A multi-directional RFID radio frequency tag identification method and system

Abstract

The present invention relates to the technical field of data acquisition, and in particular to a multi-directional RFID radio frequency tag identification method and system. The method comprises: determining candidate positioning points based on RFID radio frequency signals received by various RFID receivers in various directions, fusing the signal qualities of the various RFID radio frequency signals constituting the candidate positioning points, and obtaining candidate indicators of the candidate positioning points, wherein the signal quality is obtained by fusing signal quality sub-indicators, and the signal quality sub-indicators include signal stability, signal superposition, and signal interference represented by various components. The position of a positioning target is determined based on the candidate indicators of each positioning candidate point, and the multipath effect generated in the RFID radio frequency signal is eliminated to obtain the accurate signal quality of the RFID radio frequency signal, thereby accurately and reliably obtaining the candidate indicators of each positioning candidate point, and ultimately obtaining the accurate position of the positioning target, thereby improving the accuracy of target positioning.

Description

Technical Field

[0001] The present invention relates to the technical field of data acquisition, and in particular to a multi-directional RFID radio frequency tag recognition method and system. Background Art

[0002] Radio Frequency Identification (RFID) is a contactless automatic identification technology that uses the transmission characteristics of radio frequency signals and their spatial coupling to automatically identify stationary or moving objects. RFID is often referred to as an inductive electronic chip, proximity card, induction card, contactless card, electronic tag, or electronic barcode. RFID tags can be attached or mounted on various objects. Readers and writers installed in different locations read the data stored on the tags, enabling automatic identification of the objects.

[0003] Multi-directional RFID technology involves deploying multiple RFID receivers (i.e., RFID antennas or RFID readers) within an RFID system, covering different directions (such as horizontal, vertical, and diagonal) to receive and analyze RFID tag signals from multiple angles. When using multi-directional RFID technology to identify the location of RFID tags in three-dimensional space, the presence of other objects in space often reflects or absorbs the RFID signal, resulting in multipath effects. This causes the received signal to propagate along multiple paths, with each path potentially reaching the RFID receiver due to reflection, refraction, and diffraction. Because the arrival time, amplitude, and phase of RFID signals along different paths may vary, this can lead to inaccurate target location and identification. Summary of the Invention

[0004] In order to solve the technical problem that the existing multi-directional RFID radio frequency technology causes inaccurate target positioning, the purpose of the present invention is to provide a multi-directional RFID radio frequency tag recognition method and system. The technical solution adopted is as follows:

[0005] In a first aspect of the present invention, a multi-directional RFID tag identification method is provided, comprising:

[0006] Determine a candidate positioning point based on the RFID radio frequency signals received by each RFID receiver in each direction, where the candidate positioning point is a signal intersection point formed by the intersection of each RFID radio frequency signal;

[0007] The signal quality of each RFID radio frequency signal constituting the candidate positioning point is integrated to obtain a candidate index of the candidate positioning point; the signal quality is obtained by integrating signal quality sub-indicators, and the signal quality sub-indicators include signal stability, signal superposition, and signal interference represented by each component, and the each component is obtained by multi-component decomposition of the RFID radio frequency signal;

[0008] The position of the positioning target is determined based on the candidate index of each positioning candidate point.

[0009] In an exemplary embodiment, determining the position of the positioning target based on the candidate index of each positioning candidate point includes:

[0010] Obtaining the number of neighboring candidate positioning points of the candidate positioning point and the degree of fluctuation of the candidate index of the neighboring candidate positioning points; the neighboring candidate positioning points are other candidate positioning points within a preset neighborhood of the candidate positioning point; the candidate positioning point is any candidate positioning point;

[0011] Obtaining the position stability of the candidate positioning point according to the number of neighboring candidate positioning points of the candidate positioning point and the fluctuation degree of the candidate index;

[0012] Obtaining a final position probability of the candidate positioning point based at least on the position stability and candidate index of the candidate positioning point; wherein the final position probability is positively correlated with both the position stability and the candidate index;

[0013] The maximum final position probability is determined, and the position of the positioning candidate point corresponding to the maximum final position probability is used as the position of the positioning target.

