Self-adaptive radio frequency energy capturing method and system

Abstract

The invention relates to the technical field of information, and discloses a self-adaptive radio frequency energy capture method and system, and the method comprises the steps: collecting radio frequency signals in an environment, separating independent components of each frequency band signal from the radio frequency signals, determining the power density distribution and main lobe direction of each frequency band signal, and determining the deviation main direction of each frequency band signal; the antenna element spacing and the reference value of phase adjustment are determined by combining the expected gain requirement of the current environment, so that the antenna array configuration data are determined, the antenna array is controlled to scan the uncovered range of each frequency band signal, and then the full / directional capture mode is dynamically switched. The energy collection efficiency data in the current capture mode is evaluated to determine the target frequency band with sidelobe interference, the reference value of the target frequency band is adjusted, and the signal focusing effect is determined through the adjusted reference value to determine the capture priority of each frequency band signal, so that the radio frequency energy collection efficiency in the complex electromagnetic environment is effectively improved; and efficient capture and utilization of multi-band weak radio frequency signals are realized.

Description

Technical Field

[0001] The present invention relates to the field of information technology, and in particular to an adaptive radio frequency energy capture method and system. Background Art

[0002] Amid the rapid growth of wireless communications and the Internet of Things (IoT), RF energy harvesting technology, as a sustainable energy solution, is demonstrating significant application value. By collecting RF signals from the environment and converting them into electrical energy, it supports low-power devices and has become a key technology driving the widespread adoption of green communications and smart devices. Currently, RF energy harvesting relies primarily on fixed antenna designs and static energy capture patterns, which are less able to cope with fluctuations in ambient signal strength and directional shifts. This limitation significantly reduces energy harvesting efficiency when signals are unevenly distributed or when the primary direction is offset, especially in multi-band signal environments.

[0003] It can be seen that how to improve the efficiency of capturing RF energy when the distribution of environmental signals changes has become a technical problem that needs to be solved urgently by those skilled in the art. Summary of the Invention

[0004] The present invention provides an adaptive radio frequency energy capture method and system to solve the problem of how to improve the capture efficiency of radio frequency energy when the distribution of environmental signals changes.

[0005] To solve the above technical problems, the first aspect of the present invention provides an adaptive radio frequency energy capture method, comprising: Collect radio frequency signal data in the current environment in real time to obtain environmental characteristic data, and separate the independent components of each frequency band signal from the environmental characteristic data to generate a standardized frequency band signal distribution map; Determining the power density distribution and main lobe direction of each frequency band signal based on the standardized frequency band signal distribution map, and determining the deviation from the main direction of each frequency band signal according to each main lobe direction; Determining reference values ​​for antenna element spacing and phase adjustment based on each of the deviations from the main direction and the desired gain requirements, and determining antenna array configuration data based on each of the reference values ​​when it is determined that the deviation of the frequency band signal from the main direction exceeds a preset angle threshold; Controlling the antenna array to scan uncovered areas of the frequency band signals through the antenna array configuration data, and dynamically switching between an omnidirectional capture mode and a directional capture mode according to the uncovered areas, so as to evaluate energy collection efficiency data in the current capture mode; Based on the energy collection efficiency data, the target frequency band with sidelobe interference is determined, and the reference value of the target frequency band is adjusted. The signal focusing effect is determined by the adjusted reference value to determine the capture priority of each frequency band signal.

[0006] A second aspect of the present invention provides an adaptive radio frequency energy capture system, comprising: The signal spectrum generation module is used to collect the radio frequency signal data in the current environment in real time, obtain environmental characteristic data, and separate the independent components of each frequency band signal from the environmental characteristic data to generate a standardized frequency band signal distribution spectrum; a deviation direction determination module, configured to determine the power density distribution and main lobe direction of each frequency band signal based on the standardized frequency band signal distribution map, and determine the deviation main direction of each frequency band signal according to each main lobe direction; an antenna array configuration module, configured to determine reference values ​​for antenna element spacing and phase adjustment based on the deviations from the main direction and the desired gain requirements, and to determine antenna array configuration data based on the reference values ​​when it is determined that the deviation of the frequency band signal from the main direction exceeds a preset angle threshold; a collection efficiency evaluation module, configured to control the antenna array to scan uncovered areas of the frequency band signals using the antenna array configuration data, and dynamically switch between an omnidirectional capture mode and a directional capture mode according to the uncovered areas, so as to evaluate energy collection efficiency data in the current capture mode; A priority determination module is used to determine the target frequency band with sidelobe interference based on the energy collection efficiency data, and adjust the reference value of the target frequency band, and determine the signal focusing effect through the adjusted reference value to determine the capture priority of each frequency band signal.

[0007] Compared with the prior art, the embodiments of the present invention have the following advantages: (1) Through precise signal analysis, the distribution of signals in different frequency bands in the current environment can be fully and accurately understood, providing detailed and reliable basic information for subsequent antenna array configuration and signal capture; based on the power density distribution, main lobe direction and deviation from the main direction of the frequency band signal, the reference values ​​of antenna element spacing and phase adjustment are determined in combination with the expected gain requirements, and the antenna array configuration data is accurately determined based on these reference values, thereby optimizing the layout and parameter settings of the antenna array and improving the antenna's signal reception performance; (2) By controlling the antenna array to scan the uncovered range of the frequency band signal and dynamically switching between the omnidirectional capture mode and the directional capture mode according to the uncovered range, it can flexibly adapt to different signal distribution situations and improve the efficiency and comprehensiveness of signal capture; based on the energy collection efficiency data, the target frequency band with sidelobe interference is determined, and the relevant reference value is adjusted. The signal focusing effect is determined by the adjusted reference value, and then the capture priority of each frequency band signal is determined, which can effectively reduce the impact of sidelobe interference on signal capture, effectively improve the RF energy collection efficiency in complex electromagnetic environments, and realize the efficient capture and utilization of weak RF signals in multiple frequency bands. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] In order to more clearly illustrate the technical solution of the present invention, the following is a brief introduction to the drawings required for use in the implementation. Obviously, the drawings described below are only some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0009] Figure 1 This is a flow chart of an adaptive radio frequency energy capture method provided by an embodiment of the present invention; Figure 2 is a structural diagram of an adaptive radio frequency energy capture system provided by an embodiment of the present invention; Reference numerals: Among them, 10, signal spectrum generation module; 20, deviation direction determination module; 30, antenna array configuration module; 40, collection efficiency evaluation module; 50, priority determination module. DETAILED DESCRIPTION

[0010] The following is a clear and complete description of the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings and embodiments. Obviously, the embodiments described are only some embodiments of the present invention, rather than all embodiments. The purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0011] In the description of this application, the terms "first," "second," "third," etc. are used for descriptive purposes only and should not be understood to indicate or imply relative importance or implicitly specify the number of the technical features indicated. Therefore, a feature specified as "first," "second," "third," etc. may explicitly or implicitly include one or more of the features. In the description of this application, unless otherwise specified, "plurality" means two or more.

[0012] In the description of this application, it should be noted that, unless otherwise expressly specified and limited, the terms "installed", "connected" and "connected" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or an indirect connection through an intermediate medium, or it can be a communication between the two components. The terms "vertical", "horizontal", "left", "right", "up", "down" and similar expressions used herein are for illustrative purposes only, and do not indicate or imply that the system or component referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention. The term "and / or" used herein includes any and all combinations of one or more related listed items. For those of ordinary skill in the art, the specific meanings of the above terms in this application can be understood according to the specific circumstances.

