Method and system for focusing energy regulation of electromagnetic wave phased array of dipole array

Abstract

The present application relates to the field of phased array focusing regulation, and more particularly, the present application discloses a kind of electromagnetic wave phased array focusing energy regulation method and system of dipole array.First, based on medical image data and biological tissue relaxation parameter, construct the wideband complex frequency domain dielectric property space distribution reflecting nonlinear dispersion characteristics, based on the dynamic boundary smoothing of local space information entropy feature, the parameter mutation caused by image artifact is inhibited, and the corrected dielectric property distribution is obtained.The distribution is replaced by forced reverse to introduce virtual negative thermodynamic dissipation factor to static conductivity, excitation is injected into the target region, and pseudo-inverse electromagnetic evolution is carried out, so that the wave front information reaching each radiation port section is calculated from the target region, and the delay phase compensation amount and energy distribution weight coefficient for accurately controlling the radiation channel of phased array are obtained.The method can effectively improve the energy focusing accuracy and efficiency of the deep target region of biological tissue.

Description

Technical Field

[0001] This invention relates to the field of phased array focusing and control. More specifically, this invention relates to a method and system for focusing energy of electromagnetic wave phased arrays using dipole arrays. Background Technology

[0002] In the field of electromagnetic wave phased array focusing energy modulation for biological tissues, existing technical solutions generally rely on modeling medical image data of the target area. Typically, the image grayscale values ​​are statically and linearly mapped to tissue conductivity and dielectric constant parameters at a certain fixed frequency, simplifying biological tissues with significant frequency-varying characteristics into idealized, non-frequency-response homogeneous or simple layered medium models.

[0003] Furthermore, due to the limitations of medical imaging equipment resolution, grayscale artifacts are generated in the interface areas of different tissues during the imaging process. These artifacts are directly mapped as sharp abrupt changes in the dielectric parameter space, resulting in non-physical scattering and oscillation noise in subsequent electromagnetic field numerical simulations. Consequently, any wavefront modulation calculations use distorted data, leading to a decrease in the focusing accuracy of the electromagnetic wave phased array.

[0004] To achieve energy focusing in deep target areas, traditional methods often draw on the time reversal principle from optics and acoustics. However, this principle relies on the complete reversibility of the wave process, which cannot be satisfied in biological media with high electrical conductivity and significant Joule heat loss.

[0005] When attempting to reverse-engineer the wavefront signal arriving at the array port on the body surface from the deep target area, the positive conductivity of the tissue causes the wavefront energy to decay exponentially along the propagation path. This results in the amplitude of the reverse signal arriving at the port potentially being lower than the simulated noise floor, thus rendering the extracted phase and amplitude information completely ineffective and unusable for beamforming of electromagnetic wave phased arrays. Summary of the Invention

[0006] To address the urgent technical problem of constructing a stable electromagnetic model and control method in biological tissue environments characterized by high heterogeneity, strong dispersion, and significant energy dissipation, this invention provides solutions in the following aspects.

[0007] In a first aspect, the present invention provides a method for focusing energy modulation of an electromagnetic wave phased array of a dipole array, the method comprising:

[0008] Based on medical imaging data and biological tissue relaxation parameters, the water content and lipid concentration of the region are extracted, and a broadband complex frequency domain dielectric property spatial distribution reflecting nonlinear dispersion characteristics is constructed accordingly.

[0009] For the spatial distribution of dielectric properties in the broadband complex frequency domain, local spatial information entropy features are extracted and pseudo-boundary abrupt change is identified. Based on the identification results, dynamic boundary smoothing processing is applied to obtain the corrected spatial distribution of dielectric properties.

[0010] Using the modified dielectric property spatial distribution, a virtual negative thermodynamic dissipation factor is introduced by forcibly replacing the static conductivity with a reverse phase. Based on the virtual negative thermodynamic dissipation factor, pulse excitation is injected into the target area to perform a pseudo-reverse electromagnetic evolution deduction.

