference, the correction coefficient for adjusting the output matching network performance is determined to be B1;

[0049] Moreover, B1<B2<B3.

[0050] Further, determining whether the optimization of the low noise amplifier is completed according to the relationship between the secondary performance score and the preset performance score includes:

[0051] When the secondary performance score is lower than the preset performance score, it is determined that the low noise amplifier optimization is not completed, and the optimization parameters are adjusted until the secondary performance score is higher than the preset performance score;

[0052] When the secondary performance score is higher than the preset performance score, it is determined that the optimization of the low noise amplifier is completed, and the operating parameters of the low noise amplifier are adjusted according to the optimization parameters.

[0053] Further, when adjusting the operating parameters of the low noise amplifier according to the optimization parameters, it includes:

[0054] Obtaining the difference between the optimization parameters and the operating parameters;

[0055] Determining the correction coefficient for adjusting each of the working parameters according to the relationship between each of the parameter differences and the preset parameter difference;

[0056] Wherein, a first preset parameter difference and a second preset parameter difference are preset, and the first preset parameter difference is smaller than the second preset parameter difference;

[0057] When the parameter difference is less than or equal to the first preset parameter difference, the correction coefficient for adjusting the working parameter is determined to be P1;

[0058] When the parameter difference is greater than the first preset parameter difference, and the parameter difference is less than or equal to the second preset parameter difference, the correction coefficient for adjusting the working parameter is determined to be P2;

[0059] When the parameter difference is greater than the second preset parameter difference, the correction coefficient for adjusting the working parameter is determined to be P3;

[0060] Moreover, P1<P2<P3.

[0061] Compared with the prior art, the beneficial effect of the present invention is that a systematic performance scoring system is established by acquiring and analyzing the working parameters of the amplifier, thereby realizing an objective evaluation of the amplifier performance. Compared with the traditional subjective evaluation method, this evaluation system based on specific parameters is more accurate and credible. By comparing the working parameters with the preset parameters, it is possible to more accurately judge whether the amplifier performance meets the expected requirements, providing a clear direction for subsequent optimization. In the optimization process, a closed-loop feedback mechanism is formed by adopting the method of simulation verification and gradual adjustment of optimization parameters. This means that the optimization effect will be verified after each adjustment, and then further adjustments will be made based on the verification results. This cyclic iterative optimization method effectively ensures the continuous progress of the optimization process, and the optimization results can be accurately evaluated and adjusted at each step. In this way, problems can be discovered and corrected in a timely manner, avoiding deviations and errors that may occur in the optimization process, thereby improving the reliability and stability of the optimization process. At the same time, traditional optimization methods often rely on the experience and subjective judgment of engineers, and are easily affected by personal preferences and experience, resulting in uncertainty in the optimization results. The closed-loop feedback mechanism based on systematic evaluation of working parameters and simulation verification makes the optimization process more objective and scientific, reduces the impact of personal subjective factors on the optimization results, and ensures the objectivity and stability of the optimization process. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0063] Figure 1 A flowchart of a method for optimizing an S-band low noise amplifier based on HEMT provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0064] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art. It should be noted that, in the absence of conflict, the embodiments of the present invention and the features described in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0065] like Figure 1 As shown, in some embodiments of the present application, this embodiment provides an S-band low noise amplifier optimization method based on HEMT, including:

[0066] Step S100: obtaining the working parameters of the low noise amplifier, wherein the working parameters include scattering parameters, noise parameters and power gain decibels.

[0067] Step S200: Perform a performance score on the low noise amplifier according to the relationship between the operating parameters and the preset operating parameters, and determine whether to optimize the low noise amplifier based on the relationship between the performance score and the preset performance score.

[0068] Specifically, when a performance score is performed on a low noise amplifier based on the relationship between the working parameters and the preset working parameters, it includes: a scattering parameter difference between the obtained scattering parameter and the preset scattering parameter, a noise parameter difference between the noise parameter and the preset noise parameter, and a gain decibel difference between the power gain decibel and the preset power gain decibel. A performance score between the scattering parameter difference, the noise parameter difference, and the gain decibel difference is obtained based on a formula, wherein the formula is as follows:

[0069] Q=(z1*L)+(z2*K)+(z3*J).

