CN110231592A - Indoor orientation method, device, computer readable storage medium and terminal device - Google Patents
Indoor orientation method, device, computer readable storage medium and terminal device Download PDFInfo
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- CN110231592A CN110231592A CN201910288968.1A CN201910288968A CN110231592A CN 110231592 A CN110231592 A CN 110231592A CN 201910288968 A CN201910288968 A CN 201910288968A CN 110231592 A CN110231592 A CN 110231592A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
- G01S5/02—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves
- G01S5/0252—Radio frequency fingerprinting
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Abstract
The invention belongs to indoor positioning technologies field more particularly to a kind of indoor orientation method, device, computer readable storage medium and terminal devices.The method obtains the inertia measurement data of terminal device acquisition;The first positioning coordinate of the terminal device is calculated according to the inertia measurement data;Obtain the Wi-Fi finger print data of the terminal device acquisition;The second positioning coordinate of the terminal device is calculated according to the Wi-Fi finger print data;The first positioning coordinate and the second positioning coordinate are input in preset Kalman filter model and are corrected processing, the positioning coordinate after obtaining the terminal device correction.By Kalman filter model, the error that inertial positioning is accumulated at any time is constantly corrected using Wi-Fi fingerprint location, while making up the unstability of Wi-Fi fingerprint location using inertial positioning, to substantially increase the precision of final positioning result.
Description
Technical field
The invention belongs to indoor positioning technologies field more particularly to a kind of indoor orientation method, device, computer-readable deposit
Storage media and terminal device.
Background technique
In recent years, the extensive use due to internet and technology of Internet of things and smart phone and other wireless devices exist
The continuous of market is popularized, and various indoor positioning technologies are also developed and improve.It is present that there are many (the whole world GNSS in the market
Navigational satellite system) receiver etc product, these products use GPS (global positioning system), GLONASS (GLONASS
Navigation system), Galileo (galileo satellite navigation system) or dipper system, positioned for real-time satellite.Since satellite is believed
Number pass through building surface when will cause signal decaying therefore its reach indoor environment when a large amount of energy has been lost, furthermore
It is indoor and outdoor because environment (factors such as atmospheric density, temperature, pressure) difference will cause multipath reflection phenomenon so as to cause multipath
Propagation effect, eventually generates a large amount of artificial uncontrollable errors, therefore general Global Satellite Navigation System can not be
Play the role of in building effective.
In recent years, the method for occurring carrying out indoor positioning based on inertia measurement data, but due on the terminal device
The collected data Noise of inertial sensor, so the location technology will appear in prolonged position fixing process accumulation miss
Difference, practicability are poor.
Summary of the invention
In view of this, the embodiment of the invention provides a kind of indoor orientation method, device, computer readable storage medium and
Terminal device, to solve the existing method meeting in prolonged position fixing process for carrying out indoor positioning based on inertia measurement data
There is accumulated error, the poor problem of practicability.
The first aspect of the embodiment of the present invention provides a kind of indoor orientation method, may include:
Obtain the inertia measurement data of terminal device acquisition;
The first positioning coordinate of the terminal device is calculated according to the inertia measurement data;
Obtain the Wi-Fi finger print data of the terminal device acquisition;
The second positioning coordinate of the terminal device is calculated according to the Wi-Fi finger print data;
The first positioning coordinate and the second positioning coordinate are input in preset Kalman filter model and are carried out
Correction process, the positioning coordinate after obtaining the terminal device correction.
Further, the first positioning coordinate for calculating the terminal device according to the inertia measurement data can wrap
It includes:
Step-length, cadence and the direction deflection angle of each movement are calculated separately according to the inertia measurement data;
The distance of each movement is calculated separately according to each mobile Stride length and frequency;
The first of the terminal device is calculated according to preset starting position coordinates, the distance of each movement and direction deflection angle
Position coordinate.
Further, described according to the calculating of preset starting position coordinates, the distance of each movement and direction deflection angle
The first of terminal device positions coordinate
The first positioning coordinate is calculated according to the following formula:
Wherein, (N0,E0) it is the starting position coordinates, n and k are the serial number of each movement, dnMobile for n-th
Distance, θnFor the mobile direction deflection angle of n-th, (Nk,Ek) it is the first positioning coordinate after kth time is mobile, 1≤n≤k.
Further, the second positioning coordinate for calculating the terminal device according to the Wi-Fi finger print data can be with
Include:
It calculates separately European between each sample data and the Wi-Fi finger print data in preset sample database
Distance;
From the smallest S sample of Euclidean distance chosen in the sample database between the Wi-Fi finger print data
Data are as preferred sample data, wherein S is the integer greater than 1;
The second positioning coordinate is calculated according to the following formula:
Wherein, i is the serial number of the preferred sample data, 1≤i≤S, XiIt is corresponding with i-th of preferred sample data
Coordinate, WiFor weighting coefficient corresponding with i-th of preferred sample data, YkIt is the second positioning coordinate after kth time movement.