[0013] In the description of this application, it should be noted that, unless otherwise defined, all technical and scientific terms used in this application have the same meanings as those commonly understood by those skilled in the art. The terms used in this specification are only for describing specific embodiments and are not intended to limit the present invention. Those skilled in the art will understand the specific meanings of the above terms in this application according to specific circumstances.

[0014] In one embodiment, if Figure 1 As shown, the first aspect of the present invention provides an adaptive radio frequency energy capture method, comprising: S1. Real-time collection of radio frequency signal data in the current environment to obtain environmental characteristic data, and separation of independent components of each frequency band signal from the environmental characteristic data to generate a standardized frequency band signal distribution map; In one embodiment, the real-time collection of radio frequency signal data in the current environment to obtain environmental characteristic data includes: Collecting radio frequency signal data in the current environment in real time through multiple antenna arrays, and performing fast Fourier transform processing on the radio frequency signal data to divide the radio frequency signal data into multiple frequency band signals according to the frequency range; Calculating a power spectral density value of each frequency band signal to combine with the phase difference between each antenna unit in the antenna array to quantify the directional angle data of each frequency band signal, and determining a signal change parameter of each frequency band signal based on each directional angle data; Based on each of the signal change parameters, the frequency band signals are grouped using a K-means clustering algorithm, and the Pearson correlation coefficient of each frequency band signal in the group is calculated as a time correlation coefficient; According to the time correlation coefficient, the frequency of occurrence of the signals in each frequency band within the unit space is counted as the spatial distribution density, which is combined with the signal change parameters and the direction angle data to form environmental characteristic data that describes the dynamic change law of the radio frequency signal data in the current environment.

[0015] Specifically, the present invention deploys multiple RF receiving antenna arrays in the target monitoring area corresponding to the current environment, each antenna array includes at least four directional antenna units, and adopts a four-element or eight-element circular array layout, and maintains a spacing of λ / 2 between adjacent antenna units, where λ is the center wavelength of the monitoring frequency band. This layout can ensure that the signals received by each antenna unit have a clear phase difference relationship, providing basic data for subsequent direction estimation; each antenna unit is arranged at a preset angle interval, and the original RF signal received by each antenna unit is synchronously collected through software-defined radio equipment to obtain the signal's time domain waveform data and reception timestamp information as RF signal data; wherein the collected time domain waveform data contains the signal's amplitude and phase information, and the timestamp information is used for data synchronization between different antenna arrays. The synchronization accuracy needs to reach the microsecond level to ensure the accuracy of subsequent phase difference calculation. The RF signal data is processed by fast Fourier transform to obtain frequency domain signal data, and the RF signal data received by the antenna is divided into multiple frequency band signals according to the frequency range of the frequency domain signal data, namely, the low frequency band (30MHz to 300MHz), the mid-frequency band (300MHz to 3GHz) and the high frequency band (3GHz to 30GHz).

[0016] The Fourier transform method is used to calculate the power spectral density of each frequency band signal. The power spectral density describes the distribution of signal power in the frequency domain. By calculating the power spectral density value, the energy distribution characteristics of each frequency band signal can be understood. By comparing the phase differences of signals received by different antenna units within the same frequency band, the angle of arrival of each frequency band signal is calculated based on the relationship between the phase difference and the antenna spacing, thus obtaining the directional angle data of each frequency band signal. It should be noted that the signal arrival angle estimation is based on the phase difference measurement principle: when a plane wave signal reaches the antenna array, antenna units at different positions will produce path differences, which in turn leads to phase differences in the received signal. The present invention measures the phase difference between adjacent antenna units and, combined with the antenna spacing and signal wavelength, calculates the signal arrival angle. This method can achieve a direction-finding accuracy of less than 5 degrees under high signal-to-noise ratio conditions. Then, based on the directional angle data and power spectral density values ​​of each frequency band signal, a two-dimensional distribution matrix of the spectrum and direction at the current moment is constructed, providing an intuitive representation for visualizing the signal environment. The rows of this matrix represent different frequency band divisions, and the columns represent 360-degree directional angle divisions. Each matrix element stores the signal strength value of the corresponding frequency band in a specific direction. By subtracting the corresponding elements of the distribution matrix at the current moment from the distribution matrix at the previous moment, we can get the signal strength change value and the signal direction change value. Dividing these two change values ​​by the time interval can obtain the signal change parameters including the signal strength change rate and the signal direction change rate.

[0017] Based on the signal change parameters of each frequency band signal, the K-means clustering algorithm is used to group frequency bands with similar change patterns. It uses the signal intensity change rate and direction change rate as feature vectors and finds the optimal cluster center through iterative calculation; and calculates the Pearson correlation coefficient of the signal intensity change of each frequency band in the group as the temporal correlation coefficient; among them, the calculation of the Pearson correlation coefficient quantifies the temporal correlation between signals of different frequency bands. A correlation coefficient close to 1 indicates that the signal changes of the two frequency bands are highly synchronized, and may come from different frequency components of the same signal source.

[0018] Based on the calculated temporal correlation coefficient, the frequency of occurrence of signals in each frequency band within a unit space is counted as the spatial distribution density. This is combined with the signal variation parameters and directional angle data for each frequency band to form environmental characteristic data that describes the dynamic variation patterns of RF signals in the current environment. The spatial distribution density can also be obtained by counting the frequency of signal occurrence within a unit solid angle.

[0019] The present invention helps to more deeply analyze the characteristics and differences of signals in each frequency band by dividing the radio frequency signals; calculates the power spectrum density value of the signal in each frequency band and quantifies the directional angle data in combination with the phase difference between antenna units, which can accurately determine the source direction of the signal in each frequency band; adopts the K-means clustering algorithm to group the signals in each frequency band, and classifies signals with similar characteristics into one group, which facilitates unified processing and analysis of the signals and can also reflect the temporal change pattern of the signals; combines the spatial distribution density, signal change parameters and directional angle data to form environmental characteristic data, which comprehensively describes the dynamic change pattern of radio frequency signal data in the current environment, provides rich and accurate information for subsequent signal processing, analysis and decision-making, and helps to improve the system's adaptability and processing effect to complex radio frequency environments.

[0020] In one embodiment, separating the independent components of each frequency band signal from the environmental characteristic data to generate a standardized frequency band signal distribution map includes: Identifying and denoising the noise characteristics of the environmental characteristic data to obtain denoised characteristic data, and setting filtering parameters to perform bandpass filtering on the denoised characteristic data to obtain effective components of the signals in each of the frequency bands; Calculating the correlation between the effective components to construct a correlation matrix, performing eigenvalue decomposition on the correlation matrix, and extracting eigenvectors with eigenvalues ​​greater than a preset characteristic threshold from the decomposition results as main components to obtain independent components of the frequency band signals; Based on each of the independent components, the amplitude of each of the frequency band signals is normalized, and the normalization results are arranged according to the frequency of each of the frequency band signals to generate a standardized frequency band signal distribution map.

