Self-adaptive impedance matching method and system of microwave frequency band

Abstract

The invention provides a self-adaptive impedance matching method and system of a microwave frequency band. The method comprises the following steps: performing initial impedance measurement on a plurality of microwave component ports to obtain a complex impedance parameter as a matching reference; in the operation process, a current impedance state and a reflection coefficient are collected through a reflection monitoring mechanism, and a dynamic impedance state vector is constructed; inputting the state information into an adaptive algorithm module, generating a matching parameter vector and configuring an adjustable device to realize real-time adjustment of a matching network; calculating a matching error according to the current reflection state and a target reference value, and driving parameters to be iteratively updated; after the matching precision requirement is met, the final parameters are loaded to the controller to complete actual configuration; meanwhile, the system periodically collects environmental parameters and matching effects, and dynamically judges whether rematching is needed or not so as to maintain long-term stable operation of the system. The method has the capabilities of automatic sensing, closed-loop optimization and environmental change adaptation, and can improve the matching efficiency and signal transmission quality of a microwave system under multi-band and high-dynamic working conditions.

Description

Technical Field

[0001] The present invention relates to the field of microwave technology and radio frequency circuits, and in particular to an adaptive impedance matching method and system for microwave frequency bands. Background Art

[0002] In high-frequency scenarios such as RF communication systems, radar antenna arrays, and microwave power amplifiers, impedance matching is always a key technical link that affects the transmission efficiency and stability of the system. In order to reduce reflection loss and improve signal integrity, traditional microwave systems often use fixed matching networks or manually adjust capacitors and inductors to achieve initial impedance alignment. However, such methods usually rely on static parameter configuration and are difficult to adapt to impedance offsets caused by factors such as temperature drift, load changes, and frequency switching during operation.

[0003] At present, some dynamic matching solutions have tried to introduce controllable devices such as PIN diodes and MEMS devices for matching adjustment, but most of them only support local optimization of limited frequency points, or still rely on manual intervention in actual deployment, and cannot achieve dynamic matching control within a continuous frequency range. At the same time, traditional control strategies are usually based on fixed rules or preset table lookup methods, lacking an adjustment mechanism based on real-time status feedback, and the matching effect is prone to decline as the environment changes.

[0004] Therefore, there is an urgent need for an adaptive impedance matching method with real-time state perception, data-driven analysis and automatic parameter adjustment capabilities, which can model and evaluate impedance state changes and achieve rapid response and continuous optimization of the matching network through an algorithmic control mechanism to meet the matching performance requirements of microwave systems in complex environments and multi-band operating conditions. Summary of the invention

[0005] The present invention provides a microwave frequency band adaptive impedance matching method, which includes: S10, initially measuring the port impedances of multiple components in the microwave system, obtaining initial impedance parameters of each node, and using the parameters as a reference for subsequent matching control; S20, inputting the initial impedance parameters into the impedance matching module, dynamically collecting the port impedance value and signal reflection coefficient under the current operating state through the reflection monitoring mechanism, and constructing real-time impedance state information; S30, inputting the real-time impedance information into the adaptive algorithm module, executing parameter calculation and configuration update of the adjustable elements in the matching network, so that the system reflection coefficient gradually converges to the minimum value, and realizing dynamic impedance matching; S40, comparing the current reflection coefficient with a preset target reflection reference value, calculating a matching error value as a feedback signal, and driving the matching network parameters to further iterate until the set matching accuracy condition is met; S50, after the matching conditions meet the set requirements, output the optimized matching parameter group and load it into the controller to complete the configuration and adjustment of the actual signal channel; S60. Verify the optimized matching parameters in multiple frequency bands and under different environmental conditions, output the matching status evaluation results, and provide adaptive parameter support for the long-term stable operation of the system.

[0006] The microwave frequency band adaptive impedance matching method as described above, wherein the port impedances of multiple components in the microwave system are initially measured, the initial impedance parameters of each node are obtained, and the parameters are used as a reference for subsequent matching control, including: Inject calibration signals into each component port in turn as stimulus input; Collect the excitation response data of each port, calculate and output the complex impedance parameters at the corresponding frequency; The initial complex impedance data is written into the matching reference storage module for subsequent impedance modeling and comparison reference.

[0007] A microwave frequency band adaptive impedance matching method as described above, wherein the initial impedance parameters are input into the impedance matching module, the port impedance value and the signal reflection coefficient under the current operating state are dynamically collected through the reflection monitoring mechanism, and the real-time impedance state information is constructed, including: Inputting the incident wave and reflected wave of the microwave signal into the reflection monitoring module; Perform amplitude and phase analysis on the reflected wave and calculate the current reflection coefficient value; The obtained reflection coefficient and impedance measurement value are synchronously written into the timing cache queue for dynamic model construction and subsequent algorithm processing.

