Intelligent file cabinet file query method based on RFID technology

Abstract

The invention discloses an intelligent file cabinet file query method based on the RFID technology, and relates to the technical field of intelligent file management.The internal space of a file cabinet is divided into small grid units through virtual grid modeling, each grid has a clear number, preliminary positioning of each RFID tag is achieved, and the file query efficiency is improved. According to the method, the file is not limited to an approximate area any more and is accurate to a specific grid, multi-antenna cooperative reading is combined with multiple reading and analysis of signal intensity and phase angles, the positioning accuracy is further improved, errors can be corrected according to signal differences and phase angles through a maximum likelihood estimation model, more accurate file position query is achieved, and the positioning accuracy is improved. According to the technical scheme, labels in a coverage area are read for multiple times in a multi-antenna cooperative reading mode, interference is reduced through signal calibration between the antennas, and errors caused by signal reflection, interference or overlapping are reduced by carrying out weighted average on signal strength and correcting differences between the antennas through a least square method.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent file management, in particular to an intelligent file cabinet file query method based on RFID technology. Background Art

[0002] In the file query of the filing cabinet, RFID radio frequency identification technology can effectively improve the convenience and accuracy of file management. Through contactless identification, the file entry, borrowing and return processes can be automatically managed. At the same time, RFID technology can quickly locate and query designated files, greatly shortening the retrieval time. RFID radio frequency identification technology provides a new digital solution for file management and promotes the intelligence of file management.

[0003] In large-capacity, high-density filing cabinets, although RFID tags can identify whether files exist, it is difficult to determine the specific location of the files in the cabinet. Due to the large number of RFID tags in the filing cabinet, signal interference between tags and reflection of RFID signals by the cabinet, it is difficult for the reader to accurately and quickly capture all tag information.

[0004] In order to improve positioning accuracy, some existing solutions will add RFID antennas or densely arrange tags in the filing cabinet to improve the reading coverage and signal strength. However, too dense tags will cause signal collisions, which will reduce reading efficiency. Some RFID systems use a single antenna to scan successively and read tags in different areas multiple times to find the location of the file. However, the reading range is limited each time, and scanning the entire filing cabinet still takes a lot of time. Therefore, an intelligent filing cabinet file query method based on RFID technology is urgently needed to solve this problem. Summary of the invention

[0005] In view of the above existing problems, the present invention is proposed.

[0006] Therefore, the present invention provides an intelligent filing cabinet file query method based on RFID technology to solve the problems of inaccurate positioning, dense label layout and reflection effect of metal filing cabinets causing serious signal interference, and multiple reading methods requiring a lot of time to scan the entire filing cabinet.

[0007] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0008] The present invention provides an intelligent filing cabinet file query method based on RFID technology, which comprises:

[0009] Step S1: grid modeling and partition layout.

[0010] The interior of the filing cabinet is modeled in a virtual grid, and the cabinet space is divided into multiple small virtual grids, each grid representing an independent storage unit; in step S1, the files corresponding to each RFID tag are divided into virtual grids to establish a preliminary grid storage structure;

[0011] Step S2: multi-antenna collaborative reading.

[0012] Based on the virtual grid division structure of step S1, multiple antennas are arranged, each antenna is responsible for covering multiple grid areas within its effective range, thereby reducing errors caused by signal interference or overlapping areas;

[0013] Step S3, signal strength and phase angle analysis,

[0014] On the basis of step S2, the signal strength and phase angle data of the preliminary reading results collected by each antenna are used to perform multi-antenna phase difference calibration to obtain the specific position of the tag. Based on the cross analysis of signal strength and phase angle, the specific area and relative position of the tag in the grid can be more accurately located;

[0015] Step S4, signal reflection optimization,

[0016] In a high-density metal environment, RFID signals are susceptible to reflection and interference. To address this problem, absorbing materials are arranged in the internal grid area of ​​the filing cabinet to reduce signal reflection and interference, and improve signal quality and reading stability.

[0017] Step S5: position marking and path prompting.

[0018] Based on the specific position of each RFID tag in the grid obtained in step S3, the position is automatically marked on the electronic map of the virtual grid structure, and an electronic distribution map of the files in the filing cabinet is generated. The electronic map shows the exact location of each file and provides a quick path prompt. Combined with the data update of the signal reading, it dynamically reflects the real-time distribution of the files in the filing cabinet.

