CN111836196B

CN111836196B - Indoor positioning method and system

Info

Publication number: CN111836196B
Application number: CN202010529354.0A
Authority: CN
Inventors: 熊运余; 何梦园; 陈果; 戚鑫
Original assignee: Chengdu Lingqi Space Software Co ltd; Sichuan University
Current assignee: Chengdu Lingqi Space Software Co ltd; Sichuan University
Priority date: 2020-06-11
Filing date: 2020-06-11
Publication date: 2022-10-21
Anticipated expiration: 2040-06-11
Also published as: CN111836196A

Abstract

The invention relates to the field of indoor positioning algorithms, and discloses an indoor positioning method, which comprises the steps of receiving one coordinate signal sent by positioning environment equipment; determining a plurality of primary coordinates based on the coordinate signals; secondary coordinates are determined based on the plurality of primary coordinates and the coordinate signal. The invention can realize the purpose of stable and accurate positioning, obtain a plurality of distances between the indoor equipment and determine the minimum value of the distances, and can more stably and accurately determine the position of the equipment.

Description

Indoor positioning method and system

Technical Field

The invention relates to the field of indoor positioning algorithms, in particular to an indoor positioning method.

Background

With the development of communication technology, location-based services have become an emerging mobile internet industry and have a good development prospect. Accordingly, the need to quickly and accurately obtain location information of a mobile terminal is becoming more urgent. The location information may also be used to support location-based services and improve network management, improving the quality of location services and network performance. Therefore, a positioning technology and a related positioning system capable of rapidly, accurately and stably acquiring location information in a wireless network have become a current research hotspot. At present, the accuracy of outdoor positioning technology such as satellite positioning can reach centimeter level, but no economic and mature scheme exists in indoor environment, mainly because of the characteristics of complex indoor positioning environment, multiple interference sources, direct wave path loss, multipath propagation, variable environment and the like. Because of the shelter of the building, the loss of the GPS signal penetrating the building is too large, and the positioning capability is greatly reduced, so that the GPS is not suitable for positioning in an indoor environment. In addition to the requirement of pure positioning technology, some artificial constraints, such as security, privacy protection, etc., also present new challenges for indoor positioning systems. The positioning precision and accuracy of the currently common indoor positioning technology are not high enough, so that a new method needs to be found or the existing positioning method needs to be optimized to meet the positioning requirements of people.

The distance location method based on signal measurement technology commonly used in fingerprint location can be divided into four location methods, i.e., time of arrival (TOA) measurement, time difference of arrival (TDOA) measurement, angle of arrival (AOA) measurement, and Received Signal Strength (RSSI) measurement. Due to the complexity of the indoor radio propagation effect, the diversity of short-distance wireless communication signals and the randomness of wireless facility deployment, the method for estimating the distance based on time, angle and the like has too low positioning accuracy to be practical. Location fingerprinting based on Received Signal Strength Indication (RSSI) is a research focus.

Because the GPS positioning cannot meet the requirements of indoor positioning, various indoor positioning methods have been proposed, and most of them are implemented by using related sensors, such as wifi, bluetooth, and RFID devices. But in the civilian area, wiFi or bluetooth is mostly used for positioning. Existing positioning algorithms can be divided into fingerprint-based positioning and signal-based positioning, and the signal-based positioning has poor positioning effect due to instability of signal propagation indoors, so that most applications use fingerprint-based positioning. And confirming the location according to the similarity between the signal and the fingerprint based on the location of the fingerprint, firstly, collecting the fingerprint of a location environment, associating the signal intensity characteristic with a corresponding location, and secondly, matching the searched signal with a fingerprint library by using a corresponding matching method in a location stage so as to confirm the fingerprint which is most matched with the searched signal and further determine the location. However, the existing fingerprint positioning algorithms such as wknn, svm, knn and the like have the problem of unstable positioning, i.e. the instantaneous error is large or the algorithm cannot adapt to the situation of poor signal, so that the positioning effect is not as expected.

Therefore, a method for fusing fingerprint positioning, which can stably and accurately position indoor equipment, is urgently needed

Disclosure of Invention

Based on the above problems, the present invention provides an indoor positioning method. The invention can realize the purpose of stable and accurate positioning, obtain a plurality of distances between the indoor equipment and determine the minimum value of the distances, and can more stably and accurately determine the position of the equipment.

