Positioning method and device, electronic equipment, storage medium and computer program product

Abstract

The invention provides a positioning method and device, electronic equipment, a storage medium and a computer program product, and relates to the technical field of positioning, and the method comprises the steps: obtaining corresponding first response data when a positioning tag group responds to a target object; determining the current location of the target object based on the similarity between the first response data and corresponding preset response data in the data set; wherein the preset response data corresponding to the plurality of positioning label groups in the data set are used for representing the data when the corresponding positioning label groups respond to the sample objects. According to the scheme in the embodiment of the invention, the pre-preparation workload of RFID positioning can be reduced, so that the RFID positioning can be applied to a pipe gallery scene, and the rapid positioning of the target object in the pipe gallery scene can be realized.

Description

Technical Field

[0001] The present application relates to the field of positioning technology, and in particular to a positioning method, device, electronic device, storage medium and computer program product. Background Art

[0002] The urban integrated pipe gallery refers to a tunnel space built underground in the city, which integrates various engineering pipelines such as electricity, communications, and water supply. It is an important infrastructure and "lifeline" to ensure the operation of the city. When inspectors carry out work in the pipe gallery, their personal safety is of vital importance. In order to ensure life safety, the whole pipe gallery monitoring, fixed telephones and other devices are installed and deployed on a large scale, but these facilities cannot realize the specific positioning analysis of personnel. In the relevant technology, positioning technology can be divided into outdoor positioning and indoor positioning. Outdoor positioning mainly relies on satellite positioning and base station positioning. Pipe gallery positioning belongs to indoor positioning. Indoor positioning technology mainly includes infrared positioning, WiFi positioning, Bluetooth positioning, ultra-wide band (UWB) positioning, ZigBee positioning and radio frequency identification technology (RFID) positioning. For indoor scenes of pipe gallery, RFID positioning is the most suitable. However, in the process of RFID positioning, most of them rely on the prior information of the reference tag to complete the distance calculation of the target tag. For long-distance scenes such as pipe gallery, a lot of work is required to measure the tags, resulting in a large amount of preparatory work for RFID positioning, which is difficult to apply in pipe gallery scenes. Summary of the invention

[0003] A positioning method, device, electronic device, storage medium and computer program product provided in the embodiments of the present application can reduce the amount of pre-preparation work for RFID positioning, so that RFID positioning can be applied in pipe gallery scenarios.

[0004] The technical solution of this application is implemented as follows:

[0005] The present application provides a positioning method, including:

[0006] Get the first response data corresponding to the positioning tag group responding to the target object;

[0007] Based on the similarity between the first response data and the corresponding preset response data in the data set, the current location of the target object is determined; wherein the preset response data corresponding to the multiple positioning tag groups in the data set are used to characterize the data when the corresponding positioning tag group responds to the sample object.

[0008] In the above scheme, the method further comprises:

[0009] Acquire second response data when the plurality of positioning tag groups respectively respond to the sample object;

[0010] Determine a target weight group corresponding to each positioning tag group based on the second response data corresponding to each positioning tag group and a preset weight group; wherein the weights in the target weight group and the second response data corresponding to the sample object meet the fitting condition; and the weights in the target weight group correspond one-to-one to the tags in the positioning tag group;

[0011] Determine the preset response data corresponding to each positioning tag group based on the target weight group and the second response data corresponding to each positioning tag group;

[0012] The data set is constructed based on the correspondence between the plurality of positioning tag groups and the respectively corresponding preset response data.

[0013] In the above solution, the step of determining the preset response data corresponding to each positioning tag group based on the target weight group and the second response data corresponding to each positioning tag group includes:

[0014] For each of the plurality of first response sub-data in the second response data, M first data values ​​are intercepted; wherein M is an integer greater than 1; the first response sub-data in the second response data corresponds one-to-one to the corresponding tag in the positioning tag group;

[0015] The preset response data corresponding to each positioning tag group is determined based on the product of the target weight group and the M groups of the first data values ​​respectively corresponding to each other; wherein the first data values ​​in each group of the first data values ​​respectively belong to the corresponding first response sub-data.

[0016] In the above solution, the obtaining of the first response data respectively corresponding to the positioning tag group responding to the target object includes:

[0017] When the distance between the target object and the current area meets a preset condition, acquiring the first response data when the positioning tag groups in the current area respectively respond to the target object;

[0018] Among them, the current area belongs to multiple areas in the path to be measured; N antennas are arranged at intervals in each of the areas; the signal range of each antenna covers K groups of positioning tags arranged at intervals; N is an integer greater than 0; K is an integer greater than 0.

[0019] In the above solution, determining the current location of the target object based on the similarity between the first response data and the corresponding preset response data in the data set includes:

[0020] Determine, based on the third response data determined by the first response data and having the same dimension as the preset response data, a similarity between the first response data and the corresponding preset response data;

[0021] The current location is determined based on the plurality of similarities and the preset locations corresponding to the plurality of positioning tag groups.

[0022] In the above solution, the third response data determined based on the first response data and having the same dimension as the preset response data, determining the similarity between the first response data and the corresponding preset response data includes:

[0023] M second data values ​​are intercepted from each of the plurality of second response sub-data in the first response data; wherein the plurality of the second response sub-data in the first response data correspond one-to-one to the tags in the positioning tag group;

[0024] Determine corresponding third response data based on the product of the target weight group corresponding to the first response data and the M groups of the second data values ​​respectively corresponding to each other; wherein the second data values ​​in each group of the second data values ​​respectively belong to the corresponding second response sub-data;

[0025] Based on the third response data and the preset response data corresponding to each of the first response data, the corresponding similarity is determined.

[0026] In the above solution, the current location is determined based on the plurality of similarities and the preset locations corresponding to the plurality of positioning tag groups, including:

[0027] Determine a target similarity among the plurality of similarities that is greater than a preset threshold;

[0028] The current location is determined based on the preset position corresponding to the location tag group corresponding to the target similarity.

[0029] In the above scheme, the positioning tag group includes: T tags; T tags are divided into P groups; T is an integer greater than 1; P is greater than 1; the method further includes:

[0030] If it is detected that the second response sub-data corresponding to the abnormal label is missing in any of the first response data, the weight corresponding to the abnormal label in the corresponding target weight group is added to the maximum weight corresponding to the label in the group to which the abnormal label belongs.

[0031] In the above scheme, the method further includes:

[0032] Based on the identifier of the positioning tag group corresponding to the current positioning, the positioning information of the target object is displayed.

[0033] In the above scheme, the method further includes:

[0034] Performing detection on the displayed positioning information according to the preset number of identifications to determine the detection result;

[0035] If the detection result indicates that the current positioning corresponding to the O positioning tag groups is abnormal, a secondary analysis is performed on the first response data corresponding to the O positioning tag groups respectively, and the identifiers corresponding to the O positioning tag groups in the positioning information are updated; wherein O is an integer greater than 1.

[0036] In the above solution, the second analysis is performed on the first response data respectively corresponding to the O positioning tag groups, and the identifiers corresponding to the O positioning tag groups in the positioning information are updated, including:

[0037] Determine the middle third response sub-data with the largest degree of dispersion among the plurality of third response sub-data in the first response data corresponding to the O positioning tag groups respectively;

[0038] Determine the target third response sub-data with the largest degree of dispersion among the O intermediate third response sub-data;

[0039] Based on the identifier of the positioning tag group to which the target third response sub-data belongs, the identifiers corresponding to the O positioning tag groups in the positioning information are updated.