[0014] In an exemplary embodiment, obtaining the final position probability of the candidate positioning point based at least on the position stability and the candidate index of the candidate positioning point includes:

[0015] According to the position stability of the candidate positioning candidate point, the candidate index and the local reachability density of the candidate positioning candidate point in space, the final position probability of the candidate positioning candidate point is obtained; the final position probability is positively correlated with the local reachability density.

[0016] In an exemplary embodiment, determining the position of the positioning target based on the candidate index of each positioning candidate point includes: taking the position of the positioning candidate point corresponding to the largest candidate index as the position of the positioning target.

[0017] In an exemplary embodiment, performing multi-component decomposition on the RFID radio frequency signal is specifically as follows: performing EMD empirical mode decomposition on the RFID radio frequency signal to obtain multiple IMF components; and performing Hilbert transform on each IMF component to obtain the instantaneous frequency, instantaneous amplitude and instantaneous phase of each IMF component at each moment.

[0018] In an exemplary embodiment, the process of acquiring the signal stability includes:

[0019] According to the instantaneous frequency and instantaneous amplitude of each IMF component at each moment, the signal strength of each IMF component at each moment is obtained;

[0020] The signal strength of the same instantaneous phase is divided into one category to obtain multiple categories;

[0021] According to the overall level of signal strength and the degree of signal strength fluctuation in each category, a category signal quality index of each category is obtained; the category signal quality index is positively correlated with the overall level of signal strength and negatively correlated with the degree of signal strength fluctuation;

[0022] A maximum category signal quality indicator among category signal quality indicators of each category is determined, wherein the signal stability condition is specifically the maximum category signal quality indicator.

[0023] In an exemplary embodiment, the process of obtaining the signal superposition condition includes: obtaining the instantaneous phase fluctuation degree according to the instantaneous phase corresponding to each category, wherein the signal superposition condition is specifically the instantaneous phase fluctuation degree;

[0024] The signal interference condition is the number of categories.

[0025] In an exemplary embodiment, the signal quality is obtained by the maximum category signal quality index, the instantaneous phase fluctuation degree and the number of categories; the signal quality is positively correlated with the maximum category signal quality index and the number of categories, and negatively correlated with the instantaneous phase fluctuation degree.

[0026] In an exemplary embodiment, the signal quality of each RFID radio frequency signal constituting the candidate positioning point is integrated to obtain the candidate index of the candidate positioning point, including:

[0027] The average value of the signal quality of each RFID radio frequency signal constituting the candidate positioning point is calculated to obtain a candidate index of the candidate positioning point.

[0028] In a second aspect of the present invention, a multi-directional RFID tag identification system is provided, comprising: a memory and a processor; the memory is connected to the processor; the memory is used to store program instructions; and the processor is used to implement the above-mentioned multi-directional RFID tag identification method when the program instructions are executed.

[0029] The present invention has the following beneficial effects: the present invention obtains multiple positioning candidate points from the signal intersection points formed between each RFID radio frequency signal, analyzes the signal quality of each RFID radio frequency signal constituting the positioning candidate point, and comprehensively obtains the candidate indicators of the positioning candidate point based on these signal qualities, wherein the signal quality is obtained based on each component obtained by multi-component decomposition of the RFID radio frequency signal. Through the multi-component decomposition, important data information implicit in the RFID radio frequency signal can be obtained, the multi-path effect generated in the RFID radio frequency signal can be eliminated, and the accurate signal quality of the RFID radio frequency signal can be obtained, thereby accurately and reliably obtaining the candidate indicators of each positioning candidate point, and finally obtaining the accurate position of the positioning target, thereby improving the accuracy of target positioning. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 This is a flow chart of a multi-directional RFID tag identification method provided by one embodiment of the present invention;

[0031] Figure 2 is a flow chart for obtaining signal stability provided by one embodiment of the present invention;

[0032] Figure 3 This is a flow chart for confirming the position of a positioning target provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0033] To further illustrate the technical means and effects employed by the present invention to achieve its intended objectives, the following detailed description of the specific embodiments, structures, features, and effects of the present invention is provided in conjunction with the accompanying drawings and preferred embodiments. In the following description, references to "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0034] Unless otherwise defined, all technical and scientific terms used herein have the same meanings as commonly understood by those skilled in the art to which this invention pertains. The data and information collected in this application were obtained with full consent and authorization.