In order to solve the technical problems, the technical scheme adopted by the invention is as follows:

the invention provides an indoor positioning method, which is characterized by comprising the following steps: receiving one coordinate signal sent by positioning environment equipment; determining a plurality of primary coordinates based on the coordinate signals; secondary coordinates are determined based on the plurality of primary coordinates and the coordinate signal.

The invention provides a system for fusing fingerprint positioning, which comprises a receiving module, a primary coordinate determination module and a secondary coordinate determination module; the receiving module is used for receiving one of the coordinate signals sent by the positioning environment equipment; the primary coordinate determination module is used for determining a plurality of primary coordinates based on the coordinate signals; the secondary coordinate determination module is used for determining secondary coordinates based on the plurality of primary coordinates and the coordinate signals.

A third aspect of the present invention provides an apparatus for fusing fingerprint localization, comprising a processor and a storage medium, wherein the storage medium is used for storing computer instructions, and the processor is used for executing the computer instructions and implementing a method for indoor localization as claimed in any one of claims 1 to 7.

A fourth aspect of the present invention provides a computer-readable storage medium, which stores computer instructions for implementing the method for indoor positioning according to any one of claims 1 to 7 when the computer instructions are executed by a processor.

In some embodiments, the steps further comprise: determining a plurality of primary coordinates based on the coordinate signals comprises: determining the primary coordinates based on a fingerprint library and a fingerprint location algorithm, wherein the fingerprint library comprises associations of signal strength values with corresponding locations.

In some embodiments, the steps further comprise: the fingerprint database construction process comprises the following steps: collecting a fingerprint of the location environment, wherein the fingerprint comprises signal strength values emitted by a location environment device and received by a corresponding location; and constructing a fingerprint library based on the fingerprints of the positioning environment.

In some embodiments, the steps further comprise: the fingerprint positioning algorithm comprises at least two of SVM, WKNN algorithm and KNN algorithm.

In some embodiments, the steps further comprise: and determining a three-level coordinate based on the first-level coordinate obtained by the SVM algorithm and the WKNN algorithm.

In some embodiments, the steps further comprise: and determining the secondary coordinate based on the tertiary coordinate, the primary coordinate and the coordinate signal.

In some embodiments, the steps further comprise: the secondary coordinates determined based on the plurality of primary coordinates and the coordinate signal include: determining distances between the plurality of primary coordinates and the coordinate signals; determining the secondary coordinates based on distance.

Additional features of the present application will be set forth in part in the description which follows. Additional features of some aspects of the present application will be apparent to those of ordinary skill in the art upon examination of the following description and accompanying drawings or may be learned by production or operation of the embodiments. The features of the present disclosure may be realized and attained by practice or use of the methodologies, instrumentalities and combinations of the various aspects of the specific embodiments described below.

Drawings

Certain features of various embodiments of the invention are set forth with particularity in the appended claims. A better understanding of the features and advantages of the present invention will be obtained by reference to the following detailed description that sets forth illustrative embodiments, in which the principles of the invention are utilized, and the accompanying drawings of which:

fig. 1 is a schematic diagram of an application scenario of a system for fusing fingerprint positioning according to some embodiments of the present disclosure.

FIG. 2 is an example flow diagram of a method of fused fingerprint localization, shown in accordance with some embodiments herein.

FIG. 3 is an example flow diagram of a method of increasing fused fingerprint positioning, shown in accordance with some embodiments herein.

FIG. 4 is a block diagram of a system for fused fingerprint localization as shown in some embodiments in accordance with the present description.

FIG. 5 is a flowchart of an example of use of a system for fused fingerprint localization, shown in accordance with some embodiments of the present description.

Detailed Description

In order to more clearly illustrate the technical solutions of the embodiments of the present specification, the drawings used in the description of the embodiments will be briefly described below. It is obvious that the drawings in the following description are only examples or embodiments of the present description, and that for a person skilled in the art, the present description can also be applied to other similar scenarios on the basis of these drawings without inventive effort. Unless otherwise apparent from the context, or stated otherwise, like reference numbers in the figures refer to the same structure or operation.

It should be understood that "system", "device", "unit" and/or "module" as used herein is a method for distinguishing different components, elements, parts, portions or assemblies at different levels. However, other words may be substituted by other expressions if they accomplish the same purpose.

