Wireless positioning method, electronic device, program product and storage medium

Abstract

The invention discloses a wireless positioning method, electronic equipment, a program product and a storage medium. The wireless positioning method comprises the following steps: acquiring a receiving signal received by an active receiving unit of the hybrid intelligent reflecting surface; processing the received signal by using a preset algorithm to obtain initial direction information of the to-be-positioned user; based on the initial direction information, passive reflection coefficients of passive reflection units of the hybrid intelligent reflection surface are regulated and controlled, a plurality of first passive reflection coefficients are obtained, the first passive reflection coefficients are used for enabling reflection signals to be directionally focused at different positions in the initial direction, a plurality of directional focusing signals are obtained, and a plurality of directional focusing signals are obtained; the reflection signal is a receiving signal reflected by the passive reflection unit; controlling the base station to determine a target focus point position and a second passive reflection coefficient corresponding to the target focus point position according to the plurality of directional focus signals; and controlling the base station to determine the position information of the user to be positioned based on the initial direction information, the target focus point position and the second passive reflection coefficient. According to the invention, the technical problem of how to improve the wireless positioning precision under the condition of not increasing the system complexity is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of signal processing, and in particular, to a wireless positioning method, an electronic device, a program product, and a storage medium. Background Art

[0002] Wireless positioning technology is an essential part of wireless communication systems. In 5G networks, high-precision positioning capabilities are crucial for supporting various application scenarios. In complex urban, industrial park, or indoor environments, non-line-of-sight propagation of signals has become the norm, which directly affects the accuracy of positioning.

[0003] As an emerging technology, Reconfigurable Intelligent Surface (RIS) can optimize the signal propagation environment and enhance wireless communication and positioning performance. However, when traditional passive RIS aids in positioning, it faces the problem of path power fading caused by multi-stage cascaded channels, which limits the positioning accuracy. At the same time, in existing hybrid RIS-aided positioning methods, all array elements require radio frequency link support, which leads to a significant increase in system complexity and cost. Therefore, how to balance positioning accuracy and system complexity and improve wireless positioning accuracy without increasing system complexity is one of the important technical problems in the related technical field.

[0004] For the above problems, no effective solutions have been proposed yet. Summary of the Invention

[0005] Embodiments of the present invention provide a wireless positioning method, an electronic device, a program product, and a storage medium to at least solve the technical problem of how to improve wireless positioning accuracy without increasing system complexity.

[0006] According to one aspect of the embodiments of the present invention, a wireless positioning method is provided, including: obtaining a received signal received by an active receiving unit of a hybrid intelligent reflecting surface; using a preset algorithm to process the received signal to obtain initial direction information of a user to be located; based on the initial direction information, adjusting the passive reflection coefficients of passive reflection units of the hybrid intelligent reflecting surface to obtain a plurality of first passive reflection coefficients, where the plurality of first passive reflection coefficients are used to make the reflected signals be directionally focused on different positions in the initial direction to obtain a plurality of directionally focused signals, and the reflected signals are the received signals reflected by the passive reflection units; according to the plurality of directionally focused signals, controlling a base station to determine a target focus point position and a second passive reflection coefficient corresponding to the target focus point position; based on the initial direction information, the target focus point position, and the second passive reflection coefficient, controlling the base station to determine the position information of the user to be located.

[0007] Optionally, the initial direction information of the user to be located includes the estimated pitch angle and the estimated azimuth angle of the user to be located.

[0008] Optionally, the active receiving units of the hybrid intelligent reflecting surface form an L-shaped array.

[0009] Optionally, using a preset algorithm to process the received signal to obtain the initial direction information of the user to be located, including: determining the autocorrelation matrix of the received signal based on the received signal; performing eigenvalue decomposition on the autocorrelation matrix to obtain a first matrix corresponding to the noise subspace; generating a first steering vector according to the first preset range of azimuth angle and the first preset range of pitch angle; determining the estimated pitch angle and the estimated azimuth angle of the user to be located according to the first matrix and the first steering vector.

[0010] Optionally, determining the estimated pitch angle and the estimated azimuth angle of the user to be located according to the first matrix and the first steering vector includes: determining a first function expression according to the first matrix and the first steering vector; determining the maximum point of the first function expression within a preset search range to obtain the estimated pitch angle and the estimated azimuth angle of the user to be located, where the preset search range is determined by the first preset range of azimuth angle and the first preset range of pitch angle.

[0011] Optionally, based on the initial direction information, adjusting the passive reflection coefficients of the passive reflection units of the hybrid intelligent reflecting surface to obtain a plurality of first passive reflection coefficients, including: determining a position list according to the initial direction information and a preset distance list; adjusting the passive reflection coefficients according to the position list and a preset passive reflection coefficient expression to obtain a plurality of first passive reflection coefficients.

[0012] Optionally, according to a plurality of directional focusing signals, controlling the base station to determine the target focusing point position and the second passive reflection coefficient corresponding to the target focusing point position, including: controlling the base station to calculate the signal power of the received plurality of directional focusing signals and determining the maximum signal power from the plurality of signal powers; determining a signal power threshold according to the maximum signal power; determining the target focusing point position based on the signal power threshold; determining the second passive reflection coefficient according to the target focusing point position.

[0013] Optionally, based on the signal power threshold, determining a target signal power from the plurality of signal powers, where the target signal power is the signal power with the smallest difference from the signal power threshold among the plurality of signal powers and the target signal power is greater than the signal power threshold; determining the target focusing point position according to the target signal power.

[0014] Optionally, based on the initial direction information, the target focus point position, and the second passive reflection coefficient, the control base station determines the position information of the user to be located, including: the control base station determines the second steering vector expression based on the second passive reflection coefficient; determines the autocorrelation matrix of the target directional focusing signal based on the target directional focusing signal corresponding to the target focus point; performs eigenvalue decomposition on the autocorrelation matrix of the target directional focusing signal to obtain a second matrix corresponding to the noise subspace; generates a second steering vector according to the target focus point position, the polar coordinate space, and the second steering vector expression, where the polar coordinate space is constructed based on a preset distance range, a second preset azimuth range, and a second preset elevation range, and the second preset azimuth range and the second preset elevation range are determined based on the initial direction information; determines the position information of the user to be located according to the second matrix and the second steering vector.

[0015] Optionally, determining the position information of the user to be located according to the second matrix and the second steering vector includes: determining a second function expression according to the second matrix and the second steering vector; determining the maximum value point of the second function expression in the polar coordinate space to obtain the position information of the user to be located.

[0016] According to another aspect of the embodiments of the present invention, there is also provided an electronic device, including: a memory storing an executable program; a processor configured to run the executable program, where the executable program, when running, executes the wireless positioning method in any one of the above.

[0017] According to another aspect of the embodiments of the present invention, there is also provided a computer program product, including a computer program that implements the wireless positioning method in any one of the above when executed by a processor.

[0018] According to another aspect of the embodiments of the present invention, there is also provided a computer-readable storage medium, where the computer-readable storage medium includes a stored executable program, and where, when the executable program runs, it controls the device where the computer-readable storage medium is located to execute the wireless positioning method in any one of the above.