[0011] Based on the results of the pseudo-reverse electromagnetic evolution, the reverse electromagnetic field vector information arriving at the port section of the array element is extracted, and the delay phase compensation measure and energy normalization allocation weight coefficient of each channel of the driving phased array are calculated based on the reverse electromagnetic field vector information.

[0012] Preferably, the step of extracting the water content and lipid concentration of the region based on medical image data and biological tissue relaxation parameters includes: converting the initial anatomical voxel gray quantification factor of the acquired medical image into the nominal water content and lipid concentration distribution ratio corresponding to the three-dimensional discrete spatial nodes in the target region.

[0013] Preferably, the construction of the broadband complex frequency domain dielectric property spatial distribution reflecting nonlinear dispersion characteristics includes: for each independent three-dimensional spatial grid, loading a multi-order relaxation reconstruction model based on the nominal water content ratio and lipid concentration distribution ratio; calculating based on the composite polarization control relationship that changes with dynamic angular frequency to generate the broadband complex frequency domain dielectric property spatial distribution spanning the microwave operating frequency band, wherein the key parameters in the composite polarization control relationship include the polarization intensity contributed by each order dipole turning process, the attenuation factor, the turning relaxation time lag constant, and the static conductivity determined by the voxel gray quantization factor.

[0014] Preferably, the step of extracting local spatial information entropy features and identifying pseudo-boundary abrupt changes for the spatial distribution of dielectric properties in the broadband complex frequency domain includes: for each target voxel node in the spatial distribution of dielectric properties in the broadband complex frequency domain, delineating and obtaining its three-dimensional neighborhood gradient feature aggregation set; extracting and calculating the degree of spatial heterogeneous distribution information entropy of the three-dimensional neighborhood gradient feature aggregation set; comparing the degree of spatial heterogeneous distribution information entropy with a preset safe transition smoothness judgment threshold to identify pseudo-boundary abrupt change regions caused by the image resolution limit.

[0015] Preferably, the step of applying dynamic boundary smoothing processing based on the identification results to obtain the corrected spatial distribution of dielectric properties includes: calculating and generating a dynamic viscosity penalty compensation term with nonlinear decay characteristics for the identified pseudo-boundary abrupt change region; applying the dynamic viscosity penalty compensation term to the original polarizability value of the voxel node in the region in a negative fusion manner to force smoothing of high-frequency polarization abrupt changes; and outputting the corrected spatial distribution of dielectric properties after smoothing processing, wherein the penalty compensation term applied to the voxel node is determined by a comprehensive measure of the voxel gray-level gradient magnitude in the neighborhood of the node and a spatial heterogeneous information entropy factor through an exponential logarithmic composite penalty control equation.

[0016] Preferably, the step of injecting pulse excitation into the target region based on the virtual negative thermodynamic dissipation factor to perform quasi-reverse electromagnetic evolution deduction includes: injecting a full-bandwidth time-domain differential Gaussian pulse source as a virtual electromagnetic excitation at the core position of the preset spatial projection coordinates of the target tumor target region; loading the modified dielectric property spatial distribution into a three-dimensional discrete mesh difference engine; and introducing the virtual negative thermodynamic dissipation factor into the electromagnetic field curl difference relationship of the mesh nodes to perform quasi-reverse time-domain evolution deduction with time step updates.

[0017] Preferably, the introduction of the virtual negative thermodynamic dissipation factor includes: in the process of the pseudo-reverse time-domain evolution deduction, performing a forced algebraic phase inversion substitution on the static conductivity corresponding to the grid nodes in the modified dielectric property spatial distribution, so as to provide equivalent wavefront amplitude gain compensation and thus compensate for the energy attenuation in the dissipation medium before wave cancellation.