As used in this specification and the appended claims, the terms "a," "an," "the," and/or "the" are not to be taken in a singular sense, but rather are to be construed to include a plural sense unless the context clearly dictates otherwise. In general, the terms "comprises" and "comprising" merely indicate that steps and elements are included which are explicitly identified, that the steps and elements do not form an exclusive list, and that a method or apparatus may include other steps or elements.

Flow charts are used in this description to illustrate operations performed by a system according to embodiments of the present description. It should be understood that the preceding or following operations are not necessarily performed in the exact order in which they are performed. Rather, the steps may be processed in reverse order or simultaneously. Meanwhile, other operations may be added to or removed from these processes.

Currently, indoor positioning is increasingly emphasized by people, and nowadays, fingerprint positioning is a normal status. How to accurately locate the indoor equipment is crucial in location fingerprinting. The idea of positioning the indoor equipment is to position the indoor equipment based on the position fingerprint of signal strength, the positioning indoor equipment does not only perform position fingerprint positioning through an access point of WiFi and mobile equipment, but transmits signals through equipment to be positioned, and receiving equipment senses the signals or information of the equipment to be positioned and positions the equipment through a fingerprint positioning algorithm. The position fingerprint positioning can position indoor equipment in a complex indoor environment. The position fingerprint positioning can be applied to various scenes, and relates to but is not limited to the petrochemical industry, the building construction industry, the electric power energy industry, the coal mine/mine industry, the tunnel/subway construction industry, the prison/guard post and the like.

Location fingerprint positioning based on signal strength is to collect fingerprints in the positioning environment, associate signal strength characteristics with corresponding locations, and then match the searched signal strength with a fingerprint library by using a corresponding matching method in the positioning stage so as to determine the most matched fingerprint and further determine the location.

In the above scheme, a core problem is how to obtain a stable and accurate positioning result on the premise of positioning the indoor equipment, that is, the equipment to be positioned can be stably and accurately positioned indoors even when the indoor signal is poor or the instantaneous error is large. Therefore, in order to obtain a stable and accurate positioning result, some embodiments of the present disclosure provide an indoor positioning method, which may measure a plurality of primary coordinates relative to a positioning environment device in a plurality of matching methods based on one of coordinate signals sent by the positioning environment device, compare distances between the plurality of primary coordinates and the positioning environment device, and determine a coordinate with a minimum distance from the positioning environment device as a secondary coordinate. It should be understood that the above examples are by way of illustration only and should not be construed to limit the present solution. The technical scheme disclosed by the specification is illustrated through the description of the attached drawings.

Fig. 1 is a schematic diagram of an application scenario of a system for fusing fingerprint positioning according to some embodiments of the present disclosure. As shown in FIG. 1, the system for fused fingerprint location may include a signal receiver 110, a location context device 120, and a fingerprint repository 130.

The signal receiver 110 may be a device with data acquisition, storage, computation, and/or transmission capabilities, such as a tablet, a cell phone, a smart device, a headset, and the like. The signal receiver 110 may be configured to perform a fingerprinting algorithm based on the received signals and based on their signal strengths to derive specific location coordinates of the signal receiver 110 relative to the localization environment device 120. For example, the signal receiver 110 may acquire a signal via the localization environment device 120 and then perform a fingerprint localization algorithm based on the strength of the acquired signal to obtain specific location coordinates of the signal receiver 110 relative to the localization environment device 120. In some embodiments, the signal receiver may be provided in a tablet, a cell phone, a smart device, or a bluetooth device.

The positioning environment device 120 is a device capable of sending a signal, the positioning environment in the positioning environment device 120 refers to an indoor place such as a mall, a movie theater, a hospital, an indoor parking lot, a home, etc., and the device in the positioning environment device 120 may be a router, a computer, a mobile phone, a base station, etc. The positioning environment device 120 sends out a signal, and the signal receiver 110 receives the signal and obtains the specific position of the signal receiver 110 relative to the positioning environment device 120 through a fingerprint positioning algorithm.

The location fingerprints in the fingerprint repository 130 can be of various types, and any "location-unique" (helpful in distinguishing locations) feature can be used as a location fingerprint. Such as the multipath structure of the communication signal at a location, whether an access point or base station can be detected at a location, the RSSI (received signal strength) of the signal from the base station detected at a location, the round trip time or delay of the signal when communicating at a location, can all be used as a location fingerprint, or can be combined to be used as a location fingerprint, the most common being the signal strength. In some embodiments, the localization environment device emits a signal and the signal receiver 110 determines the location of the localization environment device based on the signal strength of the received signal.