[0040] The present application also provides a positioning device, including:

[0041] A data acquisition unit, used to acquire first response data corresponding to when the positioning tag group responds to the target object;

[0042] A positioning unit is used to determine the current positioning of the target object based on the similarity between the first response data and the corresponding preset response data in the data set; wherein the preset response data corresponding to the multiple positioning tag groups in the data set are used to characterize the data when the corresponding positioning tag group responds to the sample object.

[0043] An embodiment of the present application further provides an electronic device, including a memory and a processor, wherein the memory stores a computer program that can be run on the processor, and the processor implements the steps in the above method when executing the computer program.

[0044] An embodiment of the present application further provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps in the above method are implemented.

[0045] An embodiment of the present application also provides a computer program product, including a computer program, which implements the steps in the above method when executed by a processor.

[0046] In the embodiment of the present application, the first response data corresponding to the positioning tag group responding to the target object is obtained; based on the similarity between the first response data and the corresponding preset response data in the data set, the current location of the target object is determined; wherein the preset response data corresponding to the multiple positioning tag groups in the data set are used to characterize the data when the corresponding positioning tag group responds to the sample object. In this way, the current positioning scheme is determined based on the comparison between the obtained first response data and the preset response data, without relying on the prior information of the reference tag, which can reduce the amount of preparatory work for RFID positioning, so that RFID positioning can be applied in the pipe corridor scene, and then the rapid positioning of the target object in the pipe corridor scene can be achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 An optional flowchart of a positioning method provided in an embodiment of the present application;

[0048] Figure 2 A schematic diagram of an optional effect of the positioning method provided in an embodiment of the present application;

[0049] Figure 3 A schematic diagram of an optional effect of the positioning method provided in an embodiment of the present application;

[0050] Figure 4 A schematic diagram of an optional effect of the positioning method provided in an embodiment of the present application;

[0051] Figure 5 A schematic diagram of an optional effect of the positioning method provided in an embodiment of the present application;

[0052] Figure 6 An optional flowchart of a positioning method provided in an embodiment of the present application;

[0053] Figure 7 A schematic diagram of an optional effect of the positioning method provided in an embodiment of the present application;

[0054] Figure 8 An optional flowchart of a positioning method provided in an embodiment of the present application;

[0055] Fig. 9 An optional flowchart of a positioning method provided in an embodiment of the present application;

[0056] Fig.10 An optional flowchart of a positioning method provided in an embodiment of the present application;

[0057] Fig.11 An optional flowchart of a positioning method provided in an embodiment of the present application;

[0058] Fig.12 A schematic diagram of an optional effect of the positioning method provided in an embodiment of the present application;

[0059] Fig.13 An optional flowchart of a positioning method provided in an embodiment of the present application;

[0060] Fig.14 An optional flowchart of a positioning method provided in an embodiment of the present application;

[0061] Fig.15 A schematic diagram of an optional effect of the positioning method provided in an embodiment of the present application;

[0062] Fig.16 A schematic diagram of the structure of a positioning device provided in an embodiment of the present application;

[0063] Fig.17 A hardware entity schematic diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0064] In order to make the purpose, technical solutions and advantages of the present application clearer, the technical solutions of the present application are further elaborated in detail below in conjunction with the drawings and embodiments. The described embodiments should not be regarded as limiting the present application. All other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present application.

[0065] In the following description, reference is made to “some embodiments”, which describe a subset of all possible embodiments, but it will be understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0066] If similar descriptions of "first / second" appear in the application documents, the following instructions are added. In the following description, the terms "first\second\third" involved are merely used to distinguish similar objects and do not represent a specific ordering of the objects. It can be understood that "first\second\third" can be interchanged in a specific order or sequence where permitted, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein.

[0067] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

[0068] In the related technologies, positioning technology can be divided into outdoor positioning and indoor positioning. Outdoor positioning mainly relies on satellite positioning and base station positioning. Pipeline corridor positioning belongs to indoor positioning. Indoor positioning technologies mainly include infrared positioning, WiFi positioning, Bluetooth positioning, UWB positioning, ZigBee positioning and RFID positioning. Infrared positioning technology uses infrared rays to determine the position of objects. Due to the long wavelength, low frequency and poor penetration of infrared rays, direct irradiation is usually required to effectively transmit information. It is also easily affected by factors such as occlusion and interference, and its use scenarios are limited. WiFi positioning technology has been widely used in indoor navigation in large scenes such as airports, hotels, exhibitions and basements. However, since the WiFi positioning accuracy is usually at the meter level and is limited by the coverage of WiFi signals, it is not suitable for application scenarios with higher precision requirements. Bluetooth positioning technology installs Bluetooth transmitters on objects to implement precise positioning, but due to the small range of Bluetooth positioning, large errors and easy interference from the environment, its use scenarios are limited. ZigBee positioning technology is a short-range wireless communication technology. The system achieves positioning by deploying sensor nodes and needs to consider factors such as network topology, node layout, and channel selection. Therefore, its cost is relatively high. In addition, its positioning accuracy is also affected by multipath in indoor environments. RFID positioning technology attaches tags to objects to identify target objects. The RFID reader reads the wireless signal through backscattering, and obtains information such as RSSI and phase of the wireless signal to determine the location of the target object. In addition, RFID positioning technology has the following advantages: (1) High accuracy: RFID can achieve centimeter-level positioning accuracy, which is more accurate than some traditional positioning technologies. (2) Non-line-of-sight communication: RFID positioning technology does not require a line of sight between the tag and the reader, and can be positioned in the presence of obstacles, walls, and other obstructions. (3) Strong anti-interference: RFID readers are not interfered with by other wireless devices and can obtain tag information in complex electromagnetic environments. (4) High security: RFID uses digital communication and the tag data is encrypted with a password, which has high security. (5) Low cost: Each RFID tag costs only a few cents and can be deployed on a large scale. In summary, RFID positioning technology has the advantages of high precision, non-line-of-sight communication, strong anti-interference, high security and low cost in indoor positioning, and has good application prospects.

[0069] With the rapid development of Internet of Things technology, the demand for accurate location information of sensing devices is also growing. Radio Frequency Identification (RFID), as one of the short-range communication technologies of the Internet of Things, has been widely used in the field of indoor positioning due to its advantages of low cost, non-contact and high precision. In the pipeline corridor scenario, it is usually necessary to obtain the time series data of combustible gas concentration and wind speed, record the coordinates of the leakage source, the coordinates of the sensor, the start time of gas leakage and the leakage direction, and establish a deep learning prediction model to achieve rapid prediction and positioning of the leakage situation. The ship personnel cabin positioning scheme based on RFID and inertial technology first determines the distribution of the received signal strength indication (RSSI) value according to the Gaussian function to filter the data, uses the linear regression method to establish the RSSI value and the equation group to obtain the optimal value, and uses a group of weighted centroid positioning methods to make full use of anchor nodes to reduce the influence of distance on the positioning result; at the same time, the sliding window average preprocessed data is combined with the multi-threshold constraint to perform the inertial positioning mode of gait monitoring, and the fusion positioning scheme of RFID and inertial positioning is established. The RSSI-based RFID indoor positioning algorithm uses the received signal strength RSSI measured by the reader as the input of the RBF neural network. In three-dimensional space, the reference tags are placed on the top and side of the space. The distance from the tag to the reader is obtained according to the RSSI value received by the reader. Then, space segmentation is performed to preliminarily determine the area where the tag to be located is located. Finally, the IHHO algorithm is used to calculate the optimal value of the objective function as the final estimated position.