[0019] Furthermore, in step S1, the virtual gridding modeling method is:

[0020] Assume that the length, width and height of the three-dimensional space inside the filing cabinet are L, W and H respectively, and divide the entire cabinet space into N x 、N y and N z grid cells, partitioned in the x-axis, y-axis, and z-axis directions:

[0021] Where L is the length of the filing cabinet along the x-axis, W is the width of the filing cabinet along the y-axis, H is the height of the filing cabinet along the z-axis, and N is x Indicates the number of grids along the x-axis, Ny Indicates the number of grids along the y-axis, N z represents the number of grids along the z-axis, Δx, Δy, Δz represent the lengths in the x, y, z directions;

[0022] Each grid unit is represented by a three-dimensional coordinate (i, j, k), where i, j, and k represent the position number of the grid in the x-axis, y-axis, and y-axis directions, respectively, and the number ranges are:

[0023] i=1,2,…,N x ,j=1,2,…,N y ,k=1,2,…,N z , the number uniquely identifies the position of each grid unit in the entire cabinet space.

[0024] Furthermore, in step S1, the virtual grid modeling method further includes:

[0025] The three-dimensional coordinates of the center point of each grid cell are defined as:

[0026] (x i ,y j ,z k )=((i-0.5)·Δx, (j-0.5)·Δy, (k-0.5)·Δz), where, x i represents the coordinates of the center point of the i-th grid in the x-axis direction, y j represents the coordinates of the center point of the jth grid in the y-axis direction, z k represents the coordinates of the center point of the kth grid in the z-axis direction, Δx, Δy, and Δz are the lengths of each grid unit in the x, y, and z directions respectively;

[0027] The total number of grids in the cabinet space N total For: N total =N x ×N y ×N z , where N total Represents the total number of grids inside the cabinet, N x 、N y 、N z Indicates the number of grids in the x, y, and z directions.

[0028] Furthermore, in step S2, a multi-antenna collaborative reading method is used to collect data from the RFID tag multiple times. Each antenna reads the tags in its coverage area multiple times and integrates the read data with other antennas. The data between antennas are calibrated in real time to obtain preliminary reading results.

[0029] Furthermore, the multi-antenna collaborative reading method in step S2 is:

[0030] Assume there are M antennas inside the filing cabinet, and the positions of the antennas are A m =(x m ,y m ,z m ), where m = 1, 2, ..., M represents the antenna number, and each antenna is responsible for covering a certain area;

[0031] The signal strength S received by each antenna m From multiple tags in the cabinet, when antenna m reads the nth RFID tag, the received signal strength S m,n It is expressed as: Among them, P t Indicates the antenna transmission power, G m represents the gain of antenna m, G n represents the gain of tag n, λ represents the wavelength of the signal, Where c is the speed of light, f is the signal frequency, d m,n Indicates the distance from antenna m to tag n, distance d m,n represents the geometric distance between antenna m and tag n, that is:

[0032] Among them, x tag,n ,y tag,n ,z tag,n is the three-dimensional coordinate position of label n, x m ,y m ,z m is the three-dimensional coordinate position of antenna m;

[0033] Each antenna m reads the signal of tag n multiple times. Assuming that each antenna reads K times, let the signal read by antenna m for the kth time be The average value of the signal obtained by multiple readings is used as the preliminary reading result:

[0034] in, represents the average signal strength of antenna m to tag n, It represents the reading signal of tag n by antenna m during the kth acquisition, and K represents the number of readings of each antenna.

[0035] Furthermore, the multi-antenna collaborative reading method in step S2 further includes:

[0036] Multiple antennas read the same tag n, and the signal strength obtained is It will be different in space, using the data obtained by multiple antennas to perform weighted average integration of signal strength:

[0037] Among them, S nrepresents the integrated signal strength of tag n, w m represents the weight of antenna m;

[0038] The least square method is used to correct the difference between antennas and minimize the difference between the reading results of each antenna and the integrated signal S n The difference between

[0039] According to the integrated signal strength S n , combined with the relative position of each antenna, the triangulation positioning algorithm is used to preliminarily estimate the position of tag n in three-dimensional space. Assuming that the distance between antennas is known, the time difference Δt m,n Estimate the initial position r of the label n :

[0040] Among them, r n represents the initial estimated position of label n, A m represents the coordinate position of antenna m, v represents the signal propagation speed, Δt m,n It represents the time difference of the signal from tag n to antenna m.