[0018] Preferably, the step of extracting the reverse electromagnetic field vector information arriving at the array element port section based on the pseudo-reverse electromagnetic evolution deduction result includes: recording the time-domain inversion attenuation trace generated by the pseudo-reverse electromagnetic evolution at the receiving port of the outer skin antenna array; performing a discrete Fourier transform on the time-domain inversion attenuation trace, and extracting the complex frequency domain steady-state reverse electric and magnetic field vectors corresponding to each antenna port section as the reverse electromagnetic field vector information.

[0019] Preferably, the step of calculating the delay phase compensation measure and energy normalization allocation weight coefficient of each channel of the driving phased array based on the reverse electromagnetic field vector information includes: extracting the comprehensive conjugate phase angle of the reverse electric field vector on the port section of a single array element, taking its opposite as the array element delay phase compensation measure, wherein the output value of the array element delay phase compensation measure is constrained within the standard cyclic radian space; calculating the reverse energy flux density flux on the effective aperture coverage section of a single array element based on the equivalent principle of the reverse Poynting energy flux density spatial flux integration; dividing the reverse energy flux density flux by the total reverse energy flux density flux of all array element ports to obtain the port energy normalization allocation weight coefficient of a single array element, thereby obtaining the sum of the weight coefficients of all array elements to be 1.

[0020] Secondly, an electromagnetic wave phased array focusing energy control system for a dipole array includes: a processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, the electromagnetic wave phased array focusing energy control method for the dipole array described in any one of the claims is implemented.

[0021] The embodiments of the present invention have at least the following beneficial effects:

[0022] 1. A nonlinear multi-order relaxation reconstruction model accurately reflects the frequency-varying characteristics of biological tissues, improving the physical consistency and prediction accuracy of energy regulation. Based on the relaxation parameters of biological tissues, voxel grayscale information is converted into water content and lipid concentration distributions. Then, based on the multi-order relaxation reconstruction model, a broadband complex frequency domain dielectric property spatial distribution matrix spanning the operating frequency band is calculated using composite polarization equations. This allows electromagnetic simulations to be based on a more realistic electromagnetic response of biological tissues, ensuring that the medium parameters upon which phased array delay and amplitude regulation calculations depend have frequency relevance. This provides correct input for achieving accurate beamforming in complex dispersive media and improves the model distortion problem caused by static mapping.

[0023] 2. Adaptive boundary smoothing based on local spatial information entropy is achieved, effectively suppressing numerical instability caused by image artifacts and ensuring the robustness of large-scale simulations under complex models. Partial volumetric effects in medical images can produce artifacts at tissue boundaries. If directly mapped to abrupt changes in dielectric parameters, this will cause non-physical scattering and computational divergence in numerical simulations. This invention intelligently identifies pseudo-boundary abrupt change regions for each voxel node in the dielectric property matrix by calculating the degree of spatial heterogeneous distribution information entropy of its three-dimensional neighborhood. For identified high-risk regions, a nonlinear penalty compensation term defined by an exponential-logarithmic composite equation is dynamically generated and applied to the original polarizability in a negative fusion manner, equivalent to an adaptive, localized digital low-pass filter, suppressing high-frequency parameter noise while preserving the true tissue boundaries to the maximum extent.

[0024] 3. A quasi-reverse electromagnetic evolution method with the introduction of a virtual negative thermodynamic dissipation factor is proposed. In the quasi-reverse evolution propagating from the target region in reverse, the static conductivity of the grid nodes is forcibly replaced with its algebraic inverse value, that is, a virtual negative thermodynamic dissipation factor is introduced. This provides each grid cell on the propagation path with a virtual energy gain that precisely cancels out the medium loss, thus solving the problem that wavefront information is difficult to reconstruct effectively in strongly dissipative media. Attached Figure Description

[0025] Figure 1 The schematic diagram illustrates the steps of the electromagnetic wave phased array focusing energy control method of the dipole array in this invention. Detailed Implementation

[0026] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0027] The specific embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0028] S1: Based on medical imaging data and biological tissue relaxation parameters, the water content and lipid concentration of the extracted regions are used to construct a broadband complex frequency domain dielectric property spatial distribution that reflects nonlinear dispersion characteristics.