[0070] In the study of indoor positioning, RFID-based solutions have been widely used in the field of indoor positioning due to their advantages of low cost, non-contact and high precision. Infrared technology has high positioning accuracy, but the path of infrared transmission is easily affected by obstacles, which will prevent the infrared signal from reaching the optical sensor, so it can only be transmitted under line-of-sight conditions and the transmission distance is short. In addition, infrared is also easily affected by environmental factors such as smoke and lights, and has poor anti-interference ability. Therefore, infrared technology is currently only suitable for positioning within a small area, and it is not feasible to deploy infrared sensors over a large area in long-distance pipe corridors. Although Bluetooth technology has the characteristics of low power consumption and strong scalability, transmission and reception are still affected by multipath interference, and the positioning accuracy is heavily dependent on the deployment density and location of Bluetooth beacons. UWB positioning technology has the advantages of strong anti-interference, short delay, and high positioning accuracy, but the deployment cost is high and the energy consumption is large. The above article introduces several RFID-based indoor positioning solutions, which are basically based on the tag features (RSSI, phase and other information) read by the RFID reader to achieve positioning. Most of their positioning relies on the prior information of the reference tag and then completes the distance calculation of the target tag. For long-distance scenarios such as pipe corridors, a large amount of work is required to measure the tags, which poses high challenges to construction costs and construction progress, resulting in the existing RFID positioning solutions being unsuitable for pipe corridor scenarios.

[0071] In the embodiments of the present application, the main purpose is to solve the problem of positioning the inspection personnel in the tunnel. The tunnel cannot receive satellite signals, so only indoor positioning can be used. Since the tunnel is interconnected and the total length exceeds 100 kilometers, on the one hand, the accuracy of positioning must be guaranteed, and on the other hand, the deployment cost must also be taken into account. This proposal proposes an RFID-based tunnel positioning solution that can achieve meter-level positioning at the positioning tag group level. Among them, the positioning method can be applied to the positioning device for managing the tunnel, which may include: a background terminal of multiple positioning tag groups, or a server, a cloud server, etc.

[0072] This application embodiment provides a positioning method, see Figure 1 , is an optional flow chart of the positioning method provided in the embodiment of the present application, which will be combined with Figure 1 The steps shown are explained:

[0073] S101: Acquire first response data corresponding to a positioning tag group responding to a target object.

[0074] In the embodiment of the present application, for each of the multiple areas in the path to be measured, a certain number of positioning tag groups are arranged at intervals. The positioning device can obtain the first response data of each positioning tag group in each area in real time. In some embodiments, when the target object appears in the path to be measured, the positioning device can only obtain the first response data of each positioning tag group in the current area where the target object is located.

[0075] The path to be measured may be a pipe gallery or other path that can be used to locate the target object. The target object may be a person, a car, an animal or other entity with mobile characteristics. The first response data may include the following corresponding to the positioning tag group: the number of times the tag group is read, the electronic product code (EPC) ID (Identity document) of the tag in the tag group, the antenna number, RSSI, frequency, phase (starting phase, ending phase), timestamp, etc.

[0076] For example, one RFID reader can be set up in one area, and one reader can be connected to multiple antennas. A certain number of positioning tag groups are arranged at intervals within the signal coverage range of each antenna. In order to reduce the difficulty of construction, combined with Figure 2 , the reader 200 is connected to 4 antennas, and the antennas are installed in such a way that antennas 1 and 2 face the same direction, and antennas 3 and 4 face another direction. Each antenna is responsible for 5 positioning tag groups. The tags in the positioning tag group are arranged as follows Figure 3 As shown, the positioning tag group includes 9 positioning tags arranged in a matrix. In other embodiments, the positioning tag group can also be constructed with other numbers of tags and other arrangements. On the one hand, this tag combination method can reduce the impact of multipath causing tag excitation failure and thus the inability to obtain tag features. On the other hand, it can enhance the ability to express external changes through combination and better reflect the characteristics of external changes. In order to make each reader and each antenna cover more tags, the positioning tag group can be deployed on the metal bracket of the pipe gallery. After a large number of experimental tests, when using a 9dB antenna, each antenna can cover a distance of about 13 meters while ensuring stable inventory of tags. Based on this data, it can be designed Figure 2 In the deployment scheme shown, each tag group is spaced 2 meters apart and each antenna covers a range of 10 meters. Figure 4, the reader 200 corresponding to each area is connected to a personal computer (PC) 100, that is, a positioning device, and each reader 200 is connected to an antenna 300 in the area. The antenna 300 can receive the first response data corresponding to the positioning tag group 400 through the electromagnetic field, and transmit the received first response data to the PC 100 through the reader 200. When the target object appears near the positioning tag group 400, the electromagnetic field between the positioning tag group 400 and the antenna 300 changes, so the first response data received by the antenna 300 will also change accordingly.

[0077] S102. Determine the current location of the target object based on the similarity between the first response data and the corresponding preset response data in the data set; wherein the preset response data corresponding to the plurality of positioning tag groups in the data set are used to represent the data when the corresponding positioning tag group responds to the sample object.

[0078] In an embodiment of the present application, the positioning device can pre-construct a data set. Among them, the data set includes the correspondence between multiple positioning tag groups and corresponding preset response data in the path to be measured. The preset response data is used to characterize the data of the corresponding positioning tag group when responding to the sample object. After the positioning device obtains the first response data, each first response data can be compared with the preset response data corresponding to the corresponding positioning tag group, and based on the similarity between the first response data and the corresponding preset response data, the current positioning is determined by the preset position corresponding to the positioning tag group corresponding to the most similar first response data and preset response data.

[0079] Among them, the preset response data may include: the number of readings of the tag group, the EPCID of the tags in the tag group, the antenna number, RSSI, frequency, phase (starting phase, ending phase), timestamp, etc., when the positioning tag group responds to the sample object. There are a variety of feature combinations for the positioning of the target object achieved with the above available data, such as relying only on the phase or only using RSSI strength information, or a combination of the two. More complex combinations can consider the number of readings within the time window, RSSI variance, phase variance, etc. In the application embodiment, the position of the target object is mainly determined based on the change of RSSI strength information. The preset response data may be the RSSI data when the positioning tag group responds to the sample object. The first response data may also be the RSSI data when the positioning tag group responds to the target object. The positioning device may determine the positioning tag group in which the target object is currently located based on the similarity between the two RSSI data, and then determine the current positioning of the target object.

[0080] In an embodiment of the present application, the positioning device can also determine the positioning tag group in which the target object is currently located based on the similarity between the graph formed by the RSSI data when the positioning tag group responds to the sample object and the graph formed by the RSSI data when the positioning tag group responds to the target object, and then determine the current positioning of the target object.

[0081] Exemplary, combined Figure 5 , because the distance of the corridor is long, each area covers a distance of about 40 meters, so for large-scale deployment of RFID positioning tag groups, the management of equipment is crucial. The corridor positioning system is used to manage large-scale RFID equipment. Through the system, all RFID devices in the system can be stably and reliably dispatched, including S nodes, antennas, tags, etc. To this end, we divide the system into four parts. The first level is the device layer, the second level is the preprocessing layer (constructing RSSI gallery), the third level is the positioning service, and the fourth level is the display layer. Among them, the device layer mainly completes the configuration of device ID, port, etc., and configures the IP addresses of all readers to the same subnet, so as to facilitate the aggregation of response data collected by all readers through MQTT broker. In addition, the information of reader devices, antenna numbers, positioning tag groups covered by each antenna, and tags in the positioning tag group (including preset positions and device identification) is organized into a database to facilitate unified management of devices and tags, avoid information confusion, and affect the accuracy of positioning. Preprocessing is mainly used to form a data set. The positioning service mainly uses the first response data of the user positioning tag group to respond to the target object to perform similarity matching in the data set to determine the current position. The display layer is used to display the position of the target object in the tunnel, so that the back-end security monitoring personnel can locate the position of the target object in time and provide quick rescue when a dangerous situation occurs.

