Antenna array optimization method, device, terminal and storage medium

Abstract

The present invention discloses an antenna array optimization method, device, terminal and storage medium. The method obtains an antenna array to be optimized, wherein the antenna array to be optimized is a uniform planar array; according to the antenna array to be optimized, a plurality of target antennas are determined, wherein the plurality of target antennas are all located in a target logarithmic spiral band; according to the plurality of target antennas, a target antenna array corresponding to the antenna array to be optimized is determined. The present invention deploys target antennas on a logarithmic spiral band in a nonlinear manner to obtain a target antenna array. Compared with a uniform planar array, the target antenna array uses fewer antennas, thereby solving the problem of high cost of large uniform planar antenna arrays with high resolution in the prior art.

Description

Technical Field

[0001] The present invention relates to the field of antenna array design, and in particular to an antenna array optimization method, device, terminal and storage medium. Background Art

[0002] In the field of positioning systems, AoA tracking systems are gaining more and more attention, mainly because AoA tracking systems can be used to determine the angle of arrival (AoA) of the signal, which reflects the propagation direction of the RF signal. AoA tracking systems facilitate a wide range of wireless positioning, sensing and communication applications, such as indoor positioning, passive tracking, security control, Wi-Fi imaging and activity recognition, etc. However, current AoA tracking systems require large uniform linear antenna arrays or planar antenna arrays, each of which is connected to an independent signal processing channel (with an ADC added to the front end) to achieve the effect of receiving and processing multiple copies of the RF signal in parallel. However, for the consumer-oriented market, the cost of large uniform planar antenna arrays with high resolution is too expensive.

[0003] Therefore, the existing technology still needs to be improved and developed. Summary of the invention

[0004] The technical problem to be solved by the present invention is to provide an antenna array optimization method in view of the above-mentioned defects of the prior art, aiming to solve the problem of high cost of high-resolution large-scale uniform planar antenna arrays in the prior art.

[0005] The technical solution adopted by the present invention to solve the problem is as follows:

[0006] In a first aspect, an embodiment of the present invention provides an antenna array optimization method, wherein the method includes:

[0007] Acquire an antenna array to be optimized, wherein the antenna array to be optimized is a uniform planar array;

[0008] Determining a plurality of target antennas according to the antenna array to be optimized, wherein the plurality of target antennas are all located in a target logarithmic spiral band;

[0009] According to the plurality of target antennas, a target antenna array corresponding to the antenna array to be optimized is determined.

[0010] In one embodiment, the target logarithmic spiral band includes two Fibonacci spiral lines, wherein the two Fibonacci spiral lines are symmetrical about the center of a target point, and the target point is the center point of an array area corresponding to the antenna array to be optimized.

[0011] In one implementation, determining a plurality of target antennas according to the antenna array to be optimized includes:

[0012] Dividing the array area corresponding to the antenna array to be optimized into a plurality of grids, wherein each of the grids is a square with a side length of a preset half wavelength;

[0013] A plurality of target antennas are determined according to the plurality of grids and the two Fibonacci spirals, wherein each of the target antennas is located at an intersection of an end point of the grid and the target logarithmic spiral band.

[0014] In one embodiment, the target resolution interval corresponding to the target antenna array is the same as the original resolution interval corresponding to the antenna array to be optimized, wherein the target resolution interval is determined based on the resolution degrees corresponding to a number of antenna pairs, a number of antenna pairs are determined based on a number of target antennas in pairs, and the original resolution interval is determined based on the array size corresponding to the antenna array to be optimized.

[0015] In one embodiment, the resolution degree corresponding to each antenna pair includes a first resolution degree and a second resolution degree, wherein the first resolution degree is determined based on the difference between the horizontal coordinates corresponding to the two target antennas in the antenna pair, and the second resolution degree is determined based on the difference between the vertical coordinates corresponding to the two target antennas in the antenna pair.

[0016] In one implementation, the resolutions respectively corresponding to the plurality of antenna pairs cover the target resolution range, and the overlap rate of the resolutions respectively corresponding to the antenna pairs is the lowest.

