A WiFi imaging method and device based on whirling electromagnetic waves

Abstract

The application provides a WiFi imaging method and device based on vortex electromagnetic waves, and the method comprises the following steps: connecting a plurality of vortex wave patch antennas with a WiFi device to generate multi-modal vortex waves; transmitting the vortex waves to a target, receiving a reflected signal by using a receiving antenna of the WiFi device and extracting channel state information; after preprocessing the channel state information, extracting a target signal reflected by the target; constructing a corresponding relationship between the target signal and an imaging plane, processing the target signal by using a two-dimensional inverse fast Fourier transform based on a ray tracing technology, restoring an imaging plane pixel, and realizing two-dimensional imaging of the target. The method provided by the application can realize high-precision imaging for a static target.

Description

Technical Field

[0001] This invention relates to the field of WiFi imaging technology, and in particular to a WiFi imaging method and apparatus based on vortex electromagnetic waves. Background Technology

[0002] With the widespread adoption of WiFi signals indoors, WiFi-based spatial sensing has attracted considerable attention from academia and industry. Compared to traditional cameras, the scattering and diffraction capabilities of WiFi signals are unaffected by lighting conditions or line-of-sight obstructions, thus enabling non-invasive wireless sensing to provide users with a superior interactive experience. WiFi-based sensing applications primarily include activity monitoring, health monitoring, and posture imaging. Among these, WiFi-based imaging technology can provide more intuitive results, depicting the contours of the human body or objects and acquiring visually discernible sensory information.

[0003] Wireless signal imaging typically requires acquiring information in at least two dimensions: distance and orientation. With the continuous improvement of WiFi bandwidth, the resolution in the distance direction is no longer a bottleneck. However, the resolution in the orientation direction is often limited by factors such as the number of antennas on the WiFi device and the relative motion between the device and the imaging target, which may lead to unsatisfactory final imaging results.

[0004] Existing research indicates that the resolution in the imaging azimuth direction is related to the signal wavelength and the size of the antenna aperture or the length of the antenna array. Since the signal wavelength is fixed, the resolution in the imaging azimuth direction can only be improved by adjusting the latter. Figure 1 As shown, the first method to improve the azimuth resolution of imaging is based on antenna arrays, which increases the array length by deploying large-scale antenna arrays, thereby improving resolution. The second method utilizes a single antenna, but requires the target to be in motion to increase signal sampling from different viewpoints, thus simulating the effect of an antenna array. If the target is stationary, the same array effect can be simulated by moving a single antenna.

[0005] Existing commercial WiFi network cards, such as those from Intel and Qualcomm, are equipped with only three antennas. This means that without using multiple WiFi devices, it's virtually impossible to improve WiFi imaging resolution by deploying an antenna array. Furthermore, deploying large-scale antenna arrays increases costs and is relatively difficult to implement in indoor home environments. In addition, indoor WiFi devices, such as WiFi routers, are relatively stationary. When these devices and the target being sensed are both relatively still, it's impossible to simulate an antenna array by moving them to improve WiFi imaging resolution.

[0006] Therefore, there is an urgent need for a static target imaging method that can be implemented on commercial WiFi devices to overcome the above-mentioned technical limitations and improve imaging quality. Summary of the Invention

[0007] In view of this, embodiments of the present invention provide a WiFi imaging method and apparatus based on vortex electromagnetic waves to eliminate or improve one or more defects existing in the prior art.

[0008] On one hand, the present invention provides a WiFi imaging method based on vortex electromagnetic waves, the method comprising the following steps:

[0009] Multiple vortex wave patch antennas are connected to WiFi devices to generate multimode vortex waves;

[0010] The vortex wave is emitted toward the target, the reflected signal is received using the receiving antenna of the WiFi device, and channel state information is extracted; after preprocessing the channel state information, the target signal reflected back from the target is extracted;

[0011] The correspondence between the target signal and the imaging plane is constructed. Based on ray tracing technology, the target signal is processed by two-dimensional inverse fast Fourier transform to restore the pixels of the imaging plane and realize two-dimensional imaging of the target. The imaging plane is a predefined image of the plane where the target is located.

[0012] In some embodiments of the present invention, the receiving antenna of the WiFi device is used to receive reflected signals and extract channel state information, including: using three receiving antennas, which are placed vertically in pairs to receive reflected signals from various directions.

