CN108307308B - Positioning method, device and storage medium for wireless local area network equipment - Google Patents
Positioning method, device and storage medium for wireless local area network equipment Download PDFInfo
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- H04—ELECTRIC COMMUNICATION TECHNIQUE
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- H04W4/02—Services making use of location information
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Abstract
The disclosure relates to a positioning method, a positioning device and a storage medium of wireless local area network equipment, relating to the technical field of terminals, wherein the method comprises the following steps: the method comprises the steps of acquiring a plurality of target coordinates of the mobile terminal acquired within a preset time period, clustering the plurality of target coordinates by using a density-based clustering algorithm when the target coordinates are the coordinates of the mobile terminal when a signal of the WLAN device received by the mobile terminal meets a preset condition, so as to determine a coordinate cluster with the highest coordinate density, and determining the position of the WLAN device according to the coordinate cluster with the highest coordinate density. The method and the device can reduce the dependence on the signal strength of the WLAN equipment and improve the positioning accuracy when the position of the WLAN equipment is positioned.
Description
Technical Field
The present disclosure relates to the field of terminal technologies, and in particular, to a method and an apparatus for positioning a wireless local area network device, and a storage medium.
Background
In the related art, the WLAN (english: Wireless Local Area Networks, chinese: Wireless Local Area Networks) technology is widely used in people's daily life by virtue of the advantages of convenience in moving, convenience in installation, easiness in expansion and the like, for example, the Wi-Fi (english: Wireless fidelity, chinese: Wireless fidelity) technology is the most widely used WLAN technology at present, and has gradually become the basic function of various intelligent devices. With the continuous development and popularization of WLAN technology, the deployment of WLAN devices is becoming more and more intensive, and therefore, the positioning requirement of WLAN devices is generated. Currently, the location of a WLAN device is generally determined by WLAN signal strength.
Disclosure of Invention
To overcome the problems in the related art, the present disclosure provides a method, an apparatus, and a storage medium for positioning a wireless lan device.
According to a first aspect of the embodiments of the present disclosure, there is provided a positioning method for a wireless local area network device, the method including:
acquiring a plurality of target coordinates of a mobile terminal acquired within a preset time period, wherein the target coordinates are coordinates of the mobile terminal when a signal of a Wireless Local Area Network (WLAN) device received by the mobile terminal meets a preset condition;
clustering the target coordinates by using a density-based clustering algorithm to determine a coordinate cluster with the highest coordinate density;
and determining the position of the WLAN equipment according to the coordinate cluster with the highest coordinate density.
Optionally, the preset condition is preset signal strength, and the obtaining of the multiple target coordinates of the mobile terminal collected in the preset time period includes:
acquiring a plurality of position coordinates of the mobile terminal acquired within the preset time period;
and determining a coordinate in which the signal intensity of the WLAN equipment received by the mobile terminal is greater than the preset signal intensity from a plurality of position coordinates of the mobile terminal to obtain a plurality of target coordinates.
Optionally, the density-based clustering algorithm is a DBSCAN algorithm, and the clustering the plurality of target coordinates by using a preset density-based clustering algorithm to determine a coordinate cluster with the highest coordinate density includes:
the target coordinates, a preset scanning radius and a preset point threshold are used as input parameters of the DBSCAN algorithm, so that at least one coordinate cluster is obtained through the DBSCAN algorithm, the scanning radius is a neighborhood threshold of any coordinate, the point threshold is a threshold of coordinate density in a target coordinate set, and the number of coordinates in the neighborhood threshold range of any coordinate in the at least one coordinate cluster meets the point threshold;
and obtaining the coordinate cluster with the highest coordinate density from the at least one coordinate cluster.
Optionally, the target coordinates are longitude and latitude coordinates of the mobile terminal, and the taking the target coordinates, the preset scanning radius, and the preset point threshold as input parameters of the DBSCAN algorithm includes:
carrying out ink card holder transformation on the target coordinates to obtain ink card holder projections of the target coordinates;
and taking the mercator projections of the target coordinates, the preset scanning radius and the preset point threshold value as input parameters of the DBSCAN algorithm.
Optionally, the determining the position of the WLAN device according to the coordinate cluster with the highest coordinate density includes:
and performing ink card tray inverse transformation on the coordinate value of the geometric center of the coordinate cluster with the highest coordinate density to obtain a longitude and latitude coordinate value as the position of the WLAN equipment.