[0029] Traditional methods directly and statically map the grayscale values ​​of medical images to conductivity and dielectric constant at a fixed frequency, completely ignoring the dynamic characteristics of the dielectric properties of biological tissues as they change with electromagnetic wave frequency.

[0030] This simplified modeling approach, when dealing with living tissues that are highly heterogeneous and exhibit significant dispersion effects, leads to a serious deviation between the simulated electromagnetic field distribution and reality, causing simulation-based phase modulation strategies to fail in deep focusing.

[0031] To establish a model that accurately reflects the nonlinear dielectric relaxation behavior of biological tissues over a wide frequency band, the pre-stored set of biological tissue baseline relaxation parameters is first invoked. This set contains multi-order relaxation parameters of various typical tissues under standard conditions, serving as a prior knowledge base and boundary condition constraints for model calculation. The set of benchmark relaxation parameters for biological tissues can be obtained by searching public data, for example, the Foundation for Research on Information Technologies in Society.

[0032] Subsequently, three-dimensional voxel data from the medical imaging equipment were acquired, and the location of each voxel was extracted. gray quantization value .

[0033] Through scaling transformation algorithm, Converted to the nominal water content percentage of the tissue at that location Ratio to lipid concentration Among them, the scaling transformation algorithm is a well-known technical means and will not be described in detail.

[0034] After obtaining the component proportions of each spatial node, for any node in the space... and the angular frequency of operation Its fundamental complex frequency domain relative permittivity It can be calculated using a multi-order relaxation reconstruction model based on well-known technical means:

[0035]

[0036] In the formula, It is a complex number, where the real part represents the dielectric constant and the imaginary part is related to the conductivity, together describing the nodal structure at frequency. The complete electromagnetic properties under [the following conditions].

[0037] Represents the imaginary unit, satisfying The introduction of its complex frequency domain allows the polarization and loss characteristics of the medium to be uniformly described by the real and imaginary parts of the complex permittivity.

[0038] The optical dielectric constant as the frequency approaches infinity is expressed as the nominal water content is extracted. lipid concentration ratio The remaining dry matter ratio, calculated from this, is used as a weighting coefficient. The dielectric constants of the three-phase references of pure water, pure lipids, and dry matter are obtained by performing a linear weighted summation calculation. The linear weighted summation calculation is a well-known technique and will not be elaborated further.

[0039] The order of the relaxation process considered in the model is a hyperparameter set according to the trade-off between computational accuracy and efficiency; its empirical value is typically taken as... To cover the main relaxation frequency bands of biological tissues, the implementation can be adjusted by the implementer according to the specific implementation scenario.

[0040] n represents the relaxation order index, used to distinguish the different order dipole turning relaxation components participating in the superposition.

[0041] It is the first The contribution intensity of the first relaxation process to dielectric polarization. It is the corresponding characteristic relaxation time constant. These are parameters describing the width of the time distribution during the relaxation process. These three dispersion characteristic parameters are determined by the system. and Input as a joint retrieval index into the biological tissue baseline relaxation parameter set In the calculation, the result is obtained through a smooth transition using a spatial interpolation algorithm, which is a well-known technique and will not be described in detail here.

[0042] The static conductivity is obtained using the AND logic. Similarly, the ratio of water, lipids, and dry matter is used as weighting coefficients to perform a linear weighted summation calculation on the preset three-phase reference static conductivity. The linear weighted summation calculation is a well-known technique and will not be described in detail here.

[0043] It is the vacuum permittivity, a physical constant with a fixed value of 1 / 2. .

[0044] By analyzing all voxel nodes By performing multi-order relaxation reconstruction model calculations on the corresponding discrete operating frequency points, the spatial distribution matrix of the basic complex frequency domain dielectric properties is obtained. .

