Indoor positioning method and device, electronic equipment and computer readable medium

Abstract

The embodiment of the invention relates to the technical field of positioning navigation, in particular to an indoor positioning method and device, electronic equipment and a computer readable medium. The indoor positioning method comprises the following steps: determining a first position where user equipment is located at the current moment based on a wireless fidelity Wi-Fi signal; estimating the position change of the user equipment based on step counting data of a step counting sensor; and determining a second position of the user equipment at the next moment based on the first position and the position change.

Description

Technical Field

[0001] The present application relates to the field of positioning and navigation technology, and in particular to a method, device, electronic device and computer-readable medium for indoor positioning. Background Art

[0002] The Global Navigation Satellite System (GNSS) is an airborne radio navigation and positioning system that can provide users with all-weather three-dimensional coordinates, speed, and time information at any location on the Earth's surface or near-Earth space. Using the GNSS observation data of smart terminals, high-precision positioning can be achieved in outdoor environments.

[0003] However, for indoor spaces with dense crowds and complex spatial structures, traditional positioning and navigation methods are difficult to meet users' positioning and navigation needs. For example, in transportation hubs such as subway stations and railway stations, the positioning accuracy of GNSS-based positioning and navigation is low because GNSS signals are easily interfered by walls, ground, and people. Summary of the invention

[0004] The purpose of the embodiments of the present application is to provide a method, device, electronic device and computer-readable medium for indoor positioning, which can improve the accuracy of indoor positioning.

[0005] To solve the above technical problems, the embodiments of the present application are implemented through the following aspects.

[0006] In a first aspect, an embodiment of the present application provides a method for indoor positioning, including: determining a first position of a user device at a current moment based on a wireless fidelity Wi-Fi signal; estimating a position change of the user device based on step data of a pedometer sensor; and determining a second position of the user device at a next moment based on the first position and the position change.

[0007] In a second aspect, an embodiment of the present application provides an indoor positioning device, comprising: a first determination module, used to determine a first position of a user device at a current moment based on a wireless fidelity Wi-Fi signal; an estimation module, used to estimate a position change of the user device based on step data of a pedometer sensor; and a second determination module, used to determine a second position of the user device at a next moment based on the first position and the position change.

[0008] In a third aspect, an embodiment of the present application provides an electronic device, comprising: a memory, a processor, and computer executable instructions stored in the memory and executable on the processor, wherein the computer executable instructions, when executed by the processor, implement the indoor positioning method described in the first aspect above.

[0009] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, which is used to store computer-executable instructions. When the computer-executable instructions are executed by a processor, the indoor positioning method described in the first aspect is implemented.

[0010] In a fifth aspect, an embodiment of the present application provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium, and the computer program includes program instructions. When the program instructions are executed by a computer, the computer executes the indoor positioning method described in the first aspect above.

[0011] In an embodiment of the present application, the first location of the user device at the current moment is determined based on the wireless fidelity Wi-Fi signal; the position change of the user device is estimated based on the step data of the pedometer sensor; and the second location of the user device at the next moment is determined based on the first position and the position change, thereby improving the accuracy of indoor positioning. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0013] Figure 1 A schematic diagram showing a flow chart of an indoor positioning method provided by an embodiment of the present application;

[0014] Figure 2 Another schematic diagram showing a flow chart of an indoor positioning method provided by an embodiment of the present application;

[0015] Figure 3 Another schematic diagram showing a flow chart of an indoor positioning method provided by an embodiment of the present application;

[0016] Figure 4 A schematic diagram showing the structure of an indoor positioning device provided in an embodiment of the present application is shown;

[0017] Figure 5 A schematic diagram of the hardware structure of an electronic device for executing an indoor positioning method provided in an embodiment of the present application. DETAILED DESCRIPTION

[0018] In order to enable those skilled in the art to better understand the technical solutions in this application, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are only part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this application.

[0019] Figure 1 A flow chart of the method for indoor positioning provided by an embodiment of the present application is shown, and the method can be executed by an electronic device, such as a terminal device or a server device. In other words, the method can be executed by software or hardware installed in the terminal device or the server device. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc. As shown in the figure, the method may include the following steps S110 to S130.

[0020] Step S110: Determine a first location of the user equipment at a current moment based on a Wireless Fidelity (Wi-Fi) signal.