[0008] A microwave frequency band adaptive impedance matching method as described above, wherein real-time impedance information is input into an adaptive algorithm module, and parameter calculation and configuration update of adjustable elements in a matching network are performed so that the system reflection coefficient gradually converges to a minimum value, and dynamic impedance matching is achieved, including: Input the currently measured impedance value and the initial impedance parameters into the adaptive algorithm module; The matching parameter vector is calculated and generated by the adaptive algorithm module; The configuration of adjustable capacitors, inductors or MEMS elements in the matching network is updated according to the matching parameter vector to achieve real-time dynamic adjustment of parameters.

[0009] A microwave frequency band adaptive impedance matching method as described above, wherein the current reflection coefficient is compared with a preset target reflection reference value, a matching error value is calculated as a feedback signal, and the matching network parameters are driven to further iterate until the set matching accuracy conditions are met, including: Inputting the reflection coefficient of the current output signal and the preset target reflection coefficient into the error evaluation module; The error evaluation module calculates the matching error value as a matching performance criterion; If the matching error value does not meet the set convergence condition, the system will recalculate the parameters based on the matching error value and start the next round of matching adjustment.

[0010] A microwave frequency band adaptive impedance matching method as described above, wherein after the matching condition reaches the set requirement, an optimized matching parameter group is output and loaded into the controller to complete the configuration and adjustment of the actual signal channel, including: Write the final matching parameter group into the controller internal register through the control interface; The controller drives the physical matching network to complete the actual configuration according to the written parameters; The configured status is output to the matching record module to record the current matching parameter group and system status.

[0011] The microwave frequency band adaptive impedance matching method as described above, wherein the optimized matching parameters are verified in multiple frequency bands and under different environmental conditions, and the matching state evaluation results are output, so as to provide adaptive parameter support for the long-term stable operation of the system, including: Periodically collect reflection coefficient values ​​within the set frequency band; Input the collected frequency band environmental parameters into the adaptability judgment module to identify changes in environmental status; When an environmental offset or matching performance degradation is detected, a rematch trigger signal is output to start the system to re-enter the matching process to maintain matching stability.

[0012] The present invention also provides a microwave frequency band adaptive impedance matching system, which includes: An impedance measurement module is configured to inject a calibration signal into each component port of the microwave system and collect the stimulus response, and calculate the complex impedance parameters of the output port at the target frequency as a reference for system initialization; A signal monitoring module, configured to collect current impedance values ​​and reflection coefficients of the ports during system operation, and output a time series data stream for constructing a dynamic impedance state model; An adaptive adjustment module, connected to the signal monitoring module, receives real-time impedance data, performs parameter optimization calculations and outputs configuration instructions for the adjustable network; An error evaluation module, connected to the adaptive adjustment module, is used to calculate the matching error between the reflection coefficient and the target value, and feed the error back to the adjustment module to form a closed-loop control; A control execution module is configured to receive target matching parameters, control the component states of the adjustable matching network in real time, and complete the actual parameter loading and signal channel configuration; The stability verification module is configured to periodically collect environmental status and system matching conditions, and output a rematch trigger signal when the recognition performance degrades or the parameters drift, so as to achieve stable adaptive adjustment of the system for long-term operation.

[0013] The beneficial effects achieved by the present invention are as follows: The present invention proposes an adaptive impedance matching method based on multi-parameter perception and closed-loop control, which can realize automatic parameter adjustment and dynamic impedance optimization in multiple frequency bands. The system can collect the current impedance state and reflection characteristics in real time, combine the initial reference parameters with environmental changes, output precise matching instructions, improve the reflection suppression ability and long-term stability of the signal channel, and is suitable for the strict requirements of dynamic matching performance in high-reliability RF communication scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0015] Figure 1 This is a flow chart of an adaptive impedance matching method for a microwave frequency band provided in Example 1 of the present application. DETAILED DESCRIPTION

[0016] The following is a clear and complete description of the technical solutions in the embodiments of the present invention 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. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0017] Embodiment 1 like Figure 1 As shown, the first embodiment of the present application provides an adaptive impedance matching method in a microwave frequency band, comprising the following steps: S10, initially measuring the port impedances of multiple components in the microwave system, obtaining initial impedance parameters of each node, and using the parameters as a reference for subsequent matching control; In this embodiment, the system first performs an impedance initialization step to measure the complex impedance parameters of multiple key RF component ports as reference inputs for subsequent adaptive matching calculations, which specifically includes the following sub-steps: S101, injecting calibration signals into the ports of each component in turn as excitation input; The system control module selects the target component ports in turn and injects a standard calibration signal into each port.

