Tracking and positioning methods, devices, electronic devices, and storage media

Abstract

A tracking and positioning method is disclosed, which includes the steps of: positioning a tracked target and obtaining an initial position of the tracked target; collecting and obtaining movement data of the tracked target; determining a movement pattern of the tracked target based on the movement data; and determining an actual position of the tracked target based on the initial position and the movement pattern. A tracking and positioning device, an electronic device, and a computer-readable storage medium are further disclosed.

Description

Technical Field

[0001] (Cross-reference to Related Applications) This application claims priority to Chinese Patent Application CN202210345811.X, filed on March 31, 2022, with the title "Tracking and Positioning Method, Device, Electronic Device, and Storage Medium", and incorporates all of its contents into this disclosure by reference.

[0002] This disclosure relates to the field of intelligent devices, and particularly to a tracking and positioning method, device, electronic device, and storage medium.

Background Art

[0003] Currently, the types of terminal products in the Internet of Things are very rich, and customers' requirements for the functions and performance of products are also becoming increasingly high. Products such as trackers generally perform tracking and positioning using conventional positioning technologies such as GPS (Global Positioning System) / WIFI (Wireless Communication Technology) / base stations.

Summary of the Invention

Problems to be Solved by the Invention

[0004] This disclosure provides a tracking and positioning method, and further provides a tracking and positioning device, an electronic device, and a computer-readable storage medium.

Means for Solving the Problems

[0005] In a first aspect, this disclosure provides a tracking and positioning method, which includes steps of positioning a tracking target to obtain an initial position of the tracking target, collecting and obtaining movement data of the tracking target, identifying a movement pattern of the tracking target based on the movement data, and identifying an actual position of the tracking target based on the initial position and the movement pattern.

[0006] In a second aspect, the Disclosure provides a tracking positioning device comprising: an initial positioning module configured to position a tracking target and obtain an initial position of the tracking target; a movement data acquisition module configured to collect and obtain movement data of the tracking target; a movement pattern recognition module configured to identify a movement pattern of the tracking target based on the movement data; and a precision positioning module configured to identify the actual position of the tracking target based on the initial position and the movement pattern.

[0007] In a third embodiment, the Disclosure provides an electronic device comprising: a memory configured to store a computer program; and a processor configured to, when the computer program is executed, perform any one of the steps of the tracking positioning method described above.

[0008] In a fourth embodiment, the Disclosure provides a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, any step of the tracking positioning method described above is realized.

[0009] The drawings herein are included in and constitute part of the specification, illustrate embodiments consistent with the disclosure, and are used together with the specification to illustrate the principles of the disclosure.

[0010] To more clearly explain the related technology and the technical concepts in the embodiments of this disclosure, the accompanying drawings necessary for describing the related technology and embodiments of this disclosure are briefly described below. Of course, the accompanying drawings relating to the embodiments of this disclosure described below only illustrate some embodiments of this disclosure, and those skilled in the art can obtain other accompanying drawings based on the provided drawings without any creative work, and these other accompanying drawings also fall within the scope of this disclosure. [Brief explanation of the drawing]

[0011] [Figure 1] This is a schematic flowchart of the tracking and positioning method provided by the embodiments of this disclosure. [Figure 2] This is a schematic diagram of a road layout provided by an embodiment of the present invention. [Figure 3] This is a schematic flowchart of another tracking and positioning method provided by the embodiments of this disclosure. [Figure 4] This is a schematic flowchart of the method for constructing a movement pattern database provided by the embodiments of this disclosure. [Figure 5] This is a schematic flowchart of yet another tracking and positioning method provided by embodiments of the present disclosure. [Figure 6] This is a machine learning flowchart provided by an embodiment of the present invention. [Figure 7] This is a tracking positioning flowchart provided by the embodiments of this disclosure. [Figure 8] This is a schematic diagram of the configuration of a tracking and positioning device provided by an embodiment of the present disclosure. [Figure 9] This is a schematic diagram of the configuration of an electronic device provided by one embodiment of the present disclosure. [Modes for carrying out the invention]

[0012] To further clarify the purpose, technical proposal, and advantages of this disclosure, the technical proposal in the embodiments of this disclosure will be described clearly and completely below, in combination with the accompanying drawings in the embodiments of this disclosure. It is clear that the embodiments described are not all embodiments of this disclosure, but only a selection of embodiments. All other embodiments that a person skilled in the art could obtain without creative work based on the embodiments of this disclosure are within the scope of protection of this disclosure.