According to a second aspect of the embodiments of the present disclosure, there is provided a positioning apparatus for a wireless local area network device, the apparatus including:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is configured to acquire a plurality of target coordinates of the mobile terminal acquired within a preset time period, and the target coordinates are coordinates of the mobile terminal when a signal of the WLAN equipment received by the mobile terminal meets a preset condition;
a clustering module configured to cluster the plurality of target coordinates by using a density-based clustering algorithm to determine a coordinate cluster having a highest coordinate density;
a positioning module configured to determine a location of the WLAN device according to the coordinate cluster with the highest coordinate density.
Optionally, the preset condition is preset signal strength, and the obtaining module includes:
the obtaining submodule is configured to obtain a plurality of position coordinates of the mobile terminal collected in the preset time period;
and the screening submodule is configured to determine, from the plurality of position coordinates of the mobile terminal, a coordinate in which the signal strength of the WLAN device received by the mobile terminal is greater than the preset signal strength, so as to obtain the plurality of target coordinates.
Optionally, the density-based clustering algorithm is a DBSCAN algorithm, and the clustering module includes:
the input sub-module is configured to use the target coordinates, a preset scanning radius and a preset point threshold as input parameters of the DBSCAN algorithm, so as to obtain at least one coordinate cluster through the DBSCAN algorithm, wherein the scanning radius is a neighborhood threshold of any coordinate, the point threshold is a threshold of coordinate density in the target coordinate set, and the number of coordinates in the neighborhood threshold range of any coordinate in the at least one coordinate cluster meets the point threshold;
a selection submodule configured to acquire the coordinate cluster with the highest coordinate density from the at least one coordinate cluster.
Optionally, the target coordinate is a longitude and latitude coordinate of the mobile terminal, and the input sub-module is configured to:
carrying out ink card holder transformation on the target coordinates to obtain ink card holder projections of the target coordinates;
and taking the mercator projections of the target coordinates, the preset scanning radius and the preset point threshold value as input parameters of the DBSCAN algorithm.
Optionally, the positioning module is configured to:
and performing ink card tray inverse transformation on the coordinate value of the geometric center of the coordinate cluster with the highest coordinate density to obtain a longitude and latitude coordinate value as the position of the WLAN equipment.
According to a third aspect of the embodiments of the present disclosure, there is provided a positioning apparatus for a wireless local area network device, including:
a processor;
a memory for storing processor-executable instructions;
wherein the processor is configured to:
acquiring a plurality of target coordinates of a mobile terminal acquired within a preset time period, wherein the target coordinates are coordinates of the mobile terminal when a signal of a Wireless Local Area Network (WLAN) device received by the mobile terminal meets a preset condition;
clustering the target coordinates by using a density-based clustering algorithm to determine a coordinate cluster with the highest coordinate density;
and determining the position of the WLAN equipment according to the coordinate cluster with the highest coordinate density.
According to a fourth aspect of embodiments of the present disclosure, there is provided a computer-readable storage medium having stored thereon computer program instructions, which when executed by a processor, implement the steps of the positioning method of a wireless local area network device provided in the first aspect of the present disclosure.
The technical scheme provided by the embodiment of the disclosure can have the following beneficial effects: the method comprises the steps of screening the coordinates of the mobile terminal according to the signal intensity of the WLAN equipment received by the mobile terminal, selecting target coordinates capable of being used for positioning the WLAN equipment, clustering the target coordinates through a density-based clustering algorithm by taking the target coordinates as the input of a preset density-based clustering algorithm, so as to obtain a coordinate cluster with the highest coordinate density in the clustered coordinate clusters, and finally determining the position information of the WLAN equipment according to the coordinate cluster with the highest coordinate density. The method and the device can reduce the dependence on the signal intensity of the WLAN equipment when the position of the WLAN equipment is positioned, enable the positioning error precision to be controllable, and improve the positioning accuracy.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure.
Fig. 1 is a flow chart illustrating a method of positioning a wireless local area network device in accordance with an example embodiment;
fig. 2 is a flow chart illustrating another method of locating a wireless local area network device in accordance with an example embodiment;
fig. 3 is a flow chart illustrating yet another method of positioning a wireless local area network device in accordance with an exemplary embodiment;
FIG. 4 is a block diagram illustrating a positioning apparatus of a wireless local area network device in accordance with an exemplary embodiment;
FIG. 5 is a block diagram illustrating another positioning apparatus for a wireless local area network device in accordance with an exemplary embodiment;
FIG. 6 is a block diagram illustrating a positioning apparatus of yet another wireless local area network device in accordance with an exemplary embodiment;
fig. 7 is a block diagram illustrating a positioning apparatus of a wireless local area network device according to an example embodiment.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the exemplary embodiments below are not intended to represent all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present disclosure, as detailed in the appended claims.