[0021] User equipment is a communication device with wireless communication function carried by the user, such as a mobile phone, a tablet computer (Tablet Personal Computer), a laptop computer (Laptop Computer), a notebook computer, a personal digital assistant (Personal Digital Assistant, PDA), a handheld computer, a netbook, an ultra-mobile personal computer (Ultra-mobile Personal Computer, UMPC), a mobile Internet device (Mobile Internet Device, MID), augmented reality (Augmented Reality, AR), virtual reality (Virtual Reality, VR) equipment, a robot, a wearable device (Wearable Device), etc. Among them, wearable devices include smart watches, smart bracelets, smart headphones, smart glasses, smart jewelry (smart bracelets, smart bracelets, smart rings, smart necklaces, smart anklets, smart anklets, etc.), smart wristbands, smart clothing, etc. The type of user equipment is not limited here. The positioning of user equipment based on Wi-Fi signals can be based on the principles of signal acquisition, signal processing, fingerprint establishment and positioning calculation. When the user equipment collects the Wi-Fi signal strength of the indoor space, the first position of the user equipment in the indoor space can be obtained by matching and calculating. The indoor space may be a subway station, a railway station, a subway railway station complex, etc., which has a complex floor layout, dense flow of people, and also includes special space structures such as entry and exit passages.

[0022] Compared with the positioning method based on GNSS signals, the positioning method based on Wi-Fi signals can more accurately determine the user's first position in the indoor space at the current moment.

[0023] Step S120: estimating the position change of the user equipment based on the step counting data of the step counting sensor.

[0024] A pedometer sensor, also known as a pedometer, can be a unit with a pedometer function built into the user's device, such as an application for pedometers in a mobile phone; it can also be a device carried by the user independently of the user's device, such as a pedometer wristband. A pedometer is mainly composed of a vibration sensor and a counter. The pedometer data of the pedometer sensor is used to represent the user's movement in an indoor space, and may include the number of steps, speed, distance, step length, direction of travel, exercise duration, user gender, user weight, exercise calories consumed, etc. The position change of the user's device can be the distance the user's device has moved, the user's moving direction, or the user's estimated position in the future, where the future is the moment after the current moment.

[0025] The pedometer sensor carried by the user is used to obtain pedometer data used to represent the user's movement status; based on the pedometer data, the possible position changes of the user and the user device can be estimated.

[0026] Step S130: Determine a second location of the user equipment at a next moment based on the first location and the location change.

[0027] Based on the first position and the distance or direction that the user device may move, determine the second position of the user at the next moment, where the next moment is a moment after the current moment. Alternatively, determine the second position based on the first position and the estimated position of the user device at a future moment. The second position may be located in the aforementioned indoor space, or may be another position near the indoor space, such as a station passage position, which is not limited here.

[0028] In an embodiment of the present application, a first position of a user device at a current moment is determined based on a wireless fidelity Wi-Fi signal; a position change of the user device is estimated based on the step data of a pedometer sensor; and a second position of the user device at a next moment is determined based on the first position and the position change. Since the use of GNSS signals is avoided, the problem of low indoor positioning accuracy caused by GNSS signals can be overcome; and Wi-Fi signals and step data are not easily affected by indoor walls, floors, human traffic, etc., and therefore can be accurately positioned in indoor spaces, thereby improving indoor positioning accuracy.

[0029] Figure 2 Another schematic flow chart of the indoor positioning method provided by the embodiment of the present application is shown. As shown in the figure, the method may include the following steps S211 to S230.

[0030] Step S211: measuring the distance between the user equipment and a Wi-Fi access point with a known location, where there are multiple Wi-Fi access points.

[0031] A Wi-Fi access point is a device used by a wireless local area network to allow user devices to access the network. It is also called a hotspot and its location in an indoor space is known. Using the propagation characteristics of Wi-Fi signals, the distance between a user device and a Wi-Fi access point can be measured.

[0032] Step S212: Determine the first position using a triangulation positioning algorithm based on the distance between the user equipment and each Wi-Fi access point.

[0033] Based on the principle of multi-lateration positioning, the precise location of the user device can be calculated using a triangulation positioning algorithm based on the distance between the user device and at least three Wi-Fi access points. This distance measurement and triangulation positioning method can determine the location of the user device within a coarse-grained grid. This grid not only includes the location of the Wi-Fi access points, but also takes into account the spatial distribution characteristics of special areas such as station entrances and transfer channels.

[0034] Step S220: estimating the position change of the user equipment based on the step counting data of the step counting sensor.

[0035] Step S230: Determine a second location of the user equipment at a next moment based on the first location and the location change.