[0013] When tracking and positioning using conventional positioning technologies such as GPS (Global Positioning System), Wi-Fi (Wireless Communication Technology), and base stations, problems often arise where the determined location is inaccurate due to factors such as GPS signal blockage, lack of Wi-Fi hotspots, and uneven base station placement. For example, while conventional GPS positioning technology can determine that a tracker is located on a road, it becomes impossible to pinpoint its exact location on the road, whether it's on a vehicle on the roadway, or on the sidewalk, due to unfavorable factors such as signal blockage or weak signals. As this illustrates, conventional tracking and positioning technologies have the problem of inaccurate positioning.

[0014] Therefore, how to effectively improve the accuracy of tracking and positioning is a problem that those skilled in the art should solve as soon as possible.

[0015] The tracking and positioning method provided in this disclosure may be implemented by a tracking and positioning device. This tracking and positioning device may be a portable device or wearable device such as a mobile phone or smart bracelet that a user can carry with them, or it may be a small tracker that can be attached to the tracking target in the form of an accessory. For example, if the tracking target is a child or an elderly person, the tracking and positioning function can be integrated into a smart bracelet; if the tracking target is an animal, a small tracker can be attached to the animal's collar; and if the tracking target is a transported object, a small tracker can be placed inside the transport box in which the transported object is located.

[0016] Note that the tracking and positioning method provided by the embodiments of the present disclosure may be executed in real time, or may be executed regularly / irregularly. The execution mode can be customized and set by the user according to actual needs, and the present disclosure does not limit this. For example, a switch button may be provided on the tracking and positioning device to control the on and off of the tracking and positioning function (for example, directly select on or off on the smart bracelet). A switch button may be provided on the remote control device of the tracking and positioning device to remotely control the on and off of the tracking and positioning function (for example, use a mobile phone to control the on and off of the small tracker). Of course, the above two control methods may coexist and the user may be allowed to freely select. Also, in the process of periodically executing the tracking and positioning method, the user may set the periodic execution timing on the tracking and positioning device or its remote control device according to actual needs, for example, to perform a tracking and positioning operation once every 24 hours.

[0017] Based on this, the embodiments of the present disclosure provide a tracking and positioning method.

[0018] Referring to FIG. 1 which is a schematic flowchart of the tracking and positioning method provided by the embodiments of the present disclosure, this tracking and positioning method may include steps S101 to S104.

[0019] In S101, position the tracking target and obtain the initial position of the tracking target.

[0020] This step aims to achieve the initial positioning of the tracking target and obtain its initial position. Among them, the tracking target is a target object that needs to be tracked and positioned, and it may be a person or an object. For example, when the tracking target is a person, the function of positioning a child or an elderly person can be realized. When the tracking target is an object, functions such as logistics tracking and animal monitoring can be realized.

[0021] In the process of realization, this initial positioning process can be realized using any conventional positioning technology. Since conventional positioning technologies have the drawback that the positioning is inaccurate, the initial position obtained in this step is a general position that is not sufficiently accurate. For example, by performing initial positioning on a tracking target, it is possible to identify which road the tracking target is on, but it is impossible to identify the position of the tracking target on that road. Based on this, in combination with each step described later, accurate positioning of the tracking target can be realized. That is, the position of the tracking target on the above road, such as on the sidewalk of the road, on the roadway, or inside a building beside the road, can be identified.

[0022] In S102, collect and obtain the movement data of the tracking target.

[0023] This step aims to realize the collection of the movement data of the tracking target. This movement data is, namely, data information representing the current movement form of the tracking target, and its content does not affect the implementation of this technical solution and can be set by the user according to actual needs. For example, it may include speed, acceleration, gravitational acceleration, etc., but the present disclosure does not limit this.

[0024] Among these, the collection of the movement data may be realized based on corresponding data collection devices such as sensor devices. For different types of movement data, corresponding types of sensors may be provided in the tracking and positioning device. Of course, the type and number of sensors are determined by the type and number of movement data that needs to be obtained.

[0025] In S103, based on the movement data, identify the movement pattern of the tracking target.

[0026] This step aims to recognize movement patterns, that is, to identify and specify the movement patterns of the tracked target based on the tracked target's movement data. These movement patterns are used in conjunction with the initial position to achieve more accurate positioning of the tracked target, and include, but are not limited to, walking, running, going up / down stairs, going up / down elevators, and riding various different modes of transportation (e.g., subway, bus).