[0082] In the embodiment of the present application, the first response data corresponding to each positioning tag group when responding to the target object is obtained; based on the similarity between the first response data and the corresponding preset response data in the data set, the current location of the target object is determined; wherein the preset response data corresponding to each of the multiple positioning tag groups in the data set is used to characterize the data when the corresponding positioning tag group responds to the sample object. In this way, the current positioning scheme is determined based on the comparison between the obtained first response data and the preset response data, without relying on the prior information of the reference tag, which can reduce the amount of preparatory work for RFID positioning, so that RFID positioning can be applied in the pipe corridor scene, and then the rapid positioning of the target object in the pipe corridor scene can be achieved.

[0083] See also Figure 6 , which is an optional flow chart of the positioning method provided in the embodiment of the present application, will be described in conjunction with the steps shown:

[0084] S201, obtaining second response data when a plurality of positioning tag groups respectively respond to a sample object.

[0085] In the embodiment of the present application, after the arrangement of each positioning tag group is completed in the path to be tested, the sample object can be arranged to pass through each positioning tag group. The positioning device can obtain the second response data when the sample object passes through the positioning tag group.

[0086] The sample object needs to be consistent with the type of the target object. The sample object may include people of different body types. For example, 20 people of different body types may be selected and asked to walk back and forth near the positioning tag group in the path to be measured. The positioning device obtains the RSSI data of all tags in the positioning tag group when walking.

[0087] In some other embodiments, after the arrangement of each positioning tag group is completed in the path to be tested, the positioning device can obtain the response data when the sample object does not pass through each positioning tag group. Exemplarily, constructing a data set means storing the RSSI data of all positioning tag groups in the quiet state and the positioning state into the data respectively. The quiet state is a stable state when no one passes by, and the positioning state is an RSSI oscillation state when someone passes by, corresponding to Figure 7 The two waveforms shown are Figure 7 It can be seen that there are obvious differences in the RSSI waveforms in the calm state and the positioning state.

[0088] S202. Determine a target weight group corresponding to each positioning tag group based on the second response data corresponding to each positioning tag group and a preset weight group; wherein the weights in the target weight group and the second response data corresponding to the sample object meet a fitting condition; and the weights in the target weight group correspond one-to-one to the tags in the positioning tag group.

[0089] In the embodiment of the present application, since the positioning tag group includes multiple positioning tags, the second response data includes the first response sub-data of each positioning tag in the corresponding positioning tag group. The positioning device can set a corresponding weight for each positioning tag, and then obtain a preset weight group. After obtaining the second response data when the positioning tag group responds to the sample object, the positioning device can build a fitting function based on the first response sub-data in each second response data and the corresponding preset weight group, and then build a fitting function for different sample objects to solve and determine the target weight group. Among them, the weights in the target weight group meet the fitting conditions with the second response data corresponding to the sample object; the weights in the target weight group correspond one-to-one to the tags in the positioning tag group.

[0090] For example, the tags can be arranged in a 3x3 matrix to form a positioning tag group A. There are 9 tags in tag group A, and the EPC tags are arranged in column priority. The weights contributed by each EPC tag in the preset weight group are

[0091] Timestamp alignment: sort the RSSI data (first response sub-data) of each tag in the second response data corresponding to the positioning tag group according to the timestamp, and take the RSSI data values ​​of the same sample object with the timestamp size to form a vector: (r1 r2 r3 r4 r5 r6 r7 r8 r9) T , where r is used to represent the RSSI data value extracted according to the timestamp size in the RSSI data of the corresponding tag, and T represents transposition. Dimension alignment: Since there may be cases where individual tags fail to be counted, we first fill in the RSSI data of the missing tags in the same sample object, so as to ensure that each batch of RSSI data is always 9. After the second response data is collected for 20 people, the start time and end time of the RSSI data fluctuation of each positioning tag group are recorded, and the number of RSSI values ​​in the positioning state interval is confirmed M; where M is an integer greater than 1. A fitting function can be established Among them, r i Represents the RSSI data value corresponding to the i-th tag. That is, the best RSSI curve fitting of the positioning state is solved when the target weight group responds to all sample objects.

[0092] S203: Determine the preset response data corresponding to each positioning tag group based on the target weight group and the second response data corresponding to each positioning tag group.

[0093] In the embodiment of the present application, after determining the target weight group corresponding to each positioning tag group, the positioning device can determine the preset response data corresponding to each positioning tag group based on multiplying the target weight group with the second response data of different sample objects corresponding to the positioning tag group.

[0094] In an embodiment of the present application, after determining the target weight group corresponding to each positioning tag group, the positioning device can multiply the target weight group with the numerical matrix of the first response sub-data extracted from the second response data corresponding to different sample objects, to determine a group of data corresponding to different sample objects for each positioning tag group, and then determine the corresponding preset response data based on the fusion of the group of data corresponding to different sample objects.

[0095] S204: construct the data set based on the correspondence between the plurality of positioning tag groups and the respectively corresponding preset response data.

[0096] In the embodiment of the present application, the positioning device constructs the data set based on the correspondence between multiple positioning tag groups and the respectively corresponding preset response data.

[0097] In the embodiment of the present application, the second response data of multiple positioning tag groups when they respond to the sample object respectively are obtained; based on the second response data corresponding to each positioning tag group and the preset weight group, the target weight group corresponding to each positioning tag group is determined; wherein, the weight in the target weight group and the second response data corresponding to the sample object meet the fitting condition; the weight in the target weight group corresponds to the label in the positioning tag group one by one; based on the second response data corresponding to the target weight group and each positioning tag group, the preset response data corresponding to each positioning tag group is determined; based on the correspondence between multiple positioning tag groups and the preset response data respectively corresponding, a data set is constructed. In this way, the preset response data of the positioning tag group in response to different sample objects can be predetermined, and when the target object appears in the current area, the first response data of each positioning tag group in the current area can be used to perform similarity matching with the preset response data, and then the positioning tag group with the largest similarity is determined as the positioning tag group closest to the target object, and then the current positioning of the target alignment can be accurately determined. In this process, there is no need to use the prior information of the tag, which can reduce the amount of preparatory work for RFID positioning, so that RFID positioning can be applied in the pipe gallery scene, and then the rapid positioning of the target object in the pipe gallery scene can be achieved.

[0098] See also Figure 8 , is an optional flow chart of a positioning method provided in an embodiment of the present application, Figure 6 The illustrated S203 may also be implemented through S301 to S302, which will be described in conjunction with the illustrated steps:

[0099] S301 . Extract M first data values ​​for each of the plurality of first response sub-data in the second response data; wherein the first response sub-data in the second response data correspond one-to-one to the tags in the corresponding positioning tag group.

[0100] In the embodiment of the present application, the first response sub-data in the second response data corresponds to the tags in the corresponding positioning tag group one by one. The positioning device can intercept M first data values ​​according to the timestamp for each first response sub-data.