[0036] Step S220 and step S230 may adopt the description of the corresponding steps in the previous embodiment, and the repeatable parts will not be repeated here.

[0037] In the embodiment of the present application, the user equipment is positioned in a coarse-grained grid according to the Wi-Fi signal, and the approximate location of the user equipment is preliminarily estimated. Considering the complexity of the subway train station complex scene, this approximate location can provide a basis for subsequent positioning.

[0038] Figure 3 Another flow chart of the indoor positioning method provided by the embodiment of the present application is shown. As shown in the figure, the method may include the following steps S310 to S342.

[0039] Step S310: Determine a first location of the user equipment at a current moment based on a wireless fidelity Wi-Fi signal.

[0040] This step may adopt the description of the corresponding steps in the aforementioned embodiment, and the repeatable parts will not be repeated here.

[0041] Step S320: Based on at least one of the stride, the stride frequency and the motion pattern, using a Kalman filter, the position change is estimated.

[0042] The stride length is used to indicate the length of each step of the user, which can be an average value; the step frequency is used to indicate the number of steps of the user per unit time, such as 150 steps per minute. The exercise mode may include walking, jogging, and running. Optionally, different exercise modes correspond to different stride lengths and step frequencies.

[0043] The user's position and speed are used as state variables and represented by vectors. The Kalman filter uses a state vector and a covariance matrix to describe the state and uncertainty. In the prediction step, the user's position at the next moment is predicted based on at least one of the step length, step frequency, and movement mode of the pedometer sensor. Assuming that the user moves with a constant step length and step frequency, the step length and step frequency can be used to predict the user's position change. Using the state transition equation x k+1 =Fx k +Bu k +w k Perform state estimation and prediction, where x k is the state vector including the user position and velocity, F is the state transfer matrix, B is the control input matrix, and u k is the control input, w k is process noise. Specifically, the step counting data of the pedometer sensor is used as each column of the control input matrix B; the user position data is used as each column of the state transfer matrix, and the measured user movement direction is the control input u k Furthermore, in the prediction step, we use Predict the state, using P k|k-1 =FP k-1|k-1 F T +Q prediction covariance. Where P is the prediction error covariance matrix of the system state estimation, which represents the covariance of the current state prediction error and is used to measure the uncertainty of the state.

[0044] Step S330: Determine a second location of the user equipment at a next moment based on the first location and the location change.

[0045] This step may adopt the description of the corresponding steps in the aforementioned embodiment, and the repeatable parts will not be repeated here.

[0046] Step S341: Determine the third location of the user equipment at the next moment based on the Wi-Fi signal.

[0047] Step S342: Based on the difference between the second position and the third position, update the state vector and covariance matrix of the Kalman filter.

[0048] The third position is the position of the user device at the next moment based on the Wi-Fi signal measurement; the second position is the position estimated based on the step counting data. When new Wi-Fi signal strength data arrives, the difference between the measured position and the predicted position is calculated, and the difference is used to update the state vector and covariance matrix of the Kalman filter. The measured position and the predicted position can be combined by weighted averaging to reduce the position error. In the update step, K is used. l =P k|k-1 HT (HP k|k-1 H T +R) -1 Update the Kalman gain; use Update status; use P k|k =(IK k H)P k|k-1 Update the covariance. Where H is the observation matrix, which is used to map the state vector of the system to the observation space, which defines how to generate observations from the state vector; R is the covariance matrix of the observation noise, which is used to represent the statistical characteristics of the measurement noise, for example, to represent the degree of measurement uncertainty, which is usually estimated based on the characteristics of the actual measurement; I is the identity matrix.

[0049] In an embodiment of the present application, the position change of the user device can be predicted based on the stride, step frequency and movement pattern recorded by the pedometer sensor; combining the position change and the first position determined based on the Wi-Fi signal, a second position with higher positioning accuracy can be obtained; and based on the difference between the measured position and the predicted position, the Kalman filter used for estimation is updated to reduce the position error.

[0050] In a possible implementation, determining the first location of the user equipment at the current moment based on a wireless fidelity Wi-Fi signal includes: determining the first location of the user equipment at the current moment based on a Beidou signal forwarded by a room antenna and the Wi-Fi signal.

[0051] The Beidou signal is forwarded losslessly to the indoor space by using a 5G indoor antenna. The number of the indoor antennas is multiple.

[0052] In a possible implementation, determining the first location of the user equipment at a current moment based on the Beidou signal and the Wi-Fi signal forwarded by the indoor antenna includes: dividing the indoor space into multiple areas based on the signal strength of the Beidou signal; optimizing the multiple areas based on the influencing factors of the Beidou signal in the indoor space; and determining the first location based on the optimized areas.