[0027] As mentioned above, movement data may include speed, acceleration, gravitational acceleration, etc. By performing analysis on this movement data, the current movement pattern of the tracked target can be further recognized and identified. For example, based on the tracked target's speed, it can be determined whether it is in a walking pattern (corresponding to low speed) or a riding pattern (corresponding to high speed), and based on the tracked target's gravitational acceleration (high gravity or zero gravity), it can be determined whether it is in an elevator riding pattern.

[0028] In S104, the actual location of the tracking target is determined based on the initial position and movement pattern.

[0029] This step aims to achieve accurate positioning of the tracking target and obtain its actual location. Based on S101, the initial position of the tracking target is obtained, and based on S102 and S103, the movement pattern of the tracking target is obtained. By combining the initial position and the movement pattern, the actual location of the tracking target can be determined. This actual location is, in other words, more accurate location information than the initial position.

[0030] For example, taking positioning on a road as an example, and referring to Figure 2, a schematic diagram of the road layout provided in the embodiment of this disclosure, if the initial positioning process in S101 identifies the tracking target as being on a road (XX Street shown in Figure 2), and if the tracking target's movement pattern is recognized as a bus boarding pattern in a certain direction, the tracking target's position P1 (on the bus on the roadway) can be identified. If the tracking target's movement pattern is recognized as a walking pattern in a certain direction, the tracking target's position P2 (on the left sidewalk) or P3 (on the right sidewalk) can be identified. Similarly, positioning can be performed up to other locations such as P4 (inside the roadway), P5 (on the stairs inside a building beside the road), P6 (on the elevator inside a building beside the road), thus enabling accurate positioning of the tracking target.

[0031] As can be seen, the tracking positioning method provided by the embodiments of this disclosure first acquires the initial position of the tracking target by initial positioning, then collects the movement data of the tracking target, and performs movement pattern recognition on it. This makes it possible to accurately determine the position of the tracking target by combining the movement pattern and the initial position, thereby realizing the integration of the tracking target's movement pattern into the tracking positioning technology. Compared to conventional tracking positioning technology, this not only effectively improves positioning accuracy but also allows acquisition of the movement state of the tracking target, thereby enriching the functionality of the tracker product and improving the positioning performance of the product.

[0032] Based on the above embodiment, in one embodiment of the present disclosure, the step of positioning a tracking target and obtaining the initial position of the tracking target may include the step of positioning a tracking target and obtaining the initial position using GPS positioning technology, WIFI positioning technology, or base station positioning technology.

[0033] The embodiments of this disclosure provide three different positioning technologies: GPS positioning technology, Wi-Fi positioning technology, and base station positioning technology. Of these, GPS positioning technology is a technology that obtains location information by calculation after error processing is performed on the signal received by a GPS receiver. Wi-Fi positioning technology, i.e., Wi-Fi real-time positioning, is a technology that uses an associated wireless network, in conjunction with Wi-Fi tags and associated mobile terminal devices (e.g., Wi-Fi mobile phones, PDAs, laptops, etc.), and further uses a corresponding positioning algorithm to determine location information. Base station positioning technology, i.e., mobile location service, is a communication service that calculates a rough location based on the communication time difference between a base station and a mobile terminal device. It should be noted that the above three positioning technologies are merely three implementation methods provided by the embodiments of this disclosure, and of course, it is possible to implement them using other positioning technologies, and this disclosure is not limited to that.

[0034] In one embodiment of the present disclosure, the step of collecting and acquiring motion data of a tracked target may include the step of collecting and acquiring motion data of a tracked target using a motion sensor, wherein the motion sensor includes one or more of a gravity sensor, an acceleration sensor, and a velocity sensor.

[0035] Embodiments of this disclosure provide a method for acquiring movement data, that is, a method implemented using a movement sensor. In the implementation process, by placing the movement sensor inside a tracking positioning device and equipping the tracking positioning device on a tracking target, various types of movement data can be collected for the tracking target.

[0036] On the other hand, embodiments of the present disclosure provide three different types of motion sensors: gravity sensors, acceleration sensors, and velocity sensors. The gravity sensor is used to collect the gravitational acceleration of a tracked target, the acceleration sensor is used to collect the horizontal acceleration of a tracked target, and the velocity sensor is used to collect the velocity of a tracked target.