[0017] In one embodiment, the method further comprises:

[0018] Acquire, through the target antenna array, first spatial spectra corresponding to a plurality of reference electronic tags and second spatial spectra corresponding to a target electronic tag, wherein position data corresponding to the plurality of reference electronic tags are known, and the target electronic tag is located on the target to be located;

[0019] Comparing each of the first spatial spectrums with the second spatial spectrum, obtaining similarities corresponding to each of the first spatial spectrums;

[0020] determining a plurality of target reference electronic tags according to the similarities respectively corresponding to the first spatial spectrums;

[0021] The target position data corresponding to the target to be located is determined according to the position data respectively corresponding to the plurality of target reference electronic tags.

[0022] In a second aspect, an embodiment of the present invention further provides an antenna array optimization device, wherein the device includes:

[0023] An array acquisition module, used to acquire an antenna array to be optimized, wherein the antenna array to be optimized is a uniform planar array;

[0024] A spiral band determination module, used to determine a plurality of target antennas according to the antenna array to be optimized, wherein the plurality of target antennas are all located in a target logarithmic spiral band;

[0025] The array element optimization module is used to determine the target antenna array corresponding to the antenna array to be optimized according to the plurality of target antennas.

[0026] In a third aspect, an embodiment of the present invention further provides a terminal, wherein the terminal includes a memory and one or more processors; the memory stores one or more programs; the program includes instructions for executing any of the antenna array optimization methods described above; and the processor is used to execute the program.

[0027] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium on which a plurality of instructions are stored, wherein the instructions are suitable for being loaded and executed by a processor to implement the steps of any of the above-mentioned antenna array optimization methods.

[0028] Beneficial effects of the present invention: The embodiment of the present invention obtains an antenna array to be optimized, wherein the antenna array to be optimized is a uniform planar array; according to the antenna array to be optimized, a plurality of target antennas are determined, wherein the plurality of target antennas are all located in a target logarithmic spiral band; according to the plurality of target antennas, a target antenna array corresponding to the antenna array to be optimized is determined. The present invention deploys target antennas on a logarithmic spiral band in a nonlinear manner to obtain a target antenna array. Compared with a uniform planar array, the target antenna array uses fewer antennas, thereby solving the problem of high cost of large uniform planar antenna arrays with high resolution in the prior art. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0030] Figure 1 It is a flowchart of the antenna array optimization method provided in an embodiment of the present invention.

[0031] Figure 2 It is a schematic diagram of the principle of determining various resolution degrees corresponding to the target antenna array provided by an embodiment of the present invention.

[0032] Figure 3 It is a schematic diagram of a process of locating an electronic tag according to a target antenna array provided in an embodiment of the present invention.

[0033] Figure 4 It is a schematic diagram of various resolution degrees corresponding to the original antenna array provided in an embodiment of the present invention.

[0034] Figure 5 It is a schematic diagram of various resolution degrees corresponding to after redundant antennas in the original antenna array are deleted, provided by an embodiment of the present invention.

[0035] Figure 6 It is a spatial spectrum generated based on the original antenna array provided by an embodiment of the present invention.

[0036] Figure 7 This is a spatial spectrum generated based on a sparse antenna array provided by an embodiment of the present invention.

[0037] Figure 8 It is a module schematic diagram of the antenna array optimization device provided in an embodiment of the present invention.

[0038] Fig. 9 It is a principle block diagram of a terminal provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0039] The present invention discloses an antenna array optimization method, device, terminal and storage medium. In order to make the purpose, technical solution and effect of the present invention clearer and more specific, the present invention is further described in detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0040] It will be understood by those skilled in the art that, unless expressly stated, the singular forms "one", "said", and "the" used herein may also include plural forms. It should be further understood that the term "comprising" used in the specification of the present invention refers to the presence of the features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or groups thereof. It should be understood that when we refer to an element as being "connected" or "coupled" to another element, it may be directly connected or coupled to the other element, or there may be intermediate elements. In addition, the "connection" or "coupling" used herein may include wireless connection or wireless coupling. The term "and / or" used herein includes all or any unit and all combinations of one or more associated listed items.

[0041] It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as generally understood by those skilled in the art in the art to which the present invention belongs. It should also be understood that terms such as those defined in general dictionaries should be understood to have meanings consistent with the meanings in the context of the prior art, and will not be interpreted with idealized or overly formal meanings unless specifically defined as herein.