[0045] S2: Extract local spatial information entropy features from the spatial distribution of dielectric properties in the broadband complex frequency domain to identify pseudo-boundary abrupt changes, and apply dynamic boundary smoothing processing to obtain the corrected spatial distribution of dielectric properties.

[0046] However, directly generated from image data It includes spatial artifacts caused by the limited resolution of imaging equipment, resulting in abrupt discontinuities at the boundaries of different tissues due to differences in parameters.

[0047] This mutation can trigger numerical oscillations and scattering in electromagnetic simulations, severely interfering with the accuracy of electromagnetic wavefront information.

[0048] Therefore, it is necessary to Smoothing is performed, and local spatial information entropy is introduced as a metric to identify and suppress these pseudo-boundaries.

[0049] For matrix Any target node in First, its three-dimensional neighborhood is defined. , usually a Centered A set of voxels, in which, The range of voxel sets is an empirical value and can be adjusted by the implementer according to the specific implementation scenario.

[0050] Calculate the gradient distribution of the real part of the dielectric constant in this neighborhood and solve for its information entropy. The formula for calculating information entropy is a well-known technique and will not be elaborated further.

[0051] Information entropy The higher the value, the more drastic and disordered the parameter changes are within that neighborhood, and the more likely it is to be a false boundary.

[0052] Preset a smoothing threshold ,when When, determine the node. Located in a pseudo-boundary region that requires smoothing.

[0053] Subsequently, a gradient magnitude related to that node is calculated. and local entropy Related nonlinear penalty compensation terms This is used to correct the attribute value of the node.

[0054] Dielectric properties in the complex frequency domain The corrected formula is as follows:

[0055]

[0056] In the formula, It is an indicator function, when hour Otherwise .

[0057] It is a frequency-dependent normalization factor that ensures the penalty term has a consistent relative strength across different frequencies; typically, it can be taken as... .

[0058] in, It is a binary switch function, when The value is 1 when it is identified as a false boundary point, and 0 otherwise.

[0059] Penalty items The specific calculation formula is as follows:

[0060]

[0061] In this penalty item, It is a node The L2 norm of the dielectric property gradient is used to sense the intensity of the mutation.

[0062] It is a variance parameter that controls smoothing sensitivity. An empirical value is usually set at around 1.5 to match the voxel size of typical medical images. It can be adjusted by the implementer according to the specific implementation scenario.

[0063] It is the calculated local spatial information entropy.

[0064] This is the boundary smoothing static bias coefficient, used to control the strength of the overall smoothing; its empirical value is taken as... To ensure that artifacts are suppressed without excessively blurring the real tissue interface, the implementation can be adjusted by the implementer according to the specific implementation scenario.

[0065] Through the Perform the above operations on all nodes to obtain the corrected spatial distribution matrix of dielectric properties in the complex frequency domain. .

[0066] S3: Using the modified dielectric property spatial distribution, a virtual negative thermodynamic dissipation factor is introduced to perform quasi-reverse electromagnetic evolution deduction, and the reverse electromagnetic field vector information is extracted to analyze the delay phase compensation measure and energy normalization allocation weight coefficient of each channel of the phased array.

[0067] After obtaining the corrected spatial distribution of dielectric properties Afterwards, inverse electromagnetic calculations need to be performed to obtain array control parameters. However, traditional time inversion techniques rely on the time symmetry of the wave equation, which is only strictly true in dissipative media.

[0068] Biological tissues, as typical strong dissipative media, have low electrical conductivity. The Joule heat loss it represents is thermodynamically irreversible, making it difficult for traditional methods to be applied in deep focusing applications.

[0069] When attempting to simulate reverse wave propagation from a deep target area to an external array port, the wavefront energy decays exponentially due to the tissue's true positive conductivity, resulting in a signal amplitude arriving at the port that is lower than the computational noise floor, rendering the extracted phase and amplitude information invalid.

[0070] In numerical simulation, a virtual gain mechanism with the same magnitude but opposite sign as the real loss mechanism is introduced to accurately compensate for the energy attenuation caused by positive conductivity on the reverse propagation path.