[0037] Similarly, the three types of motion sensors described above are merely three implementations provided by the embodiments of this disclosure, and other types of motion sensors, such as multi-axis sensors, may be provided according to actual needs to achieve the collection of diverse motion data, and this disclosure is not limited thereto. It is conceivable that the greater the types and number of motion sensors, the greater the types and number of motion data collected and acquired, which will help to achieve more accurate and diverse motion pattern recognition.

[0038] Embodiments of this disclosure provide an alternative tracking and positioning method.

[0039] Referring to Figure 3, which is a schematic flowchart of another tracking and positioning method provided by an embodiment of the present disclosure, this tracking and positioning method may include steps S201 to S205.

[0040] In S201, the tracking target is positioned, and its initial position is obtained.

[0041] In S202, movement data of the tracked target is collected and acquired.

[0042] In S203, kinematic analysis is performed on the movement data to obtain movement characteristics.

[0043] In S204, movement pattern matching is performed based on movement characteristics to identify the movement pattern of the tracked target.

[0044] In S205, the actual location of the tracking target is determined based on the initial position and movement pattern.

[0045] In the embodiments of this disclosure, an implementation method is provided for realizing movement patterns based on movement data.

[0046] After collecting and acquiring movement data of the tracking target, kinematic analysis may be performed on each piece of data to obtain corresponding movement characteristics. Here, kinematic analysis can be achieved by calculating kinematic equations. Movement characteristics are used to recognize movement patterns, and their content can be pre-set by engineers according to the actual situation. For example, the distance and direction of movement of the tracking target can be calculated and obtained based on movement data such as velocity and acceleration, and the hypergravity and weightlessness states of the tracking target can be calculated and obtained based on movement data such as velocity and gravitational acceleration.

[0047] Furthermore, by performing movement pattern matching based on each movement characteristic, the movement pattern of the tracked target can be identified. Here, movement pattern matching may be threshold-based matching (movement characteristics of different movement patterns correspond to different standard thresholds). For example, based on the velocity value, it is possible to identify whether the tracked target is in a walking pattern or a riding pattern. By matching the direction of movement, it is possible to identify which road (regular vehicles or rail vehicles) or sidewalk (left-hand sidewalk or right-hand sidewalk) the tracked target is on. Based on gravitational acceleration, it is possible to identify whether the tracked target is in an elevator riding pattern, and by combining this with hypergravity and zero-gravity conditions, it is possible to further identify whether the tracked target is in an elevator ascending pattern or an elevator descending pattern.

[0048] In one embodiment of the present disclosure, each movement pattern and a standard movement feature are stored in a movement pattern database in correspondence. Based on this, with reference to Figure 4, which is a schematic flowchart of the movement pattern database construction method provided by an embodiment of the present disclosure, this movement pattern database construction method may include steps S301 to S304.

[0049] In S301, movement data samples of the tracking target are collected and acquired for each movement pattern.

[0050] In S302, kinematic analysis is performed on the moving data sample to obtain a moving characteristic sample.

[0051] In S303, machine learning techniques are used to modify the moving feature samples and obtain standard moving features.

[0052] In S304, a mapping relationship between movement patterns and standard movement features is established, and a movement pattern database is generated.

[0053] To make it easier to understand, the following explanation will combine some of the steps described above.

[0054] Each movement pattern and its corresponding standard movement features may be stored in a movement pattern database. In other words, the movement pattern database stores additions or deletions of movement patterns, for example, the mapping relationships between movement patterns and standard movement features. That is, different movement patterns correspond to different standard movement features. By acquiring movement data of a tracking target, analyzing and identifying its movement features, and then matching these movement features with standard movement features in the movement pattern database, movement pattern recognition can be achieved.

[0055] Here, the process of generating a movement pattern database can be implemented based on machine learning techniques. First, sample data is collected from the tracking target, and movement data samples are obtained for various different movement patterns. It is understood that a large number of movement data samples can be collected for each movement pattern to ensure the accuracy of the mapping relationships. Then, kinematic analysis is performed on each movement data sample to obtain corresponding movement feature samples. This implementation process can be found in S203 above. Furthermore, by modifying the movement feature samples using machine learning techniques, standard movement features corresponding to movement patterns are obtained. For example, the standard movement feature corresponding to a walking pattern is that the speed is below a certain standard speed value. The standard movement feature corresponding to a rail vehicle riding pattern is that the speed exceeds a certain standard speed value. Finally, after obtaining the standard movement features corresponding to each movement pattern, a mapping relationship between each movement pattern and the standard movement features is constructed, stored in a pre-configured memory space, and a movement pattern database can be generated.