[0070] Where Q is the primary performance score, L is the scattering parameter difference, K is the noise parameter difference, J is the gain decibel difference, z1, z2 and z3 are weight coefficients, and the sum of z1, z2 and z3 is 1.

[0071] Specifically, according to the relationship between the working parameters and the preset parameters, the differences of the scattering parameters, noise parameters and power gain decibels are calculated, namely, the scattering parameter difference, noise parameter difference and gain decibel difference. These differences reflect the degree of deviation between the amplifier and the ideal state in actual work, and are important indicators for evaluating performance. Then, these differences are substituted into the scoring formula for calculation to obtain a performance score. This score represents the comprehensive performance of the amplifier and can intuitively reflect the degree of deviation from the expected performance. In the scoring calculation, different weight coefficients of different parameters are given different importance. Such a trade-off takes into account the degree of influence of different parameters on the performance of the amplifier. By adjusting the weight coefficient, the performance score can be adjusted more accurately according to the specific situation, so that the score is more in line with the actual situation. Therefore, this scoring method is not only objective and accurate, but also flexible and can meet the evaluation needs in different scenarios.

[0072] It can be seen that the performance of the low noise amplifier is evaluated by calculating the difference between the scattering parameter, noise parameter and power gain decibel and the preset parameters. In the scoring calculation formula, the weight coefficient of each parameter determines its contribution to the performance score. This design makes the scoring more objective and detailed. Through this performance scoring, you can intuitively understand the deviation between the performance of the amplifier and expectations, and then decide whether optimization is needed. Finally, by calculating and weighting the performance of the amplifier, it provides an important reference for optimization decisions. Its technical principle is concise and clear, and can effectively assist engineers in making accurate judgments and decisions during the amplifier design and optimization process.

[0073] Step S300: when it is determined that the low noise amplifier needs to be optimized, the optimization parameters of the low noise amplifier are obtained, and simulation verification is performed according to the optimization parameters.

[0074] Specifically, when it is determined that the low noise amplifier needs to be optimized, the optimization parameters of the low noise amplifier are obtained, and when the optimization parameters are simulated and verified, it includes: comparing the scattering parameter difference, noise parameter difference and gain decibel difference obtained respectively with zero, and determining the optimization scheme of the low noise amplifier according to the comparison result, wherein: when the scattering parameter difference is greater than zero, and the noise parameter difference and the gain decibel difference are both less than zero, it is determined that the gate size and gate index of the high electron mobility transistor of the low noise amplifier need to be adjusted. When the noise parameter difference is greater than zero, and the scattering parameter difference and the gain decibel difference are both less than zero, it is determined that the input matching network performance of the low noise amplifier needs to be adjusted. When the gain decibel difference is greater than zero, and the scattering parameter difference and the noise parameter difference are both less than zero, it is determined that the output matching network performance of the low noise amplifier needs to be adjusted. When the scattering parameter difference, the noise parameter difference and the gain decibel difference are all less than zero, it is determined that the gate size and gate index of the high electron mobility transistor of the low noise amplifier and the input matching network performance and the output matching network performance need to be adjusted.

[0075] It is understandable that when determining the need to optimize the low noise amplifier, the key is to obtain the optimization parameters and perform comparative analysis. By obtaining the comparison of the scattering parameter difference, the noise parameter difference and the gain decibel difference with zero, the deviation of each performance parameter of the amplifier can be accurately evaluated. This comparative analysis is the basis for the formulation of the optimization plan and provides an important reference for subsequent adjustments. Secondly, the optimization plan for different parameter deviations is determined based on the comparison results. By analyzing the combination of the scattering parameter, the noise parameter and the gain decibel difference, targeted optimization measures are determined. For example, when the scattering parameter difference is greater than zero and the noise parameter difference and the gain decibel difference are both less than zero, it is necessary to adjust the gate size and gate index of the high electron mobility transistor to optimize the overall performance of the amplifier. Furthermore, corresponding adjustment plans are formulated for different combinations of noise parameters, gain decibels and scattering parameter differences. The formulation of these plans is based on an in-depth understanding and analysis of the mutual influence between different components and performance indicators of the amplifier. Through targeted adjustments, the performance of the low noise amplifier can be effectively improved to make it more in line with the design requirements. Through in-depth analysis and comparison of working parameters, combined with the understanding of various performance parameters of the amplifier, targeted optimization measures were formulated. This process not only reflects the in-depth understanding of the amplifier performance, but also provides specific and feasible guidelines for actual optimization work.