[0021] Specifically, the present invention identifies and denoises the noise characteristics of environmental feature data: calculates the mean, variance and kurtosis statistical characteristic values ​​of the signal in each frequency band, where the mean reflects the DC component of the signal, the variance characterizes the power distribution of the signal, and the kurtosis describes the sharpness of the signal distribution. When the kurtosis value is in the range of 2.8 to 3.2, it indicates that the noise conforms to the Gaussian distribution characteristics and is determined to be Gaussian noise; when the kurtosis value is less than 2.5 or greater than 3.5, it indicates the presence of pulse noise or other non-Gaussian interference and is determined to be non-Gaussian noise; selects the corresponding denoising method according to the noise type to denoise the environmental feature data corresponding to the signal in each frequency band: for Gaussian noise, adopts the wavelet threshold denoising method to process it, and for non-Gaussian noise, adopts the nonlinear filtering method to process it, thereby obtaining denoised feature data. For the denoising feature data, the filtering parameters are set according to the frequency distribution range of the signals in each frequency band. The passband frequency is set to 30MHz to 300MHz for the low frequency band, 300MHz to 3GHz for the medium frequency band, and 3GHz to 30GHz for the high frequency band. The bandpass filtering method is used to filter each frequency band signal and its denoising feature data separately, and then the effective components in the signals in each frequency band are extracted.

[0022] The independent component separation process is based on the principle of statistical independence of signals. The present invention calculates the correlation between the effective components in each frequency band signal, namely the Pearson correlation coefficient, and constructs a correlation matrix based on the calculated correlation. Each element in the matrix represents the degree of linear correlation between the corresponding two frequency band signals; then the correlation matrix is ​​subjected to eigenvalue decomposition, that is, the correlation matrix is ​​converted into a diagonal form. The larger eigenvalue corresponds to the main signal component, and the smaller eigenvalue is usually related to noise or secondary components. The eigenvector with an eigenvalue greater than the preset characteristic threshold is extracted as the main component, and the original signal is linearly transformed according to the main component to separate the unrelated frequency band signal components, avoid co-channel interference and intermodulation interference, and obtain the independent components of each frequency band signal. In addition, the selection of the main component can also adopt the cumulative contribution rate criterion. When the cumulative sum of the current several largest eigenvalues ​​reaches 95% of the total eigenvalue sum, the corresponding eigenvector can represent the main component of the signal.

[0023] Based on the independent components of the signals in each frequency band, the maximum and minimum amplitude values ​​of each frequency band signal are calculated. The signal amplitude is normalized to the standard range of 0 to 1 through linear mapping. The normalized data of each frequency band is arranged in order from low to high frequency, and a two-dimensional distribution relationship between frequency and amplitude is constructed. A standardized frequency band signal distribution spectrum is generated to intuitively reflect the spectrum occupancy of the electromagnetic environment. Each data point in the spectrum represents the normalized signal strength at a specific frequency, and continuous data points form the spectrum envelope. The construction of the two-dimensional distribution relationship between frequency and amplitude can use a logarithmic frequency axis, which can clearly show the distribution characteristics of low-frequency and high-frequency signals simultaneously.

[0024] The present invention can effectively remove interference noise in the signal and improve the purity of the signal by identifying and denoising the noise characteristics of environmental feature data; setting filtering parameters for bandpass filtering can accurately extract the effective signal components of each frequency band data and avoid mutual interference between signals of different frequency bands; constructing a correlation matrix by calculating the correlation between the effective components, and performing eigenvalue decomposition to extract the main components, thereby accurately separating the independent components of each frequency band signal, which helps to gain an in-depth understanding of the essential characteristics of each frequency band signal; normalizing the amplitude of each frequency band signal, and generating a standardized frequency band signal distribution map based on the frequency arrangement normalization results, so that the amplitude and frequency information of signals of different frequency bands can be displayed and compared on a unified scale, intuitively presenting the distribution of signals of each frequency band, and facilitating subsequent analysis, evaluation and decision-making on the signal distribution.

[0025] S2. Determine the power density distribution and main lobe direction of each frequency band signal based on the standardized frequency band signal distribution map, and determine the deviation from the main direction of each frequency band signal according to each main lobe direction; In one embodiment, step S2 includes: Performing spatial filtering on the standardized frequency band signal distribution spectrum to perform beamforming analysis, and determining a weighting coefficient for each antenna unit in the antenna array based on the analysis results to calculate the array output power in each direction to obtain power distribution data; Determining power density data and main lobe directions of signals in each of the frequency bands based on the power distribution data; The angle between each main lobe direction and the normal direction of the antenna array is calculated, and when the angle exceeds a preset deviation threshold, it is determined that the main lobe direction of the corresponding frequency band signal deviates from the main direction.

[0026] Specifically, the present invention performs spatial filtering on the signals of each frequency band in the standardized frequency band signal distribution map to perform beamforming analysis. The setting of the weighting coefficient directly determines the effect of beamforming. When it is desired to receive a signal in a specific direction, it is necessary to calculate the phase difference of the signal reaching each antenna unit in that direction. Then, based on the inverse compensation value of this phase difference, the weighting coefficient is set so that the signal in the desired direction is superimposed in phase after weighted summation, while the signals in other directions cancel each other out due to phase inconsistency. The present invention sets the weighting coefficient of each antenna unit in the antenna array based on the analysis results and the desired signal direction. The coefficient can be calculated based on the array manifold vector, which can form a main lobe in the desired direction, enhance the signal reception in that direction, align the phases of the signals of each unit in the desired signal direction, and achieve coherent superposition of signals in a specific direction through weighted summation while canceling signals in other directions. All possible directional angles are traversed and the array output power in each direction is calculated to obtain power distribution data of the signals of each frequency band in different directions. This power distribution data can reflect the strength of the signal in each direction. Among them, traversing all possible direction angles is achieved by setting the angle scanning step size. In the azimuth range from 0 degrees to 360 degrees, the array output power in that direction is calculated every 1 degree. For each direction, the corresponding weighting coefficient can also be calculated based on the geometric relationship between the direction and each antenna unit, and then the received signal of each antenna is multiplied by the corresponding weight value and summed up. This process is equivalent to filtering in the spatial domain, enhancing the signal in a specific direction and suppressing interference in other directions.

[0027] The power density data and main lobe direction are determined based on the power distribution data of the signals in each frequency band. By comparing the power values ​​in all directions, the direction with the highest power can be found. This direction is the main lobe direction. The main lobe represents the actual direction of the signal source and is the direction with the best beamforming effect.

[0028] Based on the mainlobe direction of each frequency band signal, the angle between the mainlobe direction of each frequency band signal and the normal direction of the antenna array is calculated. If the calculated angle exceeds the preset deviation threshold, the frequency band signal is determined to have deviated from the main direction, and the deviation angle value and the corresponding frequency band identifier are recorded to complete the identification of the signal that deviated from the main direction. The definition of the normal direction of the antenna array is crucial for calculating the deviation angle. For a planar array, the normal direction is perpendicular to the array plane and points forward; for a circular array, the normal direction is the radial direction with the center of the circle pointing outward. The deviation angle is calculated using the vector angle formula. The dot product operation is performed on the mainlobe direction vector and the normal direction vector, and the angle value is obtained by the inverse cosine function. The setting of the preset deviation threshold needs to take into account the actual application requirements. In mobile communication base stations, the preset deviation threshold is usually set to 30 degrees. Signals exceeding this range may come from interference from adjacent cells. In radar systems, the preset deviation threshold may be set to 5 degrees for accurate target tracking.