[0101] Exemplarily, each first response sub-data in the second response data may be 1, 2, 3, 4, 5, 6, 7, 8, 9. The locating device may intercept 5 first data values ​​including 1, 3, 5, 7, 9 in each first response sub-data.

[0102] S302. Determine the preset response data corresponding to each positioning tag group based on the product of the target weight group and the M groups of the first data values; wherein the first data values ​​in each group of the first data values ​​belong to the corresponding first response sub-data.

[0103] In the embodiment of the present application, after determining the M first data values ​​corresponding to each first response sub-data, M groups of first data values ​​can be extracted in the order of the first data values ​​corresponding to each first response sub-data. Among them, one first data value in each group of first data values ​​belongs to the first response sub-data corresponding to a tag. The positioning device determines a group of data based on the product of the target weight group and each group of first data values, and then obtains M groups of data corresponding to a sample object, and determines the preset response data corresponding to the positioning tag group based on the fusion data of the M groups of data.

[0104] Exemplarily, 5 first data values ​​intercepted from each of the 9 first response sub-data may include 1, 3, 5, 7, and 9. 5 groups of first data values ​​may be extracted for the 5 first data values ​​intercepted from each of the first response sub-data, wherein the first group of first data values ​​may include: 1, 1, 1, 1, 1, 1, 1, 1. The target weight group is multiplied by the first group of first data values ​​to obtain a group of data.

[0105] In the embodiment of the present application, M first data values ​​are intercepted for the multiple first response sub-data in the second response data; wherein the first response sub-data in the second response data corresponds one-to-one to the label in the corresponding positioning label group; based on the product of the target weight group and the M groups of first data values ​​respectively corresponding to each other, the preset response data corresponding to each positioning label group is determined; wherein the first data value in each group of first data values ​​respectively belongs to the corresponding first response sub-data. In this way, by solving the optimal allocation weight for each label in the positioning label group in the manner of the positioning label group, each first response sub-data can be better fitted to adapt to the changes of different environments and different objects, and then the target weight group fitting different sample objects can be obtained. The preset response data determined by the target weight group can reflect the fluctuations of the positioning label group when responding to different sample objects, thereby obtaining a more accurate similarity comparison effect and improving the accuracy of the current positioning.

[0106] See also Fig. 9 , is an optional flow chart of a positioning method provided in an embodiment of the present application, Figure 1 S101 to S102 shown can also be implemented by S401 to S403, which will be described in conjunction with the steps shown:

[0107] S401: When the distance between the target object and the current area meets a preset condition, obtain the first response data when the positioning tag groups in the current area respond to the target object respectively.

[0108] In the embodiment of the present application, the current area belongs to multiple areas in the path to be measured; N antennas are arranged at intervals in each of the areas; the signal range of each antenna covers K positioning tag groups arranged at intervals; N is an integer greater than 0; K is an integer greater than 0. When the distance between the target object and the current area is less than the preset distance, the reader corresponding to the current area transmits the first response data of each positioning tag group obtained by the N antennas in the current area to the positioning device.

[0109] Among them, due to the large number of multiple areas, if the response data in all areas are simultaneously gathered to the positioning device, it will cause greater communication pressure on the MQTT server in the positioning device. In addition, more computing resources will be wasted during data analysis, resulting in low positioning efficiency. Therefore, a predetermined number of RFID tags (two tags) can be configured for the target object, and the number of inventory counts of the two tags can be counted by the reader in the current area through the sensing data transmitted by the antenna in the current area. When the number of inventory counts reaches a predetermined number, it can be determined that the distance between the target object and the current area meets the preset conditions. On this basis, the reader in the current area uploads the first response data of each positioning tag group in the corresponding area to the positioning device. At the same time, in order to ensure the low power operation of the system, the readers in other areas can also stop sending the corresponding response data. Only when the distance between the target object and a certain area meets the preset conditions, the reader in a certain area starts to send the corresponding response to the positioning owner to ensure the uninterrupted recovery of the response data.

[0110] S402: Determine the similarity between the first response data and the corresponding preset response data based on the third response data determined by the first response data and having the same dimension as the preset response data.

[0111] In the embodiment of the present application, the positioning device converts the first response data into third response data having the same dimension as the preset response data, and determines the corresponding similarity by calculating the cosine distance between the third response data and the corresponding preset response data.

[0112] S403: Determine the current location based on the plurality of similarities and the preset locations corresponding to the plurality of positioning tag groups.

[0113] In the embodiment of the present application, the positioning device can determine multiple similarities corresponding to multiple positioning tag groups in the current area. The positioning device can determine the target similarity greater than a preset threshold among the multiple similarities, and then determine the current location of the target object based on the preset position of the positioning table tag group corresponding to the target similarity.

[0114] In an embodiment of the present application, when the distance between the target object and the current area meets a preset condition, the first response data when the positioning tag group in the current area responds to the target object respectively is obtained. In this way, the number of response data processed by the positioning device can be effectively reduced, the amount of positioning calculation can be reduced, and the positioning rate can be improved. And the similarity between the first response data corresponding to each positioning tag group and the corresponding preset response data is determined, and then based on multiple similarities and preset positions corresponding to multiple positioning tag groups, it is determined that the current positioning scheme does not need to use the prior information of the tag, which can reduce the amount of preparatory work for RFID positioning, so that RFID positioning can be applied in the pipe corridor scene, and then the rapid positioning of the target object in the pipe corridor scene can be achieved.

[0115] See also Fig.10 , is an optional flow chart of a positioning method provided in an embodiment of the present application, Fig. 9 S402 to S403 shown can also be implemented through S501 to S405, which will be described in conjunction with the steps shown:

[0116] S501. Extract M second data values ​​from each of the plurality of second response sub-data in the first response data; wherein the second response sub-data in the first response data has a one-to-one correspondence with tags in the positioning tag group.

[0117] In the embodiment of the present application, the plurality of second response sub-data in each first response data corresponds one-to-one to the tags in the corresponding positioning tag group. The positioning device can intercept M second data values ​​according to the timestamp in each second response sub-data.

[0118] S502. Determine corresponding third response data based on the product of the target weight group corresponding to the first response data and M groups of the second data values ​​respectively corresponding to each other; wherein the second data values ​​in each group of the second data values ​​respectively belong to the corresponding second response sub-data.

[0119] In the embodiment of the present application, the positioning device groups the second data values ​​intercepted each time for each second response sub-data into a group to obtain M groups of second data values. The second data values ​​in each group of the second data values ​​belong to the corresponding second response sub-data. The positioning device can multiply the target weight group corresponding to the first response data with each group of the second data value to obtain M groups of data. The M groups of data are fused to determine the third response data corresponding to the positioning tag group.

[0120] Exemplarily, each first response data may be dimensionally aligned. If the RSSI of a certain EPC tag is missing in the first response data, it is filled with 0. Then, the RSSI value (second data value) window is set to M, and the RSSI second data value of length M is intercepted for each tag's RSSI data each time, thereby obtaining M groups of RSSI second data values. Finally, the target weight group corresponding to the positioning tag group is weighted and summed with each group of RSSI second data values ​​to obtain a new group of data, and then the M groups of newly obtained data are fused to obtain the third response data. Exemplarily, the new group of data rssi can be determined by formula (1): i .

[0121]

[0122] Among them, (w1 w2...w9) represents the target weight group, r represents the second data value of the corresponding label, i represents the i-th group of second data values, and i is not greater than M.

[0123] S503: Determine the corresponding similarity based on the third response data and the preset response data corresponding to each first response data.