[0018] The calibration signal is a frequency-adjustable narrowband swept frequency excitation, whose frequency range covers the main working frequency band preset by the system. The signal characteristics include stable amplitude, linear phase, and controllable harmonic components. To avoid interference between ports, the system adopts serial injection mode, and only stimulates one component port at a time.

[0019] S102, collecting excitation response data of each port, calculating and outputting complex impedance parameters at corresponding frequencies; After the calibration signal is injected, the system collects the excitation response returned by the port in real time through a high-precision impedance sampling module. The response signal includes the complex components of the reflected wave and the transmitted wave.

[0020] The system uses the fast Fourier transform (FFT) algorithm to convert the time domain sampling data into frequency domain expression, extract the complex components V(f) and I(f) of voltage and current, and calculate the complex impedance at the current frequency point according to the following formula: , where A(f), B(f), C(f), and D(f) are the real and imaginary parts after amplitude and phase demodulation. The system performs multiple sampling on each port and uses mean filtering to eliminate occasional interference to improve measurement accuracy.

[0021] S103, writing the initial complex impedance data into a matching reference storage module for subsequent impedance modeling and comparison reference.

[0022] The system packages the complex impedance parameters calculated at the corresponding frequency point of each port into a structured data group and marks them according to fields such as port number, frequency index, and measurement time.

[0023] The system then writes the data into the matching benchmark storage module, which uses a frequency-band-divided storage structure to support fast indexing and historical data backtracking for subsequent matching algorithm modeling, initial value setting, and error correction benchmarks.

[0024] S20, inputting the initial impedance parameters into the impedance matching module, dynamically collecting the port impedance value and signal reflection coefficient under the current operating state through the reflection monitoring mechanism, and constructing real-time impedance state information; After completing step S10, the system obtains the frequency of each component port at different frequency points. Complex impedance parameters under For the sake of uniform expression, the static measurement impedance parameter is recorded as the initial impedance below, which is expressed as: The system inputs the initial parameters into the impedance matching module as a reference for impedance deviation calculation during dynamic operation. Subsequently, the system collects the incident signal and reflected signal in real time under the operating state through the reflection monitoring mechanism to construct dynamic impedance state information under the frequency-time two-dimensional structure. This step includes the following sub-steps: S201, inputting the incident wave and the reflected wave of the microwave signal into a reflection monitoring module; The system sets up a broadband directional coupler at each key port to extract the incident wave voltage signal in the working channel in real time. Reflected wave voltage signal and input the two synchronously into the reflection monitoring module.

[0025] To ensure the consistency of phase and sampling timing, the system uses a unified master clock Dual-channel sampling triggering is realized, so that the two signals can be aligned with nanosecond time accuracy.

[0026] S202, performing amplitude and phase analysis on the reflected wave to calculate the current reflection coefficient value; The reflection monitoring module applies a window function weight to the input signal and then performs a fast Fourier transform to extract the frequency points. The complex voltage value on The complex reflection coefficient of this frequency point is calculated according to the following expression: ,in, are the real and imaginary parts of the reflected signal at the frequency point respectively; are the real and imaginary parts of the incident signal; is the reflection coefficient, which is used to describe the amplitude and phase deviation of the current matching state and serves as an important basis for system matching evaluation.

[0027] S203, synchronously writing the obtained reflection coefficient and impedance measurement value into a timing cache queue for dynamic model construction and subsequent algorithm processing.

[0028] At each frequency point , Time point The complex impedance value of the current port is collected in real time and recorded as: and the initial complex impedance value obtained in step S10 To comprehensively evaluate the impedance deviation degree, the trend of drastic changes in reflected waves, and the impact of environmental disturbances under the current working state, the system constructs a matching deviation risk intensity function: ,in, Indicates the kth frequency sampling point currently being processed; Indicates the time sampling point of the current moment; Represents the real part of the current actual impedance; Represents the imaginary part of the current actual impedance; , Respectively represent the real and imaginary parts of the initial impedance at the frequency point; Represents the complex reflection coefficient of the current frequency point; The modulus length represents the reflection coefficient; It represents the derivative of the reflection coefficient mode length with respect to frequency, and is used to measure the severity of reflection fluctuations in the frequency domain; Indicates frequency point Place, time The temperature offset of The reference temperature value set for the system is used to normalize the environmental impact; Frequency point ,time The power fluctuation amount; The nominal reference power value set for the system. The larger the value of the risk function, the more obvious the matching deviation in the current state of the system, the more unstable the reflection trend or the stronger the environmental disturbance, and the priority is to enter the adjustment control process. The system constructs the above parameters as an impedance state vector: , and write to the cache queue The queue adopts a circular sliding window structure, which supports fast access indexed by frequency and time, and serves as the input basis for the subsequent matching adjustment algorithm.