[0041] Furthermore, in step 3, the preliminary reading result, i.e. the preliminary estimated position, is calibrated:

[0042] Assume that the phase of the signal received by each antenna m is φ m,n :

[0043] Among them, φ m,n represents the signal phase received by antenna m from tag n, λ represents the signal wavelength, d m,n represents the distance between antenna m and tag n, φ0 represents the initial phase of the signal;

[0044] Assume that two antennas m1 and m2 receive signals from the same tag respectively, and their phase difference is for:

[0045] This phase difference is used to correct the distance estimation between the two antennas to the tag position and construct the phase difference matrix Φ;

[0046] The joint probability model is constructed using maximum likelihood estimation:

[0047] in, represents the specific location of the label n obtained by maximum likelihood estimation, S m,n represents the signal strength of tag n received by antenna m, σ 2 represents the variance of signal strength, φ m,n Indicates the signal phase received by antenna m from tag n, represents the theoretically calculated phase, Represents the variance of phase measurement noise, thus obtaining a more accurate tag location;

[0048] Step S3 is based on the preliminary estimation result of step S2, and uses the phase angle information of the signal and the signal strength to jointly analyze and correct the position of the tag.

[0049] Furthermore, step S5 generates an electronic distribution map based on the RFID tag position obtained in step S3 in the following manner:

[0050] Based on step S3, the three-dimensional position of each RFID tag n is obtained Convert it to a grid number in the virtual grid (i grid ,j grid ,k grid ):

[0051] Among them, x n ,y n ,z n represents the actual three-dimensional position of the RFID tag n, Δx, Δy, Δz represent the step length of the grid in the x, y, and z directions, that is, the length of each grid unit, i grid ,j grid ,k grid Indicates the coordinate number of label n in the virtual grid structure,

[0052] Get the label position i grid ,j grid ,k grid After that, it is marked on the electronic map, and the virtual grid structure is defined as a three-dimensional array M[i,j,k], where each element represents a grid unit:

[0053] M[i grid ,j grid ,k grid ]=n, where the grid unit M[i grid ,j grid ,k grid ] is marked as containing label n, M[i grid ,j grid ,k grid ] represents the grid (i grid ,j grid ,k grid ), where n represents the number of the RFID tag.

[0054] Furthermore, in step S5, the method of generating the electron distribution map further includes:

[0055] The state M[i,j,k] of each grid unit is processed in two dimensions to display the cross section of the cabinet with a height of z, that is, k=k is fixed. z ,but:

[0056] M 2D [i,j]=M[i,j,k z ], at a fixed height k z In the case of 2D It is a two-dimensional representation of the electronic map, showing the labels stored in each grid at that altitude;

[0057] Assume that the position of the cabinet door is (i door ,j door ,k door ), the target output is label n in (i grid ,j grid ,k grid ), then: Among them, d path Indicates the distance from the cabinet door to the label, i door ,j door ,k door Indicates the position number of the cabinet door in the virtual grid, i grid ,j grid ,k grid Indicates the grid position of the target label.

[0058] Furthermore, in the electronic map of step S5:

[0059] When the file is moved, the electronic map is dynamically updated, and the grid number of the tag is updated to the new grid unit based on the new location of the RFID tag.

[0060] M[i new ,j new ,k new ] = n, and mark the grid at the original position as unoccupied:

[0061] M[i old ,j old ,k old ]=0;

[0062] Step S5: From the label coordinates (x n ,y n ,z n ) and mapped to the virtual grid coordinates (i grid ,j grid ,k grid ), and generate an electronic map, output the optimal path by calculating the shortest distance from the cabinet door to the target tag, and keep the map real-time by dynamically updating the tag position.