[0076] Specifically, when determining that the gate size and gate index of the high electron mobility transistor of the low noise amplifier need to be adjusted, it includes: determining the gate width of the high electron mobility transistor according to the placement volume of the high electron mobility transistor inside the low noise amplifier, and obtaining a transistor virtual model between the gate width and each gate length. Obtain the scattering parameter difference under each transistor virtual model, and remove the transistor virtual models with scattering parameter difference greater than zero. Obtain the scattering parameter difference of each transistor virtual model remaining after removing the scattering parameter difference greater than zero, and rank them in reverse order. Obtain the transistor virtual model corresponding to the scattering parameter difference ranked first, and define the gate length and gate width of the transistor virtual model as the adjusted gate size of the high electron mobility transistor.

[0077] Specifically, when determining the adjusted gate size of the high electron mobility transistor, it includes: obtaining the size difference between the adjusted gate size and the gate size, and determining the adjustment coefficient of the gate index of the high electron mobility transistor after adjustment according to the relationship between the size difference and the preset size difference: wherein a first preset size difference and a second preset size difference are preset, and the first preset size difference is less than the second preset size difference. When the size difference is less than or equal to the first preset size difference, the adjustment coefficient of the gate index of the high electron mobility transistor after adjustment is determined to be M3. When the size difference is greater than the first preset size difference, and the size difference is less than or equal to the second preset size difference, the adjustment coefficient of the gate index of the high electron mobility transistor after adjustment is determined to be M2. When the size difference is greater than the second preset size difference, the adjustment coefficient of the gate index of the high electron mobility transistor after adjustment is determined to be M1. And M1<M2<M3.

[0078] It can be understood that when determining the gate size, the gate width is determined by analyzing the transistor placement volume, and the transistor virtual model under each gate length is obtained, and the subsequent parameter adjustment is performed on this basis. Subsequently, the scattering parameter difference under the transistor virtual model is obtained, and according to the size of the scattering parameter difference, the appropriate virtual model is screened out for subsequent analysis. The purpose of this step is to select the most suitable transistor model to provide an accurate basis for subsequent adjustment. Then, according to the selected transistor model, the scattering parameter difference is further ranked, and the transistor model with the smallest scattering parameter difference is determined as the adjusted standard. When the adjusted gate size is determined, a comparison with the preset size is performed to obtain the size difference, and the adjustment coefficient of the gate index is determined according to the relationship between the size difference and the preset size difference. This series of operations and calculation processes ensures that the adjusted gate size and gate index can accurately meet the design requirements and maximize the performance of the low noise amplifier. This adjustment method based on the transistor virtual model and the scattering parameter difference provides reliable technical support for the optimization of the low noise amplifier by utilizing simulation and modeling technology. By precisely adjusting the key parameters of the transistor, the performance of the amplifier can be optimized and its stability and reliability in various application scenarios can be improved.

[0079] Specifically, when determining that the input matching network performance of the low noise amplifier needs to be adjusted, it includes: presetting a first preset noise parameter difference and a second preset noise parameter difference, and the first preset noise parameter difference is less than the second preset noise parameter difference. According to the relationship between the noise parameter difference and each preset noise parameter difference, the adjustment coefficient when the input matching network performance is adjusted is determined: when the noise parameter difference is less than or equal to the first preset noise parameter difference, the adjustment coefficient when the input matching network performance is adjusted is determined to be N3. When the noise parameter difference is greater than the first preset noise parameter difference, and the noise parameter difference is less than or equal to the first preset noise parameter difference, the adjustment coefficient when the input matching network performance is adjusted is determined to be N2. When the noise parameter difference is greater than the second preset noise parameter difference, the adjustment coefficient when the input matching network performance is adjusted is determined to be N1. And N1<N2<N3.