[0019] In an embodiment of the present invention, a received signal received by an active receiving unit of a hybrid intelligent reflecting surface is obtained; a preset algorithm is used to process the received signal to obtain initial direction information of a user to be located; based on the initial direction information, a passive reflection coefficient of a passive reflection unit of the hybrid intelligent reflecting surface is adjusted to obtain a plurality of first passive reflection coefficients, where the plurality of first passive reflection coefficients are used to make the reflected signal be directionally focused on different positions in the initial direction to obtain a plurality of directionally focused signals, and the reflected signal is the received signal reflected by the passive reflection unit; according to the plurality of directionally focused signals, a base station is controlled to determine a target focus point position and a second passive reflection coefficient corresponding to the target focus point position; based on the initial direction information, the target focus point position, and the second passive reflection coefficient, the base station is controlled to determine the position information of the user to be located. By using the active receiving unit of the hybrid intelligent reflecting surface, the present invention preliminarily estimates the user direction, realizes providing key prior information for subsequent positioning without increasing the system complexity, and at the same time, through the directional focusing of the passive reflection unit, and determining the target focus point position and the second passive reflection coefficient, realizes dynamic optimization of the reflection path, ensures that the signal propagates on the most favorable path, so as to improve the positioning accuracy, thereby solving the technical problem of how to improve the wireless positioning accuracy without increasing the system complexity. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The drawings described herein are used to provide a further understanding of the present invention, and constitute a part of this application. The illustrative embodiments of the present invention and their descriptions are used to explain the present invention, and do not constitute an improper limitation of the present invention. In the drawings:

[0021] Figure 1 is a flowchart of a wireless positioning method according to one embodiment of the present invention;

[0022] Figure 2 is a schematic architecture diagram of a wireless positioning method according to one embodiment of the present invention;

[0023] Figure 3 is a second flowchart of a wireless positioning method according to one embodiment of the present invention;

[0024] Figure 4 is a schematic diagram of positioning error comparison of a wireless positioning method according to one embodiment of the present invention under different numbers of active receiving units;

[0025] Figure 5 is a structural block diagram of a wireless positioning method according to one embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0026] To enable those skilled in the art to better understand the solution of the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the scope of protection of the present invention.

[0027] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned accompanying drawings are used to distinguish similar objects, and do not necessarily need to be used to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments of the present invention described here can be implemented in an order different from those illustrated or described here. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device comprising a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0028] According to an embodiment of the present invention, an embodiment of a wireless positioning method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system including at least one set of computer-executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that here.

[0029] This method embodiment can also be executed in an electronic device including a memory and a processor, a similar control device, or in the cloud. Taking the electronic device as an example, the electronic device may include one or more processors and a memory for storing data. Optionally, the above-mentioned electronic device may further include a communication device for communication functions and a display device. Those of ordinary skill in the art can understand that the above structural description is only illustrative and does not limit the structure of the above-mentioned electronic device. For example, the electronic device may further include more or fewer components than the above structural description, or have a configuration different from the above structural description.

[0030] The processor may include one or more processing units. For example, the processor may include a central processing unit (CPU), a graphics processing unit (GPU), a digital signal processing (DSP) chip, a microcontroller unit (MCU), a field-programmable gate array (FPGA), a neural-network processing unit (NPU), a tensor processing unit (TPU), an artificial intelligent (AI) type processor, and other processing devices. Among them, different processing units may be independent components or integrated in one or more processors. In some instances, the electronic device may also include one or more processors.

[0031] The memory can be used to store computer programs. For example, it stores the computer program corresponding to the wireless positioning method in the embodiments of the present invention. The processor realizes the above-mentioned wireless positioning method by running the computer program stored in the memory. The memory may include a high-speed random access memory and may also include a non-volatile memory, such as one or more magnetic storage devices, a flash memory, or other non-volatile solid-state memories. In some instances, the memory may further include a memory remotely set relative to the processor, and these remote memories can be connected to the electronic device through a network. Examples of the above network include but are not limited to the Internet, an enterprise intranet, a local area network, a mobile communication network, and their combinations.

[0032] The communication device is used to receive or send data via a network. Specific examples of the above network may include a wireless network provided by the communication provider of the mobile terminal. In one instance, the communication device includes a network interface controller (NIC), which can be connected to other network devices through a base station and thus communicate with the Internet. In one instance, the communication device may be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly. In some embodiments of this solution, the communication device is used to connect to mobile devices such as mobile phones and tablets, and can send instructions to the electronic device through the mobile devices.

[0033] The display device can be a touch-screen liquid crystal display (LCD) and a touch display (also known as a "touch screen" or "touch display screen"). The liquid crystal display enables a user to interact with the user interface of an electronic device. In some embodiments, the above-mentioned electronic device has a graphical user interface (GUI), and the user can perform human-computer interaction with the GUI by touching the finger on the touch-sensitive surface and / or gestures. The executable instructions for performing the above human-computer interaction functions are configured / stored in a computer program product or a readable storage medium executable by one or more processors.

[0034] Figure 1 is a flowchart of a wireless positioning method according to an embodiment of the present invention, as Figure 1 shown, the method includes the following steps:

[0035] Step S101, obtain the received signal received by the active receiving unit of the hybrid intelligent reflecting surface.

[0036] Specifically, a hybrid reconfigurable intelligent surface (HRIS) is a new type of wireless communication and signal processing technology that combines passive reflection and active reception capabilities. HRIS includes two types of units: passive reflection units and active reception units. The passive reflection units change the signal propagation path by adjusting the phase of the reflected signal to optimize the signal transmission quality; while the active reception units can directly capture and process signals for preliminary direction estimation and feedback information. The hybrid intelligent reflecting surface can dynamically adjust its function configuration according to environmental changes and signal requirements, so as to improve the performance of wireless communication and positioning systems without significantly increasing the system complexity.

[0037] Specifically, the active receiving unit is connected to a radio frequency link to receive the uplink signal transmitted by the user equipment. Obtain the uplink signal transmitted by the user captured by the active receiving unit for subsequent processing to obtain the initial direction information of the user equipment.

[0038] It should be noted that compared with a fully active antenna array, HRIS only needs a small number of active receiving units to be connected to the radio frequency link, which greatly reduces the system cost and power consumption.

[0039] Step S102, use a preset algorithm to process the received signal to obtain the initial direction information of the user to be located.

[0040] Specifically, use a preset algorithm to process the signal received by the active receiving unit to estimate the direction of the signal source.

[0041] Optionally, the preset algorithm is the two-dimensional MUSIC algorithm (Multiple Signal Classification). The two-dimensional MUSIC algorithm is a signal processing algorithm used to estimate the direction of arriving signals. The MUSIC algorithm is based on the autocorrelation matrix of the signals. Through eigenvalue decomposition and spectral peak search, it can extract the azimuth and elevation angle information of the signal sources from the received signals. The core of the MUSIC algorithm lies in utilizing the orthogonality between the noise subspace and the signal subspace. By calculating the product of the steering vector of the signal and the corresponding matrix of the noise subspace, a spectral function is formed, and this function has obvious peaks in the directions of the signal sources. By searching for the maximum value of the spectral function, the initial azimuth and initial elevation angles of the signal sources can be estimated.

[0042] Step S103: Based on the initial direction information, adjust the passive reflection coefficients of the passive reflection units of the hybrid intelligent reflecting surface to obtain a plurality of first passive reflection coefficients. Among them, the plurality of first passive reflection coefficients are used to make the reflected signals be directionally focused on different positions in the initial direction, so as to obtain a plurality of directionally focused signals. The reflected signal is the received signal reflected by the passive reflection unit.

[0043] Specifically, based on the obtained initial direction information (including the azimuth angle estimation value and elevation angle estimation value of the user to be located), different passive reflection coefficients, that is, phase shift values, are assigned to the passive reflection units of the HRIS to change the phase of the reflected signals, so as to guide the signals to form a focusing effect at different positions in the direction of the user equipment, and a plurality of directionally focused signals are obtained.