[0029] S30, inputting the real-time impedance information into the adaptive algorithm module, executing parameter calculation and configuration update of the adjustable elements in the matching network, so that the system reflection coefficient gradually converges to the minimum value, and realizing dynamic impedance matching; The dynamic impedance state information obtained in step S20 includes multi-dimensional input parameters such as the current impedance value, reflection coefficient, and matching deviation risk index. The system inputs this information into the adaptive algorithm module to achieve dynamic configuration control of various adjustable components in the matching network to ensure that the microwave system maintains the optimal matching state in each operating frequency band. This step specifically includes the following sub-steps: S301, inputting the currently measured impedance value and the initial impedance parameters into the adaptive algorithm module; The system is at the current frequency and time Under, extract the following input data: real-time complex impedance value ; Initial complex impedance value ; Current reflection coefficient ; Matching deviation index The above data is used as feature input and sent to the adaptive algorithm module for adjustment calculation.

[0030] S302, the adaptive algorithm module calculates and generates a matching parameter vector; The adaptive algorithm module calculates the configuration parameters required for each adjustment device in the matching network based on the input parameters, and uses the following multi-factor combination function to generate a matching parameter vector: ,in, represents the target matching parameter vector, which represents the control output of n adjustable devices in the matching network; is the impedance real part deviation; is the impedance imaginary part deviation; is the derivative of the reflection coefficient mode length with respect to frequency; is the matching deviation risk intensity function value; The weight coefficient and bias value used for adjusting the i-th device; represents the unit direction selection vector of the control channel of the i-th device; n represents the total number of adjustment elements involved in the configuration of the matching network. Through this calculation model, the system can comprehensively evaluate the current matching state and evolution trend and generate a set of adjustable configuration parameters for fine control.

[0031] S303 , updating the configuration of adjustable capacitors, inductors or MEMS elements in the matching network according to the matching parameter vector, so as to achieve real-time dynamic adjustment of parameters.

[0032] The system generates a matching parameter vector , through the high-speed control channel, configuration instructions are sent to various adjustable components in the matching network to complete the dynamic control of the following devices: adjustable capacitor array; variable inductor module; microelectromechanical tunable device (MEMS tuners); microstrip phase shifter; digital programmable electrical tuning network and other structured adjustment units.

[0033] The above devices can be deployed individually or in combination according to the system structure to achieve control goals such as impedance matching, phase adjustment or reflection minimization. The control instructions are directly loaded into the physical device through a digital-to-analog converter or a digital control interface to achieve continuous adjustment capabilities with sub-millisecond response.

[0034] The system monitors the adjusted reflection coefficient The change trend is used to determine whether the expected convergence condition is met. If the deviation still does not meet the set threshold, the parameter calculation and update process is re-executed to form a stable closed-loop control mechanism and achieve continuous dynamic impedance matching.

[0035] S40, comparing the current reflection coefficient with a preset target reflection reference value, calculating a matching error value as a feedback signal, and driving the matching network parameters to further iterate until the set matching accuracy condition is met; In order to achieve continuous optimization of system matching accuracy, after completing the initial parameter adjustment, the system further evaluates the deviation between the current reflection state and the ideal matching state and builds a feedback control mechanism. Through error evaluation and parameter update, multiple rounds of impedance matching process are implemented until the preset accuracy threshold is reached. This step includes the following sub-steps: S401, inputting the reflection coefficient of the current output signal and the preset target reflection coefficient into an error evaluation module; The system is at the current frequency and time Under this condition, the actual reflection coefficient of the output signal is collected. , and load the preset target reflection coefficient value .

[0036] The two are sent as input to the error evaluation module and serve as the basic data source for subsequent error calculation. It can be obtained by fitting historical test data, calculating typical impedance standards or setting engineering experience values.

[0037] S402, the error evaluation module calculates the matching error value as a matching performance criterion; In the error evaluation module, the system constructs a matching error function in the following form based on the current reflection deviation and reflection trend: ,in, is the output reflection coefficient at the current frequency point; The target reflection coefficient value preset for the system; is the square of the comprehensive error of reflection amplitude and phase; is the rate of change of the reflection coefficient over time, which is used to determine whether the system is in an unstable oscillation or non-convergent state; , is the weight coefficient, which is used to control the influence ratio of static error and dynamic error; is the matching error value, which is the core indicator for judging the current matching performance. The system calculates the matching error value based on the matching convergence threshold. Compare and decide whether further adjustment is needed.

[0038] S403: If the matching error value does not meet the set convergence condition, the system re-calculates parameters according to the matching error value and starts the next round of matching adjustment.