[0071] This allows the inverse wavefront to propagate to the array port in an ideal, lossless manner, thereby carrying the phase and amplitude information used to calculate the control parameters with high fidelity.

[0072] The pre-defined set of spatial projection coordinates of the target tumor region core position At this point, a broadband time-domain differential Gaussian pulse is injected as a virtual excitation source. .

[0073] The mathematical expression for this pulse is: ,in The pulse center time, This is the pulse width parameter, and its empirical value is based on the center frequency of the operating frequency band. Set as To ensure that the incentives cover the entire work frequency band, the implementer can adjust them according to the specific implementation scenario. A continuous-time variable used to define the virtual excitation source. Waveform evolution process in the time domain.

[0074] Then Loaded into a three-dimensional finite-difference temporal (FDTD) mesh, and initiating a quasi-inverse evolution with time-step backward updates, where update refers to... Towards Iteration.

[0075] When updating the electric and magnetic fields at each grid node, a fundamental modification is made to the discrete form of Maxwell's curl equations: the static conductivity, which characterizes the ohmic loss of the medium, is changed. Replace with its algebraic inverse value .

[0076] The parameter that is replaced is defined as the virtual negative thermodynamic dissipation factor. ,satisfy .

[0077] This means transforming the attenuation term related to conductivity in the update equation into a gain term.

[0078] With electric field Components in Yee mesh nodes Taking the update at a certain point as an example, its quasi-reverse iteration formula is:

[0079]

[0080] Among them, coefficient and It is given by the following formula:

[0081]

[0082] In the formula, and These represent the electric field values ​​at the current time step and the previous time step, respectively.

[0083] From The real part of the relative permittivity of the node is extracted (taken at the center frequency).

[0084] The vacuum permittivity is a physical constant. .

[0085] The time step that satisfies the Courant-Friedrichs-Lewy stability condition is empirically determined by the grid space step size. The maximum speed of light in the medium is determined, usually ,in The speed of light in a vacuum It can be adjusted by the implementer according to the specific implementation scenario.

[0086] This is a discrete difference approximation of the curl of the magnetic field at the current time step.

[0087] when When it is negative, the coefficient The absolute value is greater than 1, thus providing a certain value during iteration. It provides net gain to compensate for the losses that would occur during forward propagation.

[0088] Once the aforementioned pseudo-reverse evolution is completed, the wavefront information has been transferred from the target area. Spread to all parts distributed on the body surface Radiation port cross section , The channel index for the surface radiation port is used to traverse all array channels in the summation operation to calculate the total reverse energy flow.

[0089] Record the cross-section of each port. Electric field that varies with time and magnetic field Traces.

[0090] Subsequently, a discrete Fourier transform is performed on each time-domain trace to extract the operating frequency. Complex frequency domain field quantity and subscript This indicates that it is the result of reverse evolution. The Discrete Fourier Transform is a well-known technique and will not be elaborated further.

[0091] Based on the extracted complex frequency domain field quantities, two key control parameters are obtained. The first is the... Delay phase compensation for each radiation channel It calculates the cross-section of the channel port. The average phase of the reverse electric field is obtained by inverting it, i.e. .

[0092] here This indicates taking the complex phase angle; the overline indicates the angle at the port section. Spatial averaging is performed to obtain a representative value; the inversion operation is because this phase is obtained in reverse propagation and needs to be inverted before it can be used to guide the initial phase setting for forward transmission. At output, Normalized to Within the arc range.

[0093] The second key parameter is the Port energy normalization allocation weighting coefficients for each radiation channel .

[0094] Its calculation is based on the inverse Poynting vector energy flow, as shown in the following formula:

[0095]

[0096] In the formula, Represents the cross product of vectors. Indicates complex conjugation. Indicates taking the real part, Let be the area vector on the port cross-section, pointing outwards.