[0013] In some embodiments of the present invention, the preprocessing of the channel state information includes: filtering the channel state information using a low-pass filter to remove high-frequency noise; and smoothing each subcarrier of the filtered signal using discrete wavelet transform.

[0014] In some embodiments of the present invention, the preprocessing of the channel state information further includes: using a threshold method to eliminate signal segments with violent fluctuations, and retaining only segments that can characterize the target when it is stationary.

[0015] In some embodiments of the present invention, after preprocessing the channel state information, a feature decomposition method is used to extract the target signal from the preprocessed channel state information to distinguish it from other static targets, including:

[0016] The autocorrelation function of the preprocessed channel state information is calculated using the following formula:

[0017]

[0018] Where H(n) represents the channel state information; n represents the subcarrier index of the channel state information; * represents the conjugate transpose of the matrix;

[0019] The autocorrelation function is subjected to eigenvalue decomposition to obtain its eigenvalues ​​and eigenvectors, calculated as follows:

[0020] R = V∧V * V = [v1, v2, ..., v n ];

[0021] Where V represents an orthogonal matrix of eigenvectors of dimension n×n; ∧ represents a diagonal matrix with the same dimension as V; * represents the conjugate transpose of the matrix;

[0022] The target signal is obtained by selecting the first preset number of eigenvectors with the largest eigenvalues ​​from the orthogonal matrix and multiplying them by the autocorrelation function.

[0023] In some embodiments of the present invention, constructing the correspondence between the target signal and the imaging plane includes:

[0024] The imaging plane is gridded, and each grid is regarded as an antenna element. The signal is transmitted to the receiving antenna of the WiFi device; the target signal is the result of the superposition of the signals transmitted by all grids at the same time.

[0025] In some embodiments of the present invention, the correspondence between the target signal and the imaging plane is constructed, and the dynamics under a static environment are constructed using multimodal vortex waves, including:

[0026] The target is illuminated with multimodal vortex waves, with different phase factors for each mode. In the time domain, the target signal obtained based on the different modes of vortex waves is decomposed into independent signal components and recombined to obtain different wavefront states of the target.

[0027] In some embodiments of the present invention, based on ray tracing technology, the target signal is processed using a two-dimensional inverse fast Fourier transform to restore the pixels of the imaging plane, thereby achieving two-dimensional imaging of the target, including:

[0028] Based on the correspondence between the target signal and each pixel of the imaging plane, a two-dimensional fast Fourier inverse transform is performed on the target signal to restore the values ​​of each pixel of the imaging plane, and the two-dimensional image of the target is obtained by stitching them together.

[0029] The corresponding relationship is as follows:

[0030]

[0031] Wherein, H(f,t) represents the target signal; σ(m,n) represents the imaging plane pixel; B m,n (f,t) represents the basis function; M and N represent the length and width of the imaging plane, respectively.

[0032] On the other hand, this invention also provides a WiFi imaging device based on vortex electromagnetic waves, the device comprising:

[0033] The signal transceiver module includes a vortex wave transmitting antenna constructed by connecting multiple vortex wave patch antennas with a WiFi device and a receiving antenna of the WiFi device, used to transmit vortex waves of different modes to a target and receive reflected signals.

[0034] The signal processing module is used to extract channel state information from the reflected signal; and to extract the target signal after preprocessing the channel state information.

[0035] The imaging module is used to construct the correspondence between the target signal and the imaging plane. Based on ray tracing technology, it uses a two-dimensional inverse fast Fourier transform to process the target signal, restore the pixels of the imaging plane, and realize the two-dimensional imaging of the target. The imaging plane is a predefined image of the plane where the target is located.

[0036] On the other hand, the present invention also provides a computer-readable storage medium having a computer program / instructions stored thereon, which, when executed by a processor, implement the steps of any of the methods mentioned above.

[0037] This invention provides a WiFi imaging method and apparatus based on vortex electromagnetic waves, comprising: connecting multiple vortex wave patch antennas to a WiFi device to generate multimode vortex waves; transmitting vortex waves towards a target, receiving the reflected signals using the receiving antenna of the WiFi device and extracting channel state information; preprocessing the channel state information and extracting the target signal; constructing the correspondence between the target signal and the imaging plane; processing the target signal using a two-dimensional inverse fast Fourier transform based on ray tracing technology to restore the pixels of the imaging plane and achieve two-dimensional imaging of the target. This invention uses vortex wave patch antennas instead of traditional WiFi rod antennas to generate vortex electromagnetic waves in a static environment, suitable for target perception imaging in the WiFi band. Furthermore, by utilizing finite-mode vortex waves, it creates conditions for WiFi-based imaging algorithms in dynamic scenes, ultimately achieving high-quality two-dimensional imaging of static targets through a dynamic ray tracing imaging algorithm.