FIG. 2 is an example flow diagram of a method of fused fingerprint location, shown in accordance with some embodiments of the present description. Process 200 may be performed by signal receiver 110. For example, the process 200 may be stored in the signal receiver 110 in the form of a program or instructions that, when executed in a locatable environment, may implement the process 200. As shown in fig. 2, the process 200 may include:

step 201, receiving one of the coordinate signals sent by the positioning environment device. Step 201 may be performed by the receiving module.

In some embodiments, the location environment devices 120 participating in the location determination may be different devices such as a router, a computer, a cell phone, a base station, a smart watch, or other smart device. For example, some of the positioning environment devices 120 participating in positioning may be routers, some of the positioning environment devices 120 may be computers, some of the positioning environment devices 120 may be handsets, some of the positioning environment devices 120 may be base stations, and some of the positioning environment devices 120 may be smartwatches or other smart devices. In some embodiments, the coordinate signal may be a signal strength transmitted by the positioning environment device 120 participating in the positioning. For example, for an application scenario of the petrochemical industry, it is an important means of the petrochemical industry to perform chemical refinement security management and production process control, and the coordinate signal may be the signal intensity transmitted by the positioning environment device 120. For another example, in the coal mine industry, the position signal is an important safety signal for the underground personnel, and the accuracy of the position signal determines the positioning of the position of the underground personnel when a mine disaster occurs, so that the position signal can be a coordinate signal transmitted by the positioning environment equipment. For another example, for an application scene of a prison/guard, the application of the prison/guard to the position signal realizes all-weather roll calling of prisoners, performs 24-hour position monitoring and track tracking on prisoners, reduces the risk of monitoring and law enforcement, enables the monitoring work to be intelligent, improves the three-dimensional prevention and control capability, and quickly responds to emergencies. For another example, for an application scene of the building construction industry, site personnel support real-time positioning, intelligent attendance and working hour counting functions based on coordinate signals, the site management efficiency of the site is improved, the site order is maintained, site intelligent supervision is helped in an all-around manner, multi-field accurate positioning and overall operation scheduling control are realized, an electronic fence function is provided, and the personnel can give an alarm immediately when entering a dangerous area; when a dangerous condition occurs, the system can issue an evacuation command to constructors according to regions, the constructors can also automatically alarm through a positioning label SOS key, and safety rescue is guaranteed in real time; the system can monitor the behaviors of various personnel and effectively prevent safety accidents. For another example, for an application scenario of the power energy industry, the power plant can realize safe production control and safe construction control based on the coordinate signal. For another example, for an application scene of the tunnel/subway construction industry, all-weather attendance checking is supported for an indoor positioning system of tunnel workers, the workers can be automatically (position) tracked in real time, the non-card detection can be carried out by combining a camera, the movement track and the position distribution of the workers in the tunnel can be comprehensively mastered, and the bidirectional alarm under the emergency condition can be realized. Most importantly, when a tunnel accident happens, the position information of trapped people can be found rapidly, so that the safety of the people is guaranteed, and the management efficiency is effectively improved.

In some embodiments, the location environment of location environment device 120 is a mine, tunnel, hospital, mall, movie theater, prison, and other indoor environment.

In some embodiments, the coordinate signals may be used for position location, intelligent attendance and time statistics, and the like. For example, taking position location as an example, the coordinate signal may be the signal strength transmitted by the positioning environment device 120. For another example, taking intelligent attendance as an example, the intelligent attendance may be positioning of the employee arrival time based on the signal range transmitted by the positioning environment device.

In some embodiments, the device 120 for receiving the coordinate signal sent by the positioning environment may be a mobile phone, a pad, a smart watch, a smart device, or other different devices.