[0080] It can be understood that by setting a preset noise parameter difference threshold, the deviation of the noise parameter is carefully analyzed and classified. Through this preset noise parameter difference threshold, the deviation range of the noise parameter can be divided into different levels, so as to more effectively formulate an adjustment strategy for the performance of the input matching network. According to different noise parameter difference ranges, the corresponding adjustment coefficient is determined, making the adjustment process more flexible and controllable. This adjustment method based on the noise parameter difference threshold can adjust the performance of the input matching network in a targeted manner according to different noise parameter deviations, thereby optimizing the performance of the low noise amplifier. Further, the method ensures the rationality and stability of the adjustment coefficient by pre-setting the first and second preset noise parameter differences. By setting different preset noise parameter differences, a more specific and practical adjustment plan can be formulated taking into account different degrees of noise parameter deviation. At the same time, the setting of the adjustment coefficient follows a strict order of size, that is, N1<N2<N3, ensuring the orderliness and controllability of the adjustment process. This setting method effectively standardizes the selection of the adjustment coefficient, making the adjustment process more scientific and reliable.

[0081] Specifically, when determining that the output matching network performance of the low noise amplifier needs to be adjusted, it includes: presetting a first preset gain decibel difference and a second preset gain decibel difference, and the first preset gain decibel difference is less than the second preset gain decibel difference. According to the relationship between the gain decibel difference and each preset gain decibel difference, determine the correction coefficient when the output matching network performance is adjusted: when the gain decibel difference is less than or equal to the first preset gain decibel difference, the correction coefficient when the output matching network performance is adjusted is determined to be B3. When the gain decibel difference is greater than the first preset gain decibel difference, and the gain decibel difference is less than or equal to the second preset gain decibel difference, the correction coefficient when the output matching network performance is adjusted is determined to be B2. When the gain decibel difference is greater than the second preset gain decibel difference, the correction coefficient when the output matching network performance is adjusted is determined to be B1. And, B1<B2<B3.

[0082] It can be understood that when adjusting the output matching network performance of the low noise amplifier, the gain decibel deviation is classified and analyzed by the preset first and second preset gain decibel differences. Through this preset gain decibel difference, the gain deviation range can be divided into different levels, so as to more effectively formulate the adjustment strategy of the output matching network performance. According to different gain decibel difference ranges, the corresponding correction coefficient is determined, making the adjustment process more flexible and controllable. This adjustment method based on the preset gain decibel difference can adjust the output matching network performance in a targeted manner according to different gain deviation situations, thereby optimizing the overall performance of the low noise amplifier. Secondly, the rationality and stability of the correction coefficient are ensured by the preset first and second preset gain decibel differences. By setting different preset gain decibel differences, a more specific and practical adjustment plan can be formulated taking into account different degrees of gain deviation. At the same time, the setting of the correction coefficient follows a strict order of magnitude, that is, B1<B2<B3, which ensures the orderliness and controllability of the adjustment process. This setting method effectively standardizes the selection of the correction coefficient, making the adjustment process more scientific and reliable.

[0083] It can be seen that by setting the preset gain decibel difference and the correction coefficient, the performance of the low noise amplifier output matching network can be accurately adjusted. This method not only improves the flexibility and accuracy of the adjustment, but also enhances the performance stability and reliability of the low noise amplifier.

[0084] Step S400: Acquire simulation parameters after simulation verification, and perform secondary performance scoring based on the relationship between the simulation parameters and preset working parameters.

[0085] Step S500: Determine whether the low noise amplifier is optimized according to the relationship between the secondary performance score and the preset performance score.