[0044] Specifically, the generation of the directionally focused signals is achieved through a phase shift control mechanism. This process utilizes the large-scale array effect and near-field effect of the passive reflection units of the HRIS, and can form intensity peaks at different positions in the direction of the user equipment, providing multi-point references for the positioning algorithm, thereby overcoming the limitations of single-point signals in traditional positioning methods.

[0045] Among them, the large-scale array effect of the passive reflection units of the HRIS refers to that when the passive reflection units of the HRIS are arranged in a large-scale array form, the propagation direction of the signals can be controlled by finely adjusting the phase shift of each unit, forming the effect of beamforming. This effect enables the signals to be concentrated in a specific direction, increasing the signal intensity in this direction while forming attenuation in other directions, thereby achieving the directional focusing of the signals.

[0046] The near-field effect refers to the complex and non-uniform characteristics exhibited by the electromagnetic field when the distance between the emission source and the observation point is much smaller than the ratio of the wavelength to the antenna size. In the near field, the electromagnetic field includes not only the radiation component of the far field but also the induction component of the near field, which results in significant differences in the phase distribution and intensity distribution of the electromagnetic field compared to the far-field conditions. The near-field effect of the HRIS is used in the positioning technology in this invention. By intelligently adjusting the first passive reflection coefficient of the passive reflection unit, it is possible to form an enhanced region of signal intensity near the user equipment using the near-field effect, and the positions of these enhanced regions are related to the actual position of the user equipment.

[0047] Step S104: According to multiple directional focusing signals, control the base station to determine the target focusing point position and the corresponding second passive reflection coefficient of the target focusing point.

[0048] Specifically, the base station receives multiple directional focusing signals from the HRIS, and these signals have intensity peaks at different positions in the direction of the user equipment. By analyzing the signal intensity distribution, the base station determines the target focusing point and the corresponding second passive reflection coefficient of the target focusing point position. The target focusing point position provides a key reference for subsequent precise positioning of the user equipment.

[0049] Specifically, after determining the target focusing point, calculate the second passive reflection coefficient for the target focusing point, that is, the new phase shift value of the HRIS passive reflection unit. The setting of the second passive reflection coefficient ensures that the signal intensity at the target focusing point reaches the maximum, thereby further focusing the signal and improving the positioning accuracy.

[0050] Step S105: Based on the initial direction information, the target focusing point position, and the second passive reflection coefficient, control the base station to determine the position information of the user to be located.

[0051] Specifically, by combining the determined initial direction information, the target focusing point position, and the second passive reflection coefficient, use the near-field effect and the MUSIC algorithm to accurately calculate the position coordinates of the user equipment.

[0052] In an embodiment of the present invention, a received signal received by an active receiving unit of a hybrid intelligent reflecting surface is obtained; a preset algorithm is used to process the received signal to obtain initial direction information of a user to be located; based on the initial direction information, the passive reflection coefficients of the passive reflection units of the hybrid intelligent reflecting surface are adjusted to obtain a plurality of first passive reflection coefficients, where the plurality of first passive reflection coefficients are used to make the reflected signal be directionally focused at different positions in the initial direction to obtain a plurality of directionally focused signals, and the reflected signal is the received signal reflected by the passive reflection unit; according to the plurality of directionally focused signals, a base station is controlled to determine a target focus point position and a second passive reflection coefficient corresponding to the target focus point position; based on the initial direction information, the target focus point position, and the second passive reflection coefficient, the base station is controlled to determine the position information of the user to be located. By using the active receiving unit of the hybrid intelligent reflecting surface, the present invention makes a preliminary estimation of the user's direction, realizes providing key prior information for subsequent positioning without increasing the system complexity, and at the same time, through the directional focusing of the passive reflection unit, and determining the target focus point position and the second passive reflection coefficient, realizes dynamic optimization of the reflection path, ensures that the signal propagates on the most favorable path, and improves the positioning accuracy, thereby solving the technical problem of how to improve the wireless positioning accuracy without increasing the system complexity.

[0053] Optionally, the initial direction information of the user to be located includes an estimated pitch angle value and an estimated azimuth angle value of the user to be located.

[0054] Specifically, the estimated pitch angle value and the estimated azimuth angle value, as two key parameters describing the direction of the user equipment relative to the HRIS or the base station, provide important references for subsequent signal focusing and position estimation. The accuracy of the estimated pitch angle and azimuth angle values directly affects the effect of subsequent signal focusing.

[0055] Optionally, the active receiving units of the hybrid intelligent reflecting surface form an L-shaped array.

[0056] Specifically, the L-shaped array consists of two parts of units, vertical and horizontal, forming a right-angled layout. This structure can capture signals in both the vertical and horizontal directions, further estimate the azimuth angle and pitch angle of the signal, and provide two types of angle information, azimuth angle and pitch angle, for subsequent direction estimation. Compared with a linear or rectangular array, the L-shaped array can provide stable receiving performance in a wider range of pitch angles and azimuth angles, enhancing the accuracy and robustness of positioning.

[0057] In addition, the active receiving units in the HRIS form an L-shaped array, which can not only significantly improve the signal receiving ability and positioning accuracy, but also, compared with the configuration of the full-array active receiving units, the L-shaped array simplifies the number of units, effectively controls the system complexity and cost, and makes it more feasible for large-scale deployment and application.

[0058] Optionally, using a preset algorithm, the received signal is processed to obtain the initial direction information of the user to be located, including the following steps:

[0059] Step S1021: Based on the received signal, determine the autocorrelation matrix of the received signal;

[0060] Figure 2 is a schematic architecture diagram of a wireless positioning method according to an embodiment of the present invention. The following is a detailed explanation of the present invention in combination with Figure 2 to explain the present invention in detail.

[0061] Specifically, let the length of the transmitted pilot signal be T, and the number of active units of the hybrid intelligent reflecting surface be N A . The arrival elevation angle and azimuth angle of the user at the hybrid intelligent reflecting surface are respectively denoted as θ RU and φ RU . The signal received by the active receiving unit on the hybrid intelligent reflecting surface is expressed as:

[0062]

[0063] where Y (HR) is the signal received by the active receiving unit; is the steering vector of the active receiving part of the hybrid intelligent reflecting surface for the user; α' HR is the unknown path complex gain; X is the known transmitted pilot signal; W (HR) represents noise.

[0064] The two-dimensional MUSIC algorithm is used to estimate the elevation angle and azimuth angle of the user based on the received signal Y (HR) .

[0065] Specifically, calculate the autocorrelation matrix of the signal received by the active receiving unit on the hybrid intelligent reflecting surface. The autocorrelation matrix of the received signal is expressed as:

[0066]

[0067] where R HR is the autocorrelation matrix of the received signal; T is the length of the transmitted pilot signal; Y (HR) is the signal received by the active receiving unit; (Y (HR) ) H is the conjugate transpose of Y (HR) .

[0068] It should be noted that the autocorrelation matrix can reflect the correlation of the signal at different time delays and provides a basis for subsequent eigenvalue decomposition.