[0042] In view of the above-mentioned defects of the prior art, the present invention provides an antenna array optimization method, the method obtaining an antenna array to be optimized, wherein the antenna array to be optimized is a uniform planar array; according to the antenna array to be optimized, determining a plurality of target antennas, wherein the plurality of target antennas are all located in a target logarithmic spiral band; according to the plurality of target antennas, determining a target antenna array corresponding to the antenna array to be optimized. The present invention deploys target antennas on a logarithmic spiral band in a nonlinear manner to obtain a target antenna array. Compared with a uniform planar array, the target antenna array uses fewer antennas, thereby solving the problem of high cost of large uniform planar antenna arrays with high resolution in the prior art.

[0043] like Figure 1 As shown, the method comprises the following steps:

[0044] Step S100: obtaining an antenna array to be optimized, wherein the antenna array to be optimized is a uniform planar array.

[0045] Specifically, the antenna array to be optimized in this embodiment can be any large uniform planar array, that is, an array with a number of array elements greater than a preset value. For a conventional large uniform planar array, by checking the relevant protocols, it can be found that there are many redundant antennas, so these redundant antennas can be eliminated to achieve the purpose of reducing the antenna array cost.

[0046] For example, Figure 4 As shown, assume that the original antenna array is A0, A1, A2, A3. Based on the original antenna array, we can get multiple antenna pairs (A1, A0), (A2, A0), (A3, A0), (A2, A1), (A3, A1) and (A3, A2), as well as the resolutions (1, 2, 3, 1, 2, 1) corresponding to each antenna pair. Obviously, the first and second resolutions are repeated. Delete A2 from the antenna array, as shown in Figure 5As shown in the figure, the remaining sparse antenna array composed of A0, A1, A2, and A3 can be used to obtain multiple antenna pairs (A1, A0), (A3, A0), (A3, A1), and the resolutions (1, 2, 3) corresponding to each antenna pair. From the perspective of resolution, the resolution of the sparse antenna array is not repeated and is the same as the resolution covered by the original antenna array. From the perspective of spatial spectrum, Figure 6 , 7 As shown in Figure 1, no significant difference is observed in the width of the two main beams in the spatial spectra corresponding to the original antenna array and the sparse antenna array. Therefore, A2 is a redundant antenna. After removing the redundant antenna, the sparse antenna array has the same resolution as the original antenna array, but uses fewer antennas.

[0047] like Figure 1 As shown, the method further comprises the following steps:

[0048] Step S200: determining a plurality of target antennas according to the antenna array to be optimized, wherein the plurality of target antennas are all located in a target logarithmic spiral band.

[0049] In summary, this embodiment adopts a method of deploying antennas on a nonlinear logarithmic spiral band to eliminate redundant antennas in a uniform planar antenna array and maintain the resolution and accuracy of the antenna array. Specifically, for the antenna array to be optimized, a plurality of target antennas located on the target logarithmic spiral band are selected, and the original antenna array to be optimized is replaced by these target antennas to achieve the purpose of reducing the number of antennas.

[0050] In one implementation, the target logarithmic spiral band includes two Fibonacci spiral lines, wherein the two Fibonacci spiral lines are symmetrical about the center of a target point, and the target point is the center point of an array area corresponding to the antenna array to be optimized.

[0051] Specifically, the logarithmic spiral in polar coordinate form is usually given by r = ae bρ Given, where r is the distance from the origin, ρ is the angle with the x-axis, and a and b are constants, a large number of logarithmic spirals can be constructed. As for the type of logarithmic spiral, this embodiment adopts the Fibonacci spiral, which is similar to the golden spiral. In order to ensure that the accuracy and resolution of the target antenna array finally generated are consistent with the antenna array to be optimized, as Figure 2 As shown, this embodiment uses two Fibonacci spirals to deploy antennas. The polar coordinates and formulas of the two Fibonacci spirals are symmetrical with the center point / origin of the array area. Compared with using one Fibonacci spiral to deploy antennas, the two Fibonacci spirals can ensure better coverage.