[0086] Specifically, according to the relationship between the secondary performance score and the preset performance score, determining whether the optimization of the low noise amplifier is completed includes: when the secondary performance score is lower than the preset performance score, determining that the optimization of the low noise amplifier is not completed, and adjusting the optimization parameters until the secondary performance score is higher than the preset performance score. When the secondary performance score is higher than the preset performance score, determining that the optimization of the low noise amplifier is completed, and adjusting the operating parameters of the low noise amplifier according to the optimization parameters.

[0087] Specifically, when adjusting the working parameters of the low noise amplifier according to the optimization parameters, it includes: obtaining the parameter differences between the optimization parameters and the working parameters. According to the relationship between the parameter differences and the preset parameter differences, the correction coefficients when adjusting the working parameters are determined: wherein the first preset parameter difference and the second preset parameter difference are preset, and the first preset parameter difference is less than the second preset parameter difference. When the parameter difference is less than or equal to the first preset parameter difference, the correction coefficient when adjusting the working parameters is determined to be P1. When the parameter difference is greater than the first preset parameter difference, and the parameter difference is less than or equal to the second preset parameter difference, the correction coefficient when adjusting the working parameters is determined to be P2. When the parameter difference is greater than the second preset parameter difference, the correction coefficient when adjusting the working parameters is determined to be P3. And, P1<P2<P3.

[0088] Specifically, when determining whether the optimization is completed, based on the comparison between the secondary performance score and the preset performance score, if the secondary performance score is lower than the preset performance score, it is determined that the optimization is not completed, and the optimization parameters need to be adjusted until the secondary performance score is higher than the preset performance score. If the secondary performance score is higher than the preset performance score, it is confirmed that the optimization is completed, and the working parameters of the low noise amplifier can be adjusted according to the optimization parameters. When adjusting the working parameters of the low noise amplifier, first obtain the parameter differences between the optimization parameters and the working parameters. Then, according to the relationship between the parameter differences and the preset parameter differences, determine the correction coefficients when adjusting the working parameters. Through the pre-set first and second preset parameter differences, the deviation of the parameter difference is classified and analyzed, so as to determine the correction coefficients corresponding to different parameter difference ranges. This adjustment method based on the preset parameter difference can adjust the working parameters in a targeted manner according to different parameter deviations, thereby realizing the optimization of the low noise amplifier.

[0089] In the above embodiment, by acquiring and analyzing the working parameters of the amplifier, a systematic performance scoring system is established, thereby realizing an objective evaluation of the performance of the amplifier. Compared with the traditional subjective evaluation method, this evaluation system based on specific parameters is more accurate and credible. By comparing the working parameters with the preset parameters, it is possible to more accurately judge whether the performance of the amplifier meets the expected requirements, providing a clear direction for subsequent optimization. In the optimization process, a closed-loop feedback mechanism is formed by adopting the method of simulation verification and gradual adjustment of the optimization parameters. This means that the optimization effect will be verified after each adjustment, and then further adjustments will be made based on the verification results. This cyclic iterative optimization method effectively ensures the continuous progress of the optimization process, and the optimization results can be accurately evaluated and adjusted at each step. In this way, problems can be discovered and corrected in a timely manner, avoiding deviations and errors that may occur during the optimization process, thereby improving the reliability and stability of the optimization process. At the same time, traditional optimization methods often rely on the experience and subjective judgment of engineers, and are easily affected by personal preferences and experience, resulting in uncertainty in the optimization results. The closed-loop feedback mechanism based on systematic evaluation of working parameters and simulation verification makes the optimization process more objective and scientific, reduces the impact of personal subjective factors on the optimization results, and ensures the objectivity and stability of the optimization process.