[0035] This embodiment provides a multi-directional RFID radio frequency tag identification method, which is applicable to the following application scenarios: RFID receivers are installed at different positions in the space where target positioning is required, and the RFID receivers are used to identify the data information of objects with RFID tags. The space where target positioning is required varies depending on the application scenario. Taking warehousing as an example, the space where target positioning is required can be a large warehouse. In an exemplary embodiment, each RFID receiver is fixed at different positions on the inner wall of the space. The number of positions set and each position are set according to actual positioning needs, for example: each RFID receiver is evenly distributed on the inner wall of the space. By deploying multiple RFID receivers to cover different directions, multi-angle reception and analysis of RFID tag signals can be achieved. Each RFID receiver is signal-connected to the back-end data processing device for performing data processing based on the RFID radio frequency signals received by each RFID receiver to achieve position confirmation of the positioning target.

[0036] RFID tags store data in accordance with the physical properties of integrated circuits. They are essentially binary codes, using voltage transitions (a rising edge represents a "1" and a falling edge represents a "0") to convert binary data into electromagnetic signals. In this embodiment, the RFID receiver integrates a smart antenna array and a beam control unit, enabling flexible adjustment of beam direction and intensity to adapt to varying environments and tag distribution.

[0037] The object to be located (i.e., the target) is equipped with an RFID tag. When the target enters a space, each RFID receiver receives RFID radio frequency signals from all directions. RFID radio frequency signals include the reflection angle and waveform characteristics (fluctuation data). The RFID signal received by each RFID receiver is used to locate the identified RFID tag data. When performing three-dimensional positioning of an RFID tag, if there is no multipath effect, the distance can be directly determined based on the angle and phase difference of the reflected wave. The angles and distances at multiple locations can be used to determine an intersection, which provides the RFID tag's location information in three-dimensional space. However, the space in which the target is located often contains other objects that can interfere with the RFID radio frequency signal, such as metal shelves in large warehouses. This can lead to impure RFID radio frequency signals. Furthermore, the angle of the received RFID radio frequency signal may not correspond to the angle of direct reflection from the RFID tag, resulting in multiple virtual positionings and affecting positioning accuracy.

[0038] like Figure 1 As shown, this embodiment provides a multi-directional RFID tag identification method, including:

[0039] Step S1: Determine candidate positioning points based on the RFID radio frequency signals received by each RFID receiver in each direction;

[0040] Step S2: integrating the signal qualities of the RFID radio frequency signals constituting the candidate positioning points to obtain candidate indicators of the candidate positioning points;

[0041] Step S3: Determine the position of the positioning target based on the candidate index of each positioning candidate point.

[0042] Each step is described in detail below with reference to the accompanying drawings.

[0043] Step S1: Determine candidate positioning points based on RFID radio frequency signals in various directions received by various RFID receivers.

[0044] Obtain the RFID radio frequency signals in each direction received by each RFID receiver at the current moment. Since the signal directions corresponding to the RFID radio frequency signals in each direction received by each RFID receiver are not parallel to each other, each RFID radio frequency signal is extended according to its signal direction. In the extended direction, there will inevitably be a number of RFID radio frequency signals intersecting with each other, thereby obtaining the signal intersection points formed by the intersection between the RFID radio frequency signals. Usually, multiple signal intersection points are obtained, and the number of RFID radio frequency signals constituting different signal intersection points may be different. The obtained signal intersection points are defined as candidate positioning points. It should be understood that the multiple RFID radio frequency signals constituting the candidate positioning points may be RFID radio frequency signals in different directions received by different RFID receivers.

[0045] The positions of the candidate positioning points are used as candidate positioning positions. Subsequently, the positioning positions corresponding to the candidate positioning points are determined as the position information of the positioning target.