[0029] By performing spatial filtering on the standardized frequency band signal distribution spectrum, the present invention can accurately calculate the array output power in each direction and obtain precise power distribution data, which helps to gain a deeper understanding of the energy distribution of the signal in different directions; based on the power distribution data, the power density data and main lobe direction of the signal in each frequency band are determined, which can clearly identify the direction in which the signal energy is most concentrated, and help to improve the antenna's signal reception efficiency and accuracy; by calculating the angle between the main lobe direction and the normal direction of the antenna array and comparing it with a preset deviation threshold, it can promptly detect the deviation of the main lobe direction of the frequency band signal from the main direction, which helps to take measures in advance to adjust the antenna array configuration, ensure that the signal can be effectively received, and improve the stability and reliability of the system.

[0030] In one embodiment, determining the power density data and main lobe direction of each frequency band signal based on the power distribution data includes: Based on the power distribution data, the direction corresponding to the maximum power in each frequency band signal is used as the main lobe direction, and the angle position where the power drops to half of the maximum power is searched on both sides from each main lobe direction to determine the main lobe width of each frequency band signal; The sum of the power values ​​in all directions within each main lobe width is calculated, and then divided by the solid angle corresponding to each main lobe direction to obtain the power density data of the signal in each frequency band.

[0031] Specifically, based on the power distribution data of each frequency band signal, the present invention defines the direction corresponding to the maximum power as its mainlobe direction. The method then searches for the angular position where the power drops to half of the maximum value from the mainlobe direction of each frequency band signal. This angular range is defined as the mainlobe width of the signal in that frequency band. The mainlobe width is determined using a power drop method. Starting from the maximum power value in the mainlobe direction, the method searches for the position where the power drops to half of the maximum value from both sides. The angular range between these two positions is the mainlobe width. The mainlobe width reflects the directional resolution of the beam; a narrower width indicates a higher directional resolution.

[0032] The power density data for all frequency bands can be obtained by calculating the sum of the power values ​​in all directions within the main lobe width of each frequency band signal and dividing it by the solid angle corresponding to the main lobe. The calculation of power density involves the concept of solid angle, which describes the angular range in three-dimensional space and is measured in steradians. The solid angle corresponding to the main lobe can be approximated by multiplying the angular range of the main lobe width in azimuth and elevation. The power values ​​in all directions within the main lobe range are accumulated to obtain the total power, which is then divided by the solid angle to obtain the power density. Power density represents the power distribution within a unit solid angle and is an important indicator for evaluating signal strength.

[0033] The present invention determines the main lobe direction by searching for the direction corresponding to the maximum power of the signal in each frequency band in the power distribution data, which can accurately find the direction where the signal energy is most concentrated, helping to improve the efficiency of signal reception and transmission; the main lobe width is determined by searching for the angular position where the power drops to half of the maximum value on both sides from the main lobe direction, which can intuitively reflect the distribution range of the signal energy in space. The main lobe width information is of great significance for evaluating the coverage range, anti-interference ability and other aspects of the signal; by calculating the power density data, the energy distribution of the signal in space can be more accurately described, which helps to analyze the intensity differences of the signal in different areas.

[0034] S3. Determine reference values ​​for antenna element spacing and phase adjustment based on the deviations from the main direction and the expected gain requirements, and determine antenna array configuration data based on the reference values ​​when it is determined that the deviation of the frequency band signal from the main direction exceeds a preset angle threshold; In one embodiment, step S3 includes: Determining the deviation angle of each frequency band signal according to each deviation from the main direction, and combining it with the expected gain requirement, calculating the array aperture size and phase compensation amount required for each frequency band signal to achieve the expected gain requirement, as reference values ​​for the antenna element spacing and phase adjustment; Calculating a composite directivity pattern of the adjusted array based on the reference value, and obtaining actual gains in each of the deviated main directions from the composite directivity pattern to evaluate power loss data of signals in each of the frequency bands; If the deviation angle of a frequency band signal exceeds a preset angle threshold and its power loss data exceeds a preset loss threshold, it is determined that the geometric configuration of the antenna array needs to be adjusted, and the antenna array configuration data is determined by the reference value.

[0035] Specifically, the correspondence between deviation angle and gain attenuation is a core consideration in array antenna design. When the signal is incident from a direction deviating from the main axis, the effective aperture of the array will decrease, resulting in a decrease in gain. This relationship follows the cosine law, that is, the effective aperture is equal to the physical aperture multiplied by the cosine value of the incident angle. Then, when the deviation angle is 30 degrees, the effective aperture drops to 0.866 times the original value, and the corresponding gain loss is about 1.25dB. In practical applications, this loss needs to be compensated by increasing the array aperture.

[0036] The present invention determines the deviation angle of each frequency band signal based on the difference between its actual direction and the main lobe direction, and uses the corresponding relationship between the deviation angle and gain attenuation to calculate the array aperture size required to achieve the desired gain at the deviation angle, where the array aperture size is equal to the number of antenna elements multiplied by the element spacing. When the deviation angle is 30 degrees, the effective aperture is reduced to 0.866 times the original, and the corresponding gain loss is about 1.25dB. This loss needs to be compensated by increasing the array aperture in practical applications. The calculation of the array aperture size is based on the basic relationship between gain and aperture, and the gain is proportional to the ratio of the array aperture area to the square of the wavelength. The optimal spacing value of the antenna elements is determined to be an integer multiple of half a wavelength based on the wavelength of the signal frequency. If the desired gain is 20dBi, the operating frequency is 2.4GHz, and the corresponding wavelength is 12.5cm, when the signal deviates by 45 degrees, in order to compensate for the 3dB gain loss, the array aperture needs to be increased from the original 8 wavelengths to 11 wavelengths, which means that more antenna elements need to be added or the element spacing needs to be increased.

[0037] At the same time, the phase compensation required for each antenna element relative to the reference element is calculated based on the deviation angle, resulting in reference values ​​for antenna element spacing and phase adjustment (i.e., including the number of array elements, element spacing, and phase compensation). The calculation of phase compensation is based on the principle of path difference. When a signal is incident at a deviation angle θ, the path difference between adjacent elements receiving the signal is d×sin(θ), where d is the element spacing. The phase difference corresponding to this path difference needs to be compensated by a phase shifter. If the deviation angle is 30 degrees and the element spacing is half a wavelength, the phase compensation is 90 degrees. Modern phased arrays typically use digital phase shifters, adjusting phase in steps of 22.5 or 11.25 degrees.

[0038] Based on the calculated reference value, the adjusted composite pattern of the array is calculated by superimposing the radiation fields of each antenna element in the deviation direction. The actual gain value in the deviation direction is read from the composite pattern, and the power loss data of the signals in each frequency band is evaluated by comparing the difference between the actual gain and the expected gain. The calculation of the composite pattern involves the principle of vector superposition. The electric field strength generated by the radiation field of each antenna element at a certain point in space has amplitude and phase characteristics. By adjusting the excitation phase of each element, the contributions of each element in the desired direction are superimposed in phase to form the main lobe. The actual gain is read by finding the gain value corresponding to the deviation direction in the pattern. This process is similar to reading the altitude value at a specific location in a contour map. The power loss assessment can be quantified using a decibel scale. The difference between the actual gain and the expected gain directly reflects the degree of degradation in system performance.