[0124] In the embodiment of the present application, the positioning device can determine the cosine distance between the third response data corresponding to each first response data and the corresponding preset response data, and determine the similarity between each first response data and the corresponding preset response data.

[0125] In an embodiment of the present application, the similarity can also be determined for each group of data corresponding to the third response data and a group of data corresponding to the corresponding label in the preset response data, to obtain multiple similarities corresponding to multiple labels, and then the similarity between the first response data corresponding to the positioning label group and the preset response data can be determined based on the fusion of the similarities of the multiple labels.

[0126] S504: Determine a target similarity among the plurality of similarities that is greater than a preset threshold.

[0127] In the embodiment of the present application, after the similarity corresponding to each first response data is determined, a target similarity greater than a preset threshold may be determined from multiple similarities.

[0128] S505: Determine the current location based on the preset position corresponding to the positioning tag group corresponding to the target similarity.

[0129] In the embodiment of the present application, the positioning device can determine the current position of the target object based on the preset position corresponding to the positioning tag group corresponding to the target similarity.

[0130] Among them, the preset position of the target positioning tag group can be the positioning information set for the pipeline corridor, and can be exemplarily ** meters west of the * pipeline wellhead.

[0131] In an embodiment of the present application, the difference between the new M groups of RSSI data and the preset response data in the data set can be calculated, and the cosine similarity can be used to represent the similarity between the curves of the new M groups of RSSI data and a positioning tag group in the data set. When the similarity is higher than the preset threshold, it is determined that the target object has arrived near this tag group.

[0132] In the embodiment of the present application, M second data values ​​are respectively intercepted from the multiple second response sub-data in each first response data; wherein the second response sub-data in the first response data corresponds one-to-one to the label in the positioning label group; based on the product of the target weight group corresponding to the first response data and the M groups of second data values ​​respectively corresponding to each other, the corresponding third response data is determined; wherein the second data values ​​in each group of second data values ​​respectively belong to the corresponding second response sub-data; based on the third response data corresponding to each first response data and the preset response data, the corresponding similarity is determined. Through such calculation, the dimension of the determined third response data can be the same as that of the corresponding preset response data, and the scheme of determining the third response data determined by the target weight group can also make the determined third response data fit the characteristics of different sample objects, so that the similarity between the third response data and the preset response data is less affected, so the accuracy of the similarity is improved, and then the accuracy of positioning is improved.

[0133] See also Fig.11 , which is an optional flow chart of the positioning method provided in the embodiment of the present application, will be described in conjunction with the steps shown:

[0134] S601: If it is detected that the second response sub-data corresponding to the abnormal label is missing in any of the first response data, the weight corresponding to the abnormal label in the corresponding target weight group is added to the maximum weight corresponding to the label in the group to which the abnormal label belongs.

[0135] In the embodiment of the present application, the tags in each positioning tag group can be grouped. Each positioning tag group includes T tags; T tags are divided into P groups; T is an integer greater than 1; P is greater than 1. After obtaining the first response data, if it is detected that the second response sub-data corresponding to the abnormal tag in any of the first response data is missing, the weight corresponding to the abnormal tag in the corresponding target weight group is added to the maximum weight corresponding to the tag in the group to which the abnormal tag belongs.

[0136] Exemplary, combined Fig.12 , the 9 labels in the positioning label group are divided into 3 groups again, and arranged in a column-first manner. Each column in the label group matrix is ​​a subgroup, such as Fig.12 As shown, EPC1, EPC2, and EPC3 are divided into the first group, EPC4, EPC5, and EPC6 are divided into the second group, and EPC7, EPC8, and EPC9 are divided into the third group. When the RSSI data of the EPC1 code in the first group is missing, it has been filled with 0 to fill the gap. When RSSI = 0 is found, the weight corresponding to EPC1 in the target weight group is added to the tag with the larger weight in the first group. If the weights of other tags in the first group are the same, they are assigned to the next tag corresponding to EPC1.

[0137] In the embodiment of the present application, if it is detected that the second response sub-data corresponding to the abnormal label is missing in any first response data, the weight corresponding to the abnormal label in the corresponding target weight group is added to the maximum weight corresponding to the label in the group to which the abnormal label belongs. In this way, the similarity matching error caused by missing data can be effectively reduced, thereby improving the accuracy of positioning.

[0138] See also Fig.13 , which is an optional flow chart of the positioning method provided in the embodiment of the present application, will be described in conjunction with the steps shown:

[0139] S701: Display the positioning information of the target object based on the identifier of the positioning tag group corresponding to the current positioning.

[0140] In the embodiment of the present application, since the current location is determined based on the preset position corresponding to the location tag group corresponding to the target similarity, the location information of the target object can be displayed based on the identifier of the location tag group corresponding to the current location determined within a period of time.

[0141] Exemplarily, the movement trajectory of the target object in the tunnel may be displayed based on the tags of the positioning tag group corresponding to the current positioning determined within a period of time, in the form of antenna 1-tag 1, antenna 1-tag 2...antenna 4-tag 5.

[0142] In the embodiment of the present application, the positioning information of the target object is displayed based on the identification of the positioning tag group corresponding to the current positioning. In this way, the management personnel can know the real-time position of the target object more intuitively, and then quickly locate the target object when danger occurs, thereby increasing the chance of the target object being rescued.

[0143] See also Fig.14 , which is an optional flow chart of the positioning method provided in the embodiment of the present application, will be described in conjunction with the steps shown:

[0144] S801: Detect the displayed positioning information according to the preset identification number to determine the detection result.

[0145] In the embodiment of the present application, since the positioning information is formed based on the identifiers of the positioning tag group corresponding to the current positioning within a period of time, the positioning information can be a continuous identifier. The positioning device can detect the continuous identifiers according to the preset identifier number and determine the detection result. The detection result is used to characterize whether there is an abnormality in the identifier within the preset identifier number.

[0146] For example, the continuous identification displayed can be reviewed with a window size of 6 positions to further eliminate the influence of misjudgment of positioning. The window size of 6 is based on the consideration that each antenna covers 5 tags, and 6 positions can ensure that they span two antennas.

[0147] S802: If the detection result indicates that O identifiers are abnormal, perform a secondary analysis on the first response data corresponding to the O positioning tag groups, and update the identifiers corresponding to the O candidate positioning tag groups in the positioning information.

[0148] In the embodiment of the present application, if the detection result indicates that O identifications are abnormal, the middle third response sub-data with the largest degree of discreteness among the plurality of third response sub-data in the first response data corresponding to the positioning tag groups of the O identifications are determined. The target third response sub-data with the largest degree of discreteness is determined among the O middle third response sub-data. Based on the identification of the positioning tag group to which the target third response sub-data belongs, the identifications corresponding to the O positioning tag groups in the positioning information are updated. Wherein O is an integer greater than 1

[0149] The O identification anomalies may be repeated appearance of several adjacent identifications among the O identifications.

[0150] Exemplarily, the positioning device can check whether the order of antennas and tags in the window is continuous. If there is a situation of crossing tags, observe whether the tag group after the crossing position is stable. If it is stable, continue to execute. If the data in the window shows normal left and right changes, it may be due to the inspector walking back and forth, or it may be due to positioning disorder caused by factors such as occlusion and multipath. Then, the RSSI value of the tag group area with left and right position jumps is extracted from the memory, and then a secondary analysis is performed. The secondary analysis is used to make up for the shortcomings of the tag group, so a new analysis method is needed.