In some embodiments, a coordinate signal from the positioning environment device 120 may be received by the receiving module 310, where the coordinate signal is a signal strength. After acquiring the coordinate signal, a plurality of primary coordinates (the primary coordinates may refer to alternatively determined coordinates) may be determined by the primary coordinate determination module 320 based on the coordinate signal, and the determination of the plurality of primary coordinates may be based on a fingerprint library and weighted by the SVM algorithm, the WKNN algorithm, the KNN algorithm, the SVM, and the WKNN algorithm, respectively. After the plurality of primary coordinates are determined, a secondary coordinate (the secondary coordinate may refer to a determined location coordinate) may be determined by the secondary coordinate determination module 330 based on the plurality of primary coordinates and the signal strength, where the secondary coordinate is a closest coordinate of the plurality of primary coordinates to the location environment device.

In some embodiments, the fingerprint repository 130 construction process may also be performed prior to receiving one of the coordinate signals emitted by the positioning environment device 120. The fingerprint database 130 may be a database constructed by collecting fingerprints at various locations of a positioning device (e.g., a signal receiver) performing the process 200. The fingerprints in the fingerprint repository 130 may refer to signal strength values emitted by the location-related devices and received by the corresponding locations. The construction of the database 130 requires a cumbersome survey over a designated area, and the collected data is sometimes referred to as a training set. The fingerprint repository 130 is constructed to associate the corresponding location of the location environment with the strength value at which it can receive the signal from the location environment device 120. As an example, signal strength values emitted by the positioning environment device 120 are collected at respective locations in the positioning environment, and the signal strength values are associated with the respective locations, i.e., the signal strength is associated with location information of the positioning environment.

At step 202, a plurality of primary coordinates are determined based on the coordinate signals. Step 202 may be performed by a primary coordinate determination module 320.

In some embodiments, the primary coordinate determination module 320 may process the coordinate signals through a fingerprint location algorithm. The fingerprint positioning algorithm comprises an SVM algorithm, a WKNN algorithm, a KNN algorithm or a more complex calculation method, and a plurality of first-level coordinates can be obtained based on the various fingerprint positioning algorithms.

And 204, determining a three-level coordinate based on the primary coordinate obtained by the SVM algorithm and the WKNN algorithm. Step 204 may be performed by a primary coordinate determination module 320.

Fig. 3, in some embodiments, the more complex calculation method performed by the primary coordinate determination module 320 determines the tertiary coordinates for the primary coordinates obtained based on the SVM algorithm and the WKNN algorithm, and weights the positioning results (primary coordinates) obtained based on the SVM algorithm and the WKNN algorithm to obtain the tertiary coordinates.

Step 203, determining secondary coordinates based on the plurality of primary coordinates and the coordinate signal. Step 203 may be performed by secondary coordinate determination module 330.

In some embodiments, the two-pole coordinate determination module 330 may determine the secondary coordinates based on a plurality of primary coordinates, i.e., determine the secondary coordinates among a plurality of alternatively determined coordinates (primary coordinates), thereby providing more accurate location of the signal receiver 110.

Step 205, determining a secondary coordinate based on the tripolar coordinate, the primary coordinate, and the coordinate signal. Step 205 may be performed by secondary coordinate determination module 330.

Fig. 3, in some embodiments, the secondary coordinate is determined based on the tertiary coordinate, the primary coordinate, and the coordinate signal, and the secondary coordinate determination module 330 adds the tertiary coordinate to determine the secondary coordinate based on a plurality of primary coordinates, that is, adds the alternatively determined coordinates, and obtains the secondary coordinate (determined location coordinate) from the plurality of alternatively determined coordinates, thereby increasing the location accuracy of the secondary coordinate.

That is, as shown in fig. 5, the receiving module receives the signal strength and obtains the strongest signal value R, determines whether R is greater than the threshold value M, if so, ends the positioning, otherwise, the primary coordinate determining module 320 obtains a plurality of primary coordinates (S, W, K) at a certain distance from the positioning environment device through a plurality of fingerprint positioning algorithms (SVM algorithm, WKNN algorithm, KNN algorithm) and based on the obtained signal strength, and the primary coordinate determining module 320 weights the primary coordinates S and W obtained by the SVM algorithm and the WKNN algorithm to obtain the tertiary coordinates SW at a certain distance from the positioning environment device. The secondary coordinate determination module 330 first determines whether the strongest signal value R is less than N and only R signal exists, if so, the location is the midpoint between the device positions P and W, and the location is finished. If not, calculating the distance between the first-level coordinate and the third-level coordinate and the positioning environment equipment, taking the position of the minimum distance between the first-level coordinate and the third-level coordinate and the positioning environment equipment, and finishing positioning.