[0038] Additional advantages, objects, and features of the invention will be set forth in part in the description which follows, and will also become apparent in part to those skilled in the art upon studying the description, or may be learned by practice of the invention. The objects and other advantages of the invention can be realized and obtained by means of the structures specifically pointed out in the description and drawings.

[0039] Those skilled in the art will understand that the objectives and advantages achievable with the present invention are not limited to those specifically described above, and that the above and other objectives achievable with the present invention will become clearer from the following detailed description. Attached Figure Description

[0040] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, are not intended to limit the scope of the invention. In the drawings:

[0041] Figure 1 This is a schematic diagram of a method for improving imaging azimuth resolution in one embodiment of the present invention.

[0042] Figure 2 This is a schematic diagram of the steps of a WiFi imaging method based on vortex electromagnetic waves in one embodiment of the present invention.

[0043] Figure 3 This is a schematic diagram of the vortex electromagnetic wave principle in one embodiment of the present invention.

[0044] Figure 4 This is a schematic diagram of the framework of a WiFi imaging method based on vortex electromagnetic waves in one embodiment of the present invention.

[0045] Figure 5 This is a pattern fluctuation diagram of the channel state information subcarrier in motion and stationary states in one embodiment of the present invention.

[0046] Figure 6 This is a schematic diagram of the imaging coordinate system construction and vortex wave mode selection in one embodiment of the present invention.

[0047] Figure 7 This is a schematic diagram of a channel state information reassembly method in one embodiment of the present invention. Detailed Implementation

[0048] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the embodiments and accompanying drawings. Here, the illustrative embodiments and descriptions of this invention are used to explain the invention, but are not intended to limit the invention.

[0049] It should also be noted that, in order to avoid obscuring the invention with unnecessary details, only the structures and / or processing steps closely related to the solution according to the invention are shown in the accompanying drawings, while other details that are not closely related to the invention are omitted.

[0050] It should be emphasized that the term "including / comprises" as used herein refers to the presence of a feature, element, step, or component, but does not exclude the presence or addition of one or more other features, elements, steps, or components.

[0051] It should also be noted that, unless otherwise specified, the term "connection" in this article can refer not only to a direct connection, but also to an indirect connection involving an intermediary.

[0052] In the following description, embodiments of the invention will be illustrated with reference to the accompanying drawings. In the drawings, the same reference numerals represent the same or similar parts, or the same or similar steps.

[0053] To address the limitation of existing WiFi imaging technologies in relation to commercial WiFi devices and static targets, this invention provides a method, such as... Figure 2 As shown, the method includes the following steps S101 to S103:

[0054] Step S101: Connect multiple vortex wave patch antennas to a WiFi device to generate multimode vortex waves.

[0055] Step S102: Transmit vortex waves to the target, use the receiving antenna of the WiFi device to receive the reflected signal and extract the channel state information; after preprocessing the channel state information, extract the target signal reflected back from the target.

[0056] Step S103: Construct the correspondence between the target signal and the imaging plane. Based on ray tracing technology, use a two-dimensional inverse fast Fourier transform to process the target signal, restore the pixels of the imaging plane, and achieve two-dimensional imaging of the target. The imaging plane is a predefined image of the plane where the target is located.

[0057] To facilitate understanding, the principle of vortex electromagnetic wave imaging will be further explained first.

[0058] Vortex electromagnetic waves (VEMWs) are electromagnetic waves that carry orbital angular momentum (OAM), such as... Figure 3As shown. This type of wave has unique characteristics, including a hollow intensity distribution and a spiral phase wavefront. Based on the degree of wavefront distortion, vortex waves can be divided into different modes, usually represented by the letter l, with a larger value of l indicating a more severe wavefront distortion. Vortex waves of different l values ​​are spatially orthogonal, meaning they do not interfere with each other when propagating within the same frequency band.

[0059] like Figure 4 The figure shown is an overall framework diagram of the WiFi imaging method based on vortex electromagnetic waves.

[0060] In step S101, multiple vortex wave patch antennas are connected to a WiFi device to generate multimode vortex waves. For example, three q-shaped vortex wave patches are used to generate vortex waves with modes l=0, l=1, and l=2.