[0151] When the response data corresponding to most of the tags in the positioning tag group is missing, the RSSI characteristics of the tag group are represented by only a few tags, which weakens the ability of the tag group to reflect external changes, resulting in unstable positioning. In order to solve this problem, a secondary analysis can be performed on the first response data of the positioning tag group corresponding to the repeated O identifiers. The secondary analysis process is as follows: Fig.15 As shown, the identifications of positioning tag group 1, positioning tag group 2, and positioning tag 3 appear repeatedly. The corresponding variance (used to characterize the degree of discreteness) is determined for the RSSI values ​​of the tags in each positioning tag group, and then the RSSI value corresponding to the tag with the largest variance is selected as the intermediate third response sub-data, and then the target third response sub-data with the largest variance (EPC1 in positioning tag group 1) is determined in the intermediate third response sub-data corresponding to the three positioning tag groups (EPC1 in positioning tag group 1, EPC5 in positioning tag group 2, and EPC8 in positioning tag group 3). Determining the positioning tag group 1 to which the target third response sub-data belongs is the final positioning result.

[0152] In the embodiment of the present application, the displayed positioning information is tested according to the preset number of identifiers to determine the test result; if the test result indicates that O of the identifiers are abnormal, the first response data corresponding to the O positioning tag groups are analyzed again, and the identifiers corresponding to the O positioning tag groups in the positioning information are updated. In this way, a backtracking mechanism for positioning the target object can be established, which improves the robustness of the positioning algorithm, ensures the accuracy of positioning, and better protects the safety of patrol personnel.

[0153] See also Fig.16 , which is a schematic diagram of the structure of the positioning device provided in an embodiment of the present application.

[0154] The embodiment of the present application further provides a positioning device 800 , including: a data acquisition unit 801 and a positioning unit 802 .

[0155] The data acquisition unit 801 is used to acquire the first response data corresponding to the positioning tag group responding to the target object;

[0156] The positioning unit 802 is used to determine the current positioning of the target object based on the similarity between the first response data and the corresponding preset response data in the data set; wherein the preset response data corresponding to the multiple positioning tag groups in the data set are used to represent the data when the corresponding positioning tag group responds to the sample object.

[0157] In the embodiment of the present application, the data acquisition unit 801 in the positioning device 800 is used to acquire second response data when the plurality of positioning tag groups respectively respond to the sample object;

[0158] Determine a target weight group corresponding to each positioning tag group based on the second response data corresponding to each positioning tag group and a preset weight group; wherein the weights in the target weight group and the second response data corresponding to the sample object meet the fitting condition; and the weights in the target weight group correspond one-to-one to the tags in the positioning tag group;

[0159] Determine the preset response data corresponding to each positioning tag group based on the target weight group and the second response data corresponding to each positioning tag group;

[0160] The data set is constructed based on the correspondence between the plurality of positioning tag groups and the respectively corresponding preset response data.

[0161] In the embodiment of the present application, the positioning device 800 is used to intercept M first data values ​​for each of the multiple first response sub-data in the second response data; wherein the first response sub-data in the second response data corresponds one-to-one to the tag in the corresponding positioning tag group; M is an integer greater than 1;

[0162] The preset response data corresponding to each positioning tag group is determined based on the product of the target weight group and the M groups of the first data values ​​respectively; wherein the first data values ​​in each group of the first data values ​​respectively belong to the corresponding first response sub-data.

[0163] In the embodiment of the present application, the data acquisition unit 801 in the positioning device 800 is used to acquire the first response data when the positioning tag group in the current area responds to the target object respectively when the distance between the target object and the current area meets the preset condition;

[0164] Among them, the current area belongs to multiple areas in the path to be measured; N antennas are arranged at intervals in each of the areas; the signal range of each antenna covers K groups of positioning tags arranged at intervals; N is an integer greater than 0; K is an integer greater than 0.

[0165] In the embodiment of the present application, the positioning unit 802 in the positioning device 800 is used to determine the similarity between the first response data and the corresponding preset response data based on the third response data determined by the first response data and having the same dimension as the preset response data;

[0166] The current location is determined based on the plurality of similarities and the preset locations corresponding to the plurality of positioning tag groups.

[0167] In the embodiment of the present application, the positioning unit 802 in the positioning device 800 is used to intercept M second data values ​​from the multiple second response sub-data in each of the first response data; wherein the second response sub-data in the first response data has a one-to-one correspondence with the tags in the positioning tag group;

[0168] Determine corresponding third response data based on the product of the target weight group corresponding to the first response data and the M groups of the second data values ​​respectively corresponding to each other; wherein the second data values ​​in each group of the second data values ​​respectively belong to the corresponding second response sub-data;

[0169] Based on the third response data and the preset response data corresponding to each of the first response data, the corresponding similarity is determined.

[0170] In the embodiment of the present application, the positioning unit 802 in the positioning device 800 is used to determine the target similarity greater than a preset threshold among the multiple similarities;

[0171] The current location is determined based on the preset position corresponding to the location tag group corresponding to the target similarity.

[0172] In an embodiment of the present application, the positioning tag group includes: T tags; T tags are divided into P groups; T is an integer greater than 1; P is greater than 1; the positioning unit 802 in the positioning device 800 is used to add the weight corresponding to the abnormal tag in the corresponding target weight group to the maximum weight corresponding to the tag in the group to which the abnormal tag belongs if it is detected that the second response sub-data corresponding to the abnormal tag is missing in any of the first response data.

[0173] In the embodiment of the present application, the positioning device 800 is used to display the positioning information of the target object based on the identifier of the positioning tag group corresponding to the current positioning.

[0174] In the embodiment of the present application, the positioning device 800 is used to detect the displayed positioning information according to the preset identification number and determine the detection result;

[0175] If the detection result indicates that O of the identifiers are abnormal, a secondary analysis is performed on the first response data corresponding to the O positioning tag groups, and the identifiers corresponding to the O candidate positioning tag groups in the positioning information are updated; wherein O is an integer greater than 1.

[0176] In the embodiment of the present application, the positioning device 800 is used to determine the middle third response sub-data with the largest degree of dispersion among the plurality of third response sub-data in the first response data corresponding to the O positioning tag groups respectively;

[0177] Determine the target third response sub-data with the largest degree of dispersion among the O intermediate third response sub-data;

[0178] Based on the identifier of the positioning tag group to which the target third response sub-data belongs, the identifiers corresponding to the O positioning tag groups in the positioning information are updated.

[0179] It should be noted that in the embodiments of the present application, if the above-mentioned method for processing item information is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present application can be essentially or partly reflected in the form of a software product that contributes to the relevant technology. The computer software product is stored in a storage medium and includes several instructions for enabling an item information processing device (which can be a personal computer, etc.) to execute all or part of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a magnetic disk or an optical disk. In this way, the embodiments of the present application are not limited to any specific combination of hardware and software.

[0180] Correspondingly, an embodiment of the present application provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps in the method on the positioning device 800 side are implemented.

[0181] It should be noted here that the description of the above storage medium and device embodiments is similar to the description of the above method embodiments, and has similar beneficial effects as the method embodiments. For technical details not disclosed in the storage medium and device embodiments of this application, please refer to the description of the method embodiments of this application for understanding.

[0182] It should be noted that Fig.17 A hardware entity diagram of an electronic device provided in an embodiment of the present application, such as Fig.17As shown, an embodiment of the present application provides an electronic device 900, including a memory 902 and a processor 901, wherein the memory 902 stores a computer program that can be run on the processor 901, and the processor 901 implements the steps in the above method when executing the program, wherein;

[0183] The processor 901 generally controls the overall operation of the electronic device 900 .