Before introducing the positioning method, apparatus, and storage medium of the wireless local area network device provided by the present disclosure, an application scenario related to each embodiment in the present disclosure is first introduced, where a mobile terminal is located in a coverage area of a WLAN device, the mobile terminal can acquire a signal of the WLAN device, and meanwhile, the mobile terminal can acquire a position (longitude and latitude coordinates) of the mobile terminal through built-in map software or a positioning module. The WLAN device may be a Wi-Fi (Wireless-Fidelity, chinese) device, a WAPI (Wireless LAN Authentication and Privacy Infrastructure, chinese) device, or other WLAN-enabled devices. The mobile terminal may be, for example, a mobile terminal such as a smart phone, a tablet computer, a smart tv, a smart watch, a PDA (Personal Digital Assistant, chinese), a portable computer, or the like.
Fig. 1 is a flowchart illustrating a positioning method of a wireless local area network device according to an exemplary embodiment, as shown in fig. 1, the method includes the following steps:
in step 101, a plurality of target coordinates of the mobile terminal collected within a preset time period are obtained, where the target coordinates are coordinates of the mobile terminal when a signal of the WLAN device received by the mobile terminal meets a preset condition.
For example, since the WLAN device is usually located indoors, since the indoor physical environment can be complicated and there may be various wireless signal interferences, which cause various unpredictable factors, the signal strength of the WLAN device can only reflect the distance between the mobile terminal and the WLAN device in general due to multipath propagation and interference, i.e. the stronger the signal strength of the WLAN device, the closer the mobile terminal is to the WLAN device. If the position of the WLAN device is determined directly from the mapping relationship between the signal strength and the distance determined by the signal strength of the WLAN device and the radio wave propagation model, a large error may be generated in the positioning result. Therefore, the collected coordinates of the mobile terminal can be screened according to the signal strength of the WLAN device received by the mobile terminal, and a plurality of target coordinates capable of being used for positioning the WLAN device are selected. Further, since the WLAN device is movable, the coordinates of the mobile terminal collected within the preset time period can reflect the latest position of the WLAN device.
In step 102, a plurality of target coordinates are clustered by using a density-based clustering algorithm to determine a coordinate cluster with the highest coordinate density.
In an example, the density-based clustering algorithm can divide a plurality of data into different clusters according to the density, and in the coverage area of the WLAN device, when the mobile terminal is densely present, the position of the WLAN device can be reflected, so that a plurality of target coordinates are used as the input of the density-based clustering algorithm, the plurality of target coordinates are clustered through the density-based clustering algorithm, one or more coordinate clusters meeting preset conditions are obtained through clustering, and the coordinate cluster with the highest coordinate density is selected from the one or more coordinate clusters. Wherein, the preset condition may be: the distance between any two target coordinates in the coordinate cluster meets a certain condition, or the number of the target coordinates in the coordinate cluster meets a certain condition.
In step 103, the position of the WLAN device is determined according to the coordinate cluster with the highest coordinate density.
For example, the coordinate cluster with the highest coordinate density represents that the mobile terminals in the area corresponding to the target coordinate in the coordinate cluster are very densely present, and therefore, the position of the WLAN device can be reflected. For example, the coordinates of the geometric center of the coordinate cluster with the highest coordinate density may be used as the position of the WLAN device, or the coordinates of the geometric center of gravity of the coordinate cluster with the highest coordinate density may be used as the position of the WLAN device.
That is to say, the technical solution provided in the embodiment of the present disclosure is to determine a position where the activity of the trusted mobile terminal is dense through the steps and the method shown in steps 101-103, and use the position as the position of the WLAN device, so that the error of the position of the WLAN device can be reduced to not exceed the signal coverage of the WLAN device, for example, if the signal coverage of the WLAN device is a square circle with the signal coverage as the center being 20m, the error of the position of the WLAN device through the above method is not more than 20m at most.