Further, described that the first positioning coordinate and the second positioning coordinate are input to preset Kalman and filtered
Processing is corrected in wave pattern, the positioning coordinate after obtaining the terminal device correction may include:
Positioning coordinate after calculating the terminal device correction according to the following formula:
xk'=xk+K*(yk-H*xk)
Wherein, xkFor the first positioning coordinate, ykFor the second positioning coordinate, H is unit matrix, and K is preset card
Germania gain, xk' for the terminal device correction after positioning coordinate.
The second aspect of the embodiment of the present invention provides a kind of indoor positioning device, may include:
First data acquisition module, for obtaining the inertia measurement data of terminal device acquisition;
First positioning coordinate calculation module is determined for calculating the first of the terminal device according to the inertia measurement data
Position coordinate;
Second data acquisition module, for obtaining the Wi-Fi finger print data of the terminal device acquisition;
Second positioning coordinate calculation module, for calculating the second of the terminal device according to the Wi-Fi finger print data
Position coordinate;
Kalman filtering module, for the first positioning coordinate and the second positioning coordinate to be input to preset card
Processing is corrected in Kalman Filtering model, the positioning coordinate after obtaining the terminal device correction.
Further, the first positioning coordinate calculation module may include:
First computing unit, for calculating separately step-length, cadence and the side of each movement according to the inertia measurement data
To drift angle;
Second computing unit, for calculating separately the distance of each movement according to each mobile Stride length and frequency;
Third computing unit, for being calculated according to preset starting position coordinates, the distance of each movement and direction deflection angle
First positioning coordinate of the terminal device.
Further, the third computing unit is specifically used for calculating the first positioning coordinate according to the following formula:
Wherein, (N0,E0) it is the starting position coordinates, n and k are the serial number of each movement, dnMobile for n-th
Distance, θnFor the mobile direction deflection angle of n-th, (Nk,Ek) it is the first positioning coordinate after kth time is mobile, 1≤n≤k.
Further, the second positioning coordinate calculation module may include:
Metrics calculation unit, for calculating separately each sample data in preset sample database and the Wi-Fi
Euclidean distance between finger print data;
Sample selection unit, for European between the Wi-Fi finger print data from being chosen in the sample database
Apart from the smallest S sample data as preferred sample data, wherein S is the integer greater than 1;
Coordinate calculating unit, for calculating the second positioning coordinate according to the following formula:
Wherein, i is the serial number of the preferred sample data, 1≤i≤S, XiIt is corresponding with i-th of preferred sample data
Coordinate, WiFor weighting coefficient corresponding with i-th of preferred sample data, YkIt is the second positioning coordinate after kth time movement.
Further, the Kalman filtering module is specifically used for calculating according to the following formula and determine after the terminal device corrects
Position coordinate:
xk'=xk+K*(yk-H*xk)
Wherein, xkFor the first positioning coordinate, ykFor the second positioning coordinate, H is unit matrix, and K is preset card
Germania gain, xk' for the terminal device correction after positioning coordinate.
The third aspect of the embodiment of the present invention provides a kind of computer readable storage medium, the computer-readable storage
Media storage has computer-readable instruction, and the computer-readable instruction realizes that any of the above-described kind of interior is fixed when being executed by processor
The step of position method.
The fourth aspect of the embodiment of the present invention provides a kind of terminal device, including memory, processor and is stored in
In the memory and the computer-readable instruction that can run on the processor, the processor executes the computer can
The step of any of the above-described kind of indoor orientation method is realized when reading instruction.
Existing beneficial effect is the embodiment of the present invention compared with prior art: the embodiment of the present invention obtains terminal device and adopts
The inertia measurement data of collection;The first positioning coordinate of the terminal device is calculated according to the inertia measurement data;Described in acquisition
The Wi-Fi finger print data of terminal device acquisition;It is sat according to the second positioning that the Wi-Fi finger print data calculates the terminal device
Mark;The first positioning coordinate and the second positioning coordinate are input in preset Kalman filter model and are corrected place
Reason, the positioning coordinate after obtaining the terminal device correction.Through the embodiment of the present invention, it is merged using Kalman filter model
Based on the method that inertia measurement data carry out the method for indoor positioning and carry out indoor positioning based on Wi-Fi finger print data, base
There is preferable stability in the method that inertia measurement data carry out indoor positioning, but can go out in prolonged position fixing process
The problem of showing accumulated error, and accumulated error be not present based on the method that Wi-Fi finger print data carries out indoor positioning, but position
As a result it is easy to happen jump, stability is poor, by Kalman filter model, constantly corrects inertia using Wi-Fi fingerprint location
The error accumulated at any time is positioned, while making up the unstability of Wi-Fi fingerprint location using inertial positioning, to mention significantly
The high precision of final positioning result.