[0061] In step S102, the multi-mode vortex waves generated in step S101 are used to illuminate the target respectively, and the reflected signals of the target are received by the receiving antenna of the WiFi device and the channel state information (CSI) is extracted.

[0062] In some embodiments, the WiFi device employs three receiving antennas, arranged in pairs perpendicularly, to receive reflected signals from various directions.

[0063] The extracted channel state information is subjected to signal processing, which includes signal denoising, motion cancellation, and static target differentiation.

[0064] In some embodiments, the channel state information is first subjected to signal denoising processing, specifically including: filtering the channel state information using a low-pass filter to remove high-frequency noise; preferably, a low-pass filter with a stage frequency of 60Hz is selected. Then, a Discrete Wavelet Transform (DWT) is used to smooth each subcarrier of the filtered signal.

[0065] In some embodiments, motion cancellation processing is then applied to the channel state information. For example... Figure 5 The three channel state information subcarriers shown will exhibit different fluctuations when the human body is active and stationary. Therefore, in this invention, a threshold method is used to eliminate signal segments with severe fluctuations, retaining only the segments that can characterize the target when it is stationary.

[0066] In some embodiments, static target differentiation is further performed on the channel state information. Considering that there are relatively many static targets in indoor scenes, further signal processing is required to extract signals that belong only to the imaging target. Since the q-shaped vortex patch antenna radiates signals in one main direction, and the target is usually directly facing the antenna during imaging, with their planes being parallel, this invention uses a feature decomposition method to extract target signals from the preprocessed channel state information to distinguish other static targets, including the following steps:

[0067] First, the autocorrelation function of the preprocessed channel state information is calculated, as shown in formula (1):

[0068]

[0069] Where H(n) represents channel state information; n represents the subcarrier index of the channel state information; * represents the conjugate transpose of the matrix.

[0070] Then, the autocorrelation function R(n) is subjected to eigenvalue decomposition to obtain its eigenvalues ​​and eigenvectors, as shown in formula (2):

[0071] R = V∧V * V = [v1, v2, ..., v n (2)

[0072] Where V represents an orthogonal matrix of eigenvectors of dimension n×n; ∧ represents a diagonal matrix with the same dimension as V; * represents the conjugate transpose of the matrix.

[0073] Select the first n eigenvectors with the largest eigenvalues ​​from the orthogonal matrix V, and multiply them with the autocorrelation function R(n) to obtain the target signal that can represent the current target reflected by the target.

[0074] In step S103, as Figure 6 As shown, the receiving antenna of the WiFi device is taken as the origin of the coordinate system, and the mutually perpendicular receiving antennas correspond to the x-axis, y-axis, and z-axis of the coordinate system, respectively. An image of a preset size representing the plane containing the target is defined as the imaging plane. This imaging plane is then gridded, with each grid cell considered as an antenna element. Signals are transmitted to the receiving antenna of the WiFi device, resulting in the target signal being the superposition of signals transmitted simultaneously from all grid cells.

[0075] Taking human sleeping posture imaging as an example, we define the plane containing the target as an image of size M×N. After meshing it, the width of each grid is Δd, and the coordinates can be represented as (d... x +mΔd,d y The transmission distance of each grid to the receiving antenna of the WiFi device can also be calculated using the corresponding coordinates.

[0076] In this invention, by selecting vortex wave modes, the changes in the pixels of the imaging plane are constructed in a static scene to simulate the wavefront state that may occur when the target is not stationary, thus creating conditions for algorithms to achieve imaging based on WiFi in dynamic scenes. Figure 6 The three vortex wave modes listed within the red dashed lines have different phase factors at the same pixel location due to different mode l, which are distinguished by different colors in the figure. Therefore, vortex waves with three different orbital angular momentum modes are used to illuminate the target to achieve imaging. Figure 7 As shown, the present invention provides a CSI reconstruction method, which decomposes the target signal obtained based on different modal vortex waves into independent signal components and reconstructs them in the time domain to obtain different wavefront states of the target.

[0077] The dynamic characteristics resulting from the selection of different modes of vortex waves create the necessary conditions for imaging using ray tracing techniques. Therefore, imaging is achieved by backpropagating the target signal to each pixel of the imaging plane.