[0090] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0091] The present application is described with reference to flowcharts and / or block diagrams of methods, devices (systems) and computer program products according to embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0092] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0093] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0094] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for optimizing an S-band low noise amplifier based on HEMT, characterized in that: include: Acquiring operating parameters of the low noise amplifier when it is working, wherein the operating parameters include scattering parameters, noise parameters and power gain decibels; A performance score is performed on the low noise amplifier according to the relationship between the operating parameter and the preset operating parameter, and a relationship between the performance score and the preset performance score is used to determine whether to optimize the low noise amplifier, wherein: When it is determined that the low noise amplifier needs to be optimized, obtaining optimization parameters of the low noise amplifier, and performing simulation verification according to the optimization parameters; Acquire simulation parameters after simulation verification, and perform secondary performance scoring according to the relationship between the simulation parameters and the preset working parameters; Determining whether the low noise amplifier is optimized according to the relationship between the secondary performance score and the preset performance score, wherein: When the secondary performance score is lower than the preset performance score, it is determined that the low noise amplifier optimization is not completed, and the optimization parameters are adjusted until the secondary performance score is higher than the preset performance score.

2. The method for optimizing an S-band low noise amplifier based on HEMT according to claim 1, characterized in that: When a performance score is performed on the low noise amplifier according to the relationship between the operating parameter and the preset operating parameter, it includes: Acquire a scattering parameter difference between the scattering parameter and a preset scattering parameter, a noise parameter difference between the noise parameter and a preset noise parameter, and a gain decibel difference between the power gain decibel and a preset power gain decibel; A primary performance score between the scattering parameter difference, the noise parameter difference and the gain decibel difference is obtained based on a formula, wherein the formula is as follows: Q = (z1*L) + (z2*K) + (z3*J); In the formula, Q is the primary performance score, L is the scattering parameter difference, K is the noise parameter difference, J is the gain decibel difference, z1, z2 and z3 are weight coefficients, and the sum of z1, z2 and z3 is 1.

3. The method for optimizing an S-band low noise amplifier based on HEMT according to claim 1, characterized in that: When it is determined that the low noise amplifier needs to be optimized, obtaining the optimization parameters of the low noise amplifier, and simulating and verifying according to the optimization parameters, includes: The scattering parameter difference, noise parameter difference and gain decibel difference are obtained respectively and compared with zero, and the optimization scheme of the low noise amplifier is determined according to the comparison results, wherein: When the scattering parameter difference is greater than zero, and the noise parameter difference and the gain decibel difference are both less than zero, it is determined that the gate size and gate index of the high electron mobility transistor of the low noise amplifier need to be adjusted; When the noise parameter difference is greater than zero, and the scattering parameter difference and the gain decibel difference are both less than zero, it is determined that the input matching network performance of the low noise amplifier needs to be adjusted; When the gain decibel difference is greater than zero, and the scattering parameter difference and the noise parameter difference are both less than zero, it is determined that the output matching network performance of the low noise amplifier needs to be adjusted; When the scattering parameter difference, the noise parameter difference and the gain decibel difference are all less than zero, it is determined that the gate size and gate index of the high electron mobility transistor of the low noise amplifier and the input matching network performance and the output matching network performance need to be adjusted.

4. The method for optimizing an S-band low noise amplifier based on HEMT according to claim 3, characterized in that: When determining that the gate size and gate index of the high electron mobility transistor of the low noise amplifier need to be adjusted, the method comprises: Determining a gate width of the high electron mobility transistor according to a placement volume of the high electron mobility transistor inside the low noise amplifier, and acquiring a transistor virtual model between the gate width and each gate length; Obtaining scattering parameter differences under each of the transistor virtual models, and removing the transistor virtual models whose scattering parameter differences are greater than zero; Obtaining the scattering parameter differences of the transistor virtual models remaining after removing the scattering parameter differences greater than zero, and ranking them in descending order; A transistor virtual model corresponding to the scattering parameter difference value ranked first is obtained, and a gate length and a gate width of the transistor virtual model are defined as the adjusted gate size of the high electron mobility transistor.