[0039] If the deviation angle of a frequency band signal exceeds the preset angle threshold and its power loss data exceeds the preset loss threshold, it is determined that the geometric configuration of the antenna array needs to be adjusted, and the antenna array configuration data is determined by the calculated reference value. Among them, the setting of the threshold needs to comprehensively consider the system requirements and actual constraints. The preset angle threshold is usually determined according to the coverage requirements of the system. For example, the horizontal half-power beamwidth of the base station antenna is generally 65 degrees, and the preset angle threshold can be set to 32.5 degrees. When both conditions are met at the same time, it indicates that the existing array configuration can no longer meet the performance requirements and the geometric configuration needs to be adjusted, such as changing the array arrangement or increasing the number of antenna elements.

[0040] In one embodiment, the calculation of antenna array configuration data may be performed by the following steps: A compensation coefficient is calculated based on the deviation angle of the signal in each frequency band. This compensation coefficient is equal to the inverse of the cosine of the deviation angle. The new element spacing is obtained by multiplying the reference antenna array element spacing by the compensation coefficient. Array synthesis techniques (such as Chebyshev synthesis or Taylor synthesis) are used to determine the excitation amplitude ratio of each antenna element based on the gain requirements in each direction of the power distribution. This results in an adjusted phase parameter baseline value to meet the specified radiation pattern requirements. The cosine relationship between the signal deviation angle and the effective aperture is a fundamental principle in array antenna compensation design. When an electromagnetic wave is incident on an antenna array at an angle off-normal, the array's effective receiving area decreases according to the cosine of the incident angle. For example, if the signal is incident at a 30-degree deviation, the cosine value is 0.866, meaning the effective aperture is only 86.6% of that for head-on incidence. The compensation coefficient, the inverse of the cosine value, needs to be 1.15 in this example, meaning the physical aperture must be expanded by 15% to maintain the original receiving capability. Adjusting the antenna element spacing directly affects the spatial resolution of the array. The original design used half-wavelength spacing, operating in the 2.4 GHz band, with a spacing of 6.25 cm. When compensating for a 45-degree misalignment angle, the compensation factor reaches 1.414, requiring a new element spacing of 8.84 cm. While increasing the spacing compensates for the misalignment angle, it also reduces the array's resolution in other directions, demonstrating the trade-offs in antenna design. The excitation amplitude ratio is determined based on the specific power distribution requirements. Different application scenarios have different requirements for beam shape: broadcast applications favor wide beam coverage, while point-to-point communications require narrow beams. By adjusting the excitation amplitude of each antenna element, the mainlobe width and sidelobe levels can be controlled. For example, using Taylor distribution amplitude weighting, with the excitation amplitude set to 1 for the center element and gradually decreasing to 0.3 for the edge elements, the sidelobe level can be suppressed to 25 dB below the mainlobe.

[0041] Based on the adjusted phase parameter reference value, the new physical position coordinates of each antenna element are calculated with the array center as the origin. The required phase delay angle value for each element is obtained by dividing the distance difference between the new physical position coordinates and the origin by the signal wavelength and then multiplying it by 360 degrees. The phase delay angle value is quantized as an integer multiple of the phase shifter's minimum step unit to obtain the physical position coordinates and phase delay setting value of each antenna element. It should be noted that the calculation of the phase delay angle value is based on the path difference principle: it uses the array center as the reference origin. The distance from each antenna element to the origin is different, resulting in a phase difference in the received signal. The phase difference increases by 360 degrees for each wavelength increase in the distance difference. In actual calculations, if an antenna element is 50 cm from the origin and the operating wavelength is 12.5 cm, the phase delay is 1440 degrees, which is equivalent to 4 complete cycles. This periodic characteristic means that the actual phase shifter only needs to achieve a phase adjustment range of 0 to 360 degrees. Modern digital phase shifters typically use 5-bit or 6-bit control, corresponding to 32 or 64 discrete phase states. If a 5-bit phase shifter is used, the minimum step is 11.25 degrees. When the calculated theoretical phase delay is 157 degrees, it needs to be quantized to the nearest discrete value of 156.25 degrees, corresponding to 14 step units. Although this quantization error is inevitable, it can be controlled within an acceptable range through reasonable design.

[0042] Based on the physical position coordinates and phase delay setting values ​​of each antenna unit and the new element spacing value, an array configuration parameter set containing the antenna unit number, position coordinates, phase delay setting values, and new element spacing values ​​is constructed. By integrating the configuration parameters of all antenna units and adding their operating frequency and array type identification information, the antenna array configuration data is generated. Among them, the unit number is used for unique identification, the position coordinates define the physical layout, the phase delay setting value controls the beam pointing, and the additional operating frequency information ensures that the configuration matches the specific frequency band. The array type identification distinguishes different configurations such as linear array, planar array, or circular array. This systematic configuration data structure facilitates subsequent array control and optimization.

[0043] The present invention determines the reference values ​​of antenna element spacing and phase adjustment according to the deviation of the main direction of the signal in each frequency band and the expected gain requirements, and can optimize the specific conditions of the signals in different frequency bands to ensure that the antenna can achieve the expected gain effect in each frequency band and improve the overall performance of the antenna; the synthetic radiation pattern of the adjusted array is calculated based on the reference value, and the actual gain in each deviation from the main direction is obtained to evaluate the power loss data, which can intuitively understand the performance change of the antenna when it deviates from the main direction, and provide an accurate basis for subsequent adjustment and optimization; when there is a frequency band signal with a deviation angle exceeding the preset angle threshold and the power loss data exceeds the preset loss threshold, the antenna array configuration data is determined by the reference value, and measures can be taken in time to adjust the antenna array to solve the problem of excessive power loss caused by the signal deviation from the main direction, thereby ensuring stable transmission and reception of the signal.

[0044] S4. Controlling the antenna array to scan uncovered areas of the frequency band signals using the antenna array configuration data, and dynamically switching between an omnidirectional capture mode and a directional capture mode according to the uncovered areas to evaluate energy collection efficiency data in the current capture mode; In one embodiment, step S4 includes: Based on the antenna array configuration data, the radiation pattern is adjusted through a phase control instruction to scan the intensity of the signal in each frequency band point by point to obtain spatial distribution data of the multi-frequency band signal; determining, based on the spatial distribution data, a spatial region where the signal strength is lower than the receiver sensitivity as an uncovered range, and calculating a coverage integrity index based on the uncovered range; Adaptively switching the omnidirectional capture mode or the directional capture mode as the current capture mode according to the coverage integrity indicator; According to the current capture mode, the ratio of the total received power to the array aperture area is calculated to obtain energy collection efficiency data.

[0045] In one embodiment, adaptively switching the omnidirectional capture mode or the directional capture mode as the current capture mode based on the coverage integrity indicator includes: Based on the coverage integrity index and signal strength distribution, determine whether to switch to the directional capture mode. If the coverage integrity index is lower than the preset integrity threshold or the signal strength is concentrated in the preset direction, switch to the directional capture mode as the current capture mode. Otherwise, maintain the omnidirectional capture mode as the current capture mode and generate a capture mode selection result.