Detailed description of the invention
It to describe the technical solutions in the embodiments of the present invention more clearly, below will be to embodiment or description of the prior art
Needed in attached drawing be briefly described, it should be apparent that, the accompanying drawings in the following description is only of the invention some
Embodiment for those of ordinary skill in the art without any creative labor, can also be according to these
Attached drawing obtains other attached drawings.
Fig. 1 is a kind of one embodiment flow chart of indoor orientation method in the embodiment of the present invention;
Fig. 2 is the schematic flow diagram according to the first of inertia measurement data computing terminal equipment the positioning coordinate;
Fig. 3 is the periodically variable waveform diagram of acceleration signal;
Fig. 4 is the according to preset starting position coordinates, the distance of each movement and direction deflection angle computing terminal equipment
The schematic diagram of one positioning coordinate;
Fig. 5 is a kind of one embodiment structure chart of indoor positioning device in the embodiment of the present invention;
Fig. 6 is a kind of schematic block diagram of terminal device in the embodiment of the present invention.
Specific embodiment
In order to make the invention's purpose, features and advantages of the invention more obvious and easy to understand, below in conjunction with the present invention
Attached drawing in embodiment, technical scheme in the embodiment of the invention is clearly and completely described, it is clear that disclosed below
Embodiment be only a part of the embodiment of the present invention, and not all embodiment.Based on the embodiments of the present invention, this field
Those of ordinary skill's all other embodiment obtained without making creative work, belongs to protection of the present invention
Range.
Referring to Fig. 1, a kind of one embodiment of indoor orientation method may include: in the embodiment of the present invention
Step S101, the inertia measurement data of terminal device acquisition are obtained.
In the present embodiment, three axis can be acquired by inertial sensors such as accelerometer in terminal device and gyroscopes
The inertia measurements data such as acceleration and angular speed.Inertial sensor has all been loaded in current most terminal device, for number
According to acquisition do not need additional hardware device, terminal device level is held in the hand by pedestrian, the vertical direction of human body be Z axis just
Direction, the direction that terminal device is directed toward are the positive directions of Y-axis, and terminal device horizontal direction is X-direction.Human body take a step walking
When terminal device there is slight vibration, accelerometer can collect the acceleration of tri- axis of X, Y, Z, and gyroscope is capable of measuring coordinate
Axis is compared with the angular speed that previous position rotates.Calculating of the collected acceleration information for cadence detection and step-size estimation, angle speed
Degree is then calculated for angle detecting.
Step S102, the first positioning coordinate of the terminal device is calculated according to the inertia measurement data.
It is to be moved under conditions of knowing current time position by measurement according to the method that inertia measurement data are positioned
Dynamic distance and bearing, the method for calculating subsequent time position.Its basic principle is to obtain list using accelerometer and gyroscope
Then corner and displacement information in the time of position pass through previous moment carrier (being in the present embodiment the mobile terminal)
Position and course calculate the boat position at next moment.
As shown in Fig. 2, step S102 can specifically include following procedure:
Step S1021, step-length, cadence and the direction deflection angle of each movement are calculated separately according to the inertia measurement data.
Human body gait for often making a move when walking has a periodic regularity, paces frequency when pedestrian's normal walking
Rate is 90 to 130 step per minute, and the step-length of each step is 50-80cm, and in the case where at the uniform velocity walking, pedestrian often makes a move can be with
Approximation is used as fixed step size.
Due to pedestrian's gait processes be constantly be swung left and right, pitch cycle movement state, cadence detection by plus
The changing rule of the collected acceleration signal wave period of speedometer carries out step recognition.It calculates according to the following formula first
The resultant acceleration of three axis:Wherein, ax、ay、az, be respectively X-axis, Y-axis, Z axis acceleration, a ' be three
The resultant acceleration of axis, then rejects acceleration of gravity according to the following formula: a "=a '-g, wherein g is acceleration of gravity, a " to reject
Resultant acceleration after acceleration of gravity is the regularly changing waveform diagram of a " shown in Fig. 3, each step can be observed from figure
It only will appear one trough of a wave crest in step period, the starting point taken a step every time is a value among peak value and valley, is claimed
For threshold value.Since the period taken a step every time is not quite similar, so threshold value also constantly changes, it occurs first period of taking a step
Afterwards, the dynamic threshold in subsequent each period is updated to the peak value of previous step and the average value of peak valley.Under normal conditions, human body exists
The time range that row makes a move of taking a step is 0.2 to 2 second, so if the time difference of continuous two starting points of taking a step is in this section model
It encloses and there was only unique wave crest and trough between the two starting points of taking a step, then succeed step counting, otherwise step counting again.