In summary, according to the present disclosure, firstly, coordinates of the mobile terminal are screened according to the signal intensity of the WLAN device received by the mobile terminal, target coordinates capable of being used for positioning the WLAN device are selected, then, a plurality of target coordinates are used as input of a preset density-based clustering algorithm, the plurality of target coordinates are clustered through the density-based clustering algorithm, so as to obtain a coordinate cluster with the highest coordinate density in the clustered coordinate clusters, and finally, the position information of the WLAN device is determined according to the coordinate cluster with the highest coordinate density. The method and the device can reduce the dependence on the signal intensity of the WLAN equipment when the position of the WLAN equipment is positioned, enable the positioning error precision to be controllable, and improve the positioning accuracy.
Fig. 2 is a flowchart illustrating another positioning method for a wireless local area network device according to an exemplary embodiment, where as shown in fig. 2, the preset condition is a preset signal strength, and step 101 includes:
in step 1011, a plurality of position coordinates of the mobile terminal collected within a preset time period are obtained.
In step 1012, a coordinate with a signal strength of the WLAN device received by the mobile terminal greater than a preset signal strength is determined from the plurality of location coordinates of the mobile terminal, so as to obtain a plurality of target coordinates.
For example, in a preset time period, a plurality of position coordinates of the mobile terminal may be acquired according to a preset acquisition frequency, where the number of the position coordinates is a product of the preset time period and the acquisition frequency. Each of the plurality of location coordinates is filtered based on the signal strength of the WLAN device. Taking the first coordinate as any one of the plurality of position coordinates as an example, when the first coordinate is acquired, the signal intensity of the WLAN device received by the mobile terminal is greater than the preset signal intensity, the first coordinate belongs to the target coordinate, and if the signal intensity of the WLAN device received by the mobile terminal is less than or equal to the preset signal intensity, the first coordinate does not belong to the target coordinate.
In the embodiment, the position coordinates of the mobile terminal are screened by setting the preset signal intensity, so that the target coordinates capable of more accurately reflecting the position of the WLAN equipment are obtained, and the positioning accuracy of the WLAN equipment is improved.
Fig. 3 is a flowchart illustrating a positioning method for a wireless local area network device according to an exemplary embodiment, where as shown in fig. 3, the density-based clustering algorithm is a DBSCAN algorithm, and step 102 includes:
in step 1021, the target coordinates, the preset scanning radius and the preset point threshold are used as input parameters of the DBSCAN algorithm, so as to obtain at least one coordinate cluster through the DBSCAN algorithm, the scanning radius is a neighborhood threshold of any coordinate, the point threshold is a threshold of coordinate density in a target coordinate set, and the number of coordinates in a neighborhood threshold range of any coordinate in the at least one coordinate cluster all meets the point threshold.
In step 1022, a coordinate cluster with the highest coordinate density is obtained from the at least one coordinate cluster.
For example, the Density-Based clustering algorithm is a DBSCAN (English: Density-Based spatial clustering of Applications with Noise, Chinese: Density-Based clustering method with Noise) algorithm, and accordingly, the input parameters of the DBSCAN algorithm are as follows: a plurality of target coordinates, a preset scanning radius and a preset point threshold. The scanning radius is a neighborhood threshold of any coordinate, and the point threshold is a threshold of coordinate density in a target coordinate set. In the coordinate cluster obtained through clustering, the number of coordinates in the neighborhood threshold range satisfying any coordinate in the coordinate cluster satisfies the point threshold, wherein the condition that the number of coordinates in the neighborhood threshold range satisfying the point threshold can be understood as that the number of coordinates in the neighborhood threshold range satisfying any coordinate in the coordinate cluster is greater than or equal to the point threshold. The output of the DBSCAN algorithm is one or more clustered coordinate clusters, and the coordinate cluster with the highest coordinate density is selected from the one or more clustered coordinate clusters. And if the neighborhood threshold is 1.5 meters and the point threshold is 7, the clustered coordinate clusters all meet, wherein the point of the coordinate in the neighborhood of 1.5 meters of any target coordinate is more than or equal to 7.
In the embodiment, the DBSCAN algorithm is used for clustering the target coordinate values to obtain the coordinate cluster with the highest coordinate density, so that the accuracy of selecting the coordinate cluster with the highest coordinate density is improved.
Optionally, the target coordinate is a longitude and latitude coordinate of the mobile terminal, and step 1021 includes:
and carrying out ink card holder transformation on the plurality of target coordinates to obtain ink card holder projections of the plurality of target coordinates.