[0069] Step S1022: Perform eigenvalue decomposition on the autocorrelation matrix to obtain the first matrix corresponding to the noise subspace;

[0070] In an alternative embodiment, the number of signal sources is known to be a single signal source. The autocorrelation matrix is subjected to eigenvalue decomposition to obtain a set of eigenvalues and corresponding eigenvectors. The obtained eigenvalues and eigenvectors can be divided into two parts: the eigenvalues and eigenvectors corresponding to the signal subspace, and the eigenvalues and eigenvectors corresponding to the noise subspace. Among them, the eigenvalue corresponding to the signal subspace is the largest eigenvalue, and the eigenvector corresponding to the signal subspace is the eigenvector corresponding to the largest eigenvalue. The eigenvectors other than those corresponding to the signal subspace are combined to form a first matrix corresponding to the noise subspace, and the first matrix corresponding to the noise subspace is used for subsequent direction estimation.

[0071] Optionally, when the number of signal sources is not a single signal source, the autocorrelation matrix is subjected to eigenvalue decomposition to obtain a first matrix corresponding to the noise subspace in the case of non-single signal sources. Exemplarily, when the number of signal sources is 2, the autocorrelation matrix is subjected to eigenvalue decomposition. Among them, the eigenvalues corresponding to the signal subspace are the largest 2 eigenvalues among the decomposed eigenvalues, and the eigenvectors corresponding to the signal subspace are the eigenvectors corresponding to the largest 2 eigenvalues. The eigenvectors other than those corresponding to the signal subspace are combined to form a first matrix corresponding to the noise subspace.

[0072] Specifically, the autocorrelation matrix R of the received signal calculated above HR is subjected to eigenvalue decomposition to obtain a first matrix U corresponding to the noise subspace n,HR .

[0073] Step S1023: Generate a first steering vector according to the first preset range of azimuth angle and the first preset range of elevation angle;

[0074] Specifically, the steering vector is a core concept in the direction estimation algorithm and is used to represent the angle information of the signal arriving at the HRIS or the base station.

[0075] Specifically, the first preset range of azimuth angle is set as θ ∈ (0, π), and the first preset range of elevation angle is set as φ ∈ (-π / 2, π / 2). A first steering vector is generated within the preset azimuth angle and elevation angle ranges

[0076] Step S1024: Determine the estimated elevation angle and azimuth angle of the user to be located according to the first matrix and the first steering vector.

[0077] Specifically, based on the first matrix and the first steering vector, spectral peak search is performed through a preset algorithm (such as MUSIC algorithm) to obtain the estimated elevation angle and azimuth angle of the user.

[0078] Exemplarily, the MUSIC algorithm utilizes the orthogonality between the noise subspace and the signal subspace to determine the direction of signal arrival by calculating the orthogonality degree between the steering vector and the noise subspace.

[0079] Optionally, based on the first matrix and the first steering vector, determining the elevation angle estimate and the azimuth angle estimate of the user to be located includes the following steps:

[0080] Step S10241, determining a first function expression according to the first matrix and the first steering vector;

[0081] Specifically, according to the obtained first matrix U n,HR and the first steering vector determine the MUSIC algorithm spectral function expression, that is, the first function expression, and the first function expression can be expressed as:

[0082]

[0083] Step S10242, determining the maximum value point of the first function expression within a preset search range to obtain the elevation angle estimate and the azimuth angle estimate of the user to be located, where the preset search range is determined by the first preset range of the azimuth angle and the first preset range of the elevation angle.

[0084] Specifically, based on the generated MUSIC algorithm spectral function expression (the first function expression), perform spectral peak search within the preset search range to find the maximum value point of the spectral function and obtain the estimated values of the user's elevation angle and azimuth angle and where the spectral peak search refers to finding the maximum value point of the spectral function within the preset search range, so as to obtain the azimuth angle estimate and the elevation angle estimate of the user to be located.

[0085] Optionally, based on the initial direction information, adjusting the passive reflection coefficients of the passive reflection units of the hybrid intelligent reflecting surface to obtain multiple first passive reflection coefficients includes the following steps:

[0086] Step S1031, determining a position list according to the initial direction information and the preset distance list;

[0087] Specifically, the directional focusing signal received by the base station can be expressed as:

[0088]

[0089] where α B represents an unknown shadow fading coefficient, f c represents the carrier frequency, ξ represents an unknown synchronization error between the base station and the user, W (B) represents noise, p U represents the user position, represents the channel between the passive reflection unit of the hybrid intelligent reflecting surface and the user's location, and Φ represents the first passive reflection coefficient of the hybrid intelligent reflecting surface. represents the channel between the base station and the passive reflection unit of the hybrid intelligent reflecting surface. The (b, r)-th element can be expressed as:

[0090]

[0091] where d BR represents the distance between the base station and the hybrid intelligent reflecting surface, and λ c represents the carrier wavelength.

[0092] It should be noted that different directional focusing signals correspond to different values of Φ.

[0093] Under the near-field condition, The r-th element can be expressed as:

[0094]

[0095] where p r represents the position of the passive reflection unit r in the hybrid intelligent reflecting surface, represents the speed of light.

[0096] Specifically, select N parameters d representing distances i (i = 1,... N) to form a preset distance list. According to the initial direction information and the preset distance list, determine the position list p F(d i )(i = 1,..., N). p F (d i ) can be expressed as:

[0097]

[0098] where and are the estimated values of the user's elevation angle and azimuth angle.

[0099] Step S1032: According to the position list and the preset passive reflection coefficient expression, regulate the passive reflection coefficient to obtain multiple first passive reflection coefficients.

[0100] Specifically, regulate the passive reflection coefficient Φ, and determine the multiple passive reflection coefficients that can focus the reflected signal to different positions included in the position list as multiple first passive reflection coefficients. Φ can be expressed as:

[0101]

[0102] where denotes the Kronecker product, is the matrix a vector composed of the phases of the elements in any row, represents the channel between the passive reflection unit of the hybrid intelligent reflecting surface and the focal point, the r-th component element of is expressed as

[0103] Based on the passive reflection coefficient expression, Φ is set so that the reflected signal can be focused on multiple positions in the position list, and then multiple directional focusing signals are obtained.

[0104] Optionally, according to the multiple directional focusing signals, the base station is controlled to determine the target focal point position and the second passive reflection coefficient corresponding to the target focal point position, including the following steps:

[0105] Step S1041, the base station is controlled to calculate the signal power of the received multiple directional focusing signals and determine the maximum signal power from the multiple signal powers;

[0106] Specifically, the base station receives these signals regulated by the HRIS passive reflection unit, and by calculating the power of the received signals, a series of signal power values can be obtained.

[0107] Specifically, the base station obtains the signal powers corresponding to N directional focusing signals and determines the maximum signal power P from the N different signal powers R，max .

[0108] Step S1042, according to the maximum signal power, determine the signal power threshold;

[0109] Specifically, the setting of the signal power threshold is based on the maximum signal power value and is used to screen out the focal points whose signal quality meets the positioning requirements. The selection of the threshold needs to consider factors such as positioning accuracy requirements, signal environment, and fading in transmission to ensure that the signal quality of the selected focal points is good enough to support subsequent accurate position estimation.

[0110] Specifically, according to the determined maximum signal power P R，max , a threshold value based on P R，max is set as the signal power threshold.

[0111] Optionally, in actual engineering, the threshold value is usually set to P R，max / 2.

[0112] Step S1043, based on the signal power threshold, determine the target focal point position;

[0113] Specifically, after determining the signal power threshold, all signal power values are further analyzed, and the focal point position corresponding to the signal power that is greater than the signal power threshold and has the smallest difference from the signal power threshold is selected as the candidate target focal point position, which is an approximation of the most likely position of the user.