In some embodiments, the location environment has a fingerprint repository 130, and SVM and KNN regression training is performed on the fingerprint repository 130 to obtain correlation models S and K, with WKNN not being used for training. Under the positioning environment, the M value is-55, and the N value is-80. The maximum value of the signal in the fingerprint data is-40, and the minimum value is-95.

Let the current signal value array be [ { rssi: -60, device.

rssi is the signal value, device is the device ID, and the locations calculated using the S, K model and WKNN are S, K, W, respectively. The maximum signal value in rssi at this time is-60, with position P. Since it is between M and N, the distances between S, K, W and P are calculated as SP, KP, WP, respectively. And the weighted positioning SW between the WKNN and the SVM is as follows:

SW＝((-40-(-60))/(-40-(-95)))*(SP/(SP+WP)*W)+(1-(-40-(-60))/(-40-(-95))*S

and calculating the distance from SW to P as SWP, wherein the median values of KP, SP, SWP and WP are respectively 10.12610223 m, 5.8209593 m, 1.72646838 m and 4.00918751 m, and then selecting SWP as final positioning, namely SVM and WKNN weighted positioning values. The final distances between the final positioning value and the actual positioning value L are 10.146943106436, 5.816695395832251, 1.723419173994553 and 4.002811060328816 meters respectively, so that the invention can be seen to obtain better positioning effect.

The average error and the maximum error of the multiple groups of positioning data in the existing environment are improved by statistics. The statistical results are as follows (units/m):

in some embodiments, FIG. 5, determining distances of a plurality of primary coordinates from the coordinate signal; secondary coordinates are determined based on the distance. The secondary coordinates (determined positioning coordinates) are determined by calculating the minimum distance between the primary coordinates and the coordinate signals, and the most accurate positioning coordinates can be obtained from positioning results obtained by a plurality of fingerprint positioning algorithms.

It should be noted that the above description related to the flow 200 is only for illustration and description, and does not limit the application scope of the present specification. Various modifications and alterations to flow 200 will be apparent to those skilled in the art in light of this description. However, such modifications and variations are intended to be within the scope of the present description. For example, the

steps

202 and 204 may be performed in parallel, etc., as described herein with respect to flow steps.

FIG. 4 illustrates modules of a system that incorporates fingerprint location according to some embodiments of the present description. The system may receive the coordinate signal of the positioning environment device 120, and obtain a plurality of primary coordinates from the coordinate signal based on a fingerprint positioning algorithm for the coordinate signal, and obtain a minimum value from the positioning environment device among the plurality of primary coordinates as a secondary coordinate. As shown in fig. 4, the system may include a receiving module 310, a primary coordinate determination module 320, and a secondary coordinate determination module 330.

The receiving module 310 may receive a coordinate signal.

In some embodiments, the receiving module 310 may acquire coordinate signals of the positioning environment device 120. The coordinate signal may be a signal strength. In some embodiments, the coordinate signal is the strongest signal strength.

The primary coordinate determination module 320 may process the coordinate signal based on a fingerprint location algorithm to obtain primary coordinates.

The secondary coordinate determination module 330 may determine the coordinate closest to the location environment device as the secondary coordinate from the primary coordinates derived from the plurality of fingerprint location algorithms.

For a detailed description of the modules of the system for fused fingerprint localization, reference may be made to the flow chart section of the present application, for example, the related description of fig. 2 to 3.

It should be understood that the system and its modules shown in FIG. 4 may be implemented in a variety of ways. For example, in some embodiments, the system and its modules may be implemented in hardware, software, or a combination of software and hardware. Wherein the hardware portion may be implemented using dedicated logic; the software portions may be stored in a memory and executed by a suitable instruction execution system, such as a microprocessor or specially designed hardware. Those skilled in the art will appreciate that the methods and systems described above may be implemented using computer executable instructions and/or embodied in processor control code, for example such code provided on a carrier medium such as a diskette, CD-or DVD-ROM, programmable memory such as read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. The system and its modules in this specification may be implemented not only by hardware circuits such as very large scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., but also by software executed by various types of processors, for example, or by a combination of the above hardware circuits and software (e.g., firmware).