[0063] The beneficial effects of the present invention are:

[0064] The present invention divides the internal space of the filing cabinet into small grid units through virtual grid modeling. Each grid has a clear number, which realizes the preliminary positioning of each RFID tag, so that the archives are no longer limited to the general area, but can be accurate to the specific grid. In addition, multi-antenna collaborative reading combines multiple readings and analyses of signal strength and phase angle to further improve the accuracy of positioning. The maximum likelihood estimation model can correct errors according to signal differences and phase angles, thereby realizing more accurate archive location queries.

[0065] The present invention uses a multi-antenna collaborative reading method to read tags within the coverage area multiple times, reduces interference through signal calibration between antennas, and corrects the difference between antennas by weighted averaging the signal strength and using the least squares method to reduce errors caused by signal reflection, interference or overlap. For high-density RFID tags, it can significantly reduce collision problems and improve data collection efficiency.

[0066] The present invention arranges wave-absorbing materials in the filing cabinet to effectively reduce the multi-path interference problem caused by signal reflection.

[0067] The present invention efficiently covers all grid areas through the coordinated work of multiple antennas and real-time calibration between antennas. Compared with the traditional RFID system, the signal is collected multiple times and averaged, which reduces the randomness and error of a single reading. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0069] Figure 1 The figure is a flow chart of the intelligent filing cabinet file query method of the present invention. DETAILED DESCRIPTION

[0070] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0071] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0072] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0073] Example 1, reference Figure 1 This embodiment provides a smart filing cabinet file query method based on RFID technology, comprising the following steps:

[0074] Step S1: grid modeling and partition layout.

[0075] The interior of the filing cabinet is modeled in a virtual grid, and the cabinet space is divided into multiple small virtual grids, each grid representing an independent storage unit; in step S1, the files corresponding to each RFID tag are divided into virtual grids to establish a preliminary grid storage structure;

[0076] In step S1, the virtual grid modeling method is:

[0077] Assume that the length, width and height of the three-dimensional space inside the filing cabinet are L, W and H respectively, and divide the entire cabinet space into N x 、N y and N z grid cells, partitioned in the x-axis, y-axis, and z-axis directions:

[0078] Where L is the length of the filing cabinet along the x-axis, W is the width of the filing cabinet along the y-axis, H is the height of the filing cabinet along the z-axis, and N x Indicates the number of grids along the x-axis, N y Indicates the number of grids along the y-axis, N z represents the number of grids along the z-axis, Δx, Δy, Δz represent the lengths in the x, y, z directions;

[0079] Each grid unit is represented by a three-dimensional coordinate (i, j, k), where i, j, and k represent the position number of the grid in the x-axis, y-axis, and y-axis directions, respectively, and the number ranges are:

[0080] i=1,2,…,N x ,j=1,2,…,N y ,k=1,2,…,N z ,The number uniquely identifies the position of each grid unit in the entire cabinet space;

[0081] In step S1, the virtual grid modeling method also includes:

[0082] The three-dimensional coordinates of the center point of each grid cell are defined as:

[0083] (x i ,y j ,z k )=((i-0.5)·Δx, (j-0.5)·Δy, (k-0.5)·Δz), where, x i represents the coordinates of the center point of the i-th grid in the x-axis direction, y j represents the coordinates of the center point of the jth grid in the y-axis direction, z k represents the coordinates of the center point of the kth grid in the z-axis direction, Δx, Δy, and Δz are the lengths of each grid unit in the x, y, and z directions respectively;

[0084] The total number of grids in the cabinet space N total For: N total =N x ×N y ×N z , where N total Represents the total number of grids inside the cabinet, N x 、N y 、N z Indicates the number of grids in the x, y, and z directions;

[0085] Specifically, the three-dimensional space inside the filing cabinet is divided, and each grid represents an independent storage unit. The grid structure greatly improves the system's storage management capabilities and realizes the preliminary positioning of RFID tags. Compared with traditional fuzzy storage and tag query methods, virtual grid modeling can accurately assign a spatial location to each file, greatly reducing the ambiguity and error in file positioning.

[0086] Step S2: multi-antenna collaborative reading.