[0052] In one implementation, the Fibonacci spiral can be derived from a particular sequence in which the next number is the sum of the two numbers before it. In another implementation, a Fibonacci spiral can be constructed by using a square whose side lengths represent the Fibonacci numbers and drawing quarter-circle arcs to connect the opposite corners of the square. Specifically, each time p sweeps π / 2, the distance r increases discretely by following the Fibonacci sequence. That is, and In contrast, the polar coordinates and formula of the symmetric Fibonacci sequence are symmetric about the origin.

[0053] In one implementation, step S200 specifically includes the following steps:

[0054] Step S201, dividing the array area corresponding to the antenna array to be optimized into a plurality of grids, wherein each of the grids is a square with a side length of a preset half wavelength;

[0055] Step S202: Determine a plurality of target antennas according to the plurality of grids and the two Fibonacci spirals, wherein each of the target antennas is located at an intersection of an endpoint of the grid and the target logarithmic spiral band.

[0056] Specifically, the size of a small unit in the grid is λ / 2×λ / 2, each Fibonacci spiral contains six segments (the arc between adjacent nodes is one segment), and each segment is a quarter-circle arc contained in a large unit cell. In this embodiment, the target antenna is deployed at the intersection of the spiral and the unit angle to ensure that the horizontal and / or vertical distance between any two target antennas is an integer multiple of λ / 2.

[0057] For example, Figure 2 As shown, two Fibonacci spirals are shown, and the deployment of multiple antennas A0 to A11 is illustrated. Since the AOA arrival angle is a 3D angle, the antennas are deployed in a grid or a circle in this embodiment to decompose the direction into two orthogonal angles, namely the yaw angle and the elevation angle.

[0058] In one implementation, the target resolution interval corresponding to the target antenna array is the same as the original resolution interval corresponding to the antenna array to be optimized, wherein the target resolution interval is determined based on the resolution degrees corresponding to a number of antenna pairs, a number of antenna pairs are determined based on a number of target antennas in pairs, and the original resolution interval is determined based on the array size corresponding to the antenna array to be optimized.

[0059] In order to ensure that the accuracy of the target antenna array is consistent with the antenna array to be optimized, this embodiment needs to ensure that the target resolution interval corresponding to the target antenna array can cover the original resolution interval corresponding to the antenna array to be optimized. Specifically, by pairing each target antenna in pairs, the antenna pairs corresponding to the target antenna array are determined. Then, the resolution degrees corresponding to each antenna pair are determined one by one, and the target resolution interval corresponding to the target antenna array can be determined. Since the antenna array to be optimized is a uniform planar array, its corresponding original resolution interval can be directly obtained from its array size / specification.

[0060] In one implementation, the resolution degree corresponding to each antenna pair includes a first resolution degree and a second resolution degree, wherein the first resolution degree is determined based on the difference between the horizontal coordinates corresponding to the two target antennas in the antenna pair, and the second resolution degree is determined based on the difference between the vertical coordinates corresponding to the two target antennas in the antenna pair.

[0061] Specifically, in order to obtain the resolution degree of each antenna pair, for each antenna pair, this embodiment will project its corresponding two antennas onto the X-axis and the Y-axis to achieve the study of the resolution degree of the antenna pair from a two-dimensional level. The first resolution degree corresponding to the antenna pair can be determined by the difference in the horizontal coordinates of the two antennas obtained after projection; the second resolution degree corresponding to the antenna pair can be determined by the difference in the vertical coordinates of the two antennas obtained after projection. It can be understood that, accordingly, the target resolution interval corresponding to the target antenna array and the original resolution interval corresponding to the antenna array to be optimized also have two intervals respectively, one for reflecting the resolution interval corresponding to the horizontal coordinate on the two-dimensional level, and the other for reflecting the resolution interval corresponding to the vertical coordinate on the two-dimensional level. The resolution interval on the horizontal coordinate corresponding to the target antenna array needs to be the same as the resolution interval on the horizontal coordinate corresponding to the antenna array to be optimized, and the resolution interval on the vertical coordinate corresponding to the target antenna array also needs to be the same as the resolution interval on the vertical coordinate corresponding to the antenna array to be optimized.

[0062] In one implementation, the resolutions corresponding to the plurality of antenna pairs cover a target resolution range, and the overlap rate of the resolutions corresponding to the antenna pairs is the lowest.