[0046] Specifically, phase control of the phase shifter is the core mechanism for achieving antenna array beam scanning. Each phase shifter adjusts the phase by changing the electrical length of the signal passing through it, thereby controlling the beam's direction. Based on the antenna array configuration data and utilizing the phase control principles of array antenna theory, the present invention generates phase control instructions. These instructions are sent to the phase shifters of each antenna element to adjust the radiation pattern. The system then scans point by point within the azimuth and elevation ranges according to a preset scanning step size, recording the signal strength values ​​for each frequency band at each scanning point to obtain spatial distribution data for the multi-band signals. Among them, spatial scanning uses a rasterization method to cover the entire monitoring area: the azimuth angle ranges from 0 degrees to 360 degrees, with a scanning point set every 5 degrees; the pitch angle ranges from -60 degrees to 60 degrees, also with a step size of 5 degrees, thus forming a 72×25 spatial grid of 1,800 scanning points; at each scanning point, the system stays for enough time to collect signal strength data of each frequency band. Due to the longer wavelength of the low-frequency band, the residence time needs to be longer to obtain stable measurement values; the high-frequency band can complete sampling quickly, so that the spatial distribution data of the generated multi-band signals presents complex three-dimensional characteristics, and the signal strength of each frequency band signal in different directions reflects the spatial distribution of the signal source of the frequency band. For example, the mobile communication base station signal is mainly concentrated in the horizontal direction, while the satellite signal comes from the high elevation angle direction. By superimposing the spatial distribution data of each frequency band, a complete electromagnetic environment situation map can be obtained.

[0047] By analyzing the spatial distribution data of multi-band signals, spatial areas where signal strength is lower than the receiver sensitivity are identified as uncovered areas, and the proportion of uncovered areas to the total scanned space is calculated as a coverage integrity indicator. It should be noted that receiver sensitivity is a key parameter for determining whether a signal is detectable. It defines the minimum signal power level that a receiver can reliably detect. Receiver sensitivity varies for different frequency bands. In the 2.4 GHz band, the typical receiver sensitivity is -90 dBm. In the 28 GHz millimeter wave band, due to the increased noise figure, the sensitivity drops to -75 dBm. When the signal strength of a spatial area is lower than the receiver sensitivity of the corresponding frequency band, it indicates that the area is uncovered.

[0048] When coverage integrity is above 80% and the signal distribution is relatively uniform in all directions, omnidirectional acquisition mode can effectively collect signal energy from all directions. Conversely, when the signal is primarily concentrated in a specific sector, such as when there is a strong signal only within the range of 90 to 180 degrees, directional acquisition mode can achieve higher received power by concentrating the array gain in that direction. Therefore, the present invention determines whether to switch to directional acquisition mode based on the coverage integrity index and signal strength distribution. If the coverage integrity index is below a preset integrity threshold or the signal strength distribution is concentrated in a specific direction, the system switches to directional acquisition mode. Otherwise, the system maintains omnidirectional acquisition mode, resulting in the current acquisition mode selection result.

[0049] Based on the current capture mode, the total received power is calculated by summing the received power of all frequency bands within the coverage area. The ratio of the total received power to the physical aperture area of ​​the antenna array is then calculated as the actual power density. The ratio of the actual power density to the electromagnetic wave power density in free space is defined as the energy collection efficiency, completing the calculation of the energy collection efficiency for the current mode. The total received power is obtained by integrating the power of all frequency bands within the coverage area. The electromagnetic wave power density in free space depends on the distribution of signal sources in the environment. Typical values ​​are 100 milliwatts per square meter in urban environments (high-density signal areas), 25 milliwatts per square meter in suburban areas / towns (medium-density signal areas), and 2.5 milliwatts per square meter in rural areas / open areas (low-density signal areas). This value can be determined based on actual conditions.

[0050] By scanning the signal strength of each frequency band point by point and determining the uncovered range, the present invention can accurately identify areas with weak signals, and then adjust the capture mode in a targeted manner, effectively improving the integrity of signal coverage, reducing signal blind spots, and ensuring communication quality; by dynamically adjusting the capture mode and optimizing the array configuration, it can significantly improve energy collection efficiency and achieve efficient utilization of complex electromagnetic environments.

[0051] S5. Determine a target frequency band with sidelobe interference based on the energy collection efficiency data, adjust a reference value of the target frequency band, and determine a signal focusing effect using the adjusted reference value to determine a capture priority of signals in each frequency band; In one embodiment, step S5 includes: Calculating a power ratio of a main lobe to a side lobe in the energy collection efficiency data; if the power ratio exceeds a preset ratio threshold, determining that side lobe interference exists, and using a frequency band signal having side lobe interference as a target frequency band; The reference value of the target frequency band is adjusted using a Chebyshev weighting method, and the main lobe gain and side lobe suppression of the radiation pattern are calculated based on the adjusted reference value to obtain optimized signal focusing effect data; According to the signal focusing effect data, the potential energy contribution value of each of the frequency band signals is calculated to determine the capture priority of each of the frequency band signals through sorting.

[0052] Specifically, the present invention decomposes and analyzes the energy collection efficiency data, calculates the received power in the main lobe direction and the side lobe direction respectively, and obtains a power ratio by dividing the side lobe power by the main lobe power. If this ratio exceeds a preset ratio threshold, it is determined that side lobe interference exists, and the frequency band identifier causing the interference is recorded and its corresponding frequency band signal is used as the target frequency band. For example, in a 16-element linear array, if the received power in the main lobe direction is 100 milliwatts and the total received power in all side lobe directions reaches 30 milliwatts, the power ratio is 0.3. When this ratio exceeds the preset threshold of 0.2, it indicates that the side lobe interference has seriously affected the directionality of energy collection. Side lobe interference manifests itself in various forms in real environments. In urban environments, reflected signals from high-rise buildings often enter the antenna system from the side lobe direction. Near airports, radar signals from different directions may exist simultaneously, causing multi-source interference. Such interference not only reduces the signal-to-noise ratio in the main lobe direction, but also causes energy dispersion, reducing the overall collection efficiency.

[0053] For the target frequency bands with recorded sidelobe interference, the Chebyshev weighting method is used to adjust their reference values ​​to reduce the sidelobe levels. The mainlobe gain and sidelobe suppression of the directivity pattern are then recalculated based on the adjusted reference values ​​to obtain optimized signal focusing effect data. The Chebyshev weighting method can suppress all sidelobes to the same low level while keeping the mainlobe gain basically unchanged. The weighting coefficients are calculated based on Chebyshev polynomials. The amplitude weight of each antenna element is determined by setting the desired sidelobe level. For example, when the sidelobe level is required to be 30dB lower than the mainlobe, the weight of the center element is 1, and the weight of the edge element is reduced to 0.2. The directivity pattern can be calculated using array antenna theory. The mainlobe gain represents the signal amplification capability of the antenna array in the desired direction, while the sidelobe suppression quantifies the power difference between the mainlobe and the highest sidelobe.