[0056] In one embodiment of the present disclosure, after the steps of establishing a mapping relationship between movement patterns and standard movement features and generating a movement pattern database, the present embodiment may further include a step of performing an update operation on the movement pattern database when an update command is received. Herein, the update operation includes adding or deleting movement patterns and / or modifying each standard movement feature in the movement pattern database.

[0057] To effectively ensure the accuracy of movement pattern recognition results and further the accuracy of tracking and positioning results, periodic or irregular updates may be performed on the movement pattern database. For example, if the tracking target is a child, as the child grows, the corresponding movement characteristics for the same movement pattern will inevitably change significantly, and the movement patterns will become more diverse. Therefore, the corresponding movement pattern database may be updated periodically, for example, once a year.

[0058] Of these, update operations on the movement pattern database mainly consist of two types: one is adding or deleting movement patterns in the movement pattern database, for example, adding new mapping relationships between movement patterns and standard movement features; the other is modifying each standard movement feature in the movement pattern database to obtain standard movement features corresponding to each movement pattern that are better suited to the current tracking target.

[0059] Here, the execution of update operations on the movement pattern database can be carried out based on received update commands. In periodic update mode, the system may automatically respond to update commands at pre-set time intervals. In irregular update mode, update commands may be initiated by a remote control device of the tracking and positioning equipment. For example, a human-machine interaction interface may be provided on the remote control device, allowing the user to initiate update commands on this human-machine interaction interface.

[0060] By performing update operations on the movement pattern database in this way, it is possible to effectively ensure that the mapping relationships between movement patterns in the database and standard movement features are more suitable for the current tracking target, thereby guaranteeing the accuracy of these mapping relationships, which helps to achieve more accurate movement pattern recognition and effectively guarantees the accuracy of tracking positioning results.

[0061] Embodiments of this disclosure provide yet another tracking and positioning method.

[0062] Referring to Figure 5, which is a schematic flowchart of yet another tracking and positioning method provided by embodiments of the present disclosure, this tracking and positioning method may include steps S401 to S405.

[0063] In S401, the tracking target is positioned, and its initial position is obtained.

[0064] In S402, movement data of the tracking target is collected and acquired.

[0065] In S403, the movement pattern of the tracking target is identified based on the movement data.

[0066] In S404, the actual location of the tracking target is determined based on the initial position and movement pattern.

[0067] In S405, the actual location is uploaded to the cloud server and / or sent to the designated terminal.

[0068] The tracking and positioning method provided by the embodiments of this disclosure can further implement a location information upload function. That is, the acquired physical location can be uploaded to a cloud server and / or transmitted directly to a designated terminal. In the implementation process, after acquiring the physical location, the physical location can be uploaded to the cloud server via a mobile network or the like. Then, a designated monitoring device or remote control device (e.g., a mobile phone, PC, etc.) can log in to the cloud server and query the location information. The physical location information may also be transmitted directly to a designated terminal. This designated terminal may be a monitoring device or a remote control device.

[0069] For example, if the tracking target is a child or an elderly person, the default device may be the parent's or child's mobile phone. By tracking and determining the actual location of the child or elderly person, and then directly transmitting that information to the default device, the safety of the child or elderly person can be effectively ensured. If the tracking target is a shipment, the actual location of the shipment can be tracked and then directly uploaded to the cloud server so that the receiving and shipping managers can log in to the cloud server as needed to inquire about the shipment's current location. Of course, both the function of uploading the actual location to the cloud server and the function of transmitting it to the default device can exist simultaneously, making it easy to inquire about location information as needed.

[0070] Furthermore, the location information upload function may be real-time or periodic, and can be customized and selected according to actual needs, but this disclosure is not limited to this.

[0071] As can be seen therefrom, the tracking and positioning method provided by the embodiments of this disclosure can effectively ensure that administrators know the precise location of the tracking target in a timely manner in order to implement a location information upload function.

[0072] Based on the embodiments described above, the embodiments of this disclosure provide a tracking and positioning method that mainly comprises a machine learning flow and a tracking and positioning flow.

[0073] First, referring to Figure 6, which is a machine learning flowchart provided by an embodiment of the present invention, the implementation flow may include the following steps (1) to (5).

[0074] (1) Use the movement sensors within the Tracker to collect movement data (i.e., movement data samples) for various movement patterns.

[0075] (2) The movement data acquired in (1) is transmitted to a processor such as a CPU or a single-chip computer, and movement features (i.e., movement feature samples) are extracted for each type of movement data.