[0046] Step S2: The signal qualities of the RFID radio frequency signals constituting the candidate positioning points are integrated to obtain candidate indicators of the candidate positioning points.

[0047] For any RFID radio frequency signal, the first step is to determine its signal quality. This quality is derived from the integration of signal quality sub-indicators, which include signal stability, signal superposition, and signal interference, represented by various components. Each component is derived from multi-component decomposition of the RFID radio frequency signal.

[0048] In an exemplary embodiment, the RFID radio frequency signal is subjected to EMD (Empirical Mode Decomposition) decomposition to obtain multiple IMF (Intrinsic Mode Function) components. This EMD decomposition can be used to decompose and distinguish information from the original RFID radio frequency signal, even when signals are superimposed. In a multipath propagation environment, the IMF components can be used to extract different frequency components and reflection path information. EMD decomposition can decompose a complex signal into multiple IMF components, each containing a specific frequency component. A Hilbert transform is then performed on each IMF component to obtain the instantaneous frequency, amplitude, and phase of each IMF component at each moment. The Hilbert transform is a mathematical method used to generate an analytical expression for a signal. It provides a complex number representation for each IMF component, which allows for easy extraction of the instantaneous frequency, amplitude, and phase.

[0049] In an exemplary embodiment, Figure 2 As shown, a specific process of obtaining the signal stability is given below:

[0050] Step S21: obtaining the signal strength of each IMF component at each moment according to the instantaneous frequency and instantaneous amplitude of each IMF component at each moment.

[0051] For the sake of convenience, any IMF component of the RFID radio frequency signal is assumed to be IMF components, Any moment in the IMF components is the moment. The first of the IMF components The higher the instantaneous frequency at a moment, the higher the instantaneous amplitude. The first of the IMF components The higher the signal strength at the moment, the more likely it is that the information data is reflected by the RFID tag. In an exemplary embodiment, the The first of the IMF components The calculation formula of the signal strength at a moment is as follows:

[0052] ;

[0053] in, Indicates the The first of the IMF components The signal strength at a given moment, Indicates the The first of the IMF components The instantaneous frequency at a moment, Indicates the The first of the IMF components The instantaneous amplitude at a moment. Represents a normalization function. The normalization method here can be: obtain the product of the instantaneous frequency and the instantaneous amplitude at each moment in each IMF component of all RFID radio frequency signals, then obtain the maximum and minimum values ​​of the product of the instantaneous frequency and the instantaneous amplitude, and finally use the maximum and minimum value normalization method to perform the normalization on the first IMF component of the RFID radio frequency signal. The first of the IMF components of a moment Perform normalization.

[0054] Step S22: Classify the signal strengths of the same instantaneous phase into one category to obtain multiple categories.

[0055] The instantaneous phase of each IMF component at each moment is an important characteristic reflecting the periodicity of signal fluctuations. Step S21 obtains the signal strength of each IMF component of the RFID radio frequency signal at each moment. Since each IMF component has a corresponding instantaneous phase at each moment, there is a one-to-one correspondence between the instantaneous phase and the signal strength.

[0056] Classification is based on instantaneous phase. The classification rule is: RFID signals with the same instantaneous phase are grouped together, and the signal strengths of the same instantaneous phase are grouped together, resulting in multiple categories. Each category includes multiple signal strengths, and the signal strengths within the same category have the same instantaneous phase.

[0057] Step S23: obtaining a category signal quality index for each category based on the overall signal strength level and signal strength fluctuation degree in each category.

[0058] For any category, the signal strengths of each signal within that category are obtained, and then the average of the signal strengths within that category is calculated. This average is used as the overall signal strength level for that category. The degree of signal strength fluctuation within that category is obtained. In one exemplary embodiment, the degree of fluctuation is characterized by variance. Then, the variance of the signal strength within that category is calculated, and this variance is used as the degree of signal strength fluctuation for that category.