Human body keeps hand-held mobile terminal to be parallel to the horizontal plane and walk along Y-axis positive direction when walking, this
The angle for the rotation that sample obtains is the direction deflection angle of horizontal direction.The angular velocity data of gyroscope acquisition can be calculated indirectly
The variation in direction out integrates the corner in this available period by the angular speed to a period of time, thus the side of reaching
To the purpose of detection.
It is known that everyone step-length when walking is different, thus fixed step-length for location Calculation will cause compared with
Big error.The present embodiment is established when carrying out step-length estimation using the combination of the variance of the mould of acceleration and cadence
Model improves the accuracy of algorithm positioning so that the step-length to different pedestrians is approximately estimated.Research shows that everyone step-length
It is linear with the variance of the frequency of walking and the accelerometer's signals of each step, thus step-length can by cadence and
The variance of the mould of acceleration indicates:
SL=α f+ β σ2+γ
Wherein, f is cadence, σ2For the variance of the mould of acceleration, α, β, γ are constant coefficient, can pass through least square
Method solves, and acquires multiple groups (SL, f, σ in advance2) data obtain equation group:
The right and left summation:
Coefficient is solved by differential, optimal solution meets:
Step S1022, the distance of each movement is calculated separately according to each mobile Stride length and frequency.
Specifically, the distance of each movement: d can be calculated separately according to the following formulan=SLn×fn, wherein SLnFor n-th
Mobile step-length, fnFor the mobile cadence of n-th, dnFor the mobile distance of n-th.
Step S1023, the terminal is calculated according to preset starting position coordinates, the distance of each movement and direction deflection angle
First positioning coordinate of equipment.
As shown in figure 4, initial time t0 carrier, in the position S0, coordinate is (N0,E0), it has arrived t1 moment carrier and has been moved to S1
At position, moving distance d1, the angle with N axis is θ1, then S1 can be calculated to obtain by S0.And so on, it can be according to the following formula
Calculate the first positioning coordinate of any moment:
Wherein, (N0,E0) it is the starting position coordinates, n and k are the serial number of each movement, dnMobile for n-th
Distance, θnFor the mobile direction deflection angle of n-th, (Nk,Ek) it is the first positioning coordinate after kth time is mobile, 1≤n≤k.
Step S103, the Wi-Fi finger print data of the terminal device acquisition is obtained.
Wi-Fi fingerprint refers to that terminal device collected reception signal in an interior for being covered with Wi-Fi signal is strong
It spends (Received Signal Strength, RSS).Because Wi-Fi signal strength can be with propagation during spatial
The increase of distance and weaken, therefore terminal device is closer with a distance from signal emitting-source, and the RSS value obtained is bigger, conversely, eventually
End equipment is remoter from signal emitting-source, and the RSS value obtained is with regard to smaller.
In the present embodiment, the number of all signal emitting-sources in current building is denoted as N, then theoretically, terminal
Equipment can be respectively received the RSS value of this N number of signal emitting-source namely the collected Wi-Fi finger print data of terminal device is
The data of one N-dimensional, each dimension both correspond to the RSS value an of signal emitting-source.
Step S104, the second positioning coordinate of the terminal device is calculated according to the Wi-Fi finger print data.
Specifically, each sample data that can be calculated separately first in preset sample database refers to the Wi-Fi
Euclidean distance between line data.
The sample database is in designated period of time in each predetermined position of current building (its known specific seat
Mark) acquisition Wi-Fi finger print data set, wherein each predetermined position acquisition Wi-Fi finger print data be the data
A sample in library.The vector form of the Wi-Fi finger print data is denoted as herein: (r1,r2,r3,...,rn,...,rN),
Wherein, n is the serial number of signal emitting-source, 1≤n≤N, rnFor n-th of signal emitting-source in the Wi-Fi finger print data
The vector form of any sample data can be similarly denoted as: (ρ by RSS value1,ρ2,ρ3,...,ρn,...,ρN), wherein ρn
For the RSS value of n-th of signal emitting-source in the sample data, then Euclidean distance between the two can be calculated according to the following formula:
Wherein, D is Euclidean distance between the two.
It is then possible to minimum from the Euclidean distance chosen in the sample database between the Wi-Fi finger print data
S sample data as preferred sample data.
Wherein, S is the integer greater than 1, and specific value is configured according to the actual situation, for example, can be arranged
For 3,5,10 or other values etc., the present embodiment is not especially limited it.
Finally, the second positioning coordinate can be calculated according to the following formula:
Wherein, i is the serial number of the preferred sample data, 1≤i≤S, XiIt is corresponding with i-th of preferred sample data
Coordinate, WiFor weighting coefficient corresponding with i-th of preferred sample data, can calculate according to the following formula and each preferred sample data
Corresponding weighting coefficient:diIt is European between i-th of preferred sample data and the Wi-Fi finger print data
Distance, YkIt is the second positioning coordinate after kth time movement.