It should be noted that the above description of the system for fusing fingerprint positioning and the modules thereof is only for convenience of description and should not limit the present specification to the scope of the illustrated embodiments. It will be appreciated by those skilled in the art that, given the teachings of the present system, any combination of modules or sub-system configurations may be used to connect to other modules without departing from such teachings. For example, in some embodiments, for example, the receiving module, the primary coordinate determination module, and the secondary coordinate determination module disclosed in fig. 4 may be different modules in a system, and it may be said that one module realizes the functions of two or more modules. For example, the receiving module and the primary coordinate determination module may be two modules, or one module may have both the acquiring and processing functions. For example, each module may share one memory module, and each module may have its own memory module. Such variations are within the scope of the present description.

The embodiments of the present disclosure may bring about beneficial effects including, but not limited to: (1) In the system fusing fingerprint positioning, a plurality of primary coordinates are determined based on a coordinate signal to obtain a plurality of alternatively determined coordinates, and a coordinate closest to the positioning environment equipment 120 is selected from the plurality of alternatively determined coordinates. (2) And determining a three-level coordinate for the first-level positioning coordinate obtained based on an SVM algorithm and a WKNN algorithm, so that a candidate determined coordinate is added, and determining a second-level coordinate is based on a tripolar coordinate and a dipolar coordinate, namely, the error of the second-level coordinate is reduced. (3) The secondary coordinates are determined based on the primary coordinates and the distance of the coordinate signals, thereby making the signal receiver more accurate relative to the coordinates between the positioning environment devices.

Having thus described the basic concept, it will be apparent to those skilled in the art that the foregoing detailed disclosure is to be considered as illustrative only and not limiting, of the present invention. Various modifications, improvements and adaptations to the present description may occur to those skilled in the art, though not explicitly described herein. Such modifications, improvements and adaptations are proposed in the present specification and thus fall within the spirit and scope of the exemplary embodiments of the present specification.

Also, the description uses specific words to describe embodiments of the specification. Reference throughout this specification to "one embodiment," "an embodiment," and/or "some embodiments" means that a particular feature, structure, or characteristic described in connection with at least one embodiment of the specification is included. Therefore, it is emphasized and should be appreciated that two or more references to "an embodiment" or "one embodiment" or "an alternative embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, some features, structures, or characteristics of one or more embodiments of the specification may be combined as appropriate.

Moreover, those skilled in the art will appreciate that aspects of the present description may be illustrated and described in terms of several patentable categories or situations, including any new and useful combination of processes, machines, manufacture, or materials, or any new and useful modification thereof. Accordingly, aspects of this description may be performed entirely by hardware, entirely by software (including firmware, resident software, micro-code, etc.), or by a combination of hardware and software. The above hardware or software may be referred to as "data block," module, "" engine, "" unit, "" component, "or" system. Furthermore, aspects of the present description may be represented as a computer product, including computer readable program code, embodied in one or more computer readable media.

The computer storage medium may comprise a propagated data signal with the computer program code embodied therewith, for example, on baseband or as part of a carrier wave. The propagated signal may take any of a variety of forms, including electromagnetic, optical, etc., or any suitable combination. A computer storage medium may be any computer-readable medium that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code located on a computer storage medium may be propagated over any suitable medium, including radio, cable, fiber optic cable, RF, or the like, or any combination of the preceding.

Computer program code required for the operation of various portions of this specification may be written in any one or more programming languages, including an object oriented programming language such as Java, scala, smalltalk, eiffel, JADE, emerald, C + +, C #, VB.NET, python, and the like, a conventional programming language such as C, visual Basic, fortran 2003, perl, COBOL 2002, PHP, ABAP, a dynamic programming language such as Python, ruby, and Groovy, or other programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any network format, such as a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet), or in a cloud computing environment, or as a service, such as a software as a service (SaaS).

Additionally, the order in which elements and sequences are described in this specification, the use of numerical letters, or other designations are not intended to limit the order of the processes and methods described in this specification, unless explicitly stated in the claims. While certain presently contemplated useful embodiments of the invention have been discussed in the foregoing disclosure by way of various examples, it is to be understood that such detail is solely for that purpose and that the appended claims are not limited to the disclosed embodiments, but, on the contrary, are intended to cover all modifications and equivalent arrangements that are within the spirit and scope of the embodiments herein described. For example, although the system components described above may be implemented by hardware devices, they may also be implemented by software-only solutions, such as installing the described system on an existing server or mobile device.