[0114] By determining the target focal point position, it is ensured that the positioning process focuses on the area with the best signal quality.

[0115] Step S1044: Determine the second passive reflection coefficient according to the target focal point position.

[0116] Specifically, once the target focal point position is determined, the passive reflection unit of the HRIS will be configured with the corresponding second passive reflection coefficient to optimize the transmission of the signal at the target focal point.

[0117] Optionally, based on the signal power threshold, determining the target focal point position includes the following steps:

[0118] Step S10431: Determine the target signal power from multiple signal powers based on the signal power threshold, where the target signal power is the signal power with the smallest difference from the signal power threshold among the multiple signal powers, and the target signal power is greater than the signal power threshold;

[0119] Specifically, among the multiple signal powers, the signal power that is greater than the signal power threshold and has the smallest difference from the signal power threshold is screened out, and this signal power is defined as the target signal power.

[0120] Step S10432: Determine the target focal point position according to the target signal power.

[0121] Specifically, according to the screened target signal power, the corresponding focal point position is determined, which is the target focal point position.

[0122] Optionally, based on the initial direction information, the target focal point position, and the second passive reflection coefficient, controlling the base station to determine the location information of the user to be located includes the following steps:

[0123] Step S1051: Control the base station to determine the second steering vector expression based on the second passive reflection coefficient;

[0124] Specifically, the determined second passive reflection coefficient (optimal reflection coefficient) is set as the passive reflection unit coefficient of the hybrid intelligent reflecting surface. At this time, the target directional focusing signal received by the base station can be expressed as:

[0125]

[0126] Among them, the second steering vector The expression is defined as:

[0127]

[0128] Among them, Φ is the determined second passive reflection coefficient, and ||·|| represents the l 2 norm of the vector.

[0129] Step S1052: Determine the autocorrelation matrix of the target-oriented focusing signal based on the target-oriented focusing signal corresponding to the target focusing point;

[0130] Specifically, based on the target-oriented focusing signal determined according to formula (8), determine the autocorrelation matrix of the target-oriented focusing signal. The autocorrelation matrix of the target-oriented focusing signal can be expressed as:

[0131]

[0132] Among them, R B is the autocorrelation matrix of the target-oriented focusing signal, T is the length of the transmitted pilot signal, and Y (B) is the target-oriented focusing signal; (Y (B) ) H is the conjugate transpose of Y (B) .

[0133] Step S1053: Perform eigenvalue decomposition on the autocorrelation matrix of the target-oriented focusing signal to obtain a second matrix corresponding to the noise subspace;

[0134] Specifically, perform eigenvalue decomposition on the autocorrelation matrix R B to obtain a second matrix U n，B corresponding to the noise subspace.

[0135] Step S1054: Generate a second steering vector according to the target focusing point position, the polar coordinate space, and the second steering vector expression. Among them, the polar coordinate space is constructed based on a preset distance range, a second preset azimuth range, and a second preset elevation range, and the second preset azimuth range and the second preset elevation range are determined based on the initial direction information;

[0136] Specifically, for the target focusing point position p, based on the preset distance range (d min , d max ), the second preset elevation range and the second preset azimuth range constitute the polar coordinate space. In the above polar coordinate space, multiple discrete points are sampled to determine the positions of the multiple discrete points. Substitute the obtained positions of the multiple discrete points into the second steering vector expression (10) to generate the second steering vector Among them, the second steering vector expression is a function expression about the position.

[0137] Step S1055: Determine the location information of the user to be located according to the second matrix and the second steering vector.

[0138] Specifically, based on the determined second matrix U n，B and the second steering vector use the MUSIC algorithm to determine the location information of the user to be located.

[0139] Optionally, determining the location information of the user to be located according to the second matrix and the second steering vector includes the following steps:

[0140] Step S10551: Determine the second function expression according to the second matrix and the second steering vector;

[0141] Specifically, according to the obtained second matrix U n，B and the second steering vector re-determine the MUSIC algorithm spectrum function expression, that is, the second function expression, and the second function expression can be expressed as:

[0142]

[0143] Step S10552: Determine the maximum point of the second function expression in the polar coordinate space to obtain the location information of the user to be located.

[0144] Specifically, according to the determined second function expression, perform spectrum peak search in the polar coordinate space to determine the maximum point of the second function expression, and obtain the estimated value of the user's location that is, realize the positioning of the user.

[0145] In summary, the present invention uses the active receiving unit of the hybrid intelligent reflecting surface to preliminarily estimate the user's direction, realizes providing key prior information for subsequent positioning without increasing the system complexity, and at the same time, through the directional focusing of the passive reflecting unit, and determining the target focusing point position and the second passive reflection coefficient, realizes dynamic optimization of the reflection path, ensures that the signal propagates on the most favorable path, so as to improve the positioning accuracy, thereby solving the technical problem of how to improve the wireless positioning accuracy without increasing the system complexity.

[0146] Optionally, Figure 3 is the second flowchart of the wireless positioning method according to an embodiment of the present invention. As Figure 3 shown, the wireless positioning method disclosed by the present invention can also be implemented as follows:

[0147] First, use the L-shaped array composed of a small number of active receiving units of the hybrid intelligent reflecting surface to estimate the elevation angle and azimuth angle of the user, and obtain a rough estimate of the user's direction. Secondly, adjust the passive reflection unit coefficients of the hybrid intelligent reflecting surface to focus the signal at different distances in the direction of the user roughly estimated by the active part, and obtain multiple received signal powers. Then, among all the obtained received signal powers, select the position corresponding to the received power closest to the threshold value as the finally determined focusing point and set the passive reflection coefficient of the hybrid intelligent reflecting surface to the reflection coefficient corresponding to the finally determined focusing point. Finally, directly locate the user using the near-field effect between the passive part of the hybrid intelligent reflecting surface and the user with the MUSIC algorithm.

[0148] Exemplarily, the following simulations are performed on the positioning method provided by the present invention:

[0149] First, construct simulation experiment parameters, define that the base station is equipped with 64 antennas, the total number of units of the hybrid intelligent reflecting surface is 60×60, the distance between the base station and the hybrid intelligent reflecting surface is 4.5 meters, and the distance between the hybrid intelligent reflecting surface and the user is 5 meters.

[0150] Set different numbers N of active units of the hybrid intelligent reflecting surface A , and statistically analyze the relationship between the average positioning error of 100 positioning experiments and the average received signal-to-noise ratio. Figure 4 Shows the positioning error situation of the wireless positioning method according to an embodiment of the present invention under different numbers of active receiving units.

[0151] From Figure 4 it can be seen that the wireless positioning method disclosed by the present invention can obtain good positioning performance even with a small number of active receiving units in the high signal-to-noise ratio region. The positioning accuracy of the positioning method proposed by the present invention can reach the decimeter level in the positioning scenario.

[0152] Through the description of the above embodiments, those skilled in the art can clearly understand that the method according to the above embodiments can be implemented by means of software plus a necessary general hardware platform. Of course, it can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention, in essence, or the part that makes a contribution to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disc), and includes several instructions for causing a terminal device (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods described in various embodiments of the present invention.

[0153] In an embodiment of the present invention, a wireless positioning system is further provided to implement the above embodiments and preferred implementation manners, and those that have been described will not be repeated. As used hereinafter, the term "module" may be a combination of software and / or hardware that implements a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware is also possible and contemplated.