5. The method for optimizing an S-band low noise amplifier based on HEMT according to claim 4, characterized in that: When determining the adjusted gate size of the high electron mobility transistor, the method includes: Acquiring a size difference between the adjusted gate size and the gate size, and determining an adjustment coefficient of the adjusted gate index of the high electron mobility transistor according to a relationship between the size difference and a preset size difference; Wherein, a first preset size difference and a second preset size difference are preset, and the first preset size difference is smaller than the second preset size difference; When the size difference is less than or equal to the first preset size difference, determining the adjustment coefficient of the adjusted gate index of the high electron mobility transistor to be M3; When the size difference is greater than the first preset size difference, and the size difference is less than or equal to the second preset size difference, determining the adjustment coefficient of the adjusted gate index of the high electron mobility transistor to be M2; When the size difference is greater than the second preset size difference, determining the adjustment coefficient of the adjusted gate index of the high electron mobility transistor to be M1; And M1<M2<M3.

6. The method for optimizing an S-band low noise amplifier based on HEMT according to claim 3, characterized in that: When determining that the input matching network performance of the low noise amplifier needs to be adjusted, the method includes: Presetting a first preset noise parameter difference and a second preset noise parameter difference, wherein the first preset noise parameter difference is smaller than the second preset noise parameter difference; Determining, according to the relationship between the noise parameter difference and each preset noise parameter difference, an adjustment coefficient when adjusting the performance of the input matching network; When the noise parameter difference is less than or equal to the first preset noise parameter difference, determining that the adjustment coefficient for adjusting the input matching network performance is N3; When the noise parameter difference is greater than the first preset noise parameter difference, and the noise parameter difference is less than or equal to the first preset noise parameter difference, determining that the adjustment coefficient for adjusting the input matching network performance is N2; When the noise parameter difference is greater than the second preset noise parameter difference, the adjustment coefficient when the input matching network performance is adjusted is determined to be N1; And N1<N2<N3.

7. The method for optimizing an S-band low noise amplifier based on HEMT according to claim 3, characterized in that: When it is determined that the output matching network performance of the low noise amplifier needs to be adjusted, the method includes: Presetting a first preset gain decibel difference and a second preset gain decibel difference, wherein the first preset gain decibel difference is smaller than the second preset gain decibel difference; Determining a correction coefficient for adjusting the performance of the output matching network according to a relationship between the gain decibel difference and each preset gain decibel difference; When the gain decibel difference is less than or equal to the first preset gain decibel difference, the correction coefficient for adjusting the output matching network performance is determined to be B3; When the gain decibel difference is greater than the first preset gain decibel difference, and the gain decibel difference is less than or equal to the second preset gain decibel difference, the correction coefficient for adjusting the output matching network performance is determined to be B2; When the gain decibel difference is greater than the second preset gain decibel difference, the correction coefficient for adjusting the output matching network performance is determined to be B1; Moreover, B1<B2<B3.

8. The method for optimizing an S-band low noise amplifier based on HEMT according to claim 1, characterized in that: Determining whether the low noise amplifier is optimized according to the relationship between the secondary performance score and the preset performance score includes: When the secondary performance score is lower than the preset performance score, it is determined that the low noise amplifier optimization is not completed, and the optimization parameters are adjusted until the secondary performance score is higher than the preset performance score; When the secondary performance score is higher than the preset performance score, it is determined that the optimization of the low noise amplifier is completed, and the operating parameters of the low noise amplifier are adjusted according to the optimization parameters.

9. The method for optimizing an S-band low noise amplifier based on HEMT according to claim 8, characterized in that: When adjusting the operating parameters of the low noise amplifier according to the optimization parameters, it includes: Obtaining the difference between the optimization parameters and the operating parameters; Determining the correction coefficient for adjusting each of the working parameters according to the relationship between each of the parameter differences and the preset parameter difference; Wherein, a first preset parameter difference and a second preset parameter difference are preset, and the first preset parameter difference is smaller than the second preset parameter difference; When the parameter difference is less than or equal to the first preset parameter difference, the correction coefficient for adjusting the working parameter is determined to be P1; When the parameter difference is greater than the first preset parameter difference, and the parameter difference is less than or equal to the second preset parameter difference, the correction coefficient for adjusting the working parameter is determined to be P2; When the parameter difference is greater than the second preset parameter difference, the correction coefficient for adjusting the working parameter is determined to be P3; Moreover, P1<P2<P3.

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