[0059] According to the overall level of signal strength of the category and the degree of signal strength fluctuation, the category signal quality index of the category is obtained. Among them, the higher the overall level of signal strength, the higher the signal strength of the category, that is, the higher the category signal quality index of the category, and the category signal quality index is positively correlated with the overall level of signal strength. The larger the variance of the signal strength in the category, that is, the higher the degree of fluctuation of the signal strength of the category, the more unstable the signal strength in the category, and the worse the signal quality of the category, that is, the lower the category signal quality index of the category, and the category signal quality index is inversely correlated with the degree of fluctuation of signal strength. In an exemplary embodiment, a specific quantification method of the category signal quality index is given as follows:

[0060] ;

[0061] in, Indicates the RFID radio frequency signal corresponding to the The signal quality indicators of the categories are Indicates the RFID radio frequency signal corresponding to the The overall level of signal strength for each category, Indicates the RFID radio frequency signal corresponding to the The signal strength fluctuation degree of each category is calculated, thereby obtaining the category signal quality index of each category corresponding to the RFID radio frequency signal.

[0062] Step S24: determining the maximum category signal quality indicator among the category signal quality indicators of each category, wherein the signal stability condition is specifically the maximum category signal quality indicator.

[0063] The higher the category signal quality index, the better the signal quality and the more stable the signal. Therefore, the maximum category signal quality index is obtained from the category signal quality indexes of each category corresponding to the RFID radio frequency signal, and the maximum category signal quality index represents the signal stability of the RFID radio frequency signal.

[0064] In an exemplary embodiment, the process of obtaining the signal superposition of the RFID radio frequency signal includes: obtaining the instantaneous phase corresponding to each category of the RFID radio frequency signal, and then obtaining the degree of instantaneous phase fluctuation. Here, the degree of fluctuation is represented by variance. Specifically, the variance of the instantaneous phase corresponding to each category of the RFID radio frequency signal is calculated. This variance represents the degree of instantaneous phase fluctuation of the RFID radio frequency signal. The degree of instantaneous phase fluctuation of the RFID radio frequency signal represents the signal superposition of the RFID radio frequency signal. The greater the variance of the instantaneous phase, that is, the higher the degree of instantaneous phase fluctuation, the more multiple signals are superimposed on the RFID radio frequency signal.

[0065] In an exemplary embodiment, the number of instantaneous phases of the RFID radio frequency signal, that is, the number of categories into which the RFID radio frequency signal is divided, is obtained, and the number of categories is used as the interference status of the RFID radio frequency signal. The greater the number of categories, the less interference the data after the RFID radio frequency signal is decomposed is subjected to.

[0066] Accordingly, the signal quality of the RFID radio frequency signal is obtained based on the maximum category signal quality index, the instantaneous phase fluctuation degree, and the number of categories of the RFID radio frequency signal. Among them, the larger the maximum category signal quality index, the higher the signal quality; the more categories there are, the less interference the signal receives and the higher the signal quality; the smaller the instantaneous phase fluctuation degree, the higher the signal quality. Therefore, the signal quality is positively correlated with the maximum category signal quality index and the number of categories, and negatively correlated with the instantaneous phase fluctuation degree. In an exemplary embodiment, first, the instantaneous phase fluctuation degree and the number of categories of the RFID radio frequency signal are normalized respectively, wherein the maximum and minimum normalization method is adopted. Specifically: the maximum and minimum values ​​of the instantaneous phase fluctuation degrees of all RFID radio frequency signals are obtained, and then the maximum and minimum normalization method is adopted to normalize the instantaneous phase fluctuation degree of the RFID radio frequency signal; the maximum and minimum values ​​of the number of categories of all RFID radio frequency signals are obtained, and then the maximum and minimum normalization method is adopted to normalize the number of categories of the RFID radio frequency signal. Accordingly, a specific quantification method of the signal quality of the RFID radio frequency signal is:

[0067] ;

[0068] in, Indicates the signal quality of the RFID radio frequency signal. Indicates the number of normalized categories of the RFID radio frequency signal, Indicates the normalized instantaneous phase fluctuation of the RFID radio frequency signal. Indicates the maximum signal quality index of the RFID radio frequency signal.