[0063] In simple terms, by deleting redundant antennas, a sparse array can be obtained from a uniform array of the same size. However, in order to further reduce the cost of the antenna array, the target antenna array in this embodiment is not only a sparse array, but also needs to be a sparse array with minimum resolution redundancy. Specifically, the target antenna array in this embodiment needs to meet the requirements of covering the complete original resolution range of the antenna array to be optimized, and it is also necessary to reduce the overlap rate of the resolutions corresponding to each antenna pair, so that the target antenna array no longer has redundant antennas.

[0064] For example, assume that the antenna array to be optimized is equipped with N antennas (denoted as A0, A1, ..., A N-1 ), and determine the corresponding sparse antenna array based on the equidistant antenna array. Represents the remaining antenna groups in the sparse antenna array. Contains A0,A N-1 , to provide the maximum resolution (i.e. N degrees). When the sparse antenna array meets the following conditions, the sparse antenna array is the target antenna array corresponding to the antenna array to be optimized:

[0065] 1. The resolutions of the antenna pairs corresponding to the sparse array do not overlap. That is, Where i, j, k, l = 0, 1, ..., N-1, and i> j, k> l. However, when M ≥ 4, this condition is no longer satisfied. When M = 4, the antennas A0, A1, A3 and A4 are retained in the sparse array, and their paired combinations provide (1, 3, 4, 2, 3, 1) resolutions, where 1 and 3 are repeated. Therefore, in this embodiment, while satisfying the coverage of the original resolution interval, the overlap rate of the resolutions corresponding to each antenna pair is minimized.

[0066] 2. Sparse arrays can cover the entire resolution range from 1 to N-1 degrees.

[0067] In one implementation, several target antennas are first deployed at each corner of the target area to obtain more resolution degrees. After each corner is deployed, the resolution level currently lacking in the entire resolution level from 1 to N-1 degrees is determined, and target antennas are added again according to the lacking resolution level until the entire resolution level from 1 to N-1 degrees is covered.

[0068] For example, Figure 2As shown, the figure shows the deployment of nine antennas A0 to A11. This embodiment projects the antennas onto the X-axis and Y-axis to study their resolution in two dimensions. In general, the deployment provides (1, 2, ···, 17) resolution and (1, 2, ····, 12) resolution in two dimensions, respectively. Specifically, antennas A0 to A8 are first deployed at the corners of the cell starting or ending at each corner. Deploying antennas in corners can obtain (1, 2, 3, 4, 5, 6, 7, 8, 12) and (1, 2, 3, 4, 5, 6, 7, 8, 9, 12, 16) resolutions, almost completely covering the entire resolution range. These antennas are represented by black solid hollow circles in the figure, and the projections are represented by gray dotted hollow circles. The current deployment is an approximate minimum redundant array that can provide 75% and 68% resolution. However, (11, 12) and (4, 7) resolutions are missing. These levels can therefore be compensated by adding A9, A10 and A11 to achieve full coverage. The added antennas and their projections are shown in the figure as grey filled circles.

[0069] In one implementation, to avoid duplication of array elements, the array elements on the spiral line with an inner radius of 1 only retain one antenna pair, and the resolution corresponding to the antenna pair does not overlap with the resolutions of other antenna pairs.

[0070] For example, Figure 2 As shown, to avoid duplication of array elements, the array elements on the spiral line with an inner radius of 1 only retain A0 and A1 instead of the focus of the entire spiral and unit angle (other array element combinations overlap with A2 and A3).

[0071] like Figure 1 As shown, the method further comprises the following steps:

[0072] Step S300: Determine a target antenna array corresponding to the antenna array to be optimized according to the plurality of target antennas.

[0073] Specifically, since each target antenna is an antenna deployed based on a target logarithmic spiral band with reference to the resolution range of the antenna array to be optimized, the target antenna array determined according to each target antenna can achieve the accuracy of the antenna array to be optimized and has fewer antennas than the antenna array to be optimized. Using the target antenna array instead of the antenna array to be optimized can effectively reduce the cost of the antenna array.