[0053] Analyze the Beidou signals forwarded to the indoor space and divide the area according to the signal overlap area. The signal overlap area is the intersection of two or more indoor antenna signal coverage areas. By analyzing the signal strength of the signal overlap area, the boundaries of different functional areas are defined.

[0054] For the divided areas, optimization is performed based on the influencing factors of the Beidou signal. The influencing factors of the Beidou signal include at least one of the following: signal stability, signal interference, and indoor space changes. Using signal stability to constrain the divided areas can ensure that the Beidou signal within each divided area maintains a certain stability and continuity after being forwarded by the 5G indoor antenna, thereby ensuring the accuracy and reliability of positioning and navigation. Signal interference includes interference or weakening of the signal by walls, elevator shafts, large metal structures, etc. Indoor space changes are changes in the indoor space relative to its modeling and division, such as temporary structures built in the indoor space or changes in the flow of people in the indoor space. Optionally, modeling and regional division of indoor space are performed based on the distribution of indoor antennas.

[0055] Optimize multiple areas, including re-dividing the areas. That is, based on the above-mentioned influencing factors, introduce a dynamic adjustment mechanism for area division to improve the accuracy of area division. In addition, the mechanism can adjust the area boundaries according to real-time data to improve the adaptability and flexibility of positioning navigation.

[0056] Optionally, the BeiDou signal strength forwarded by multiple 5G indoor antennas is collected simultaneously to determine the boundaries and characteristics of different areas. The data of the BeiDou positioning system and the data of the 5G indoor system are fused to create a comprehensive signal strength map. The signal strength map can show the signal strength and stability of different areas, which can serve as the basis for regional division and regional re-division.

[0057] In a possible implementation manner, when a signal strength change value of a Beidou signal or a Wi-Fi signal is greater than a predetermined threshold, the first position is corrected.

[0058] The signal strength change value of the Beidou signal or the Wi-Fi signal is greater than the predetermined threshold value, including the signal strength change value of the area corresponding to the Beidou signal is greater than the predetermined threshold value, or the signal strength change value of the coarse-grained grid corresponding to the Wi-Fi signal is greater than the predetermined threshold value. If the signal strength of the area corresponding to the Beidou signal changes significantly, the positioning error of the area is automatically detected, and according to the detection result, the position determined according to the area is corrected in real time. Or when the signal strength of the grid corresponding to the Wi-Fi signal changes significantly, the positioning error is automatically detected, it is determined whether the grid needs to be switched, and real-time correction is performed through the fusion algorithm.

[0059] Optionally, the environment in the indoor space is monitored. When the change in the indoor space exceeds a specified threshold, for example, the volume of a temporary structure built indoors is greater than a predetermined volume threshold or the change in indoor human flow is greater than a predetermined human flow change threshold, the positioning model and related parameters are adjusted to improve the continuity and stability of positioning.

[0060] By modeling indoor spaces such as subway train station complexes and dividing the space into regions based on the distribution of indoor antennas in the indoor space, this step can improve the accuracy of positioning compared to positioning methods that do not take indoor space characteristics into account, as both modeling and region division are based on the structural characteristics of the indoor space.

[0061] In a possible implementation manner, after determining the second location of the user equipment at a next moment, the method further includes: determining a path from the second location to a target location based on the second location.

[0062] The second position is the user device location updated in real time based on the first position and position changes, and the target position is the destination the user is going to. The second position is compared with the target position, and the best navigation path is calculated. The best navigation path can be a path that avoids signal blind spots or crowded areas and has the strongest signal and the shortest distance. When calculating the navigation path, path planning and navigation prompts can be provided to the user based on the functions and signal characteristics of different areas. Optionally, when calculating the navigation path, regional division will be used for path planning and navigation prompts. The calculated best navigation path guides the user to reach the target correctly. Optionally, the navigation information is displayed on the user device in the form of icons or text.

[0063] In a possible implementation, a method for indoor positioning includes the following steps 1) to 6).

[0064] 1) Model and divide the indoor space into areas.

[0065] 2) Distance measurement and triangulation based on Wi-Fi signals.

[0066] 3) Collect pedometer sensor data.

[0067] 4) Preliminary estimation of user location: Based on Wi-Fi signals, the user is located in a coarse-grained grid to preliminarily estimate the user's approximate location.