[0076] (3) The movement features in (3) are modified using machine learning to obtain standard movement features corresponding to the movement patterns.

[0077] (4) A mapping relationship between movement patterns and standard movement features is constructed and stored in memory to generate a movement pattern database.

[0078] (5) Update the movement pattern database using machine learning. This includes, but is not limited to, adding new mapping relationships between movement patterns and standard movement features, or modifying standard movement features within each mapping relationship.

[0079] Furthermore, referring to Figure 7, which is a tracking positioning flowchart provided by the embodiments of this disclosure, the implementation flow may include the following steps (1) to (6).

[0080] (1) The Tracker obtains the initial location of the tracked object (tracking target) using positioning technologies such as GPS / WIFI / base stations.

[0081] (2) The Tracker acquires movement data of the tracked object via a movement sensor.

[0082] (3) The Tracker's processor analyzes the movement data and extracts and acquires movement features.

[0083] (4) The Tracker's processor compares the movement features from (3) with the movement pattern database to confirm the movement pattern of the target being tracked.

[0084] (5) The Tracker's processor merges the initial position from (1) with the movement pattern from (4) to obtain more accurate position information.

[0085] (6) The Tracker's processor transmits the location information from (5) to the cloud server or monitoring side.

[0086] As can be seen, the tracking positioning method provided by the embodiments of this disclosure first acquires the initial position of the tracking target by initial positioning, then collects the movement data of the tracking target, and performs movement pattern recognition on it. This makes it possible to accurately determine the position of the tracking target by combining the movement pattern and the initial position, thereby realizing the integration of the tracking target's movement pattern into the tracking positioning technology. Compared to conventional tracking positioning technology, this not only effectively improves positioning accuracy but also allows acquisition of the movement state of the tracking target, thereby enriching the functionality of the tracker product and improving the positioning performance of the product.

[0087] Embodiments of this disclosure provide a tracking and positioning device.

[0088] Referring to Figure 8, a schematic diagram of the configuration of a tracking and positioning device provided in an embodiment of the present disclosure, the tracking and positioning device may include: an initial positioning module 1 configured to position a tracking target and obtain the initial position of the tracking target; a movement data acquisition module 2 configured to collect and acquire movement data of the tracking target; a movement pattern recognition module 3 configured to identify the movement pattern of the tracking target based on the movement data; and a precision positioning module 4 configured to identify the actual position of the tracking target based on the initial position and the movement pattern.

[0089] As can be seen, the tracking and positioning device provided by the embodiments of this disclosure first positions the tracking target to obtain its initial position, then collects movement data of the tracking target, and performs movement pattern recognition on it. This allows for the precise location of the tracking target to be determined by combining the movement pattern and the initial position, thereby realizing the integration of the tracking target's movement pattern into tracking and positioning technology. Compared to conventional tracking and positioning technology, this not only effectively improves positioning accuracy but also allows for the acquisition of the tracking target's movement state, thereby enriching the functionality of the tracker product and improving the product's positioning performance.

[0090] In one embodiment of the present disclosure, the movement pattern recognition module 3 may include a kinematic analysis unit configured to perform kinematic analysis on movement data to obtain movement characteristics, and a matching recognition unit configured to perform movement pattern matching based on the movement characteristics to identify the movement pattern of a tracking target.

[0091] In one embodiment of the present disclosure, each movement pattern and a standard movement feature are stored in a movement pattern database in correspondence. The tracking positioning device may further include a movement pattern database construction module, which may include: a sample data acquisition unit configured to collect and acquire movement data samples of a tracking target in each movement pattern; a sample data analysis unit configured to perform kinematic analysis on the movement data samples to obtain movement feature samples; a machine learning unit configured to modify the movement feature samples using machine learning techniques to obtain standard movement features; and a movement pattern database construction unit configured to construct a mapping relationship between movement patterns and standard movement features and generate a movement pattern database.

[0092] In one embodiment of the present disclosure, the tracking positioning device may further include a movement pattern database update module configured to perform update operations on the movement pattern database upon receiving an update command, after establishing a mapping relationship between movement patterns and standard movement features and generating a movement pattern database, wherein the update operations include adding or deleting movement patterns and / or modifying each standard movement feature in the movement pattern database.

[0093] In one embodiment of the present disclosure, the initial positioning module 1 may be configured to position a tracking target and acquire an initial position using GPS positioning technology, WIFI positioning technology, or base station positioning technology.