And taking the mercator projections of the target coordinates, the preset scanning radius and the preset point threshold value as input parameters of the DBSCAN algorithm.
Accordingly, step 103 includes:
and performing ink card tray inverse transformation on the coordinate value of the geometric center of the coordinate cluster with the highest coordinate density to obtain a longitude and latitude coordinate value as the position of the WLAN equipment.
For example, the target coordinates are obtained through map software or a positioning module built in the mobile terminal, and are in the form of longitude and latitude coordinates on a spherical surface, while the euclidean distance adopted by the DBSCAN algorithm is a distance on a plane, so that to cluster a plurality of target coordinates by using the DBSCAN algorithm, the plurality of target coordinates need to be subjected to mercator transformation, and mercator projection of the plurality of target coordinates is obtained. And then, clustering the target coordinates by taking the mercator projections of the target coordinates, the preset scanning radius and the preset point threshold value as input parameters of the DBSCAN algorithm. Similarly, after the coordinate cluster with the highest coordinate density is selected from the one or more coordinate clusters obtained through clustering, the coordinate of the geometric center of the coordinate cluster with the highest coordinate density is the coordinate on the plane, the longitude and latitude coordinate value on the corresponding spherical surface which is obtained through the reverse transformation of the mercator is needed, and the longitude and latitude coordinate value is used as the position of the WLAN device.
In the embodiment, the position of the mobile terminal is converted from longitude and latitude coordinates on a spherical surface to coordinates on a plane by carrying out mercator transformation on a plurality of target coordinates, so that the clustering precision of the DBSCAN algorithm can be improved.
In summary, according to the present disclosure, firstly, coordinates of the mobile terminal are screened according to the signal intensity of the WLAN device received by the mobile terminal, target coordinates capable of being used for positioning the WLAN device are selected, then, a plurality of target coordinates are used as input of a preset density-based clustering algorithm, the plurality of target coordinates are clustered through the density-based clustering algorithm, so as to obtain a coordinate cluster with the highest coordinate density in the clustered coordinate clusters, and finally, the position information of the WLAN device is determined according to the coordinate cluster with the highest coordinate density. The method and the device can reduce the dependence on the signal intensity of the WLAN equipment when the position of the WLAN equipment is positioned, enable the positioning error precision to be controllable, and improve the positioning accuracy.
Fig. 4 is a block diagram illustrating a positioning apparatus of a wireless local area network device according to an exemplary embodiment, and as shown in fig. 4, the apparatus 200 includes:
the acquiring module 201 is configured to acquire a plurality of target coordinates of the mobile terminal acquired within a preset time period, where the target coordinates are coordinates of the mobile terminal when a signal of the WLAN device received by the mobile terminal meets a preset condition.
A clustering module 202 configured to cluster the plurality of target coordinates by using a density-based clustering algorithm to determine a coordinate cluster with the highest coordinate density.
A location module 203 configured to determine a location of the WLAN device according to the coordinate cluster with the highest coordinate density.
Fig. 5 is a block diagram of another positioning apparatus for a wireless local area network device according to an exemplary embodiment, as shown in fig. 5, where the preset condition is a preset signal strength, and the obtaining module 201 includes:
the obtaining sub-module 2011 is configured to obtain a plurality of position coordinates of the mobile terminal collected within a preset time period.
The screening sub-module 2012 is configured to determine, from the plurality of location coordinates of the mobile terminal, a coordinate where the signal strength of the WLAN device received by the mobile terminal is greater than a preset signal strength, so as to obtain a plurality of target coordinates.
Fig. 6 is a block diagram illustrating a positioning apparatus of another wireless lan device according to an exemplary embodiment, where as shown in fig. 6, the density-based clustering algorithm is a DBSCAN algorithm, and the clustering module 202 includes:
the input sub-module 2021 is configured to use the multiple target coordinates, a preset scanning radius, and a preset point threshold as input parameters of the DBSCAN algorithm, so as to obtain at least one coordinate cluster through the DBSCAN algorithm, where the scanning radius is a neighborhood threshold of any coordinate, the point threshold is a threshold of coordinate density in a target coordinate set, and the number of coordinates in a neighborhood threshold range of any coordinate in the at least one coordinate cluster satisfies the point threshold.
A selecting sub-module 2022 configured to obtain a coordinate cluster with the highest coordinate density from the at least one coordinate cluster.