[0184] The memory 902 is configured to store instructions and applications executable by the processor 901, and can also cache data to be processed or processed by the processor 901 and various modules in the electronic device 900 (for example, image data, audio data, voice communication data, and video communication data), which can be implemented through flash memory (FLASH) or random access memory (Random Access Memory, RAM).

[0185] Correspondingly, an embodiment of the present application further provides a computer program product, including a computer program, which can be executed by a processor 901 of an electronic device 900 to complete the steps in the method on the positioning device 800 side.

[0186] It should be understood that "one embodiment" or "an embodiment" mentioned throughout the specification means that specific features, structures or characteristics related to the embodiment are included in at least one embodiment of the present application. Therefore, "in one embodiment" or "in an embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. In addition, these specific features, structures or characteristics can be combined in one or more embodiments in any suitable manner. It should be understood that in various embodiments of the present application, the size of the sequence number of the above-mentioned processes does not mean the order of execution, and the execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application. The above-mentioned sequence numbers of the embodiments of the present application are only for description and do not represent the advantages and disadvantages of the embodiments.

[0187] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0188] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored, or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the device or unit can be electrical, mechanical or other forms.

[0189] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units; they may be located in one place or distributed on multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0190] In addition, all functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may be a separate unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0191] A person skilled in the art can understand that all or part of the steps of implementing the above method embodiment can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps of the above method embodiment; and the aforementioned storage medium includes: a mobile storage device, a read-only memory (ROM), a magnetic disk or an optical disk, and other media that can store program codes.

[0192] Alternatively, if the above-mentioned integrated unit of the present application is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present application can be essentially or partly embodied in the form of a software product that contributes to the relevant technology. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a mobile storage device, a ROM, a magnetic disk, or an optical disk.

[0193] The above is only an implementation method of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A positioning method, characterized in that: include: Get the first response data corresponding to the positioning tag group responding to the target object; Based on the similarity between the first response data and the corresponding preset response data in the data set, the current location of the target object is determined; wherein the preset response data corresponding to the multiple positioning tag groups in the data set are used to characterize the data when the corresponding positioning tag group responds to the sample object.

2. The positioning method according to claim 1, characterized in that: The method further comprises: Acquire second response data when the plurality of positioning tag groups respectively respond to the sample object; Determine a target weight group corresponding to each positioning tag group based on the second response data corresponding to each positioning tag group and a preset weight group; wherein the weights in the target weight group and the second response data corresponding to the sample object meet the fitting condition; and the weights in the target weight group correspond one-to-one to the tags in the positioning tag group; Determine the preset response data corresponding to each positioning tag group based on the target weight group and the second response data corresponding to each positioning tag group; The data set is constructed based on the correspondence between the plurality of positioning tag groups and the respectively corresponding preset response data.

3. The positioning method according to claim 2, characterized in that: The determining the preset response data corresponding to each positioning tag group based on the target weight group and the second response data corresponding to each positioning tag group includes: For each of the plurality of first response sub-data in the second response data, M first data values ​​are intercepted; wherein the first response sub-data in the second response data corresponds one-to-one to the tags in the corresponding positioning tag group; and M is an integer greater than 1; The preset response data corresponding to each positioning tag group is determined based on the product of the target weight group and the M groups of the first data values ​​respectively corresponding to each other; wherein the first data values ​​in each group of the first data values ​​respectively belong to the corresponding first response sub-data.

4. The positioning method according to any one of claims 1 to 3, characterized in that: The obtaining of the first response data corresponding to the positioning tag group responding to the target object includes: When the distance between the target object and the current area meets a preset condition, acquiring the first response data when the positioning tag group in the current area responds to the target object; Among them, the current area belongs to multiple areas in the path to be measured; N antennas are arranged at intervals in each of the areas; the signal range of each antenna covers K groups of positioning tags arranged at intervals; N is an integer greater than 0; K is an integer greater than 0.

5. The positioning method according to any one of claims 1 to 3, characterized in that: The determining the current location of the target object based on the similarity between the first response data and the corresponding preset response data in the data set includes: Determine, based on the third response data determined by the first response data and having the same dimension as the preset response data, a similarity between the first response data and the corresponding preset response data; The current location is determined based on the plurality of similarities and the preset locations corresponding to the plurality of positioning tag groups.

6. The positioning method according to claim 5, characterized in that: The determining, based on the third response data determined by the first response data and having the same dimension as the preset response data, the similarity between the first response data and the corresponding preset response data comprises: M second data values ​​are intercepted from the plurality of second response sub-data in each of the first response data; wherein the second response sub-data in the first response data correspond one-to-one to the tags in the positioning tag group; Determine corresponding third response data based on the product of the target weight group corresponding to the first response data and the M groups of the second data values ​​respectively corresponding to each other; wherein the second data values ​​in each group of the second data values ​​respectively belong to the corresponding second response sub-data; Based on the third response data and the preset response data corresponding to each of the first response data, the corresponding similarity is determined.

7. The positioning method according to claim 5, characterized in that: The determining the current location based on the plurality of similarities and the preset locations corresponding to the plurality of positioning tag groups includes: Determine a target similarity among the plurality of similarities that is greater than a preset threshold; The current location is determined based on the preset position corresponding to the location tag group corresponding to the target similarity.

8. The positioning method according to claim 5, characterized in that: The positioning tag group includes: T tags; T tags are divided into P groups; T is an integer greater than 1; P is greater than 1; the method further includes: If it is detected that the second response sub-data corresponding to the abnormal label is missing in any of the first response data, the weight corresponding to the abnormal label in the corresponding target weight group is added to the maximum weight corresponding to the label in the group to which the abnormal label belongs.

9. The positioning method according to claim 7, characterized in that: The method further comprises: Based on the identifier of the positioning tag group corresponding to the current positioning, the positioning information of the target object is displayed.

10. The positioning method according to claim 9, characterized in that: The method further comprises: Performing detection on the displayed positioning information according to the preset number of identifications to determine the detection result; If the detection result indicates that O of the identifiers are abnormal, a secondary analysis is performed on the first response data corresponding to the O positioning tag groups, and the identifiers corresponding to the O candidate positioning tag groups in the positioning information are updated; wherein O is an integer greater than 1.

11. The positioning method according to claim 10, characterized in that: The performing secondary analysis on the first response data respectively corresponding to the O positioning tag groups, and updating the identifiers corresponding to the O positioning tag groups in the positioning information, includes: Determine the middle third response sub-data with the largest degree of dispersion among the plurality of third response sub-data in the first response data corresponding to the O positioning tag groups respectively; Determine the target third response sub-data with the largest degree of dispersion among the O intermediate third response sub-data; Based on the identifier of the positioning tag group to which the target third response sub-data belongs, the identifiers corresponding to the O positioning tag groups in the positioning information are updated.

12. A positioning device, characterized in that: include: A data acquisition unit, used to acquire first response data corresponding to when the positioning tag group responds to the target object; A positioning unit is used to determine the current positioning of the target object based on the similarity between the first response data and the corresponding preset response data in the data set; wherein the preset response data corresponding to the multiple positioning tag groups in the data set are used to characterize the data when the corresponding positioning tag group responds to the sample object.

13. An electronic device, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program executable on the processor, and the processor implements the steps of the method according to any one of claims 1 to 11 when executing the computer program.

14. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps in the method according to any one of claims 1 to 11 are implemented.

15. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the computer program implements the steps of the method according to any one of claims 1 to 11.

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