It should be noted that being averaged for K preferred sample data respective coordinates can also be taken in a kind of optional scheme
Value is as the second positioning coordinate, and still, this operation being averaged can bring certain error, therefore, in this implementation
Brought weighting coefficient into example for the K preferably sample datas chosen, enable it is each obtained apart from closer point it is bigger
Weight.The form of the weight and the inverse function (inverse) of distance are positively correlated, therefore bigger apart from the weight that smaller point obtains, away from
It is also relatively small from the weight that bigger point obtains, so as to obtain more accurate positioning result.
Step S105, the first positioning coordinate and the second positioning coordinate are input to preset Kalman filtering mould
Processing is corrected in type, the positioning coordinate after obtaining the terminal device correction.
Kalman filter model be it is a kind of carry out prediction estimation using data of the state transition equation to last moment, pass through
System inputs real-time observed data, estimates corrected algorithm model to prediction.
Assuming that the state vector of a linear system is xk, it depends on upper moment state vector xk-1With it is current defeated
Enter to motivate uk, that is, meet following difference equation:
xk=A*xk-1+B*uk+wk(wkTo predict error)
The measurement vector y that this system is got simultaneouslykIt can be by state vector xkIt is obtained by linear transformation approximation, in this way
Linear transformation be referred to as h ():
yk=H*xk+vk(vkFor measurement noise)
So amendment can be gone to calculate obtained state vector by observing obtained vector, to reduce the mistake of system
Difference, concrete operations are as follows:
xk'=xk+K*(yk-H*xk)
For this implementation, xkFor the first positioning coordinate, ykFor the second positioning coordinate, xk' set for the terminal
Positioning coordinate after standby correction, K is kalman gain, can be calculated by following formula:
(PkFor xkCovariance matrix, R vkVariance)
Wherein, PkIt can calculate to obtain by the covariance matrix of last moment:
Pk=A*Pk-1*AT+Q(Pk-1For xk-1Covariance matrix, Q wkVariance)
The end value x of correction is updated simultaneouslyk' variance:
Pk'=(I-K*H) Pk
Above six formula are that the iteration of Kalman filtering calculates equation, the observation acquired by initial position and every time
Value, continuous iteration calculates the specific location of next movement, to obtain carrier movement track.In the present embodiment, it will adopt
The Kalman filtering for taking inertia measurement data and Wi-Fi finger print data mutually to correct, and lasting estimate.Algorithm is accustomed to the use of
Property measurement data is modeled by Kalman filtering linear formula, wherein xkForukForCoefficient matrices A,
B, H is unit matrix.The second positioning coordinate that system is calculated by the Wi-Fi finger print data is as each row
Observation (the i.e. y of people's reckoningk) initial position value (N is obtained simultaneously0,E0);And the number being collected by the way that sampled point is arranged
According to, calculate R value and the regression function Q changed over time(t), R meets Gaussian Profile, and Q meets Gauss in every a certain distance
Distribution, but can increase with the increase of distance number, recurrence is calculated using linear regression model (LRM) by the data being collected into
Function.
In conclusion the embodiment of the present invention obtains the inertia measurement data of terminal device acquisition;According to the inertia measurement
Data calculate the first positioning coordinate of the terminal device;Obtain the Wi-Fi finger print data of the terminal device acquisition;According to institute
State the second positioning coordinate that Wi-Fi finger print data calculates the terminal device;The first positioning coordinate and described second is determined
Position coordinate, which is input in preset Kalman filter model, is corrected processing, and the positioning after obtaining the terminal device correction is sat
Mark.Through the embodiment of the present invention, the side that indoor positioning is carried out based on inertia measurement data has been merged using Kalman filter model
Method and the method that indoor positioning is carried out based on Wi-Fi finger print data, the method for carrying out indoor positioning based on inertia measurement data
Have preferable stability, but will appear accumulated error in prolonged position fixing process, and based on Wi-Fi finger print data into
The problem of accumulated error is not present in the method for row indoor positioning, but positioning result is easy to happen jump, and stability is poor, passes through
Kalman filter model is constantly corrected the error that inertial positioning is accumulated at any time using Wi-Fi fingerprint location, while using inertia
Positioning is to make up the unstability of Wi-Fi fingerprint location, to substantially increase the precision of final positioning result.
It should be understood that the size of the serial number of each step is not meant that the order of the execution order in above-described embodiment, each process
Execution sequence should be determined by its function and internal logic, the implementation process without coping with the embodiment of the present invention constitutes any limit
It is fixed.
Corresponding to a kind of indoor orientation method described in foregoing embodiments, Fig. 5 shows provided in an embodiment of the present invention one
One embodiment structure chart of kind indoor positioning device.