[0054] The mainlobe gain value of each frequency band signal in the optimized signal focusing effect data is extracted and combined with its signal power density to calculate its potential energy contribution value. The present invention uses the product of the mainlobe gain value and the signal power density as the potential energy contribution value of each frequency band. Then, the capture priority of each frequency band signal is determined from high to low according to the potential energy contribution value, and antenna units and processing time are preferentially allocated to high-contribution frequency bands. Finally, the sidelobe interference processing results, the optimized signal focusing effect data, and the frequency band capture priority configuration are integrated to form a complete configuration file containing antenna weight parameters, frequency band allocation scheme, and expected efficiency improvement value, and the final energy collection efficiency improvement plan is determined. Among them, the antenna weight parameters include the amplitude and phase settings of each antenna unit in different frequency bands (determined by the sidelobe interference processing results, that is, the adjusted reference value); the frequency band allocation scheme clarifies the priority order and resource occupancy ratio of the signals in each frequency band; the expected efficiency improvement value is obtained through simulation or theoretical calculation to provide a reference for actual deployment. In a typical case, by implementing this optimization solution, the energy collection efficiency was increased from the initial 40% to 65%, significantly improving the system's energy utilization and ensuring optimal energy collection performance in complex electromagnetic environments.

[0055] As a solution for improving energy collection efficiency, the present invention can accurately identify the target frequency band with sidelobe interference by calculating the power ratio of the main lobe and sidelobe in the energy collection efficiency data, which helps to solve the interference problem in a targeted manner, avoid unnecessary adjustments to the entire antenna system, and improve the system optimization efficiency; the Chebyshev weighting method is used to adjust the reference value of the target frequency band, which can effectively improve the mainlobe gain and sidelobe suppression of the radiation pattern, thereby optimizing the signal focusing effect, reducing the interference of the sidelobe to other directions, and improving the signal reception quality; the potential energy contribution value of each frequency band signal is calculated according to the optimized signal focusing effect data, and the capture priority is determined accordingly, which helps the system to prioritize the capture of frequency band signals with large energy contribution when resources are limited, improve the overall efficiency of energy collection, and meet the system's needs for signals in different frequency bands.

[0056] In the embodiment of the present application, based on the problem of how to improve the capture efficiency of RF energy when the distribution of environmental signals changes, an adaptive RF energy capture method is designed. The method generates a standardized spectrum map by separating the independent frequency band components of the environmental RF signal in real time; extracts the power density and main lobe direction of each frequency band, and calculates the signal source deviation angle; dynamically adjusts the spacing and phase of the antenna array according to the deviation angle and gain requirements; scans the signal blind area by switching between omnidirectional / directional modes, and evaluates the energy collection efficiency in real time; identifies the sidelobe interference frequency band, adjusts the parameters to optimize the signal focusing, and dynamically sets the capture priority, so as to effectively improve the RF energy collection efficiency in complex electromagnetic environments and realize the efficient capture and utilization of weak RF signals in multiple frequency bands.

[0057] It should be noted that although the steps in the above flowchart are shown in sequence as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders.

[0058] In another embodiment, if Figure 2 As shown, the second aspect of the present invention provides an adaptive radio frequency energy capture system, comprising: The signal spectrum generation module 10 is used to collect radio frequency signal data in the current environment in real time to obtain environmental characteristic data, and separate the independent components of each frequency band signal from the environmental characteristic data to generate a standardized frequency band signal distribution spectrum; a deviation direction determining module 20, configured to determine the power density distribution and main lobe direction of each frequency band signal based on the standardized frequency band signal distribution map, and determine the deviation main direction of each frequency band signal according to each main lobe direction; The antenna array configuration module 30 is configured to determine reference values ​​for antenna element spacing and phase adjustment based on the deviations from the main direction and the desired gain requirements, and to determine antenna array configuration data based on the reference values ​​when it is determined that the deviation of the frequency band signal from the main direction exceeds a preset angle threshold. a collection efficiency evaluation module 40, configured to control the antenna array to scan uncovered areas of the frequency band signals using the antenna array configuration data, and dynamically switch between an omnidirectional capture mode and a directional capture mode according to the uncovered areas, so as to evaluate energy collection efficiency data in the current capture mode; The priority determination module 50 is used to determine the target frequency band with sidelobe interference based on the energy collection efficiency data, and adjust the reference value of the target frequency band, and determine the signal focusing effect through the adjusted reference value to determine the capture priority of each frequency band signal.

[0059] It should be noted that each module in the above-mentioned adaptive RF energy capture system can be implemented in whole or in part through software, hardware, and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules. For the specific definition of an adaptive RF energy capture system, please refer to the definition of an adaptive RF energy capture method above. The two have the same functions and effects and will not be repeated here.

[0060] In summary, the present invention relates to the field of information technology, and discloses an adaptive RF energy capture method and system, which collects RF signals in the environment and separates the independent components of each frequency band signal from it to determine the power density distribution and main lobe direction of each frequency band signal, and then determines the deviation of each frequency band signal from the main direction; combines the expected gain requirements of the current environment to determine the reference values ​​of antenna element spacing and phase adjustment, thereby determining the antenna array configuration data and controlling the antenna array to scan the uncovered range of each frequency band signal, and then dynamically switches the full / directional capture mode, evaluates the energy collection efficiency data in the current capture mode to determine the target frequency band with sidelobe interference, and adjusts its reference value, and determines the signal focusing effect through the adjusted reference value to determine the capture priority of each frequency band signal, effectively improving the RF energy collection efficiency in complex electromagnetic environments, and realizing efficient capture and utilization of multi-band weak RF signals.

[0061] Each embodiment in this specification is described in a progressive manner, and the same or similar parts of each embodiment can be directly referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment. It should be noted that the various technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the various technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0062] The above-described embodiments merely represent several preferred implementations of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the patent. It should be noted that a person skilled in the art could make several improvements and substitutions without departing from the technical principles of the present invention, and these improvements and substitutions should also be considered within the scope of protection of the present application. Therefore, the scope of protection of the present patent application shall be based on the scope of protection of the claims.

Claims

1. An adaptive radio frequency energy capture method, characterized in that: include: Collect radio frequency signal data in the current environment in real time to obtain environmental characteristic data, and separate the independent components of each frequency band signal from the environmental characteristic data to generate a standardized frequency band signal distribution map; Determining the power density distribution and main lobe direction of each frequency band signal based on the standardized frequency band signal distribution map, and determining the deviation from the main direction of each frequency band signal according to each main lobe direction; Determining reference values ​​for antenna element spacing and phase adjustment based on each of the deviations from the main direction and the desired gain requirements, and determining antenna array configuration data based on each of the reference values ​​when it is determined that the deviation of the frequency band signal from the main direction exceeds a preset angle threshold; Controlling the antenna array to scan uncovered areas of the frequency band signals through the antenna array configuration data, and dynamically switching between an omnidirectional capture mode and a directional capture mode according to the uncovered areas, so as to evaluate energy collection efficiency data in the current capture mode; Based on the energy collection efficiency data, the target frequency band with sidelobe interference is determined, and the reference value of the target frequency band is adjusted. The signal focusing effect is determined by the adjusted reference value to determine the capture priority of each frequency band signal.

2. The adaptive radio frequency energy capture method according to claim 1, wherein: The real-time collection of radio frequency signal data in the current environment to obtain environmental characteristic data includes: Collecting radio frequency signal data in the current environment in real time through multiple antenna arrays, and performing fast Fourier transform processing on the radio frequency signal data to divide the radio frequency signal data into multiple frequency band signals according to the frequency range; Calculating a power spectral density value of each frequency band signal to combine with the phase difference between each antenna unit in the antenna array to quantify the directional angle data of each frequency band signal, and determining a signal change parameter of each frequency band signal based on each directional angle data; Based on each of the signal change parameters, the frequency band signals are grouped using a K-means clustering algorithm, and the Pearson correlation coefficient of each frequency band signal in the group is calculated as a time correlation coefficient; According to the time correlation coefficient, the frequency of occurrence of the signals in each frequency band within the unit space is counted as the spatial distribution density, which is combined with the signal change parameters and the direction angle data to form environmental characteristic data that describes the dynamic change law of the radio frequency signal data in the current environment.