[0069] Using the above method, the signal quality of the RFID radio frequency signals received by each RFID receiver in each direction at the current moment is obtained. For any candidate location point, the multiple RFID radio frequency signals that constitute the candidate location point are determined. Then, based on the signal quality of the multiple RFID radio frequency signals that constitute the candidate location point, a candidate index for the candidate location point is obtained. In one exemplary embodiment, the average signal quality of the RFID radio frequency signals that constitute the candidate location point is calculated and used as the candidate index for the candidate location point. This results in a candidate index for each candidate location point.

[0070] Step S3: Determine the position of the positioning target based on the candidate index of each positioning candidate point.

[0071] The higher the candidate index is, the higher the possibility that the corresponding positioning candidate point belongs to the position of the positioning target is. Therefore, in an exemplary embodiment, the position of the positioning candidate point corresponding to the largest candidate index is used as the position of the positioning target.

[0072] It should be understood that there are certain limitations in directly using the position of the positioning candidate point corresponding to the largest candidate index as the position of the positioning target. The position of the positioning candidate point corresponding to the largest candidate index is not necessarily the most accurate position at the current moment and may have a certain deviation. It is necessary to conduct a comprehensive analysis based on the actual situation of other positioning candidate points around each positioning candidate point to improve the accuracy of the positioning target position confirmation. Accordingly, in order to further improve the accuracy and reliability of the positioning target position confirmation, such as Figure 3 As shown, a specific confirmation process of the position of the positioning target is given as follows:

[0073] Step S31: obtaining the number of neighboring candidate positioning points of the candidate positioning point and the degree of fluctuation of the candidate index of the neighboring candidate positioning points.

[0074] For ease of explanation, the candidate positioning point is set to be any positioning point. The preset neighborhood range of the candidate positioning point is determined, and the preset neighborhood range of the candidate positioning point is set according to actual needs. As several examples: since the space to be positioned is a three-dimensional space, the candidate positioning point can be used as the center of the sphere and the preset radius as the radius of the sphere to make a sphere. The spherical range is the preset neighborhood range of the candidate positioning point, wherein the preset radius is determined by the actual application scenario; as another embodiment, the three-dimensional space is divided into a plurality of cubic blocks. According to the volume size of the cubic blocks, the area of ​​the cubic block where the candidate positioning point is located can be directly used as the preset neighborhood range of the candidate positioning point, or the area of ​​the cubic block where the candidate positioning point is located and other cubic blocks adjacent to the cubic block where the candidate positioning point is located can be used as the preset neighborhood range of the candidate positioning point.

[0075] In addition to the candidate positioning candidate point, other positioning candidate points existing in a preset neighborhood range of the candidate positioning candidate point are obtained. These other positioning candidate points are defined as neighborhood positioning candidate points of the candidate positioning candidate point.

[0076] The number of neighboring positioning candidate points of the candidate positioning candidate point and the degree of fluctuation of the candidate index of the neighboring positioning candidate points are obtained. The candidate index of each neighboring positioning candidate point of the candidate positioning candidate point is obtained, and then the variance of the candidate index of the neighboring positioning candidate points of the candidate positioning candidate point is calculated, and the variance is used as the degree of fluctuation of the candidate index of the neighboring positioning candidate point.

[0077] Step S32: Obtain the position stability of the candidate positioning point according to the number of neighboring candidate positioning points of the candidate positioning point and the fluctuation degree of the candidate index.

[0078] The more the number of neighborhood positioning candidate points of a candidate positioning candidate point, the higher the reliability of the position of the candidate positioning candidate point, the more accurate the position acquisition of the candidate positioning candidate point, and the higher the position stability of the candidate positioning candidate point; the larger the variance of the candidate index of each neighborhood positioning candidate point of the candidate positioning candidate point, the higher the degree of fluctuation of the candidate index, the lower the reliability of the position of the candidate positioning candidate point, the less accurate the position acquisition of the candidate positioning candidate point, and the lower the position stability of the candidate positioning candidate point. Therefore, the position stability of the candidate positioning candidate point is positively correlated with the number of neighborhood positioning candidate points and negatively correlated with the degree of fluctuation of the candidate index. In an exemplary embodiment, the number of neighborhood positioning candidate points of the candidate positioning candidate point is first normalized, and the maximum and minimum normalization method is adopted here. Specifically: the maximum and minimum values ​​of the number of neighborhood positioning candidate points of each positioning candidate point are obtained, and then the maximum and minimum normalization method is adopted to normalize the number of neighborhood positioning candidate points of the candidate positioning candidate point. A specific quantification method for position stability is given below:

[0079] ;

[0080] in, Indicates the The position stability of each candidate positioning point, Indicates the The number of neighborhood positioning candidate points after normalization of the positioning candidate points, Indicates the The fluctuation degree of candidate indicators of each positioning candidate point.

[0081] Step S33: obtaining the final position probability of the candidate positioning point at least according to the position stability degree and the candidate index of the candidate positioning point.

[0082] In an exemplary embodiment, the final position probability of the candidate positioning candidate point can be obtained only based on the position stability and candidate index of the candidate positioning candidate point. Among them, the higher the position stability of the candidate positioning candidate point, the higher the possibility that the candidate positioning candidate point belongs to the position of the positioning target, that is, the higher the final position probability of the candidate positioning candidate point; the higher the candidate index of the candidate positioning candidate point, the higher the possibility that the candidate positioning candidate point belongs to the position of the positioning target, that is, the higher the final position probability of the candidate positioning candidate point. Therefore, the final position probability is positively correlated with both the position stability and the candidate index. Specifically, a specific quantification method of the final position probability is given as follows:

[0083] ;

[0084] in, Indicates the The final position probability of the candidate positioning points, Indicates the The candidate indicators of the candidate positioning points.

[0085] As a more optimal implementation method, in order to further improve the reliability of obtaining the final position probability, the local reachable density of the candidate positioning candidate point in space is also added to the acquisition of the final position probability of the candidate positioning candidate point. Accordingly, the final position probability of the candidate positioning candidate point is obtained based on the position stability of the candidate positioning candidate point, the candidate index and the local reachable density of the candidate positioning candidate point in space.

[0086] The local reachability density (LRD) of a point in space is a core concept of the local outlier factor (LOF) algorithm, used to quantify the density distribution within a given point's neighborhood. The calculation method for the local reachability density of a point in space is well-known and will not be further explained.

[0087] The higher the local reachability density of the candidate positioning point in space, the more uniform the distribution of the positioning points in the candidate positioning point's neighborhood, the better the regularity, and the higher the probability that the candidate positioning point belongs to the location of the positioning target, that is, the higher the final location probability of the candidate positioning point. Therefore, the final location probability is positively correlated with the location stability, candidate index, and local reachability density. Specifically, a specific quantitative method for the final location probability is given as follows:

[0088] ;

[0089] in, Indicates the The local reachability density of candidate positioning points is Represents an exponential function with a natural constant as its base.

[0090] Step S34: Determine the maximum final position probability, and use the position of the positioning candidate point corresponding to the maximum final position probability as the position of the positioning target.

[0091] Step S33 obtains the final location probability of each candidate location point. The higher the final location probability, the more likely it is to be the location of the positioning target. Therefore, the maximum final location probability is obtained from the final location probabilities of each candidate location point. The location of the candidate location point with the maximum final location probability is used as the location of the positioning target, that is, the location of the RFID tag in space.

[0092] This embodiment also provides a multi-directional RFID tag identification system, including: a memory and a processor; the memory is connected to the processor, and the memory is used to store program instructions; the processor is used to implement the steps in the above-mentioned multi-directional RFID tag identification method embodiment when the program instructions are executed.

[0093] In an exemplary embodiment, the present invention provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps in the above-mentioned multi-directional RFID tag identification method embodiment.