[0039] When the error value When the system determines that the current matching state still does not meet the accuracy requirements, it immediately feeds back the error to the adaptive algorithm module. The module dynamically adjusts the matching parameter weights according to the feedback error size, re-executes the matching parameter vector calculation process, and generates a new parameter output. , and drives each adjustment device in the matching network to update the configuration.

[0040] The above adjustment process forms an automatic closed-loop matching mechanism. The system will continue to perform error detection and parameter iteration until the error value , it is determined that the matching convergence condition is reached and the matching process is terminated.

[0041] S50, after the matching conditions meet the set requirements, output the optimized matching parameter group and load it into the controller to complete the configuration and adjustment of the actual signal channel; After multiple rounds of adjustment and error feedback control, the system detects that the reflection coefficient at the current frequency point meets the preset matching accuracy condition, that is, the error index is lower than the set threshold, and the system determines that the matching process is completed. At this time, the final optimized matching parameter group is output and loaded into the controller to drive the physical matching network into the actual working state. This step includes the following sub-steps: S501, writing the final matching parameter group into the controller internal register through the control interface; The system will current frequency point The matching parameter group finally determined by the adaptive algorithm module is output and written into the dedicated register inside the controller through the control bus or high-speed interface. The parameter group contains detailed configuration data for adjustable devices, such as capacitance, inductance value, phase shift state, channel switching instructions, etc., and the controller will prepare to execute instructions based on this.

[0042] S502, the controller drives the physical matching network to complete the actual configuration according to the written parameters; The controller reads the written register value and maps the parameters to the corresponding physical actuator channel. It controls the adjustable capacitor, inductor array, microstrip structure, MEMS component or phase shift network in the matching network through voltage, current or digital pulse signal to complete the matching configuration of each key node in the RF signal path, ensuring channel impedance continuity and minimization of signal reflection.

[0043] S503: Output the configuration completion status to the matching record module, and record the current matching parameter group and system status.

[0044] To achieve system status backtracking and matching data traceability, after completing the physical configuration, the controller encapsulates the current matching parameter group and the corresponding frequency, time, temperature, power supply and other operating status information into a status record data packet and outputs it to the matching record module. This module stores the data in a structured manner, which can be used for subsequent model optimization, historical analysis or abnormal reconstruction, ensuring that the system has long-term evolution capabilities and failure self-diagnosis capabilities.

[0045] S60. Verify the optimized matching parameters in multiple frequency bands and under different environmental conditions, output the matching status evaluation results, and provide adaptive parameter support for the long-term stable operation of the system.

[0046] After the matching parameters are loaded and configured, the system enters the continuous operation stage. To ensure the adaptability and stability of the optimized matching parameters in actual use, the system periodically verifies the matching effect under key frequency bands and typical environmental conditions, and determines whether to trigger the rematching mechanism through real-time detection of changes in reflection status and external interference, so as to achieve long-term adaptive control of the system. This step includes the following sub-steps: S601, periodically collecting reflection coefficient values ​​within a set frequency band; The system performs periodic reflection coefficient measurements on multiple sampling points including the main carrier, edge frequency points, and historical high deviation frequency bands according to the preset working frequency band range. The measurement is triggered regularly by the reflection monitoring module to collect the output reflection characteristics corresponding to the frequency point and time stamp to construct a long-term impedance change trend map. The system can dynamically adjust the sampling interval and frequency point density based on historical evaluation results to optimize resource allocation efficiency.

[0047] S602, inputting the collected frequency band environment parameters into an adaptability judgment module to identify changes in the environment state; The system synchronously collects external environmental parameters corresponding to the reflection coefficient, including temperature, humidity, input power, voltage fluctuation, etc., builds a complete frequency band-environmental characteristic data pair, and inputs it into the adaptability judgment module for real-time analysis. This module identifies the changing trend of the environmental state based on the preset threshold and self-learning model, and determines whether there are potential interference factors that cause fluctuations in matching performance, such as unstable power supply, thermal drift, mechanical vibration, etc.

[0048] S603: When an environmental deviation or a degradation in matching performance is detected, a rematch trigger signal is output to start the system to re-enter the matching process to maintain matching stability.

[0049] If the system identifies that the environmental state deviation exceeds the set stability tolerance, or detects that the reflection coefficient trend is significantly rising, the system will determine that the matching performance has a risk of decline and immediately output a rematch trigger signal to the main control module. Based on this, the system starts the automatic matching process callback mechanism and re-executes the parameter measurement, error judgment and matching adjustment steps to ensure that the matching network is restored to the optimal configuration under the new working state, thereby achieving long-term matching stability control in a dynamic environment.