[0097] Molecular representation through the first The net reverse energy flow through each port, with the denominator representing the energy flow through all ports. The sum of reverse energy flow at each port.

[0098] This calculation ensures that the sum of all weight coefficients is 1, that is... This allows the total input power to be distributed to each channel in this proportion during forward emission, achieving coherent superposition and focusing of energy.

[0099] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, specific embodiments have been described above. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps described in the claims can be performed in a different order than that shown in the embodiments and still achieve the desired result. Additionally, the processes depicted in the drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0100] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

[0101] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

[0102] The present invention also provides an electromagnetic wave phased array focusing energy control system for a dipole array. The system includes a processor and a memory, the memory storing computer program instructions. When the computer program instructions are executed by the processor, the electromagnetic wave phased array focusing energy control method for a dipole array according to the first aspect of the present invention is implemented.

[0103] The system also includes other components well known to those skilled in the art, such as communication buses and communication interfaces, the settings and functions of which are known in the art and will not be described in detail here.

Claims

1. A method for focusing energy control of electromagnetic wave phased arrays using dipole arrays, characterized in that, Includes the following steps: Based on medical imaging data and biological tissue relaxation parameters, the water content and lipid concentration of the region are extracted, and a broadband complex frequency domain dielectric property spatial distribution reflecting nonlinear dispersion characteristics is constructed accordingly. For the spatial distribution of dielectric properties in the broadband complex frequency domain, local spatial information entropy features are extracted and pseudo-boundary abrupt change is identified. Based on the identification results, dynamic boundary smoothing processing is applied to obtain the corrected spatial distribution of dielectric properties. Using the modified dielectric property spatial distribution, a virtual negative thermodynamic dissipation factor is introduced by forcibly replacing the static conductivity with a reverse phase. Based on the virtual negative thermodynamic dissipation factor, pulse excitation is injected into the target area to perform a pseudo-reverse electromagnetic evolution deduction. Based on the results of the pseudo-reverse electromagnetic evolution, the reverse electromagnetic field vector information arriving at the port section of the array element is extracted, and the delay phase compensation measure and energy normalization allocation weight coefficient of each channel of the driving phased array are calculated based on the reverse electromagnetic field vector information.

2. The method for focusing energy control of electromagnetic wave phased arrays using dipole arrays according to claim 1, characterized in that, The extraction of water content and lipid concentration based on medical image data and biological tissue relaxation parameters includes: converting the initial anatomical voxel gray quantification factor of the acquired medical image into the nominal water content and lipid concentration distribution ratio corresponding to the three-dimensional discrete spatial nodes in the target area.

3. The method for focusing energy control of electromagnetic wave phased arrays using dipole arrays according to claim 2, characterized in that, The construction of the broadband complex frequency domain dielectric property spatial distribution reflecting nonlinear dispersion characteristics includes: For each independent three-dimensional space grid, a multi-order relaxation reconstruction model is loaded based on the nominal water content ratio and lipid concentration distribution ratio. The calculation is based on the composite polarization control relationship that varies with dynamic angular frequency to generate the spatial distribution of the broadband complex frequency domain dielectric properties spanning the microwave operating frequency band. The key parameters in the composite polarization control relationship include the polarization intensity, attenuation factor, and hysteresis constant of the turning relaxation time contributed by each order dipole process, as well as the static conductivity determined by the voxel gray quantization factor.

4. The method for focusing energy control of electromagnetic wave phased arrays using dipole arrays according to claim 1, characterized in that, The step of extracting local spatial entropy features and identifying pseudo-boundary abrupt changes for the spatial distribution of dielectric properties in the broadband complex frequency domain includes: For each target voxel node in the spatial distribution of dielectric properties in the broadband complex frequency domain, its three-dimensional neighborhood gradient feature aggregation set is defined and obtained. Extract and calculate the degree of spatial heterogeneous distribution information entropy of the three-dimensional neighborhood gradient feature aggregation set; By comparing the degree of spatial heterogeneous distribution information entropy with a preset safe transition smoothness judgment threshold, pseudo-boundary abrupt change regions caused by the image resolution limit are identified.