[0094] It should be noted that the order in which the embodiments of the present invention are described above is for illustrative purposes only and does not necessarily represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0095] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

Claims

1. A multi-directional RFID tag identification method, characterized in that: include: Determine a candidate positioning point based on the RFID radio frequency signals received by each RFID receiver in each direction, where the candidate positioning point is a signal intersection point formed by the intersection of each RFID radio frequency signal; The signal quality of each RFID radio frequency signal constituting the candidate positioning point is integrated to obtain a candidate index of the candidate positioning point; the signal quality is obtained by integrating signal quality sub-indicators, and the signal quality sub-indicators include signal stability, signal superposition, and signal interference represented by each component, and the each component is obtained by multi-component decomposition of the RFID radio frequency signal; Determine the position of the positioning target based on the candidate indicators of each positioning candidate point; The multi-component decomposition of the RFID radio frequency signal is specifically as follows: performing EMD empirical mode decomposition on the RFID radio frequency signal to obtain multiple IMF components; and performing Hilbert transform on each IMF component to obtain the instantaneous frequency, instantaneous amplitude and instantaneous phase of each IMF component at each moment; The process of obtaining the signal stability includes: obtaining the signal strength of each IMF component at each moment based on the instantaneous frequency and instantaneous amplitude of each IMF component at each moment; dividing the signal strength of the same instantaneous phase into one category to obtain multiple categories; obtaining a category signal quality index of each category based on the overall level of signal strength and the degree of signal strength fluctuation in each category; the category signal quality index is positively correlated with the overall level of signal strength and negatively correlated with the degree of signal strength fluctuation; determining the maximum category signal quality index among the category signal quality indicators of each category, and the signal stability is specifically the maximum category signal quality index; The acquisition process of the signal superposition condition includes: obtaining the instantaneous phase fluctuation degree according to the instantaneous phase corresponding to each category, wherein the signal superposition condition is specifically the instantaneous phase fluctuation degree; the signal interference condition is the number of categories; The signal quality is obtained by the maximum category signal quality index, the instantaneous phase fluctuation degree, and the number of categories; the signal quality is positively correlated with the maximum category signal quality index and the number of categories, and is negatively correlated with the instantaneous phase fluctuation degree; The process of obtaining the candidate index of the candidate positioning point includes: calculating the average value of the signal quality of each RFID radio frequency signal constituting the candidate positioning point to obtain the candidate index of the candidate positioning point.

2. A multi-directional RFID tag identification method as claimed in claim 1, characterized in that: The determining the position of the positioning target based on the candidate index of each positioning candidate point includes: Obtaining the number of neighboring candidate positioning points of the candidate positioning point and the degree of fluctuation of the candidate index of the neighboring candidate positioning points; the neighboring candidate positioning points are other candidate positioning points within a preset neighborhood of the candidate positioning point; the candidate positioning point is any candidate positioning point; Obtaining the position stability of the candidate positioning point according to the number of neighboring candidate positioning points of the candidate positioning point and the fluctuation degree of the candidate index; Obtaining a final position probability of the candidate positioning point based at least on the position stability and candidate index of the candidate positioning point; wherein the final position probability is positively correlated with both the position stability and the candidate index; The maximum final position probability is determined, and the position of the positioning candidate point corresponding to the maximum final position probability is used as the position of the positioning target.

3. A multi-directional RFID tag identification method as claimed in claim 2, characterized in that: The obtaining, at least based on the position stability and candidate index of the candidate positioning candidate point, a final position probability of the candidate positioning candidate point includes: According to the position stability of the candidate positioning candidate point, the candidate index and the local reachability density of the candidate positioning candidate point in space, the final position probability of the candidate positioning candidate point is obtained; the final position probability is positively correlated with the local reachability density.

4. The multi-directional RFID tag identification method according to claim 1, wherein: The determining the position of the positioning target based on the candidate indexes of the positioning candidate points includes: taking the position of the positioning candidate point corresponding to the largest candidate index as the position of the positioning target.

5. A multi-directional RFID tag identification system, characterized by comprising: Memory and processor; The memory is connected to the processor; The memory is used to store program instructions; The processor is configured to implement the multi-directional RFID tag identification method according to any one of claims 1 to 4 when the program instructions are executed.

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