[0078] Specifically, a basis function is used to correlate the target signal and the pixels of the imaging plane, and the corresponding relationship is shown in formula (3):

[0079]

[0080] Where H(f,t) represents the target signal; σ(m,n) represents the pixel in the imaging plane; B m,n (f,t) represents the basis functions; M and N represent the length and width of the imaging plane, respectively.

[0081] Formula (3) mathematically satisfies the standard paradigm of two-dimensional fast Fourier transform (2D-FFT). Therefore, to reverse the calculation of the imaging plane pixel σ(m,n), it is only necessary to perform two-dimensional inverse fast Fourier transform (2D-IFFT) on the target signal H(f,t) to restore the value of the imaging plane pixel. By stitching them together, two-dimensional imaging of the target can be achieved.

[0082] Corresponding to the WiFi imaging method based on vortex electromagnetic waves, the present invention also provides a WiFi imaging device based on vortex electromagnetic waves, comprising:

[0083] The signal transceiver module includes a vortex wave transmitting antenna constructed by connecting multiple vortex wave patch antennas with a WiFi device and a receiving antenna of the WiFi device, used to transmit vortex waves of different modes to the target and receive reflected signals.

[0084] The signal processing module is used to extract channel state information from the reflected signal; after preprocessing the channel state information, the target signal is extracted.

[0085] The imaging module is used to construct the correspondence between the target signal and the imaging plane. Based on ray tracing technology, it uses two-dimensional fast Fourier transform to process the target signal, restore the pixels of the imaging plane, and realize two-dimensional imaging of the target.

[0086] The present invention will be further illustrated by a specific embodiment described below.

[0087] Hardware preparation: Two laptops equipped with Intel 5300 network cards were used as WiFi transceivers, along with three vortex wave transmitting patch antennas and three ordinary WiFi rod antennas.

[0088] Algorithm Implementation: The receiver signal processing and imaging code for the WiFi imaging method based on vortex electromagnetic waves is implemented using Matlab.

[0089] Corresponding to the above method, the present invention also provides an electronic device, which includes a computer device, the computer device including a processor and a memory, the memory storing computer instructions, the processor executing the computer instructions stored in the memory, and when the computer instructions are executed by the processor, the electronic device performs the steps of the method as described above.

[0090] This invention also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the aforementioned edge computing server deployment method. The computer-readable storage medium can be a tangible storage medium, such as random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, floppy disks, hard disks, removable storage disks, CD-ROMs, or any other form of storage medium known in the art.

[0091] Those skilled in the art will understand that the exemplary components, systems, and methods described in conjunction with the embodiments disclosed herein can be implemented in hardware, software, or a combination of both. Whether implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this invention. When implemented in hardware, it can be, for example, electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this invention are programs or code segments used to perform the desired tasks. The programs or code segments can be stored in a machine-readable medium or transmitted over a transmission medium or communication link via data signals carried in a carrier wave.

[0092] It should be clarified that the present invention is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present invention is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of the present invention.

[0093] In this invention, features described and / or illustrated for one embodiment may be used in the same or similar manner in one or more other embodiments, and / or combined with or in place of features of other embodiments.

[0094] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, various modifications and variations of the embodiments of the present invention are possible. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A WiFi imaging method based on vortex electromagnetic waves, characterized in that, The method includes the following steps: Multiple vortex wave patch antennas are connected to WiFi devices to generate multimode vortex waves; The vortex wave is emitted toward the target, the reflected signal is received using the receiving antenna of the WiFi device, and channel state information is extracted; after preprocessing the channel state information, the target signal reflected back by the target is extracted; The correspondence between the target signal and the imaging plane is constructed. Based on ray tracing technology, the target signal is processed using a two-dimensional inverse fast Fourier transform to restore the pixels of the imaging plane and realize the two-dimensional imaging of the target. The imaging plane is a predefined image of the plane where the target is located. The process of establishing the correspondence between the target signal and the imaging plane includes: The imaging plane is gridded, and each grid is regarded as an antenna element. The signal is transmitted to the receiving antenna of the WiFi device. The target signal is the result of the superposition of the signals transmitted by all grids at the same time. After establishing the correspondence between the target signal and the imaging plane, the dynamics under a static environment are constructed using multimodal vortex waves, including: The target is irradiated with the multi-mode vortex wave, and the phase factors of the vortex waves of different modes are different; In the time domain, the target signal obtained based on different modal vortex waves is decomposed into independent signal components and recombined to obtain different wavefront states of the target; Specifically, based on ray tracing technology, the target signal is processed using a two-dimensional inverse fast Fourier transform to reconstruct the pixels of the imaging plane, thereby achieving two-dimensional imaging of the target, including: Based on the correspondence between the target signal and each pixel of the imaging plane, a two-dimensional fast Fourier inverse transform is performed on the target signal to restore the values ​​of each pixel of the imaging plane, and the two-dimensional image of the target is obtained by stitching them together. The corresponding relationship is as follows: ； in, This refers to the target signal; Represents the pixels of the imaging plane; Describe the basis functions; , These represent the length and width of the imaging plane, respectively.