[0074] In one implementation, the method further includes the following steps:

[0075] Step S400: acquiring, through the target antenna array, first spatial spectra corresponding to a plurality of reference electronic tags and second spatial spectra corresponding to a target electronic tag, wherein position data corresponding to the plurality of reference electronic tags are known, and the target electronic tag is located on the target to be located;

[0076] Step S401: Compare the first spatial spectrum with the second spatial spectrum to obtain the similarity corresponding to each of the first spatial spectrums;

[0077] Step S402: determining a number of target reference electronic tags according to the similarities respectively corresponding to the first spatial spectra;

[0078] Step S403: Determine the target location data corresponding to the target to be located according to the location data respectively corresponding to the target reference electronic tags.

[0079] In short, this embodiment can realize electronic tag positioning according to the optimized target antenna array. Specifically, each reference electronic tag is arranged in the space where the target to be located is located, and the target electronic tag is arranged on the target to be located. Then, the first spatial spectrum corresponding to each reference electronic tag and the second spatial spectrum corresponding to the target electronic tag are obtained through the target antenna array. Then, by comparing the similarity of each first spatial spectrum with the second spatial spectrum, several target reference electronic tags that are close to the target to be located are determined, and the target position data corresponding to the target to be located is determined through the position data corresponding to these target reference electronic tags.

[0080] In one implementation, the comparing the first spatial spectrum with the second spatial spectrum to obtain the similarities corresponding to the first spatial spectrums specifically includes the following steps:

[0081] For each of the first spatial spectrums, the similarity between the first spatial spectrum and the second spatial spectrum is measured by using log spectral distance (LSD).

[0082] Specifically, LSD is widely used in speech coding, so this embodiment extends LSD to 2D spectrum, and the calculation formula of the similarity between two spatial spectrums is as follows:

[0083]

[0084] The similarity is expressed in dB. The smaller the LSD of two spectra, the higher the similarity of the two spectra.

[0085] In one implementation, determining a plurality of target reference electronic tags according to the similarities respectively corresponding to the first spatial spectrums specifically includes the following steps:

[0086] The similarities corresponding to the first spatial spectrums are sorted in ascending order according to the values, and a number of the target reference electronic tags are determined according to the similarities before the preset order.

[0087] For example, the LSD between each first spatial spectrum and the second spatial spectrum is calculated, and then the first four with the smallest LSD are selected as target reference electronic tags.

[0088] In one implementation, the plurality of reference electronic tags are evenly arranged at equal distances, and the determining of the target location data corresponding to the target to be located according to the location data respectively corresponding to the plurality of target reference electronic tags specifically includes the following steps:

[0089] The target location data corresponding to the target to be located is determined based on the weighted average of the location data corresponding to each target reference electronic tag. In one implementation, the weight corresponding to each target reference electronic tag is determined based on the inverse of the similarity corresponding to the target reference electronic tag.

[0090] For ease of explanation, Figure 3 As shown, this embodiment illustrates a practical application process of locating an electronic tag through a target antenna array:

[0091] Step S1, attaching a reference electronic tag to a designated location.

[0092] Step S2: according to certain rules, the reference electronic tags are evenly arranged in space at equal distances, and a coordinate system is established to record the positions of the reference electronic tags.

[0093] Step S3: attach the target electronic tag to the target to be located.

[0094] Step S4: The target electronic tag is placed at the center of the target to be located.

[0095] Step S5: collecting phase through the antenna array.

[0096] Step S6: Use the reader to schedule the antenna according to a certain rule to collect the phase value of the tag. Assume that there are K antennas represented by A = {A0, A2, ..., A K-1}. The location of each antenna is known and connected to the same reader, and they are scheduled to read data in turn. is the measured antenna phase difference (A k ,A0).

[0097] Step S7: Calculate the spatial spectrum.

[0098] Among them, the spatial spectrum is expressed as:

[0099]

[0100] Among them, α and β are the azimuth and elevation angles used to calculate the phase difference, respectively, and F(x; μ, σ) is a Gaussian distribution The cumulative probability function of . Due to thermal noise, the measured phase values ​​are treated as random variables according to a Gaussian distribution. Then, the difference between two phase values ​​follows σ = 0.1. F(x; μ, σ) represents the probability that the guessed angle is close to the true angle.

[0101] Step S8: Compare spatial spectrum distances.