[0050] Embodiment 2 Embodiment 2 of the present application provides an adaptive impedance matching system in a microwave frequency band, including: An impedance measurement module is configured to inject a calibration signal into each component port of the microwave system and collect the stimulus response, and calculate the complex impedance parameters of the output port at the target frequency as a reference for system initialization; The impedance measurement module is used to obtain the initial impedance parameters of multiple component ports in the microwave system at the target frequency as the reference input for subsequent dynamic matching adjustment. The module is equipped with an excitation control unit, which injects calibration signals into each component port in turn according to the preset frequency list to stimulate its electrical response behavior. The response signal is collected through the measurement channel, and the amplitude and phase characteristics of the key frequency points are extracted by the signal recognition and modeling unit to build a complete port impedance model.

[0051] The module integrates a high-precision synchronous clock and response sampling controller to ensure that the stimulus and response acquisition processes have a unified time reference, improving the consistency and reliability of the measurement. To reduce the risk of error propagation during port switching, the module supports a dynamic link compensation mechanism that automatically performs calibration corrections during component polling.

[0052] All collected data are structured according to port number and frequency index, and written uniformly into matching reference storage units for subsequent dynamic comparison and adjustment. The module supports multi-channel parallel measurement strategy and can perform impedance scanning on multiple components at the same time.

[0053] A signal monitoring module, configured to collect current impedance values ​​and reflection coefficients of the ports during system operation, and output a time series data stream for constructing a dynamic impedance state model; The signal monitoring module is configured to collect the current impedance value and reflection coefficient of the component port in real time during system operation, and output a continuous data stream for building a dynamic impedance state model. The module extracts the incident wave and reflected wave signals through a directional coupler set in the signal channel, and completes synchronous acquisition through a dual-channel high-speed sampling interface to ensure the consistency of the sampled data in frequency and phase dimensions.

[0054] The module integrates reflection coefficient analysis logic and impedance state extraction unit, which can continuously obtain the port operation status at different frequency points and time periods. All collected data are packaged into time-series impedance state vectors after time stamping and written into the cache queue to provide high-frequency input for subsequent adjustment and evaluation modules.

[0055] To adapt to complex spectrum fluctuation scenarios, the module supports a sliding window data management mechanism and has a built-in reflection drastic fluctuation detection function. When the abnormal reflection change exceeds the set threshold, it can automatically issue an adjustment warning and intervene in the matching process in advance.

[0056] An adaptive adjustment module, connected to the signal monitoring module, receives real-time impedance data, performs parameter optimization calculations and outputs configuration instructions for the adjustable network; The adaptive adjustment module is connected to the signal monitoring module to receive real-time impedance state information and perform optimization calculations on matching network configuration parameters based on initial reference parameters. The module includes a feature extraction unit, a parameter modeling engine, and an adjustment instruction generator, which can calculate the difference vector based on real-time data and generate control outputs.

[0057] The module supports the combined calculation of multi-dimensional features such as the real part and imaginary part of impedance, reflection trend and risk index, and generates fine configuration parameters for each adjustable device through the built-in adaptive algorithm. The module can automatically adjust the calculation weight according to the error feedback to improve the convergence speed and control stability.

[0058] The output adjustment parameters are formatted and sent to the control execution module, which supports simultaneous adjustment of multiple control channels, adapts to multi-component network structures, and achieves high-precision and high-speed matching configuration.

[0059] An error evaluation module, connected to the adaptive adjustment module, is used to calculate the matching error between the reflection coefficient and the target value, and feed the error back to the adjustment module to form a closed-loop control; The error evaluation module is connected to the adaptive adjustment module to calculate the matching error between the current output reflection coefficient and the target reflection reference value, and feed the error back to the adjustment module to form a closed-loop control mechanism. The module contains a reference loader, an error calculator, and a feedback channel, which can complete error judgment and dynamic response adjustment in real time.

[0060] The module supports simultaneous evaluation of static deviation and dynamic trend, and determines whether the current matching result reaches the target accuracy based on the set convergence threshold. If the error is within the tolerance range, the current configuration remains unchanged; if the deviation exceeds the limit, the adaptive module is immediately driven to perform a new round of optimization calculations.

[0061] The module has the ability to adjust sensitivity and can dynamically adjust the error response strategy according to environmental factors such as frequency band, temperature, and power supply changes to ensure precision control capabilities under changing conditions.

[0062] A control execution module is configured to receive target matching parameters, control the component states of the adjustable matching network in real time, and complete the actual parameter loading and signal channel configuration; The control execution module is configured to receive the matching parameter group output by the adaptive adjustment module, and to control the status of various adjustable components in the matching network in real time, completing the parameter loading and final configuration of the signal channel. As a bridge between control logic and physical execution, the module is responsible for converting the algorithm results into specific hardware control operations.