[0068] 5) Real-time location update. As the user moves, the pedometer sensor obtains pedometer data in real time. By analyzing the number of steps and stride length in the pedometer data and combining it with the Wi-Fi positioning results, the user's location is updated in real time.

[0069] 6) Location comparison and navigation guidance: The real-time updated user location is compared with the target location, and the best navigation path is calculated to guide the user to the target location.

[0070] In an embodiment of the present application, a first position of a user device at a current moment is determined based on a wireless fidelity Wi-Fi signal; a position change of the user device is estimated based on the step data of a pedometer sensor; and a second position of the user device at a next moment is determined based on the first position and the position change. Since the use of GNSS signals is avoided, the problem of low indoor positioning accuracy caused by GNSS signals can be overcome; and Wi-Fi signals and step data are not easily affected by indoor walls, floors, human traffic, etc., and therefore can be accurately positioned in indoor spaces, thereby improving indoor positioning accuracy.

[0071] Figure 4 The schematic diagram of the structure of the indoor positioning device provided in the embodiment of the present application is shown, and the indoor positioning device 400 includes a first determination module 410, an estimation module 420 and a second determination module 430. The first determination module 410 is used to determine the first position of the user equipment at the current moment based on the wireless fidelity Wi-Fi signal; the estimation module 420 is used to estimate the position change of the user equipment based on the step counting data of the step counting sensor; the second determination module 430 is used to determine the second position of the user equipment at the next moment based on the first position and the position change.

[0072] In a possible implementation, the first determination module 410 is used to measure the distance between the user equipment and a Wi-Fi access point with a known location, where the number of the Wi-Fi access points is multiple; based on the distance between the user equipment and each Wi-Fi access point, a triangulation positioning algorithm is used to determine the first location.

[0073] In one possible implementation, the pedometer data includes the user's stride, the user's step frequency, and the user's motion pattern; the estimation module 420 is used to estimate the position change based on at least one of the stride, the step frequency, and the motion pattern using a Kalman filter.

[0074] In a possible implementation, the indoor positioning device 400 is used to determine a third location of the user equipment at the next moment based on the Wi-Fi signal; and update the state vector and covariance matrix of the Kalman filter based on the difference between the second location and the third location.

[0075] In a possible implementation, the first determination module 410 is used to determine the first location of the user equipment at a current moment based on the Beidou signal forwarded by the indoor antenna and the Wi-Fi signal.

[0076] In a possible implementation, the first determination module 410 is used to divide the indoor space into multiple areas based on the signal strength of the Beidou signal; optimize the multiple areas based on the influencing factors of the Beidou signal in the indoor space; and determine the first position based on the optimized areas.

[0077] In a possible implementation manner, the indoor positioning apparatus 400 is used to correct the first position when a signal strength change value of a Beidou signal or a Wi-Fi signal is greater than a predetermined threshold.

[0078] In a possible implementation manner, the indoor positioning device 400 is used to determine a path from the second position to a target position based on the second position.

[0079] The device 400 provided in the embodiment of the present application can execute the various methods described in the foregoing method embodiments, and realize the functions and beneficial effects of the various methods described in the foregoing method embodiments, which will not be repeated here.

[0080] Figure 5 A schematic diagram of the hardware structure of an electronic device that executes the indoor positioning method provided in an embodiment of the present application is shown. Referring to the figure, at the hardware level, the electronic device includes a processor 510, and optionally, an internal bus 520, a network interface 530, and a memory. Among them, the memory may include a memory 540, such as a high-speed random access memory (Random-Access Memory, RAM), and may also include a non-volatile memory (non-volatile memory) 550, such as at least one disk storage, etc. Of course, the electronic device may also include hardware required for other services.

[0081] The processor 510, the network interface 530 and the memory may be connected to each other via an internal bus 520, which may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, only one bidirectional arrow is used in the figure, but it does not mean that there is only one bus or one type of bus.

[0082] The memory is used to store programs. Specifically, the program may include program codes, and the program codes include computer operation instructions. The memory may include a memory 540 and a non-volatile memory 550, and provide instructions and data to the processor 510.

[0083] The processor 510 reads the corresponding computer program from the non-volatile memory 550 into the memory 540 and then runs it, forming a device for locating the target user at the logical level. The processor 510 executes the program stored in the memory and is specifically used to execute Figures 1 to 3 The method described in the embodiment achieves the same or corresponding technical effects.