[0102] The spatial spectrum of the target electronic tag is compared with the reference electronic tag in turn, and the logarithmic spectral distance (LSD) is used to measure the similarity of the two spectra. In this embodiment, LSD is extended to the 2D spectrum as shown below:

[0103]

[0104] Among them, dB represents the similarity, and the smaller the LSD of two spectra, the higher the similarity.

[0105] Step S9: determine the target position.

[0106] First, the LSD between the target electronic tag and all reference electronic tags is calculated. Then, the first four reference electronic tags with the smallest LSD are selected. The position of the target electronic tag is calculated as the weighted average of the four reference electronic tags, and the weight is the inverse of the corresponding normalized LSD.

[0107] In one implementation, the method further includes the following steps:

[0108] Step S500: performing angle of arrival detection (ie, AOA detection) of a signal according to the target antenna array.

[0109] In short, this embodiment can use the target antenna array connected to the time-division shared channel to estimate the angle of arrival (AoA) of the IoT device in 3D space. Specifically, the spatial spectrum corresponding to the target antenna array is obtained, and the spatial spectrum from (A N-1 The AOA detection result is obtained by calculating the focus angle between the narrowest beam from (A0, A1) and the widest beam from (A1, A0). Among them, A0 is the first target antenna of the target antenna array, A N is the last target antenna of the target antenna array.

[0110] In one implementation, the target antenna array can be scaled down or enlarged based on the size of the detection area to be equipped with any number of antennas, thereby meeting the requirements of different detection areas.

[0111] To demonstrate the technical effects of the present invention, the present invention prototyped a physical 12×18 uniform planar array (UPA) and four logical sparse arrays (including LSAB) to verify the technical effects of the present invention and evaluate the performance of the sparse arrays. Extensive benchmark tests show that the performance of LSAB is comparable to that of UPA and has similar resolution. Compared with existing sparse arrays, the performance of LSAB can be improved by more than 40%.

[0112] Based on the above embodiments, the present invention also provides an antenna array optimization device, such as Figure 8 As shown, the device comprises:

[0113] An array acquisition module 01 is used to acquire an antenna array to be optimized, wherein the antenna array to be optimized is a uniform planar array;

[0114] The spiral band determination module 02 is used to determine a plurality of target antennas according to the antenna array to be optimized, wherein the plurality of target antennas are all located in a target logarithmic spiral band;

[0115] The array element optimization module 03 is used to determine the target antenna array corresponding to the antenna array to be optimized according to the plurality of target antennas.

[0116] Based on the above embodiment, the present invention further provides a terminal, whose principle block diagram can be shown as follows: Fig. 9 As shown. The terminal includes a processor, a memory, a network interface, and a display screen connected through a system bus. Among them, the processor of the terminal is used to provide computing and control capabilities. The memory of the terminal includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the terminal is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, the antenna array optimization method is implemented. The display screen of the terminal can be a liquid crystal display screen or an electronic ink display screen.

[0117] Those skilled in the art will understand that Fig. 9 The principle block diagram shown in the figure is only a block diagram of a partial structure related to the scheme of the present invention, and does not constitute a limitation on the terminal to which the scheme of the present invention is applied. The specific terminal may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0118] In an implementation manner, one or more programs are stored in a memory of the terminal, and the one or more programs are configured to be executed by one or more processors, and the one or more programs include instructions for performing an antenna array optimization method.

[0119] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided by the present invention can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0120] In summary, the present invention discloses an antenna array optimization method, device, terminal and storage medium. The method obtains an antenna array to be optimized, wherein the antenna array to be optimized is a uniform planar array; according to the antenna array to be optimized, a plurality of target antennas are determined, wherein the plurality of target antennas are located in a target logarithmic spiral band; according to the plurality of target antennas, a target antenna array corresponding to the antenna array to be optimized is determined. The present invention deploys target antennas on a logarithmic spiral band in a nonlinear manner to obtain a target antenna array. Compared with a uniform planar array, the target antenna array uses fewer antennas, so the problem of high cost of large uniform planar antenna arrays with high resolution in the prior art can be solved.

[0121] It should be understood that the application of the present invention is not limited to the above examples. For ordinary technicians in this field, improvements or changes can be made based on the above description. All these improvements and changes should fall within the scope of protection of the claims attached to the present invention.