Optionally, the target coordinate is a longitude and latitude coordinate of the mobile terminal, and the input sub-module 2021 is configured to:
and carrying out ink card holder transformation on the plurality of target coordinates to obtain ink card holder projections of the plurality of target coordinates.
And taking the mercator projections of the target coordinates, the preset scanning radius and the preset point threshold value as input parameters of the DBSCAN algorithm.
Optionally, the positioning module 203 is configured to:
and performing ink card tray inverse transformation on the coordinate value of the geometric center of the coordinate cluster with the highest coordinate density to obtain a longitude and latitude coordinate value as the position of the WLAN equipment.
With regard to the apparatus in the above-described embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment related to the method, and will not be elaborated here.
In summary, according to the present disclosure, firstly, coordinates of the mobile terminal are screened according to the signal intensity of the WLAN device received by the mobile terminal, target coordinates capable of being used for positioning the WLAN device are selected, then, a plurality of target coordinates are used as input of a preset density-based clustering algorithm, the plurality of target coordinates are clustered through the density-based clustering algorithm, so as to obtain a coordinate cluster with the highest coordinate density in the clustered coordinate clusters, and finally, the position information of the WLAN device is determined according to the coordinate cluster with the highest coordinate density. The method and the device can reduce the dependence on the signal intensity of the WLAN equipment when the position of the WLAN equipment is positioned, enable the positioning error precision to be controllable, and improve the positioning accuracy.
The present disclosure also provides a computer readable storage medium having stored thereon computer program instructions which, when executed by a processor, implement the steps of the positioning method of a wireless local area network device provided by the present disclosure.
Fig. 7 is a block diagram illustrating a positioning apparatus 800 of a wireless local area network device according to an example embodiment. For example, the apparatus 800 may be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, an exercise device, a personal digital assistant, and the like.
Referring to fig. 7, the apparatus 800 may include one or more of the following components: a processing component 802, a memory 804, a power component 806, a multimedia component 808, an audio component 810, an input/output (I/O) interface 812, a sensor component 814, and a communication component 816.
The processing component 802 generally controls overall operation of the device 800, such as operations associated with display, telephone calls, data communications, camera operations, and recording operations. The processing component 802 may include one or more processors 820 to execute instructions to perform all or a portion of the steps of the method for locating a wireless local area network device described above. Further, the processing component 802 can include one or more modules that facilitate interaction between the processing component 802 and other components. For example, the processing component 802 can include a multimedia module to facilitate interaction between the multimedia component 808 and the processing component 802.
The memory 804 is configured to store various types of data to support operations at the apparatus 800. Examples of such data include instructions for any application or method operating on device 800, contact data, phonebook data, messages, pictures, videos, and so forth. The memory 804 may be implemented by any type or combination of volatile or non-volatile memory devices such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disks.
The multimedia component 808 includes a screen that provides an output interface between the device 800 and a user. In some embodiments, the screen may include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive an input signal from a user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundary of a touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 808 includes a front facing camera and/or a rear facing camera. The front camera and/or the rear camera may receive external multimedia data when the device 800 is in an operating mode, such as a shooting mode or a video mode. Each front camera and rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.
The audio component 810 is configured to output and/or input audio signals. For example, the audio component 810 includes a Microphone (MIC) configured to receive external audio signals when the apparatus 800 is in an operational mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signals may further be stored in the memory 804 or transmitted via the communication component 816. In some embodiments, audio component 810 also includes a speaker for outputting audio signals.
The I/O interface 812 provides an interface between the processing component 802 and peripheral interface modules, which may be keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to: a home button, a volume button, a start button, and a lock button.
The sensor assembly 814 includes one or more sensors for providing various aspects of state assessment for the device 800. For example, the sensor assembly 814 may detect the open/closed status of the device 800, the relative positioning of components, such as a display and keypad of the device 800, the sensor assembly 814 may also detect a change in the position of the device 800 or a component of the device 800, the presence or absence of user contact with the device 800, the orientation or acceleration/deceleration of the device 800, and a change in the temperature of the device 800. Sensor assembly 814 may include a proximity sensor configured to detect the presence of a nearby object without any physical contact. The sensor assembly 814 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 814 may also include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.