[0063] The module includes a parameter parser, a command scheduling unit and an execution interface, which can map the adjustment parameters into control signals, accurately drive capacitors, inductor arrays, MEMS tuners, microstrip phase shifters and other devices for state configuration. It supports multi-path parallel control to ensure the synchronization of impedance adjustment in complex network structures.

[0064] The module also has a status recording function. After configuration is completed, the device status is automatically packaged and output to the recording module, leaving traces of the entire adjustment process.

[0065] The stability verification module is configured to periodically collect environmental status and system matching conditions, and output a rematch trigger signal when the recognition performance degrades or the parameters drift, so as to achieve stable adaptive adjustment of the system for long-term operation.

[0066] The stability verification module is configured to periodically collect reflection coefficient and environmental status information during system operation, and continuously evaluate the effectiveness of the current matching configuration. When system performance degrades or parameters drift, the module automatically outputs a rematch trigger signal to guide the system to restart the matching process to ensure long-term operational stability.

[0067] The module is equipped with a reflection state acquisition unit and an environmental perception interface, which can periodically measure key frequency points according to the frequency scanning table and simultaneously collect environmental indicators such as temperature, voltage, and electromagnetic interference. It has the ability to analyze historical data windows, identify performance change trends, and determine matching reliability. The module supports matching status hierarchical management and multi-level triggering mechanisms, and has trend warning and self-recovery capabilities.

[0068] Corresponding to the above embodiment, an embodiment of the present invention provides a computer storage medium, including: at least one memory and at least one processor; The memory is used to store one or more program instructions; The processor is used for running one or more program instructions to execute an adaptive impedance matching method in a microwave frequency band.

[0069] Corresponding to the above-mentioned embodiment, an embodiment of the present invention provides a computer-readable storage medium, wherein the computer storage medium contains one or more program instructions, and the one or more program instructions are used by a processor to execute an adaptive impedance matching method in a microwave frequency band.

[0070] The embodiments disclosed in the present invention provide a computer-readable storage medium, in which computer program instructions are stored. When the computer program instructions are executed on a computer, the computer executes the above-mentioned adaptive impedance matching method for a microwave frequency band.

[0071] In the embodiment of the present invention, the processor may be an integrated circuit chip having the ability to process signals. The processor may be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0072] The methods, steps and logic block diagrams disclosed in the embodiments of the present invention can be implemented or executed. The general processor can be a microprocessor or the processor can also be any conventional processor, etc. The steps of the method disclosed in the embodiments of the present invention can be directly embodied as a hardware decoding processor for execution, or can be executed by a combination of hardware and software modules in the decoding processor. The software module can be located in a mature storage medium in the field such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, etc. The processor reads the information in the storage medium and completes the steps of the above method in combination with its hardware.

[0073] The storage medium may be a memory, which may be, for example, a volatile memory or a nonvolatile memory, or may include both volatile and nonvolatile memory.

[0074] Among them, the non-volatile memory can be a read-only memory (ROM), a programmable ROM (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory.

[0075] The volatile memory may be a random access memory (RAM) which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate synchronous DRAM (DDRSDRAM), enhanced synchronous DRAM (ESDRAM), synchronous link DRAM (SLDRAM), and direct RAM bus DRAM (DRRAM).

[0076] The storage media described in the embodiments of the present invention are intended to include, but are not limited to, these and any other suitable types of memory.

[0077] Those skilled in the art will appreciate that in one or more of the above examples, the functions described in the present invention can be implemented using a combination of hardware and software. When software is used, the corresponding functions can be stored in a computer-readable medium or transmitted as one or more instructions or codes on a computer-readable medium. Computer-readable media include computer storage media and communication media, wherein communication media include any media that facilitates the transmission of computer programs from one place to another. Storage media can be any available media that can be accessed by general or special-purpose computers.

[0078] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made on the basis of the technical solution of the present invention should be included in the scope of protection of the present invention.

Claims

1. A microwave frequency band adaptive impedance matching method, characterized in that: The following steps are involved: S10, initially measuring the port impedances of multiple components in the microwave system, obtaining initial impedance parameters of each node, and using the parameters as a reference for subsequent matching control; S20, inputting the initial impedance parameters into the impedance matching module, dynamically collecting the port impedance value and signal reflection coefficient under the current operating state through the reflection monitoring mechanism, and constructing real-time impedance state information; S30, inputting the real-time impedance information into the adaptive algorithm module, executing parameter calculation and configuration update of the adjustable elements in the matching network, so that the system reflection coefficient gradually converges to the minimum value, and realizing dynamic impedance matching; S40, comparing the current reflection coefficient with a preset target reflection reference value, calculating a matching error value as a feedback signal, and driving the matching network parameters to further iterate until the set matching accuracy condition is met; S50, after the matching conditions meet the set requirements, output the optimized matching parameter group and load it into the controller to complete the configuration and adjustment of the actual signal channel; S60. Verify the optimized matching parameters in multiple frequency bands and under different environmental conditions, output the matching status evaluation results, and provide adaptive parameter support for the long-term stable operation of the system.