[0154] Figure 5 is a structural block diagram of a wireless positioning system 500 according to an embodiment of the present invention. As Figure 5 shown, the system includes: an acquisition module 501, configured to acquire a received signal received by an active receiving unit of a hybrid intelligent reflecting surface; a processing module 502, configured to process the received signal by using a preset algorithm to obtain initial direction information of a user to be located; a regulation module 503, configured to regulate a passive reflection coefficient of a passive reflection unit of the hybrid intelligent reflecting surface based on the initial direction information to obtain a plurality of first passive reflection coefficients, where the plurality of first passive reflection coefficients are used to make the reflected signal be directionally focused at different positions in the initial direction to obtain a plurality of directionally focused signals, and the reflected signal is the received signal reflected by the passive reflection unit; a determination module 504, configured to control a base station to determine a target focus point position and a second passive reflection coefficient corresponding to the target focus point position according to the plurality of directionally focused signals; and a positioning module 505, configured to control the base station to determine the position information of the user to be located based on the initial direction information, the target focus point position, and the second passive reflection coefficient.

[0155] Optionally, the initial direction information of the user to be located includes an estimated pitch angle and an estimated azimuth angle of the user to be located.

[0156] Optionally, the active receiving units of the hybrid intelligent reflecting surface form an L-shaped array.

[0157] Optionally, the processing module 502 is further configured to: determine an autocorrelation matrix of the received signal based on the received signal; perform eigenvalue decomposition on the autocorrelation matrix to obtain a first matrix corresponding to a noise subspace; generate a first steering vector according to a first preset range of azimuth angles and a first preset range of pitch angles; and determine the estimated pitch angle and the estimated azimuth angle of the user to be located according to the first matrix and the first steering vector.

[0158] Optionally, the processing module 502 is further configured to: determine a first function expression according to the first matrix and the first steering vector; determine a maximum value point of the first function expression within a preset search range to obtain the estimated pitch angle and the estimated azimuth angle of the user to be located, where the preset search range is determined by the first preset range of azimuth angles and the first preset range of pitch angles.

[0159] Optionally, the regulation module 503 is further configured to: determine a position list according to the initial direction information and a preset distance list; regulate the passive reflection coefficient according to the position list and a preset passive reflection coefficient expression to obtain a plurality of first passive reflection coefficients.

[0160] Optionally, the determination module 504 is further configured to: control the base station to calculate the signal power of a plurality of received directional focusing signals and determine the maximum signal power from the plurality of signal powers; determine a signal power threshold according to the maximum signal power; determine a target focusing point position based on the signal power threshold; and determine a second passive reflection coefficient according to the target focusing point position.

[0161] Optionally, the determination module 504 is further configured to: determine a target signal power from the plurality of signal powers based on the signal power threshold, where the target signal power is the signal power with the smallest difference from the signal power threshold among the plurality of signal powers, and the target signal power is greater than the signal power threshold; and determine a target focusing point position according to the target signal power.

[0162] Optionally, the positioning module 505 is further configured to: control the base station to determine a second steering vector expression based on the second passive reflection coefficient; determine an autocorrelation matrix of the target directional focusing signal based on the target directional focusing signal corresponding to the target focusing point; perform eigenvalue decomposition on the autocorrelation matrix of the target directional focusing signal to obtain a second matrix corresponding to the noise subspace; generate a second steering vector according to the target focusing point position, the polar coordinate space, and the second steering vector expression, where the polar coordinate space is constructed based on a preset distance range, a second preset range of azimuth angles, and a second preset range of elevation angles, and the second preset range of azimuth angles and the second preset range of elevation angles are determined based on the initial direction information; and determine the position information of the user to be located according to the second matrix and the second steering vector.

[0163] Optionally, the positioning module 505 is further configured to: determine a second function expression according to the second matrix and the second steering vector; and determine the maximum value point of the second function expression in the polar coordinate space to obtain the position information of the user to be located.

[0164] An embodiment of the present invention further provides an electronic device, including: a memory storing an executable program; and a processor configured to run the executable program, where, when the executable program runs, it executes the wireless positioning method described in any of the above embodiments.

[0165] Optionally, in this embodiment, the processor in the above electronic device may be configured to run the executable program to execute the following steps:

[0166] Step S101, obtain a received signal received by an active receiving unit of a hybrid intelligent reflecting surface.

[0167] Step S102: Process the received signal using a preset algorithm to obtain initial direction information of the user to be located.

[0168] Step S103, based on the initial direction information, adjust the passive reflection coefficient of the passive reflection unit of the hybrid intelligent reflection surface to obtain multiple first passive reflection coefficients, wherein the multiple first passive reflection coefficients are used to make the reflection signal directionally focused at different positions in the initial direction to obtain multiple directional focusing signals, and the reflection signal is a received signal reflected by the passive reflection unit.

[0169] Step S104: Control the base station to determine a target focus point position and a second passive reflection coefficient corresponding to the target focus point position according to the multiple directional focus signals.

[0170] Step S105, based on the initial direction information, the target focus point position and the second passive reflection coefficient, control the base station to determine the position information of the user to be located.

[0171] Optionally, the initial direction information of the user to be located includes an estimated value of the elevation angle and an estimated value of the azimuth angle of the user to be located.

[0172] Optionally, the active receiving units of the hybrid intelligent reflective surface form an L-shaped array.

[0173] Optionally, the processor in the above-mentioned electronic device can be configured to run an executable program to perform the following steps: based on the received signal, determine the autocorrelation matrix of the received signal; perform eigenvalue decomposition on the autocorrelation matrix to obtain a first matrix corresponding to the noise subspace; generate a first steering vector based on a first preset range of azimuth angles and a first preset range of elevation angles; and determine an estimated value of the elevation angle and an estimated value of the azimuth angle of the user to be located based on the first matrix and the first steering vector.

[0174] Optionally, the processor in the above-mentioned electronic device can be configured to run an executable program to perform the following steps: determine a first function expression based on a first matrix and a first steering vector; determine the maximum value point of the first function expression within a preset search range to obtain an estimated value of the pitch angle and an estimated value of the azimuth angle of the user to be located, wherein the preset search range is determined by a first preset range of the azimuth angle and a first preset range of the pitch angle.

[0175] Optionally, the processor in the above-mentioned electronic device can be configured to run an executable program to perform the following steps: determine a position list based on initial direction information and a preset distance list; regulate the passive reflection coefficient based on the position list and a preset passive reflection coefficient expression to obtain multiple first passive reflection coefficients.

[0176] Optionally, the processor in the above-mentioned electronic device can be configured to run an executable program to perform the following steps: control the base station to calculate the signal power of multiple received directional focusing signals, and determine the maximum signal power from the multiple signal powers; determine the signal power threshold based on the maximum signal power; determine the target focusing point position based on the signal power threshold; determine the second passive reflection coefficient based on the target focusing point position.

[0177] Optionally, the processor in the above-mentioned electronic device can be configured to run an executable program to perform the following steps: based on a signal power threshold, determine a target signal power from multiple signal powers, wherein the target signal power is a signal power among the multiple signal powers having the smallest difference with the signal power threshold, and the target signal power is greater than the signal power threshold; and according to the target signal power, determine the target focus point position.

[0178] Optionally, the processor in the above-mentioned electronic device can be configured to run an executable program to perform the following steps: control the base station to determine a second steering vector expression based on a second passive reflection coefficient; determine an autocorrelation matrix of the target directional focusing signal based on the target directional focusing signal corresponding to the target focal point; perform eigenvalue decomposition on the autocorrelation matrix of the target directional focusing signal to obtain a second matrix corresponding to the noise subspace; generate a second steering vector according to the target focal point position, the polar coordinate space and the second steering vector expression, wherein the polar coordinate space is constructed based on a preset distance range, a second preset range of azimuth angles and a second preset range of elevation angles, and the second preset range of azimuth angles and the second preset range of elevation angles are determined based on initial direction information; determine the position information of the user to be located according to the second matrix and the second steering vector.