[0094] In one embodiment of the present disclosure, the motion data acquisition module 2 may be configured to collect and acquire motion data of a tracked target using a motion sensor. Here, the motion sensor includes one or more of a gravity sensor, an acceleration sensor, and a velocity sensor.

[0095] In one embodiment of the present disclosure, the tracking positioning device identifies the actual location of the tracking target based on the initial position and movement pattern, Embodiments of this disclosure provide electronic devices.

[0096] Referring to Figure 9, a schematic diagram of the configuration of an electronic device provided by this disclosure, the electronic device may include a memory configured to store a computer program, and a processor configured to enable any one of the tracking and positioning method steps described above when the computer program is executed.

[0097] Figure 9 shows a schematic diagram of the configuration of an electronic device, which may include a processor 10, memory 11, communication interface 12, and communication bus. The processor 10, memory 11, and communication interface 12 all communicate with each other via the communication bus 13.

[0098] In embodiments of this disclosure, the processor 10 may be a central processing unit (CPU), an application-specific integrated circuit, a digital signal processor, a field-programmable gate array, or other programmable logic device. The processor 10 can call a program stored in the memory 11, and the processor 10 can perform operations in embodiments of the tracking and positioning method.

[0099] Memory 11 stores one or more programs, and the programs may include program code that includes computer operation instructions. In embodiments of this disclosure, memory 11 stores at least a program for implementing the following functions: a function for positioning a tracking target and obtaining the initial position of the tracking target; a function for collecting and obtaining movement data of the tracking target; a function for identifying the movement pattern of the tracking target based on the movement data; and a function for identifying the actual position of the tracking target based on the initial position and the movement pattern.

[0100] In one possible embodiment, the memory 11 may include a program storage area and a data storage area, the program storage area may store an operating system and application programs necessary for at least one function, and the data storage area may store data created during use.

[0101] Furthermore, the memory 11 may include high-speed random-access memory, and may also include non-volatile memory, such as at least one magnetic disk memory device, or other volatile solid-state memory devices.

[0102] The communication interface 12 may also be an interface of a communication module used to connect to other devices or systems.

[0103] Of course, the configuration shown in Figure 9 does not constitute a limitation on the electronic device in the embodiments of this disclosure, and in actual applications, the electronic device may include more or fewer components than those shown in Figure 9, or a combination of some of the components.

[0104] Embodiments of this disclosure provide a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, any step of the tracking and positioning method described above can be realized.

[0105] This computer-readable storage medium may include various media capable of storing program code, such as USB memory, removable hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0106] For a description of the computer-readable storage media provided by the embodiments of this disclosure, please refer to the method embodiments described above, and the embodiments of this disclosure will not be described here.

[0107] The tracking positioning method provided in this disclosure includes the steps of: positioning a tracking target and obtaining its initial position; collecting and acquiring movement data of the tracking target; identifying the tracking target's movement pattern based on the movement data; and identifying the tracking target's actual position based on the initial position and the movement pattern. Using the proposed technology provided in this disclosure, the tracking target is initially positioned to obtain its initial position, then movement data of the tracking target is collected, and movement pattern recognition is performed on this data. This makes it possible to accurately identify the tracking target's position by combining the movement pattern and the initial position, thereby realizing the integration of the tracking target's movement pattern into the tracking positioning technology. Compared to conventional tracking positioning technologies, this not only effectively improves positioning accuracy but also allows for the acquisition of the tracking target's movement state, thereby enriching the functionality of tracker products and improving their positioning performance.

[0108] The tracking and positioning devices, electronic devices, and computer-readable storage media provided in this disclosure all have the beneficial effects described above, and therefore will not be explained here.

[0109] Each embodiment in this specification is described in a progressive manner, with emphasis on the differences between each embodiment and the others, and similar or identical parts between embodiments should be referenced to one another. Apparatus disclosed in an embodiment is described briefly as it corresponds to the method disclosed in the embodiment, and relevant parts should be referenced to the description of the method.

[0110] Those skilled in the art will further recognize that the units and algorithmic steps of each example described in relation to the embodiments disclosed herein can be implemented by electronic hardware, computer software, or a combination of both. To clearly illustrate hardware and software compatibility, the above description generally describes the configuration and steps of each example based on their function. Whether these functions are performed in hardware or software depends on the specific application of the technical proposal and the design constraints. Those skilled in the art may implement the described functions using different methods for each specific application, but such implementations should not be considered beyond the scope of this disclosure.