5. The method for focusing energy control of electromagnetic wave phased arrays using dipole arrays according to claim 1, characterized in that, The process of applying dynamic boundary smoothing based on the recognition results to obtain the corrected spatial distribution of dielectric properties includes: For the identified pseudo-boundary abrupt change regions, a dynamic viscosity penalty compensation term with nonlinear decay characteristics is calculated and generated; The dynamic viscosity penalty compensation term is applied to the original polarizability value of the voxel node in this region in a negative fusion manner to force smooth high-frequency polarization abrupt changes. The output is the smoothed and corrected spatial distribution of dielectric properties, where the penalty compensation term acting on the voxel node is determined by the comprehensive measure of the voxel gray-level gradient magnitude in the neighborhood of the node and the degree factor of spatial heterogeneous information entropy through an exponential logarithmic composite penalty control equation.

6. The method for focusing energy control of electromagnetic wave phased arrays using dipole arrays according to claim 1, characterized in that, The step of injecting pulse excitation into the target region based on the virtual negative thermodynamic dissipation factor to perform quasi-reverse electromagnetic evolution deduction includes: At the core position of the pre-defined target tumor target area spatial projection coordinates, a full-bandwidth time-domain differential Gaussian pulse source is injected as a virtual electromagnetic excitation. The modified dielectric property spatial distribution is loaded into a three-dimensional discrete mesh difference engine; A virtual negative thermodynamic dissipation factor is introduced into the electromagnetic field curl difference relation of the grid nodes to perform a quasi-inverse time-domain evolution deduction with time step backward updates.

7. The method for focusing energy control of electromagnetic wave phased arrays using dipole arrays according to claim 6, characterized in that, The introduction of the virtual negative thermodynamic dissipation factor includes: In the process of the quasi-reverse time-domain evolution deduction, the static conductivity corresponding to the grid nodes in the modified dielectric property spatial distribution is subjected to forced algebraic phase inversion replacement to provide equivalent wavefront amplitude gain compensation and thus counteract the energy attenuation in the dissipative medium before wave cancellation.

8. The method for focusing energy control of electromagnetic wave phased arrays using dipole arrays according to claim 1, characterized in that, The step of extracting the reverse electromagnetic field vector information arriving at the array element port section based on the pseudo-reverse electromagnetic evolution deduction results includes: At the receiving port of the outer skin of the antenna array, the time-domain inversion attenuation trace generated by the pseudo-reverse electromagnetic evolution is recorded; Perform a discrete Fourier transform on the time-domain inverted attenuation trace to extract the complex frequency domain steady-state reverse electric and magnetic field vectors corresponding to each antenna port cross section as the reverse electromagnetic field vector information.

9. The method for focusing energy control of electromagnetic wave phased arrays using dipole arrays according to claim 1, characterized in that, The calculation of the delay phase compensation measure and energy normalization allocation weight coefficients for each channel of the driving phased array based on the inverse electromagnetic field vector information includes: The combined conjugate phase angle of the reverse electric field vector on the port section of a single array element is extracted, and its opposite is taken as the array element delay phase compensation measure of that array element. The output value of the array element delay phase compensation measure is constrained within the standard cyclic radian space. Based on the equivalent principle of the spatial flux integral of the reverse Poynting energy flux density, the reverse energy flux density flux on the effective aperture coverage section of a single array element is calculated. Dividing the reverse energy flux density by the total reverse energy flux density at all array element ports yields the port energy normalization allocation weight coefficient for a single array element, thus ensuring that the sum of the weight coefficients for all array elements is 1.

10. A phased array focusing energy control system for electromagnetic waves using a dipole array, characterized in that, include: A processor and a memory, wherein the memory stores computer program instructions that, when executed by the processor, implement the electromagnetic wave phased array focusing energy control method for a dipole array according to any one of claims 1-9.

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