3. The adaptive radio frequency energy capture method according to claim 2, wherein: The step of separating the independent components of each frequency band signal from the environmental characteristic data and generating a standardized frequency band signal distribution map includes: Identifying and denoising the noise characteristics of the environmental characteristic data to obtain denoised characteristic data, and setting filtering parameters to perform bandpass filtering on the denoised characteristic data to obtain effective components of the signals in each of the frequency bands; Calculating the correlation between the effective components to construct a correlation matrix, performing eigenvalue decomposition on the correlation matrix, and extracting eigenvectors with eigenvalues ​​greater than a preset characteristic threshold from the decomposition results as main components to obtain independent components of the frequency band signals; Based on each of the independent components, the amplitude of each of the frequency band signals is normalized, and the normalization results are arranged according to the frequency of each of the frequency band signals to generate a standardized frequency band signal distribution map.

4. The adaptive radio frequency energy capture method according to claim 1, wherein: The determining, based on the standardized frequency band signal distribution map, the power density distribution and the main lobe direction of each frequency band signal, and determining the deviation from the main direction of each frequency band signal according to each main lobe direction, includes: Performing spatial filtering on the standardized frequency band signal distribution spectrum to perform beamforming analysis, and determining a weighting coefficient for each antenna unit in the antenna array based on the analysis results to calculate the array output power in each direction to obtain power distribution data; Determining power density data and main lobe directions of signals in each of the frequency bands based on the power distribution data; The angle between each main lobe direction and the normal direction of the antenna array is calculated, and when the angle exceeds a preset deviation threshold, it is determined that the main lobe direction of the corresponding frequency band signal deviates from the main direction.

5. The adaptive radio frequency energy capture method according to claim 4, characterized in that: The determining the power density data and the main lobe direction of each frequency band signal based on the power distribution data includes: Based on the power distribution data, the direction corresponding to the maximum power in each frequency band signal is used as the main lobe direction, and the angle position where the power drops to half of the maximum power is searched on both sides from each main lobe direction to determine the main lobe width of each frequency band signal; The sum of the power values ​​in all directions within each main lobe width is calculated, and then divided by the solid angle corresponding to each main lobe direction to obtain the power density data of the signal in each frequency band.

6. The adaptive radio frequency energy capture method according to claim 1, characterized in that: Determining reference values ​​for antenna element spacing and phase adjustment based on each of the deviations from the main direction and the expected gain requirement, and determining antenna array configuration data based on each of the reference values ​​when it is determined that the deviation of the frequency band signal from the main direction exceeds a preset angle threshold, includes: Determining the deviation angle of each frequency band signal according to each deviation from the main direction, and combining it with the expected gain requirement, calculating the array aperture size and phase compensation amount required for each frequency band signal to achieve the expected gain requirement, as reference values ​​for the antenna element spacing and phase adjustment; Calculating a composite directivity pattern of the adjusted array based on the reference value, and obtaining actual gains in each of the deviated main directions from the composite directivity pattern to evaluate power loss data of signals in each of the frequency bands; If the deviation angle of a frequency band signal exceeds a preset angle threshold and its power loss data exceeds a preset loss threshold, it is determined that the geometric configuration of the antenna array needs to be adjusted, and the antenna array configuration data is determined by the reference value.

7. The adaptive radio frequency energy capture method according to claim 1, characterized in that: The controlling the antenna array to scan the uncovered range of each frequency band signal through the antenna array configuration data, and dynamically switching the omnidirectional capture mode and the directional capture mode according to the uncovered range to evaluate the energy collection efficiency data in the current capture mode, includes: Based on the antenna array configuration data, the radiation pattern is adjusted through a phase control instruction to scan the intensity of the signal in each frequency band point by point to obtain spatial distribution data of the multi-frequency band signal; determining, based on the spatial distribution data, a spatial region where the signal strength is lower than the receiver sensitivity as an uncovered range, and calculating a coverage integrity index based on the uncovered range; Adaptively switching the omnidirectional capture mode or the directional capture mode as the current capture mode according to the coverage integrity indicator; According to the current capture mode, the ratio of the total received power to the array aperture area is calculated to obtain energy collection efficiency data.

8. The adaptive radio frequency energy capture method according to claim 7, characterized in that: Adaptively switching the omnidirectional capture mode or the directional capture mode as the current capture mode according to the coverage integrity indicator includes: Based on the coverage integrity index and signal strength distribution, determine whether to switch to the directional capture mode. If the coverage integrity index is lower than the preset integrity threshold or the signal strength is concentrated in the preset direction, switch to the directional capture mode as the current capture mode. Otherwise, maintain the omnidirectional capture mode as the current capture mode and generate a capture mode selection result.

9. The adaptive radio frequency energy capture method according to claim 1, wherein: The step of determining a target frequency band having sidelobe interference based on the energy collection efficiency data, adjusting a reference value of the target frequency band, and determining a signal focusing effect by using the adjusted reference value to determine a capture priority of signals in each frequency band includes: Calculating a power ratio of a main lobe to a side lobe in the energy collection efficiency data; if the power ratio exceeds a preset ratio threshold, determining that side lobe interference exists, and using a frequency band signal having side lobe interference as a target frequency band; The reference value of the target frequency band is adjusted using a Chebyshev weighting method, and the main lobe gain and side lobe suppression of the radiation pattern are calculated based on the adjusted reference value to obtain optimized signal focusing effect data; According to the signal focusing effect data, the potential energy contribution value of each of the frequency band signals is calculated to determine the capture priority of each of the frequency band signals through sorting.

10. An adaptive radio frequency energy capture system, characterized in that: include: The signal spectrum generation module is used to collect the radio frequency signal data in the current environment in real time, obtain environmental characteristic data, and separate the independent components of each frequency band signal from the environmental characteristic data to generate a standardized frequency band signal distribution spectrum; a deviation direction determination module, configured to determine the power density distribution and main lobe direction of each frequency band signal based on the standardized frequency band signal distribution map, and determine the deviation main direction of each frequency band signal according to each main lobe direction; an antenna array configuration module, configured to determine reference values ​​for antenna element spacing and phase adjustment based on the deviations from the main direction and the desired gain requirements, and to determine antenna array configuration data based on the reference values ​​when it is determined that the deviation of the frequency band signal from the main direction exceeds a preset angle threshold; a collection efficiency evaluation module, configured to control the antenna array to scan uncovered areas of the frequency band signals using the antenna array configuration data, and dynamically switch between an omnidirectional capture mode and a directional capture mode according to the uncovered areas, so as to evaluate energy collection efficiency data in the current capture mode; A priority determination module is used to determine the target frequency band with sidelobe interference based on the energy collection efficiency data, and adjust the reference value of the target frequency band, and determine the signal focusing effect through the adjusted reference value to determine the capture priority of each frequency band signal.

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