[0111] The technical proposals provided by this disclosure have been described in detail above. While this specification has described the principles and embodiments of this disclosure using individual examples, the descriptions of the above examples are intended only to aid in understanding the methods and core concepts of this disclosure. It should be noted that those skilled in the art can make several improvements and modifications to this disclosure without departing from the principles of this disclosure, and these improvements and modifications are also covered by this disclosure.

Claims

1. A tracking and positioning method, The steps include: positioning the tracking target and obtaining the initial position of the said target; The steps include collecting and acquiring movement data of the tracking target, The steps include identifying the movement pattern of the tracking target based on the aforementioned movement data, The steps include: determining the actual position of the tracking target based on the initial position and the movement pattern; The step of identifying the movement pattern of the tracking target based on the aforementioned movement data is: The steps include performing kinematic analysis on the aforementioned movement data to obtain movement characteristics, The steps include: performing movement pattern matching based on the aforementioned movement characteristics to identify the movement pattern of the tracking target, Each movement pattern and a standard movement characteristic are stored in a movement pattern database in correspondence, and the process for constructing the movement pattern database is as follows: A step of collecting and acquiring movement data samples of the tracking target in each of the aforementioned movement patterns, The steps include performing kinematic analysis on the aforementioned moving data sample to obtain a moving characteristic sample, The steps include: modifying the aforementioned moving feature sample using machine learning techniques to obtain the aforementioned standard moving feature; The steps include constructing a mapping relationship between the aforementioned movement patterns and the aforementioned standard movement features, and generating the aforementioned movement pattern database, The method further includes, if an update command is received after the step of constructing a mapping relationship between the movement pattern and the standard movement features and generating the movement pattern database, performing an update operation on the movement pattern database, The update operation includes adding or deleting movement patterns in the movement pattern database and / or modifying each of the standard movement features. Tracking and positioning method.

2. The step of positioning the tracking target and obtaining the initial position of the tracking target is: The process includes the step of positioning the tracking target using GPS positioning technology, Wi-Fi positioning technology, or base station positioning technology, and obtaining the initial position. The tracking and positioning method according to claim 1.

3. The step of collecting and acquiring movement data of the tracking target is: The process includes the step of collecting and acquiring movement data of the tracking target using a movement sensor, wherein the movement sensor includes one or more of a gravity sensor, an acceleration sensor, and a velocity sensor. The tracking and positioning method according to claim 1.

4. After the step of determining the actual position of the tracking target based on the initial position and the movement pattern, The step of uploading the aforementioned actual location to a cloud server and / or sending it to a designated terminal. The tracking and positioning method according to claim 1, further comprising:

5. An initial positioning module configured to position a tracking target and obtain the initial position of the said target, A movement data acquisition module configured to collect and acquire movement data of the aforementioned tracking target, A movement pattern recognition module configured to identify the movement pattern of the tracking target based on the movement data, Includes a precision positioning module configured to determine the actual position of the tracking target based on the initial position and the movement pattern, The aforementioned movement pattern recognition module is Kinematic analysis is performed on the aforementioned movement data to obtain movement characteristics, Based on the aforementioned movement characteristics, movement pattern matching is performed to identify the movement pattern of the tracking target. Each movement pattern and standard movement characteristics are stored in a corresponding movement pattern database, and the system further includes a movement pattern database construction module that performs the process of constructing the movement pattern database. The movement pattern database construction module collects and acquires movement data samples of the tracking target in each movement pattern. The aforementioned movement pattern database construction module performs kinematic analysis on the movement data samples and obtains movement feature samples. The aforementioned movement pattern database construction module uses machine learning techniques to modify the movement feature samples and obtain the standard movement features. The movement pattern database construction module constructs a mapping relationship between the movement patterns and the standard movement features, and generates the movement pattern database. The system further includes a movement pattern database update module that, after constructing a mapping relationship between the movement pattern and the standard movement features and generating the movement pattern database, performs an update operation on the movement pattern database when an update command is received. The update operation includes adding or deleting movement patterns in the movement pattern database and / or modifying each of the standard movement features. Tracking and positioning device.

6. It is an electronic device, Memory configured to store computer programs, When the computer program is executed, a processor configured to realize the steps of the tracking positioning method described in any one of claims 1 to 4 is provided. Electronic devices including those mentioned.

7. A computer program is stored, and when the computer program is executed by the processor, the steps of the tracking and positioning method described in any one of claims 1 to 4 are realized. Computer-readable storage medium.

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