2. A microwave frequency band adaptive impedance matching method as claimed in claim 1, characterized in that: Performing an initial measurement of the port impedance of multiple components in a microwave system, obtaining the initial impedance parameters of each node, and using the parameters as a reference for subsequent matching control includes the following steps: Inject calibration signals into each component port in turn as stimulus input; Collect the excitation response data of each port, calculate and output the complex impedance parameters at the corresponding frequency; The initial complex impedance data is written into the matching reference storage module for subsequent impedance modeling and comparison reference.

3. A microwave frequency band adaptive impedance matching method as claimed in claim 1, characterized in that: The initial impedance parameters are input into the impedance matching module, and the port impedance value and signal reflection coefficient under the current operating state are dynamically collected through the reflection monitoring mechanism. The construction of real-time impedance state information includes the following steps: Inputting the incident wave and reflected wave of the microwave signal into the reflection monitoring module; Perform amplitude and phase analysis on the reflected wave and calculate the current reflection coefficient value; The obtained reflection coefficient and impedance measurement value are synchronously written into the timing cache queue for dynamic model construction and subsequent algorithm processing.

4. A microwave frequency band adaptive impedance matching method as claimed in claim 1, characterized in that: Inputting real-time impedance information into the adaptive algorithm module, performing parameter calculation and configuration update of the adjustable components in the matching network, so that the system reflection coefficient gradually converges to the minimum value, and realizing dynamic impedance matching includes the following steps: Inputting the currently measured impedance value and the initial impedance parameters into the adaptive algorithm module; The matching parameter vector is calculated and generated by the adaptive algorithm module; The configuration of adjustable capacitors, inductors or MEMS elements in the matching network is updated according to the matching parameter vector to achieve real-time dynamic adjustment of parameters.

5. The microwave frequency band adaptive impedance matching method according to claim 1, characterized in that: Comparing the current reflection coefficient with the preset target reflection reference value, calculating the matching error value as a feedback signal, and driving the matching network parameters to further iterate until the set matching accuracy conditions are met include the following steps: Inputting the reflection coefficient of the current output signal and the preset target reflection coefficient into the error evaluation module; The error evaluation module calculates the matching error value as a matching performance criterion; If the matching error value does not meet the set convergence condition, the system will recalculate the parameters based on the matching error value and start the next round of matching adjustment.

6. A microwave frequency band adaptive impedance matching method as claimed in claim 1, characterized in that: After the matching conditions meet the set requirements, the optimized matching parameter group is output and loaded into the controller to complete the configuration and adjustment of the actual signal channel, including the following steps: Write the final matching parameter group into the controller internal register through the control interface; The controller drives the physical matching network to complete the actual configuration according to the written parameters; The configured status is output to the matching record module to record the current matching parameter group and system status.

7. A microwave frequency band adaptive impedance matching method as claimed in claim 1, characterized in that: Verify the optimized matching parameters in multiple frequency bands and under different environmental conditions, output the matching status evaluation results, and provide adaptive parameter support for the long-term stable operation of the system. The following steps are included: Periodically collect reflection coefficient values ​​within the set frequency band; Input the collected frequency band environmental parameters into the adaptability judgment module to identify changes in environmental status; When an environmental offset or matching performance degradation is detected, a rematch trigger signal is output to start the system to re-enter the matching process to maintain matching stability.

8. A microwave frequency band adaptive impedance matching system, characterized in that: include: An impedance measurement module is configured to inject a calibration signal into each component port of the microwave system and collect the stimulus response, and calculate the complex impedance parameters of the output port at the target frequency as a reference for system initialization; A signal monitoring module, configured to collect current impedance values ​​and reflection coefficients of the ports during system operation, and output a time series data stream for constructing a dynamic impedance state model; An adaptive adjustment module, connected to the signal monitoring module, receives real-time impedance data, performs parameter optimization calculations and outputs configuration instructions for the adjustable network; An error evaluation module, connected to the adaptive adjustment module, is used to calculate the matching error between the reflection coefficient and the target value, and feed the error back to the adjustment module to form a closed-loop control; A control execution module is configured to receive target matching parameters, control the component states of the adjustable matching network in real time, and complete the actual parameter loading and signal channel configuration; The stability verification module is configured to periodically collect environmental status and system matching conditions, and output a rematch trigger signal when the recognition performance degrades or the parameters drift, so as to achieve stable adaptive adjustment of the system for long-term operation.

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