[0087] Based on the virtual grid division structure of step S1, multiple antennas are arranged, each antenna is responsible for covering multiple grid areas within its effective range, thereby reducing errors caused by signal interference or overlapping areas;

[0088] In step S2, a multi-antenna collaborative reading method is used to collect data from RFID tags multiple times. Each antenna reads the tags in its coverage area multiple times and integrates the read data with other antennas. The data between antennas are calibrated in real time to obtain preliminary reading results.

[0089] The multi-antenna collaborative reading method in step S2 is:

[0090] Assume there are M antennas inside the filing cabinet, and the positions of the antennas are A m =(x m,y m ,z m ), where m = 1, 2, ..., M represents the antenna number, and each antenna is responsible for covering a certain area;

[0091] The signal strength S received by each antenna m From multiple tags in the cabinet, when antenna m reads the nth RFID tag, the received signal strength S m,n It is expressed as: Among them, P t Indicates the antenna transmission power, G m represents the gain of antenna m, G n represents the gain of tag n, λ represents the wavelength of the signal, Where c is the speed of light, f is the signal frequency, d m,n Indicates the distance from antenna m to tag n, distance d m,n represents the geometric distance between antenna m and tag n, that is:

[0092] Among them, x tag,n ,y tag,n ,z tag,n is the three-dimensional coordinate position of label n, x m ,y m ,z m is the three-dimensional coordinate position of antenna m;

[0093] Each antenna m reads the signal of tag n multiple times. Assuming that each antenna reads K times, let the signal read by antenna m for the kth time be The average value of the signal obtained by multiple readings is used as the preliminary reading result:

[0094] in, represents the average signal strength of antenna m to tag n, represents the reading signal of tag n by antenna m during the kth acquisition, and K represents the number of readings of each antenna;

[0095] The multi-antenna collaborative reading method in step S2 also includes:

[0096] Multiple antennas read the same tag n, and the signal strength obtained is It will be different in space, using the data obtained by multiple antennas to perform weighted average integration of signal strength:

[0097] Among them, S n represents the integrated signal strength of tag n, w m represents the weight of antenna m;

[0098] The least square method is used to correct the difference between antennas and minimize the difference between the reading results of each antenna and the integrated signal S n The difference between

[0099] According to the integrated signal strength S n , combined with the relative position of each antenna, the triangulation positioning algorithm is used to preliminarily estimate the position of tag n in three-dimensional space. Assuming that the distance between antennas is known, the time difference Δt m,n Estimate the initial position r of the label n :

[0100] Among them, r n represents the initial estimated position of label n, A m represents the coordinate position of antenna m, v represents the signal propagation speed, Δt m,n Represents the time difference of the signal from tag n to antenna m;

[0101] Specifically, multi-antenna collaborative reading technology effectively solves the problems of signal interference and multi-tag reading conflicts. It improves the accuracy of reading signals through multiple readings and signal strength integration of multiple antennas. It is still effective in high-density tag areas. Compared with traditional single-antenna reading methods, it significantly reduces errors caused by signal blind spots or reflections, achieving more efficient and accurate tag reading effects.

[0102] On this basis, by combining signal strength and phase angle analysis, the positioning accuracy of the tag is further improved. The phase difference calibration is performed using the signal phase information received by the antenna. The position of the tag is fine-tuned based on the preliminary estimate. Through the joint analysis of signal strength and phase angle, the accuracy of the tag position is greatly improved. It is optimized for scenarios with high environmental noise or severe signal reflection, and the positioning error is significantly reduced.

[0103] Step S3, signal strength and phase angle analysis,

[0104] On the basis of step S2, the signal strength and phase angle data of the preliminary reading results collected by each antenna are used to perform multi-antenna phase difference calibration to obtain the specific position of the tag. Based on the cross analysis of signal strength and phase angle, the specific area and relative position of the tag in the grid can be more accurately located;

[0105] In step 3, the preliminary reading result, i.e. the preliminary estimated position, is calibrated:

[0106] Assume that the phase of the signal received by each antenna m is φ m,n :

[0107] Among them, φ m,n represents the signal phase received by antenna m from tag n, λ represents the signal wavelength, d m,n represents the distance between antenna m and tag n, φ0 represents the initial phase of the signal;

[0108] Assume that two antennas m1 and m2 receive signals from the same tag respectively, and their phase difference is for:

[0109] This phase difference is used to correct the distance estimation between the two antennas to the tag position and construct the phase difference matrix Φ;

[0110] The joint probability model is constructed using maximum likelihood estimation:

[0111] in, represents the specific location of the label n obtained by maximum likelihood estimation, S m,n represents the signal strength of tag n received by antenna m, σ 2 represents the variance of signal strength, φ m,n Indicates the signal phase received by antenna m from tag n, represents the theoretically calculated phase, Represents the variance of phase measurement noise, thus obtaining a more accurate tag location;

[0112] Step S3, based on the preliminary estimation result of step S2, uses the phase angle information and signal strength of the signal to perform correction and optimization on the position of the tag;

[0113] Step S4, signal reflection optimization,

[0114] In a high-density metal environment, RFID signals are susceptible to reflection and interference. To address this problem, absorbing materials are arranged in the internal grid area of ​​the filing cabinet to reduce signal reflection and interference, and improve signal quality and reading stability.

[0115] Step S5: position marking and path prompting.

[0116] Based on the specific location of each RFID tag in the grid obtained in step S3, the location is automatically marked on the electronic map of the virtual grid structure, and an electronic distribution map of the files in the filing cabinet is generated. The electronic map shows the exact location of each file and provides a quick path prompt. Combined with the data update of the signal reading, it dynamically reflects the real-time distribution of the files in the filing cabinet;

[0117] Step S5 generates an electronic distribution map based on the RFID tag position obtained in step S3 in the following manner:

[0118] Based on step S3, the three-dimensional position of each RFID tag n is obtained Convert it to a grid number in the virtual grid (igrid ,j grid ,k grid ):

[0119] Among them, x n ,y n ,z n represents the actual three-dimensional position of the RFID tag n, Δx, Δy, Δz represent the step length of the grid in the x, y, and z directions, that is, the length of each grid unit, i grid ,j grid ,k grid Indicates the coordinate number of label n in the virtual grid structure,

[0120] Get the label position i grid ,j grid ,k grid After that, it is marked on the electronic map, and the virtual grid structure is defined as a three-dimensional array M[i,j,k], where each element represents a grid unit:

[0121] M[i grid ,j grid ,k grid ]=n, where the grid unit M[i grid ,j grid ,k grid ] is marked as containing label n, M[i grid ,j grid ,k grid ] represents the grid (i grid ,j grid ,k grid ), where n represents the number of the RFID tag;

[0122] In step S5, the method of generating the electron distribution map further includes:

[0123] The state M[i,j,k] of each grid unit is processed in two dimensions to display the cross section of the cabinet with a height of z, that is, k=k is fixed. z ,but:

[0124] M 2D [i,j]=M[i,j,k z ], at a fixed height k z In the case of 2D It is a two-dimensional representation of the electronic map, showing the labels stored in each grid at that altitude;

[0125] Assume that the position of the cabinet door is (i door ,j door ,k door), the target output is label n in (i grid ,j grid ,k grid ), then: Among them, d path Indicates the distance from the cabinet door to the label, i door ,j door ,k door Indicates the position number of the cabinet door in the virtual grid, i grid ,j grid ,k grid Represents the grid position of the target label;

[0126] In the electronic map of step S5:

[0127] When the file is moved, the electronic map is dynamically updated, and the grid number of the tag is updated to the new grid unit based on the new location of the RFID tag.

[0128] M[i new ,j new ,k new ] = n, and mark the grid at the original position as unoccupied:

[0129] M[i old ,j old ,k old ]=0;

[0130] Step S5: From the label coordinates (x n ,y n ,z n ) and mapped to the virtual grid coordinates (i grid ,j grid ,k grid ), and generate an electronic map, calculate the shortest distance from the cabinet door to the target tag and output the optimal path, while dynamically updating the tag position to maintain the real-time nature of the map;

[0131] Specifically, the electronic map provides users with an intuitive way to locate and query archives. Through the precise location obtained in step S3, the label location is automatically marked on the electronic map of the virtual grid structure, and the real-time distribution of archives in the cabinet is dynamically displayed, which greatly improves the efficiency of users' archive query.