[0084] The above application Figures 1 to 3 The method disclosed in the illustrated embodiment can be applied to a processor or implemented by a processor 510. The processor 510 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by an integrated logic circuit of hardware or software instructions in the processor 510. The above processor 510 can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The methods, steps and logic block diagrams disclosed in the embodiments of the present application can be implemented or executed. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc. The steps of the method disclosed in the embodiments of the present application can be directly embodied as a hardware decoding processor for execution, or a combination of hardware and software modules in the decoding processor for execution. The software module may be located in a storage medium mature in the art, such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory, and the processor 510 reads the information in the memory and completes the steps of the above method in combination with its hardware.

[0085] The electronic device can also execute the methods described in the foregoing method embodiments, and realize the functions and beneficial effects of the methods described in the foregoing method embodiments, which will not be repeated here.

[0086] Of course, in addition to software implementation, the electronic device of the present application does not exclude other implementation methods, such as logic devices or a combination of software and hardware, etc. That is to say, the execution subject of the following processing flow is not limited to each logic unit, but can also be hardware or logic devices.

[0087] The embodiment of the present application also provides a computer-readable storage medium, wherein the computer-readable medium stores one or more programs, and when the one or more programs are executed by an electronic device including a plurality of application programs, the electronic device executes Figures 1 to 3 The method described in the embodiment achieves the same or corresponding technical effects.

[0088] Furthermore, the embodiment of the present application also provides a computer program product, the computer program product comprising a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions, when the program instructions are executed by a computer, Figures 1 to 3 The method described in the embodiment achieves the same or corresponding technical effects.

[0089] In short, the above description is only a preferred embodiment of the present application and is not intended to limit the protection scope of the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

[0090] The systems, devices, modules or units described in the above embodiments may be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0091] Computer-readable media include permanent and non-permanent, removable and non-removable media that can be used to store information by any method or technology. Information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase-change RAM (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include temporary computer-readable media (transitory media), such as modulated data signals and carrier waves.

[0092] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0093] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

Claims

1. A method for indoor positioning, characterized in that: include Determine a first location of the user device at a current moment based on a wireless fidelity Wi-Fi signal; estimating a location change of the user device based on step counting data of a step counting sensor; A second location of the user equipment at a next moment is determined based on the first location and the location change.

2. The method according to claim 1, characterized in that: The determining, based on the wireless fidelity Wi-Fi signal, the first location of the user equipment at the current moment includes: Measuring a distance between the user equipment and a Wi-Fi access point with a known location, wherein there are multiple Wi-Fi access points; The first position is determined using a triangulation positioning algorithm based on the distance between the user equipment and each Wi-Fi access point.

3. The method according to claim 1, characterized in that The step counting data includes the user's stride length, the user's step frequency and the user's movement pattern; The estimating the position change of the user equipment based on the step counting data of the step counting sensor includes: The position change is estimated using a Kalman filter based on at least one of the stride length, stride frequency and movement pattern.

4. The method according to claim 3, characterized in that After determining the second location of the user equipment at the next moment, the method further includes: Determine a third location of the user device at a next moment based on the Wi-Fi signal; Based on the difference between the second position and the third position, the state vector and the covariance matrix of the Kalman filter are updated.

5. The method according to claim 1, characterized in that: The determining, based on the wireless fidelity Wi-Fi signal, the first location of the user equipment at the current moment includes: Based on the Beidou signal forwarded by the indoor antenna and the Wi-Fi signal, the first position of the user equipment at the current moment is determined.

6. The method according to claim 5, characterized in that Determining a first location of the user equipment at a current moment based on the Beidou signal forwarded by the indoor antenna and the Wi-Fi signal includes: Based on the signal strength of Beidou signals, the indoor space is divided into multiple areas; Based on the influencing factors of the Beidou signal in the indoor space, optimizing the plurality of areas; Based on the optimized area, the first position is determined.

7. The method according to claim 5, characterized in that Also includes: When the signal strength change value of the Beidou signal or the Wi-Fi signal is greater than a predetermined threshold, the first position is corrected.

8. The method according to claim 1, characterized in that After determining the second location of the user equipment at the next moment, the method further includes: Based on the second location, a path from the second location to a target location is determined.

9. An electronic device, characterized in that: include: processor; as well as A memory arranged to store computer executable instructions, wherein when the executable instructions are executed, the processor performs the indoor positioning method according to any one of claims 1 to 8.

10. A computer-readable medium, characterized in that The computer-readable medium stores one or more programs, which, when executed by an electronic device including a plurality of application programs, enable the electronic device to execute the indoor positioning method according to any one of claims 1 to 8.

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