Similarly, it should be noted that in the preceding description of embodiments of the present specification, various features are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure aiding in the understanding of one or more of the embodiments. This method of disclosure, however, is not intended to imply that more features than are expressly recited in a claim. Indeed, the embodiments may be characterized as having less than all of the features of a single embodiment disclosed above.

Numerals describing the number of components, attributes, etc. are used in some embodiments, it being understood that such numerals used in the description of the embodiments are modified in some instances by the use of the modifier "about", "approximately" or "substantially". Unless otherwise indicated, "about", "approximately" or "substantially" indicates that the number allows a variation of ± 20%. Accordingly, in some embodiments, the numerical parameters set forth in the specification and claims are approximations that may vary depending upon the desired properties sought to be obtained by a particular embodiment. In some embodiments, the numerical parameter should take into account the specified significant digits and employ a general digit preserving approach. Notwithstanding that the numerical ranges and parameters setting forth the broad scope of the range are approximations, in the specific examples, such numerical values are set forth as precisely as possible within the scope of the application.

For each patent, patent application publication, and other material, such as articles, books, specifications, publications, documents, etc., cited in this specification, the entire contents of each are hereby incorporated by reference into this specification. Except where the application history document is inconsistent or contrary to the present specification, and except where the application history document is inconsistent or contrary to the present specification, the application history document is not inconsistent or contrary to the present specification, but is to be read in the broadest scope of the present claims (either currently or hereafter added to the present specification). It is to be understood that the descriptions, definitions and/or uses of terms in the accompanying materials of the present specification shall control if they are inconsistent or inconsistent with the statements and/or uses of the present specification.

Finally, it should be understood that the embodiments described herein are merely illustrative of the principles of the embodiments of the present disclosure. Other variations are also possible within the scope of the present description. Thus, by way of example, and not limitation, alternative configurations of the embodiments of the specification can be considered consistent with the teachings of the specification. Accordingly, the embodiments of the present description are not limited to only those explicitly described and depicted herein.

Claims

1. A method of indoor positioning, comprising the steps of:

receiving one coordinate signal sent by positioning environment equipment;

determining a plurality of primary coordinates based on the coordinate signals;

determining secondary coordinates based on the plurality of primary coordinates and the coordinate signal;

wherein determining a plurality of primary coordinates based on the coordinate signals comprises:

determining the primary coordinates based on a fingerprint library and a fingerprint positioning algorithm, wherein the fingerprint library comprises associations of signal strength values and corresponding positions, and the fingerprint positioning algorithm comprises at least two of SVM, WKNN algorithm and KNN algorithm;

wherein the secondary coordinates determined based on the plurality of primary coordinates and the coordinate signal include:

determining distances of the plurality of primary coordinates from the coordinate signal;

and determining the secondary coordinates based on the primary coordinates with the minimum distance from the positioning environment equipment.

2. The method for indoor positioning according to claim 1, wherein the fingerprint database construction process comprises:

collecting a fingerprint of the location environment, wherein the fingerprint comprises signal strength values emitted by a location environment device and received by a corresponding location;

and constructing a fingerprint library based on the fingerprints of the positioning environment.

3. The method of indoor positioning of claim 1,

and determining a three-level coordinate based on the first-level coordinate obtained by the SVM algorithm and the WKNN algorithm.

4. A method of indoor positioning according to claim 3, characterized by:

and determining secondary coordinates based on the tertiary coordinates, the primary coordinates and the coordinate signals.

5. A system fusing fingerprint positioning comprises a receiving module, a primary coordinate determination module and a secondary coordinate determination module;

the receiving module is used for receiving one of the coordinate signals sent by the positioning environment equipment;

the primary coordinate determination module is used for determining a plurality of primary coordinates based on the coordinate signals;

the secondary coordinate determination module is used for determining secondary coordinates based on the plurality of primary coordinates and the coordinate signals;

and determining the secondary coordinate based on the primary coordinate with the minimum distance from the positioning environment equipment.

6. An apparatus for fusing fingerprint positioning, comprising a processor and a storage medium, wherein the storage medium is used for storing computer instructions, and the processor is used for executing the computer instructions and implementing a method for indoor positioning according to any one of claims 1 to 4.

7. A computer readable storage medium storing computer instructions which, when executed by a processor, implement a method of indoor localization as claimed in any one of claims 1 to 4.