The communication component 816 is configured to facilitate communications between the apparatus 800 and other devices in a wired or wireless manner. The device 800 may access a wireless network based on a communication standard, such as WiFi, 2G or 3G, or a combination thereof. In an exemplary embodiment, the communication component 816 receives a broadcast signal or broadcast related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 816 further includes a Near Field Communication (NFC) module to facilitate short-range communications. For example, the NFC module may be implemented based on Radio Frequency Identification (RFID) technology, infrared data association (IrDA) technology, Ultra Wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.
In an exemplary embodiment, the apparatus 800 may be implemented by one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), controllers, micro-controllers, microprocessors or other electronic components for performing the above-described method for positioning a wireless local area network device.
In an exemplary embodiment, a non-transitory computer-readable storage medium comprising instructions, such as the memory 804 comprising instructions, executable by the processor 820 of the apparatus 800 to perform the above-described method of positioning a wireless local area network device is also provided. For example, the non-transitory computer readable storage medium may be a ROM, a Random Access Memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like. The method and the device can reduce the dependence on the signal intensity of the WLAN equipment when the position of the WLAN equipment is positioned, enable the positioning error precision to be controllable, and improve the positioning accuracy.
In summary, according to the present disclosure, firstly, coordinates of the mobile terminal are screened according to the signal intensity of the WLAN device received by the mobile terminal, target coordinates capable of being used for positioning the WLAN device are selected, then, a plurality of target coordinates are used as input of a preset density-based clustering algorithm, the plurality of target coordinates are clustered through the density-based clustering algorithm, so as to obtain a coordinate cluster with the highest coordinate density in the clustered coordinate clusters, and finally, the position information of the WLAN device is determined according to the coordinate cluster with the highest coordinate density.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
It will be understood that the present disclosure is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.
Claims (8)
1. A method for positioning a wireless local area network device, the method comprising:
acquiring a plurality of target coordinates of a mobile terminal acquired within a preset time period, wherein the target coordinates are obtained by map software or a positioning module built in the mobile terminal when a signal of a Wireless Local Area Network (WLAN) device received by the mobile terminal meets a preset condition;
clustering the target coordinates by using a density-based clustering algorithm to determine a coordinate cluster with the highest coordinate density;
determining the position of the WLAN equipment according to the coordinate cluster with the highest coordinate density;
the preset condition is preset signal intensity, and the acquiring of the plurality of target coordinates of the mobile terminal acquired within the preset time period includes:
acquiring a plurality of position coordinates of the mobile terminal acquired according to a preset acquisition frequency in the preset time period;
determining a coordinate in which the signal intensity of the WLAN equipment received by the mobile terminal is greater than the preset signal intensity from a plurality of position coordinates of the mobile terminal to obtain a plurality of target coordinates;
the density-based clustering algorithm is a DBSCAN algorithm, and determining the position of the WLAN device according to the coordinate cluster with the highest coordinate density includes:
and performing ink card tray inverse transformation on the coordinate value of the geometric center of the coordinate cluster with the highest coordinate density to obtain a longitude and latitude coordinate value as the position of the WLAN equipment.
2. The method of claim 1, wherein the clustering the plurality of target coordinates by using a preset density-based clustering algorithm to determine a coordinate cluster with the highest coordinate density comprises:
the target coordinates, a preset scanning radius and a preset point threshold are used as input parameters of the DBSCAN algorithm, so that at least one coordinate cluster is obtained through the DBSCAN algorithm, the scanning radius is a neighborhood threshold of any coordinate, the point threshold is a threshold of coordinate density in a target coordinate set, and the number of coordinates in the neighborhood threshold range of any coordinate in the at least one coordinate cluster meets the point threshold;
and obtaining the coordinate cluster with the highest coordinate density from the at least one coordinate cluster.
3. The method of claim 2, wherein the target coordinates are longitude and latitude coordinates of the mobile terminal, and wherein the using the target coordinates, a preset scanning radius and a preset point threshold as input parameters of the DBSCAN algorithm comprises:
carrying out ink card holder transformation on the target coordinates to obtain ink card holder projections of the target coordinates;
and taking the mercator projections of the target coordinates, the preset scanning radius and the preset point threshold value as input parameters of the DBSCAN algorithm.