2. The WiFi imaging method based on vortex electromagnetic waves according to claim 1, characterized in that, Using the receiving antenna of the WiFi device to receive reflected signals and extract channel state information includes: Three receiving antennas are used, placed vertically in pairs, to receive reflected signals from all directions.

3. The WiFi imaging method based on vortex electromagnetic waves according to claim 1, characterized in that, Preprocessing of the channel state information includes: The channel state information is filtered using a low-pass filter to remove high-frequency noise; Discrete wavelet transform is used to smooth each subcarrier of the filtered signal.

4. The WiFi imaging method based on vortex electromagnetic waves according to claim 3, characterized in that, The preprocessing of the channel state information further includes: A thresholding method is used to eliminate signal segments with violent fluctuations, retaining only segments that can represent the target when it is stationary.

5. The WiFi imaging method based on vortex electromagnetic waves according to claim 1, characterized in that, After preprocessing the channel state information, the target signal is extracted from the preprocessed channel state information using a feature decomposition method to distinguish it from other static targets, including: The autocorrelation function of the preprocessed channel state information is calculated using the following formula: ； in, This represents the channel state information; The subcarrier index represents the channel state information; * indicates the conjugate transpose of the matrix; The autocorrelation function is subjected to eigenvalue decomposition to obtain its eigenvalues ​​and eigenvectors, calculated as follows: ； in, The dimension is The orthogonal matrix of eigenvectors; Representing dimensions and Maintain a consistent diagonal matrix; * indicates conjugate transpose of the matrix; The target signal is obtained by selecting the first preset number of eigenvectors with the largest eigenvalues ​​from the orthogonal matrix and multiplying them by the autocorrelation function.

6. A WiFi imaging device based on vortex electromagnetic waves, characterized in that, The device includes: The signal transceiver module includes a vortex wave transmitting antenna constructed by connecting multiple vortex wave patch antennas with a WiFi device and a receiving antenna of the WiFi device, used to transmit vortex waves of different modes to a target and receive reflected signals. The signal processing module is used to extract channel state information from the reflected signal; and to extract the target signal after preprocessing the channel state information. An imaging module is used to construct the correspondence between the target signal and the imaging plane. Based on ray tracing technology, it processes the target signal using a two-dimensional inverse fast Fourier transform to restore the pixels of the imaging plane, thereby achieving two-dimensional imaging of the target. The imaging plane is a predefined image of the plane where the target is located. Constructing the correspondence between the target signal and the imaging plane includes: meshing the imaging plane, treating each mesh as an antenna element, and transmitting a signal to the receiving antenna of the WiFi device. The target signal is the result of superimposing the signals transmitted simultaneously from all meshes. After constructing the correspondence between the target signal and the imaging plane, multimodal vortex waves are used to construct a static environment... The dynamic aspect includes: illuminating the target with the multimodal vortex waves, where different modes of vortex waves have different phase factors; in the time domain, decomposing the target signal obtained based on different mode vortex waves into independent signal components and recombining them to obtain different wavefront states of the target; wherein, based on ray tracing technology, the target signal is processed using a two-dimensional fast Fourier inverse transform to restore the pixels of the imaging plane and achieve two-dimensional imaging of the target, including: performing a two-dimensional fast Fourier inverse transform on the target signal according to the correspondence between the target signal and each pixel of the imaging plane, restoring the values ​​of each pixel of the imaging plane, and stitching them together to obtain a two-dimensional image of the target; the correspondence is: ； in, This refers to the target signal; Represents the pixels of the imaging plane; Describe the basis functions; , These represent the length and width of the imaging plane, respectively.

7. A computer-readable storage medium having a computer program / instructions stored thereon, characterized in that, When the computer program / instructions are executed by the processor, they implement the steps of the method as described in any one of claims 1 to 5.

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