[0132] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A smart filing cabinet file query method based on RFID technology, characterized in that: include, Step S1, grid modeling and partition layout, virtual grid modeling is performed on the interior of the filing cabinet, and the cabinet space is divided into multiple small virtual grids, each grid representing an independent storage unit; Step S2, multi-antenna collaborative reading, based on the virtual grid division structure of step S1, multiple antennas are arranged, and each antenna is responsible for covering multiple grid areas within its effective range; Step S3, signal strength and phase angle analysis: Based on step S2, the signal strength and phase angle data of the preliminary reading results collected by each antenna are used to perform multi-antenna phase difference calibration to obtain the specific location of the tag; Step S4, signal reflection optimization, arranging absorbing materials in the internal grid area of ​​the filing cabinet; Step S5, location marking and path prompting, based on the specific location of each RFID tag in the grid obtained in step S3, the location is automatically marked on the electronic map of the virtual grid structure, and an electronic distribution map of the files in the filing cabinet is generated.

2. According to the RFID-based intelligent filing cabinet file query method of claim 1, it is characterized in that: In step S1, the virtual grid modeling method is: Assume that the length, width and height of the three-dimensional space inside the filing cabinet are L, W and H respectively, and divide the entire cabinet space into N x 、N y and N z grid cells, partitioned in the x-axis, y-axis, and z-axis directions: Where L is the length of the filing cabinet along the x-axis, W is the width of the filing cabinet along the y-axis, H is the height of the filing cabinet along the z-axis, and N x Indicates the number of grids along the x-axis, N y Indicates the number of grids along the y-axis, N z represents the number of grids along the z-axis, Δx, Δy, Δz represent the lengths in the x, y, z directions; Each grid unit is represented by a three-dimensional coordinate (i, j, k), where i, j, and k represent the position number of the grid in the x-axis, y-axis, and y-axis directions, respectively, and the number ranges are: i=1,2,…,N x ,j=1,2,…,N y ,k=1,2,…,N z , the number uniquely identifies the position of each grid unit in the entire cabinet space.

3. The intelligent filing cabinet file query method based on RFID technology according to claim 2 is characterized in that: In step S1, the virtual grid modeling method further includes: The three-dimensional coordinates of the center point of each grid cell are defined as: (x i ,y j ,z k )=((i-0.5)·Δx, (j-0.5)·Δy, (k-0.5)·Δz), where, x i represents the coordinates of the center point of the i-th grid in the x-axis direction, y j represents the coordinates of the center point of the jth grid in the y-axis direction, z k represents the coordinates of the center point of the kth grid in the z-axis direction, Δx, Δy, and Δz are the lengths of each grid unit in the x, y, and z directions respectively; The total number of grids in the cabinet space N total For: N total =N x ×N y ×N z , where N total Represents the total number of grids inside the cabinet, N x 、N y 、N z Indicates the number of grids in the x, y, and z directions.

4. The intelligent filing cabinet file query method based on RFID technology according to claim 3 is characterized in that: In step S2, a multi-antenna collaborative reading method is used to collect data from RFID tags multiple times. Each antenna reads the tags in its coverage area multiple times and integrates the read data with other antennas. The data between antennas are calibrated in real time to obtain preliminary reading results.

5. The intelligent filing cabinet file query method based on RFID technology according to claim 4 is characterized in that: The multi-antenna collaborative reading method in step S2 is: Assume there are M antennas inside the filing cabinet, and the positions of the antennas are A m =(x m ,y m ,z m ), where m = 1, 2, ..., M represents the antenna number, and each antenna is responsible for covering a certain area; The signal strength S received by each antenna m From multiple tags in the cabinet, when antenna m reads the nth RFID tag, the received signal strength S m,n It is expressed as: Among them, P t Indicates the antenna transmission power, G m represents the gain of antenna m, G n represents the gain of tag n, λ represents the wavelength of the signal, Where c is the speed of light, f is the signal frequency, d m,n Indicates the distance from antenna m to tag n, distance d m,n represents the geometric distance between antenna m and tag n, that is: Among them, x tag,n ,y tag,n ,z tag,n is the three-dimensional coordinate position of label n, x m ,y m ,z m is the three-dimensional coordinate position of antenna m; Each antenna m reads the signal of tag n multiple times. Assuming that each antenna reads K times, let the signal read by antenna m for the kth time be The average value of the signal obtained by multiple readings is used as the preliminary reading result: in, represents the average signal strength of antenna m to tag n, It represents the reading signal of tag n by antenna m during the kth acquisition, and K represents the number of readings of each antenna.