Claims

1. An antenna array optimization method, characterized in that: The method comprises: Acquire an antenna array to be optimized, wherein the antenna array to be optimized is a uniform planar array; Determining a plurality of target antennas according to the antenna array to be optimized, wherein the plurality of target antennas are all located in a target logarithmic spiral band; Determine, according to the plurality of target antennas, a target antenna array corresponding to the antenna array to be optimized; The target logarithmic spiral band includes two Fibonacci spiral lines, wherein the two Fibonacci spiral lines are symmetrical about the center of a target point, and the target point is the center point of an array area corresponding to the antenna array to be optimized; According to the antenna array to be optimized, a plurality of target antennas are determined, including: Dividing the array area corresponding to the antenna array to be optimized into a plurality of grids, wherein each of the grids is a square with a side length of a preset half wavelength; A plurality of target antennas are determined according to the plurality of grids and the two Fibonacci spirals, wherein each of the target antennas is located at an intersection of an end point of the grid and the target logarithmic spiral band.

2. The antenna array optimization method according to claim 1, characterized in that: The target resolution interval corresponding to the target antenna array is the same as the original resolution interval corresponding to the antenna array to be optimized, wherein the target resolution interval is determined based on the resolution degrees corresponding to several antenna pairs respectively, several antenna pairs are determined based on several target antennas in pairs, and the original resolution interval is determined based on the array size corresponding to the antenna array to be optimized.

3. The antenna array optimization method according to claim 2, characterized in that: The resolution degree corresponding to each antenna pair includes a first resolution degree and a second resolution degree, wherein the first resolution degree is determined based on the difference between the horizontal coordinates corresponding to the two target antennas in the antenna pair, and the second resolution degree is determined based on the difference between the vertical coordinates corresponding to the two target antennas in the antenna pair.

4. The antenna array optimization method according to claim 2, characterized in that: The resolutions respectively corresponding to the plurality of antenna pairs cover the target resolution range, and the overlap rate of the resolutions respectively corresponding to the antenna pairs is the lowest.

5. The antenna array optimization method according to claim 1, characterized in that: The method further comprises: Acquire, through the target antenna array, first spatial spectra corresponding to a plurality of reference electronic tags and second spatial spectra corresponding to a target electronic tag, wherein position data corresponding to the plurality of reference electronic tags are known, and the target electronic tag is located on the target to be located; Comparing each of the first spatial spectrums with the second spatial spectrum, obtaining similarities corresponding to each of the first spatial spectrums; determining a plurality of target reference electronic tags according to the similarities respectively corresponding to the first spatial spectrums; The target position data corresponding to the target to be located is determined according to the position data respectively corresponding to the plurality of target reference electronic tags.

6. An antenna array optimization device, characterized in that: The device comprises: An array acquisition module, used to acquire an antenna array to be optimized, wherein the antenna array to be optimized is a uniform planar array; A spiral band determination module, used to determine a plurality of target antennas according to the antenna array to be optimized, wherein the plurality of target antennas are all located in a target logarithmic spiral band; An array element optimization module, used to determine a target antenna array corresponding to the antenna array to be optimized according to the plurality of target antennas; The target logarithmic spiral band includes two Fibonacci spiral lines, wherein the two Fibonacci spiral lines are symmetrical about the center of a target point, and the target point is the center point of an array area corresponding to the antenna array to be optimized; According to the antenna array to be optimized, a plurality of target antennas are determined, including: Dividing the array area corresponding to the antenna array to be optimized into a plurality of grids, wherein each of the grids is a square with a side length of a preset half wavelength; A plurality of target antennas are determined according to the plurality of grids and the two Fibonacci spirals, wherein each of the target antennas is located at an intersection of an end point of the grid and the target logarithmic spiral band.

7. A terminal, characterized in that: The terminal includes a memory and one or more processors; the memory stores one or more programs; the program contains instructions for executing the antenna array optimization method as described in any one of claims 1-5; and the processor is used to execute the program.

8. A computer-readable storage medium having a plurality of instructions stored thereon, characterized in that: The instructions are suitable for being loaded and executed by a processor to implement the steps of the antenna array optimization method described in any one of claims 1-5 above.

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