In the present embodiment, a kind of indoor positioning device may include:
First data acquisition module 501, for obtaining the inertia measurement data of terminal device acquisition;
First positioning coordinate calculation module 502, for calculating the of the terminal device according to the inertia measurement data
One positioning coordinate;
Second data acquisition module 503, for obtaining the Wi-Fi finger print data of the terminal device acquisition;
Second positioning coordinate calculation module 504, for calculating the of the terminal device according to the Wi-Fi finger print data
Two positioning coordinates;
Kalman filtering module 505, it is default for the first positioning coordinate and the second positioning coordinate to be input to
Kalman filter model in be corrected processing, the positioning coordinate after obtaining terminal device correction.
Further, the first positioning coordinate calculation module may include:
First computing unit, for calculating separately step-length, cadence and the side of each movement according to the inertia measurement data
To drift angle;
Second computing unit, for calculating separately the distance of each movement according to each mobile Stride length and frequency;
Third computing unit, for being calculated according to preset starting position coordinates, the distance of each movement and direction deflection angle
First positioning coordinate of the terminal device.
Further, the third computing unit is specifically used for calculating the first positioning coordinate according to the following formula:
Wherein, (N0,E0) it is the starting position coordinates, n and k are the serial number of each movement, dnMobile for n-th
Distance, θnFor the mobile direction deflection angle of n-th, (Nk,Ek) it is the first positioning coordinate after kth time is mobile, 1≤n≤k.
Further, the second positioning coordinate calculation module may include:
Metrics calculation unit, for calculating separately each sample data in preset sample database and the Wi-Fi
Euclidean distance between finger print data;
Sample selection unit, for European between the Wi-Fi finger print data from being chosen in the sample database
Apart from the smallest S sample data as preferred sample data, wherein S is the integer greater than 1;
Coordinate calculating unit, for calculating the second positioning coordinate according to the following formula:
Wherein, i is the serial number of the preferred sample data, 1≤i≤S, XiIt is corresponding with i-th of preferred sample data
Coordinate, WiFor weighting coefficient corresponding with i-th of preferred sample data, YkIt is the second positioning coordinate after kth time movement.
Further, the Kalman filtering module is specifically used for calculating according to the following formula and determine after the terminal device corrects
Position coordinate:
xk'=xk+K*(yk-H*xk)
Wherein, xkFor the first positioning coordinate, ykFor the second positioning coordinate, H is unit matrix, and K is preset card
Germania gain, xk' for the terminal device correction after positioning coordinate.
It is apparent to those skilled in the art that for convenience and simplicity of description, the device of foregoing description,
The specific work process of module and unit, can refer to corresponding processes in the foregoing method embodiment, and details are not described herein.
In the above-described embodiments, it all emphasizes particularly on different fields to the description of each embodiment, is not described in detail or remembers in some embodiment
The part of load may refer to the associated description of other embodiments.
The schematic block diagram that Fig. 6 shows a kind of terminal device provided in an embodiment of the present invention is only shown for ease of description
Part related to the embodiment of the present invention.
As shown in fig. 6, the indoor positioning terminal device 6 of the embodiment includes: processor 60, memory 61 and is stored in
In the memory 61 and the computer program 62 that can be run on the processor 60.The processor 60 executes the calculating
Realize the step in above-mentioned each indoor orientation method embodiment when machine program 62, such as step S101 shown in FIG. 1 is to step
S105.Alternatively, the processor 60 realizes each module/unit in above-mentioned each Installation practice when executing the computer program 62
Function, such as module 501 shown in Fig. 5 is to the function of module 505.
Illustratively, the computer program 62 can be divided into one or more module/units, it is one or
Multiple module/units are stored in the memory 61, and are executed by the processor 60, to complete the present invention.Described one
A or multiple module/units can be the series of computation machine program instruction section that can complete specific function, which is used for
Implementation procedure of the computer program 62 in the indoor positioning terminal device 6 is described.
The indoor positioning terminal device 6 can be mobile phone, tablet computer, smartwatch/bracelet, intelligent glasses, on table
Type computer, notebook and cloud server etc. calculate equipment.It will be understood by those skilled in the art that Fig. 6 is only indoor fixed
The example of position terminal device 6, does not constitute the restriction to indoor positioning terminal device 6, may include more more or less than illustrating
Component, perhaps combine certain components or different components, such as the indoor positioning terminal device 6 can also include defeated
Enter output equipment, network access equipment, bus etc..
The processor 60 can be central processing unit (Central Processing Unit, CPU), can also be
Other general processors, digital signal processor (Digital Signal Processor, DSP), specific integrated circuit
(Application Specific Integrated Circuit, ASIC), field programmable gate array (Field-
Programmable Gate Array, FPGA) either other programmable logic device, discrete gate or transistor logic,
Discrete hardware components etc..General processor can be microprocessor or the processor is also possible to any conventional processor
Deng.