[0179] Optionally, the processor in the above-mentioned electronic device can be configured to run an executable program to perform the following steps: determine a second function expression based on the second matrix and the second steering vector; determine the maximum value point of the second function expression in the polar coordinate space to obtain the position information of the user to be located.

[0180] An embodiment of the present invention further provides a computer program product, including a computer program, which implements the wireless positioning method described in any of the above embodiments when executed by a processor.

[0181] Optionally, in this embodiment, the above computer program implements the following steps when executed by a processor:

[0182] Step S101, obtaining a reception signal received by an active receiving unit of a hybrid intelligent reflective surface.

[0183] Step S102: Process the received signal using a preset algorithm to obtain initial direction information of the user to be located.

[0184] Step S103, based on the initial direction information, adjust the passive reflection coefficient of the passive reflection unit of the hybrid intelligent reflection surface to obtain multiple first passive reflection coefficients, wherein the multiple first passive reflection coefficients are used to make the reflection signal directionally focused at different positions in the initial direction to obtain multiple directional focusing signals, and the reflection signal is a received signal reflected by the passive reflection unit.

[0185] Step S104: Control the base station to determine a target focus point position and a second passive reflection coefficient corresponding to the target focus point position according to the multiple directional focus signals.

[0186] Step S105, based on the initial direction information, the target focus point position and the second passive reflection coefficient, control the base station to determine the position information of the user to be located.

[0187] Optionally, the initial direction information of the user to be located includes an estimated value of the elevation angle and an estimated value of the azimuth angle of the user to be located.

[0188] Optionally, the active receiving units of the hybrid intelligent reflective surface form an L-shaped array.

[0189] Optionally, the above-mentioned computer program implements the following steps when executed by the processor: based on the received signal, determine the autocorrelation matrix of the received signal; perform eigenvalue decomposition on the autocorrelation matrix to obtain a first matrix corresponding to the noise subspace; generate a first steering vector according to a first preset range of azimuth angles and a first preset range of elevation angles; and determine the elevation angle estimation value and azimuth estimation value of the user to be located according to the first matrix and the first steering vector.

[0190] Optionally, the above-mentioned computer program implements the following steps when executed by the processor: determine a first function expression based on the first matrix and the first steering vector; determine the maximum value point of the first function expression within a preset search range to obtain the pitch angle estimation value and the azimuth angle estimation value of the user to be located, wherein the preset search range is determined by a first preset range of azimuth angles and a first preset range of pitch angles.

[0191] Optionally, the above-mentioned computer program implements the following steps when executed by a processor: determining a position list according to initial direction information and a preset distance list; regulating the passive reflection coefficient according to the position list and a preset passive reflection coefficient expression to obtain multiple first passive reflection coefficients.

[0192] Optionally, the above-mentioned computer program implements the following steps when executed by the processor: control the base station to calculate the signal power of multiple received directional focusing signals, and determine the maximum signal power from the multiple signal powers; determine the signal power threshold based on the maximum signal power; determine the target focus point position based on the signal power threshold; determine the second passive reflection coefficient based on the target focus point position.

[0193] Optionally, when the above computer program is executed by a processor, the following steps are implemented: determining a target signal power from multiple signal powers based on a signal power threshold, where the target signal power is the signal power with the smallest difference from the signal power threshold among the multiple signal powers, and the target signal power is greater than the signal power threshold; determining a target focal point position according to the target signal power.

[0194] Optionally, when the above computer program is executed by a processor, the following steps are implemented: controlling a base station to determine a second steering vector expression based on a second passive reflection coefficient; determining an autocorrelation matrix of a target directionally focused signal based on the target directionally focused signal corresponding to a target focal point; performing eigenvalue decomposition on the autocorrelation matrix of the target directionally focused signal to obtain a second matrix corresponding to a noise subspace; generating a second steering vector according to the target focal point position, a polar coordinate space, and the second steering vector expression, where the polar coordinate space is constructed based on a preset distance range, a second preset azimuth range, and a second preset elevation range, and the second preset azimuth range and the second preset elevation range are determined based on initial direction information; determining position information of a user to be located according to the second matrix and the second steering vector.

[0195] Optionally, when the above computer program is executed by a processor, the following steps are implemented: determining a second function expression according to the second matrix and the second steering vector; determining a maximum value point of the second function expression in the polar coordinate space to obtain the position information of the user to be located.

[0196] An embodiment of the present invention further provides a computer-readable storage medium, where the computer-readable storage medium includes a stored executable program, and when the executable program runs, it controls a device where the computer-readable storage medium is located to execute the wireless positioning method described in any one of the above embodiments.

[0197] Optionally, in this embodiment, the above executable program may be set to store an executable program for executing the following steps:

[0198] Step S101, obtaining a received signal received by an active receiving unit of a hybrid intelligent reflecting surface.

[0199] Step S102, processing the received signal by using a preset algorithm to obtain initial direction information of a user to be located.

[0200] Step S103, based on the initial direction information, adjusting a passive reflection coefficient of a passive reflection unit of the hybrid intelligent reflecting surface to obtain a plurality of first passive reflection coefficients, where the plurality of first passive reflection coefficients are used to make a reflected signal directionally focused at different positions in the initial direction to obtain a plurality of directionally focused signals, and the reflected signal is the received signal reflected by the passive reflection unit.

[0201] Step S104: According to multiple directional focusing signals, control the base station to determine the target focusing point position and the corresponding second passive reflection coefficient of the target focusing point position.

[0202] Step S105: Based on the initial direction information, the target focusing point position, and the second passive reflection coefficient, control the base station to determine the position information of the user to be located.

[0203] Optionally, the initial direction information of the user to be located includes the estimated pitch angle and the estimated azimuth angle of the user to be located.

[0204] Optionally, the active receiving units of the hybrid intelligent reflecting surface form an L-shaped array.

[0205] Optionally, the above executable program can be set to store an executable program for performing the following steps: Based on the received signal, determine the autocorrelation matrix of the received signal; perform eigenvalue decomposition on the autocorrelation matrix to obtain the first matrix corresponding to the noise subspace; generate the first steering vector according to the first preset range of azimuth angle and the first preset range of pitch angle; according to the first matrix and the first steering vector, determine the estimated pitch angle and the estimated azimuth angle of the user to be located.

[0206] Optionally, the above executable program can be set to store an executable program for performing the following steps: According to the first matrix and the first steering vector, determine the first function expression; determine the maximum point of the first function expression within the preset search range to obtain the estimated pitch angle and the estimated azimuth angle of the user to be located, where the preset search range is determined by the first preset range of azimuth angle and the first preset range of pitch angle.

[0207] Optionally, the above executable program can be set to store an executable program for performing the following steps: According to the initial direction information and the preset distance list, determine the position list; according to the position list and the preset passive reflection coefficient expression, regulate the passive reflection coefficient to obtain multiple first passive reflection coefficients.

[0208] Optionally, the above executable program can be set to store an executable program for performing the following steps: Control the base station to calculate the signal power of the received multiple directional focusing signals, and determine the maximum signal power from the multiple signal powers; according to the maximum signal power, determine the signal power threshold; based on the signal power threshold, determine the target focusing point position; according to the target focusing point position, determine the second passive reflection coefficient.