6. The intelligent filing cabinet file query method based on RFID technology according to claim 5 is characterized in that: The multi-antenna collaborative reading method in step S2 also includes: Multiple antennas read the same tag n and perform weighted average integration of signal strength: Among them, S n represents the integrated signal strength of tag n, w m represents the weight of antenna m; The least square method is used to correct the difference between antennas and minimize the difference between the reading results of each antenna and the integrated signal S n The difference between Assuming the distance between the antennas is known, use the time difference Δt m,n Estimate the initial position r of the label n : Among them, r n represents the initial estimated position of label n, A m represents the coordinate position of antenna m, v represents the signal propagation speed, Δt m,n It represents the time difference of the signal from tag n to antenna m.

7. The intelligent filing cabinet file query method based on RFID technology according to claim 6 is characterized in that: In step 3, the preliminary reading result, i.e. the preliminary estimated position, is calibrated: Assume that the phase of the signal received by each antenna m is φ m,n : Among them, φ m,n represents the signal phase received by antenna m from tag n, λ represents the signal wavelength, d m,n represents the distance between antenna m and tag n, φ0 represents the initial phase of the signal; Assume that two antennas m1 and m2 receive signals from the same tag respectively, and their phase difference is for: This phase difference is used to correct the distance estimation between the two antennas to the tag position and construct the phase difference matrix Φ; The joint probability model is constructed using maximum likelihood estimation: in, represents the specific location of label n obtained by maximum likelihood estimation, S m,n represents the signal strength of tag n received by antenna m, σ 2 represents the variance of signal strength, φ m,n Indicates the signal phase received by antenna m from tag n, represents the theoretically calculated phase, represents the variance of the phase measurement noise.

8. The intelligent filing cabinet file query method based on RFID technology according to claim 7 is characterized in that: Step S5 generates an electronic distribution map based on the RFID tag position obtained in step S3 in the following manner: Based on step S3, the three-dimensional position of each RFID tag n is obtained Convert it to a grid number in the virtual grid (i grid ,j grid ,k grid ): Among them, x n ,y n ,z n represents the actual three-dimensional position of the RFID tag n, Δx, Δy, Δz represent the step length of the grid in the x, y, and z directions, that is, the length of each grid unit, i grid ,j grid ,k grid Indicates the coordinate number of label n in the virtual grid structure, Get the label position i grid ,j grid ,k grid After that, it is marked on the electronic map, and the virtual grid structure is defined as a three-dimensional array M[i,j,k], where each element represents a grid unit: M[i grid ,j grid ,k grid ]=n, where the grid unit M[i grid ,j grid ,k grid ] is marked as containing label n, M[i grid ,j grid ,k grid ] represents the grid (i grid ,j grid ,k grid ), where n represents the number of the RFID tag.

9. The intelligent filing cabinet file query method based on RFID technology according to claim 8 is characterized in that: In step S5, the method of generating the electron distribution map further includes: The state M[i,j,k] of each grid unit is processed in two dimensions to display the cross section of the cabinet with a height of z, that is, k=k is fixed. z ,but: M 2D [i,j]=M[i,j,k z ], at a fixed height k z In the case of 2D It is a two-dimensional representation of the electronic map, showing the labels stored in each grid at that altitude; Assume that the position of the cabinet door is (i door ,j door ,k door ), the target output is label n in (i grid ,j grid ,k grid ), then: Among them, d path Indicates the distance from the cabinet door to the label, i door ,j door ,k door Indicates the position number of the cabinet door in the virtual grid, i grid ,j grid ,k grid Indicates the grid position of the target label.

10. The intelligent filing cabinet file query method based on RFID technology according to claim 9 is characterized in that: In the electronic map of step S5: When the file is moved, the electronic map is dynamically updated, and the grid number of the tag is updated to the new grid unit based on the new location of the RFID tag. M[i new ,j new ,k new ] = n, and mark the grid at the original position as unoccupied: M[i old ,j old ,k old ]=0。

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