The memory 61 can be the internal storage unit of the indoor positioning terminal device 6, such as indoor positioning end
The hard disk or memory of end equipment 6.The memory 61 is also possible to the External memory equipment of the indoor positioning terminal device 6,
Such as the plug-in type hard disk being equipped on the indoor positioning terminal device 6, intelligent memory card (Smart Media Card, SMC),
Secure digital (Secure Digital, SD) card, flash card (Flash Card) etc..Further, the memory 61 may be used also
With the internal storage unit both including the indoor positioning terminal device 6 or including External memory equipment.The memory 61 is used
Other programs and data needed for storing the computer program and the indoor positioning terminal device 6.The memory
61 can be also used for temporarily storing the data that has exported or will export.
It is apparent to those skilled in the art that for convenience of description and succinctly, only with above-mentioned each function
Can unit, module division progress for example, in practical application, can according to need and by above-mentioned function distribution by different
Functional unit, module are completed, i.e., the internal structure of described device is divided into different functional unit or module, more than completing
The all or part of function of description.Each functional unit in embodiment, module can integrate in one processing unit, can also
To be that each unit physically exists alone, can also be integrated in one unit with two or more units, it is above-mentioned integrated
Unit both can take the form of hardware realization, can also realize in the form of software functional units.In addition, each function list
Member, the specific name of module are also only for convenience of distinguishing each other, the protection scope being not intended to limit this application.Above system
The specific work process of middle unit, module, can refer to corresponding processes in the foregoing method embodiment, and details are not described herein.
In the above-described embodiments, it all emphasizes particularly on different fields to the description of each embodiment, is not described in detail or remembers in some embodiment
The part of load may refer to the associated description of other embodiments.
Those of ordinary skill in the art may be aware that list described in conjunction with the examples disclosed in the embodiments of the present disclosure
Member and algorithm steps can be realized with the combination of electronic hardware or computer software and electronic hardware.These functions are actually
It is implemented in hardware or software, the specific application and design constraint depending on technical solution.Professional technician
Each specific application can be used different methods to achieve the described function, but this realization is it is not considered that exceed
The scope of the present invention.
In embodiment provided by the present invention, it should be understood that disclosed device/terminal device and method, it can be with
It realizes by another way.For example, device described above/terminal device embodiment is only schematical, for example, institute
The division of module or unit is stated, only a kind of logical function partition, there may be another division manner in actual implementation, such as
Multiple units or components can be combined or can be integrated into another system, or some features can be ignored or not executed.Separately
A bit, shown or discussed mutual coupling or direct-coupling or communication connection can be through some interfaces, device
Or the INDIRECT COUPLING or communication connection of unit, it can be electrical property, mechanical or other forms.
The unit as illustrated by the separation member may or may not be physically separated, aobvious as unit
The component shown may or may not be physical unit, it can and it is in one place, or may be distributed over multiple
In network unit.It can select some or all of unit therein according to the actual needs to realize the mesh of this embodiment scheme
's.
It, can also be in addition, the functional units in various embodiments of the present invention may be integrated into one processing unit
It is that each unit physically exists alone, can also be integrated in one unit with two or more units.Above-mentioned integrated list
Member both can take the form of hardware realization, can also realize in the form of software functional units.
If the integrated module/unit be realized in the form of SFU software functional unit and as independent product sale or
In use, can store in a computer readable storage medium.Based on this understanding, the present invention realizes above-mentioned implementation
All or part of the process in example method, can also instruct relevant hardware to complete, the meter by computer program
Calculation machine program can be stored in a computer readable storage medium, the computer program when being executed by processor, it can be achieved that on
The step of stating each embodiment of the method.Wherein, the computer program includes computer program code, the computer program generation
Code can be source code form, object identification code form, executable file or certain intermediate forms etc..The computer-readable medium
It may include: any entity or device, recording medium, USB flash disk, mobile hard disk, magnetic that can carry the computer program code
Dish, CD, computer storage, read-only memory (ROM, Read-Only Memory), random access memory (RAM,
Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium etc..It should be noted that described
The content that computer-readable medium includes can carry out increasing appropriate according to the requirement made laws in jurisdiction with patent practice
Subtract, such as does not include electric carrier signal and electricity according to legislation and patent practice, computer-readable medium in certain jurisdictions
Believe signal.
Embodiment described above is merely illustrative of the technical solution of the present invention, rather than its limitations;Although referring to aforementioned reality
Applying example, invention is explained in detail, those skilled in the art should understand that: it still can be to aforementioned each
Technical solution documented by embodiment is modified or equivalent replacement of some of the technical features;And these are modified
Or replacement, the spirit and scope for technical solution of various embodiments of the present invention that it does not separate the essence of the corresponding technical solution should all
It is included within protection scope of the present invention.
Claims (10)
1. a kind of indoor orientation method characterized by comprising
Obtain the inertia measurement data of terminal device acquisition;
The first positioning coordinate of the terminal device is calculated according to the inertia measurement data;
Obtain the Wi-Fi finger print data of the terminal device acquisition;
The second positioning coordinate of the terminal device is calculated according to the Wi-Fi finger print data;
The first positioning coordinate and the second positioning coordinate are input in preset Kalman filter model and are corrected
Processing, the positioning coordinate after obtaining the terminal device correction.