[0209] Optionally, the above executable program can be set to store an executable program for performing the following steps: determining a target signal power from multiple signal powers based on a signal power threshold, where the target signal power is the signal power with the smallest difference from the signal power threshold among the multiple signal powers, and the target signal power is greater than the signal power threshold; determining the position of the target focus point according to the target signal power.

[0210] Optionally, the above executable program can be set to store an executable program for performing the following steps: controlling the base station to determine an expression of a second steering vector based on a second passive reflection coefficient; determining an autocorrelation matrix of the target directionally focused signal based on the target directionally focused signal corresponding to the target focus point; performing eigenvalue decomposition on the autocorrelation matrix of the target directionally focused signal to obtain a second matrix corresponding to the noise subspace; generating a second steering vector according to the position of the target focus point, the polar coordinate space, and the expression of the second steering vector, where the polar coordinate space is constructed based on a preset distance range, a second preset azimuth range, and a second preset elevation range, and the second preset azimuth range and the second preset elevation range are determined based on initial direction information; determining the position information of the user to be located according to the second matrix and the second steering vector.

[0211] Optionally, the above executable program can be set to store an executable program for performing the following steps: determining a second function expression according to the second matrix and the second steering vector; determining the maximum point of the second function expression in the polar coordinate space to obtain the position information of the user to be located.

[0212] Optionally, the specific examples in this embodiment may refer to the examples described in the above embodiments and optional implementation manners, and will not be elaborated herein.

[0213] In the above embodiments of the present invention, the descriptions of the respective embodiments have their own emphases. For parts not detailed in a certain embodiment, reference may be made to the relevant descriptions of other embodiments.

[0214] In some embodiments provided by the present application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the system embodiments described above are only illustrative. For example, the division of units can be a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection between each other can be through some interfaces. The indirect coupling or communication connection of units or modules can be in an electrical or other form.

[0215] The unit described as a separation component may or may not be physically separated, and the component displayed as a unit may or may not be a physical unit, that is, it may be located in one place or may be distributed to multiple units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0216] In addition, each functional unit in various embodiments of the present invention can be integrated in a processing unit, can also be physically present separately for each unit, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of a software functional unit.

[0217] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: USB flash drives, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), mobile hard disks, magnetic disks, or optical discs and other various media that can store program codes.

[0218] The above description is only a preferred embodiment of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of the present invention.

Claims

1. A wireless positioning method, characterized in that: include: Acquire a reception signal received by an active receiving unit of the hybrid intelligent reflective surface; Using a preset algorithm, the received signal is processed to obtain initial direction information of the user to be located; Based on the initial direction information, regulating the passive reflection coefficient of the passive reflection unit of the hybrid intelligent reflection surface to obtain a plurality of first passive reflection coefficients, wherein the plurality of first passive reflection coefficients are used to directionally focus the reflection signal at different positions in the initial direction to obtain a plurality of directionally focused signals, wherein the reflection signal is the reception signal reflected by the passive reflection unit; Controlling the base station to determine a target focus point position and a second passive reflection coefficient corresponding to the target focus point position according to the multiple directional focusing signals; Based on the initial direction information, the target focus point position and the second passive reflection coefficient, the base station is controlled to determine the position information of the user to be located.

2. The wireless positioning method according to claim 1, characterized in that: The initial direction information of the user to be located includes an estimated value of the pitch angle and an estimated value of the azimuth angle of the user to be located.

3. The wireless positioning method according to claim 1, characterized in that: The active receiving units of the hybrid intelligent reflective surface form an L-shaped array.

4. The wireless positioning method according to claim 2, characterized in that: The using of a preset algorithm to process the received signal to obtain initial direction information of the user to be located includes: Based on the received signal, determining an autocorrelation matrix of the received signal; Performing eigenvalue decomposition on the autocorrelation matrix to obtain a first matrix corresponding to the noise subspace; Generate a first steering vector according to a first preset range of azimuth angles and a first preset range of elevation angles; An estimated value of a pitch angle and an estimated value of an azimuth angle of the user to be located are determined according to the first matrix and the first steering vector.

5. The wireless positioning method according to claim 4, characterized in that: The step of determining the pitch angle estimation value and the azimuth estimation value of the user to be located according to the first matrix and the first steering vector includes: Determine a first function expression according to the first matrix and the first steering vector; The maximum value point of the first function expression is determined within a preset search range to obtain an estimated value of the pitch angle and an estimated value of the azimuth angle of the user to be located, wherein the preset search range is determined by the first preset range of the azimuth angle and the first preset range of the pitch angle.

6. The wireless positioning method according to claim 1, characterized in that: The step of adjusting the passive reflection coefficient of the passive reflection unit of the hybrid intelligent reflection surface based on the initial direction information to obtain a plurality of first passive reflection coefficients includes: Determining a location list according to the initial direction information and the preset distance list; According to the position list and the preset passive reflection coefficient expression, the passive reflection coefficient is adjusted to obtain the multiple first passive reflection coefficients.

7. The wireless positioning method according to claim 1, characterized in that: The controlling the base station to determine the target focus point position and the second passive reflection coefficient corresponding to the target focus point position according to the multiple directional focus signals comprises: Controlling the base station to calculate the signal powers of the plurality of received directional focusing signals, and determining a maximum signal power from the plurality of signal powers; Determining a signal power threshold according to the maximum signal power; Based on the signal power threshold, determining the target focus point position; The second passive reflection coefficient is determined according to the target focus point position.

8. The wireless positioning method according to claim 7, characterized in that: The step of determining the target focus point position based on the signal power threshold comprises: Based on the signal power threshold, determining a target signal power from the multiple signal powers, wherein the target signal power is a signal power having a minimum difference with the signal power threshold among the multiple signal powers, and the target signal power is greater than the signal power threshold; The target focus point position is determined according to the target signal power.

9. The wireless positioning method according to claim 1, characterized in that: The controlling the base station to determine the position information of the user to be located based on the initial direction information, the target focus point position and the second passive reflection coefficient comprises: Controlling the base station to determine a second steering vector expression based on the second passive reflection coefficient; Determining an autocorrelation matrix of the target directional focusing signal based on the target directional focusing signal corresponding to the target focusing point; Performing eigenvalue decomposition on the autocorrelation matrix of the target directional focusing signal to obtain a second matrix corresponding to the noise subspace; Generate a second steering vector according to the target focus point position, the polar coordinate space and the second steering vector expression, wherein the polar coordinate space is constructed based on a preset distance range, a second preset azimuth range and a second preset elevation range, and the second preset azimuth range and the second preset elevation range are determined based on the initial direction information; The location information of the user to be located is determined according to the second matrix and the second steering vector.

10. The wireless positioning method according to claim 9, characterized in that: The step of determining the location information of the user to be located according to the second matrix and the second steering vector includes: Determine a second function expression according to the second matrix and the second steering vector; The maximum point of the second function expression is determined in the polar coordinate space to obtain the position information of the user to be located.

11. An electronic device, characterized in that: include: A memory storing an executable program; A processor, configured to run the executable program, wherein the executable program executes the method according to any one of claims 1 to 10 when running.

12. A computer program product, characterized in that It comprises a computer program which, when executed by a processor, implements the method according to any one of claims 1 to 10.

13. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored executable program, wherein when the executable program is executed, the device where the computer-readable storage medium is located is controlled to execute the method according to any one of claims 1 to 10.

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