4. An apparatus for locating a wireless local area network device, the apparatus comprising:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is configured to acquire a plurality of target coordinates of the mobile terminal acquired within a preset time period, the target coordinates are the coordinates of the mobile terminal when a signal of the WLAN equipment received by the mobile terminal meets a preset condition, and the target coordinates are acquired through map software or a positioning module built in the mobile terminal;
a clustering module configured to cluster the plurality of target coordinates by using a density-based clustering algorithm to determine a coordinate cluster having a highest coordinate density;
a positioning module configured to determine a location of the WLAN device according to the coordinate cluster with the highest coordinate density;
the acquisition module includes:
the acquisition submodule is configured to acquire a plurality of position coordinates of the mobile terminal, which are acquired according to a preset acquisition frequency within the preset time period;
the screening submodule is configured to determine, from the plurality of position coordinates of the mobile terminal, a coordinate in which the signal intensity of the WLAN device received by the mobile terminal is greater than the preset signal intensity, so as to obtain the plurality of target coordinates;
the density-based clustering algorithm is a DBSCAN algorithm, and the positioning module is configured to:
and performing ink card tray inverse transformation on the coordinate value of the geometric center of the coordinate cluster with the highest coordinate density to obtain a longitude and latitude coordinate value as the position of the WLAN equipment.
5. The apparatus of claim 4, wherein the clustering module comprises:
the input sub-module is configured to use the target coordinates, a preset scanning radius and a preset point threshold as input parameters of the DBSCAN algorithm, so as to obtain at least one coordinate cluster through the DBSCAN algorithm, wherein the scanning radius is a neighborhood threshold of any coordinate, the point threshold is a threshold of coordinate density in the target coordinate set, and the number of coordinates in the neighborhood threshold range of any coordinate in the at least one coordinate cluster meets the point threshold;
a selection submodule configured to acquire the coordinate cluster with the highest coordinate density from the at least one coordinate cluster.
6. The apparatus of claim 5, wherein the target coordinates are longitude and latitude coordinates of the mobile terminal, and wherein the input sub-module is configured to:
carrying out ink card holder transformation on the target coordinates to obtain ink card holder projections of the target coordinates;
and taking the mercator projections of the target coordinates, the preset scanning radius and the preset point threshold value as input parameters of the DBSCAN algorithm.
7. A positioning apparatus for a wireless local area network device, comprising:
a processor;
a memory for storing processor-executable instructions;
wherein the processor is configured to:
acquiring a plurality of target coordinates of a mobile terminal acquired within a preset time period, wherein the target coordinates are obtained by map software or a positioning module built in the mobile terminal when a signal of a Wireless Local Area Network (WLAN) device received by the mobile terminal meets a preset condition;
clustering the target coordinates by using a density-based clustering algorithm to determine a coordinate cluster with the highest coordinate density;
determining the position of the WLAN equipment according to the coordinate cluster with the highest coordinate density;
the preset condition is preset signal intensity, and the acquiring of the plurality of target coordinates of the mobile terminal acquired within the preset time period includes:
acquiring a plurality of position coordinates of the mobile terminal acquired according to a preset acquisition frequency in the preset time period;
determining a coordinate in which the signal intensity of the WLAN equipment received by the mobile terminal is greater than the preset signal intensity from a plurality of position coordinates of the mobile terminal to obtain a plurality of target coordinates;
the density-based clustering algorithm is a DBSCAN algorithm, and determining the position of the WLAN device according to the coordinate cluster with the highest coordinate density includes:
and performing ink card tray inverse transformation on the coordinate value of the geometric center of the coordinate cluster with the highest coordinate density to obtain a longitude and latitude coordinate value as the position of the WLAN equipment.
8. A computer-readable storage medium, on which computer program instructions are stored, which program instructions, when executed by a processor, carry out the steps of the method according to any one of claims 1 to 3.
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| CN110888866B (en) * | 2019-12-05 | 2023-01-17 | 秒针信息技术有限公司 | Data expansion method and device, data processing equipment and storage medium |
| CN111698332A (en) * | 2020-06-23 | 2020-09-22 | 深圳壹账通智能科技有限公司 | Method, device and equipment for distributing business objects and storage medium |
| CN111815361B (en) * | 2020-07-10 | 2024-06-18 | 北京思特奇信息技术股份有限公司 | Region boundary calculation method, device, electronic equipment and storage medium |
| CN113836250A (en) * | 2021-09-09 | 2021-12-24 | 摩拜(北京)信息技术有限公司 | Vehicle positioning method and device and electronic equipment |
| CN114430530B (en) * | 2022-04-06 | 2022-06-21 | 香港中文大学（深圳） | Space division method, apparatus, device, medium, and program product |
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