2. indoor orientation method according to claim 1, which is characterized in that described to be calculated according to the inertia measurement data
The first of the terminal device positions coordinate
Step-length, cadence and the direction deflection angle of each movement are calculated separately according to the inertia measurement data;
The distance of each movement is calculated separately according to each mobile Stride length and frequency;
The first positioning of the terminal device is calculated according to preset starting position coordinates, the distance of each movement and direction deflection angle
Coordinate.
3. indoor orientation method according to claim 2, which is characterized in that it is described according to preset starting position coordinates,
The distance and direction deflection angle of each movement calculate the terminal device first positioning coordinate include:
The first positioning coordinate is calculated according to the following formula:
Wherein, (N0,E0) it is the starting position coordinates, n and k are the serial number of each movement, dnFor the mobile distance of n-th,
θnFor the mobile direction deflection angle of n-th, (Nk,Ek) it is the first positioning coordinate after kth time is mobile, 1≤n≤k.
4. indoor orientation method according to claim 1, which is characterized in that described according to the Wi-Fi finger print data meter
Calculate the terminal device second positioning coordinate include:
Calculate separately between each sample data and the Wi-Fi finger print data in preset sample database it is European away from
From;
From the smallest S sample data of Euclidean distance chosen in the sample database between the Wi-Fi finger print data
As preferred sample data, wherein S is the integer greater than 1;
The second positioning coordinate is calculated according to the following formula:
Wherein, i is the serial number of the preferred sample data, 1≤i≤S, XiFor coordinate corresponding with i-th of preferred sample data,
WiFor weighting coefficient corresponding with i-th of preferred sample data, YkIt is the second positioning coordinate after kth time movement.
5. indoor orientation method according to any one of claim 1 to 4, which is characterized in that described to determine described first
Position coordinate and the second positioning coordinate are input in preset Kalman filter model and are corrected processing, obtain the terminal
Positioning coordinate after equipment calibration includes:
Positioning coordinate after calculating the terminal device correction according to the following formula:
xk'=xk+K*(yk-H*xk)
Wherein, xkFor the first positioning coordinate, ykFor the second positioning coordinate, H is unit matrix, and K is preset Kalman
Gain, xk' for the terminal device correction after positioning coordinate.
6. a kind of indoor positioning device characterized by comprising
First data acquisition module, for obtaining the inertia measurement data of terminal device acquisition;
First positioning coordinate calculation module, the first positioning for calculating the terminal device according to the inertia measurement data are sat
Mark;
Second data acquisition module, for obtaining the Wi-Fi finger print data of the terminal device acquisition;
Second positioning coordinate calculation module, for calculating the second positioning of the terminal device according to the Wi-Fi finger print data
Coordinate;
Kalman filtering module, for the first positioning coordinate and the second positioning coordinate to be input to preset Kalman
Processing is corrected in Filtering Model, the positioning coordinate after obtaining the terminal device correction.
7. indoor positioning device according to claim 6, which is characterized in that the first positioning coordinate calculation module packet
It includes:
First computing unit, the step-length, cadence and direction for calculating separately each movement according to the inertia measurement data are inclined
Angle;
Second computing unit, for calculating separately the distance of each movement according to each mobile Stride length and frequency;
Third computing unit, for according to the calculating of preset starting position coordinates, the distance of each movement and direction deflection angle
First positioning coordinate of terminal device.
8. indoor positioning device according to claim 6, which is characterized in that the second positioning coordinate calculation module packet
It includes:
Metrics calculation unit, for calculating separately each sample data in preset sample database and the Wi-Fi fingerprint
Euclidean distance between data;
Sample selection unit, for from the sample database choose and the Wi-Fi finger print data between Euclidean distance
The smallest S sample data is as preferred sample data, wherein S is the integer greater than 1;
Coordinate calculating unit, for calculating the second positioning coordinate according to the following formula:
Wherein, i is the serial number of the preferred sample data, 1≤i≤S, XiFor coordinate corresponding with i-th of preferred sample data,
WiFor weighting coefficient corresponding with i-th of preferred sample data, YkIt is the second positioning coordinate after kth time movement.
9. a kind of computer readable storage medium, the computer-readable recording medium storage has computer-readable instruction, special
Sign is, realizes that the interior as described in any one of claims 1 to 5 is fixed when the computer-readable instruction is executed by processor
The step of position method.
10. a kind of terminal device, including memory, processor and storage are in the memory and can be on the processor
The computer-readable instruction of operation, which is characterized in that the processor realizes such as right when executing the computer-readable instruction
It is required that the step of indoor orientation method described in any one of 1 to 5.
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