CN104808174B - Wireless positioning system of nuclear power station based on Kalman filter and dead reckoning - Google Patents
Wireless positioning system of nuclear power station based on Kalman filter and dead reckoning Download PDFInfo
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- CN104808174B CN104808174B CN201410693459.4A CN201410693459A CN104808174B CN 104808174 B CN104808174 B CN 104808174B CN 201410693459 A CN201410693459 A CN 201410693459A CN 104808174 B CN104808174 B CN 104808174B
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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
- G01S5/04—Position of source determined by a plurality of spaced direction-finders
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/04—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by terrestrial means
- G01C21/08—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by terrestrial means involving use of the magnetic field of the earth
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/10—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
- G01C21/12—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
- G01C21/16—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
Abstract
The invention relates to a wireless positioning system of a nuclear power station based on a Kalman filter and dead reckoning. The system is basically composed of a special mobile terminal, a smart phone, a positioning server and a positioning graphic user interface client, wherein the special mobile terminal is internally provided with a WIFI module, an MEMS sensor and an industrial special sensor, and the MEMS sensor of the special mobile terminal mainly comprises an accelerometer, a gyroscope and a magnetometer. The wireless network environment on which the system relies is necessary. The MEMS sensor in the special mobile terminal provides sensor data, the moving direction and distance of a wearer of the mobile terminal are calculated by Kalman filtering, and a calculation result, wireless signal intensity indication and terrestrial magnetism data are used to calculate the position and locus of the wearer of the mobile terminal by Kalman filtering again. The system can raise different alarm for the special working environment of the nuclear power station, including stay overtime, stationary overtime, and fall off.
Description
Technical field
The invention belongs to wireless communication technology field, and in particular to a kind of based on Kalman filter and dead reckoning
Nuclear power station wireless location system.
Background technology
Indoor positioning technologies based on WIFI (series standards of IEEE 802.11) in nuclear power station application, at home at present still
In initial stage.Because of particular/special requirement of the nuclear power station to electromagnetic environment, and the particularity of building topological structure etc., all cause
The wireless network environment of nuclear power station differs greatly from common commercial environment.
Based on the indoor positioning technologies of WIFI, when being positioned using fingerprint comparison method, it is relied heavily on
The foundation of fingerprint base.At present, setting up fingerprint base is mainly included based on two kinds of signal propagation model and field exploring, wherein：
(1) come out model and corresponding is propagated in atmosphere using signal based on signal propagation model method
Parameter, to each coordinate in positioning region, calculates certain access point (Access Point, AP) and refers to the signal intensity of the coordinate
Show (Received Signal Strength Indicator, RSSI) value.But affect what signal was propagated because interior is various
There is (such as the wall of various thickness, the wall with door OR gate hole and furniture etc.) in factor, need to consider the situation for doing special handling very
It is many.Additionally, wireless signal is after reflection, diffraction, scattering, simple propagation model is difficult for these situations to describe clear.
Nuclear power station build the complexity of topological structure and using construction material particularity more cause it is difficult based on signal propagation model method
It is heavy.
(2) field exploring method builds fingerprint base based on field exploring signal strength values, is not need indoor propagation model
, thus avoid the need for estimating the parameter of propagation model.But need to carry out positioning region offline before real-time positioning
The field level signal exploration in stage, the RSSI intensity levels gathered in each reference point locations that positioning region is chosen are special as fingerprint
Levy.When being positioned using common fingerprint comparison method, the density for choosing reference point has a significant impact to positioning precision.But
Once exploration point increases, its quantities and complexity all accordingly increase.Especially carry out in the complicated sensitive each Factory Building of nuclear power station
On-site land survey, due to implementing from nuclear power station capital construction, wireless coverage, to starting to load nuclear fuel preparation generating, there is certain
Time window, the exploration work for choosing a large amount of exploration points are hardly possible.
As can be seen here, indoor positioning is carried out in nuclear power plant environment using fingerprint comparison method, its practicality has limitation.
Additionally, the inertial navigation system of utilization MEMS (MEMS) sensor for quickly growing in recent years is fixed indoors
Also there is application in position.Inertial navigation belongs to the air navigation aid of dead reckoning (Dead Reckoning, DR) formula, and its principle is, right
The measured value of accelerometer carries out double integral and solves azimuth information.Using the inertial navigation system of high accuracy Inertial Measurement Unit
System, when it is applied to positioning, positioning precision is also very high.And high-precision Inertial Measurement Unit, due to cost, volume, power consumption etc.
Reason there is no method to widely use.In general, using the low cost such as INS errors based on MEMS sensor at any time
Between accumulate, when calculate double integral when, very big position excursion will be brought, it is impossible to work independently for a long time.We will adopt with
Lower personal dead reckoning (Personal Dead Reckoning, PDR) algorithm.
It has been generally acknowledged that the walking movement of people is two dimensional motion, its ultimate principle is plane geometry method.It is very short in the sampling period
In the case of, the walking of people is linear motion, learns a certain moment positional information, it is possible to release previous moment or subsequent time
Positional information and the displacement of sampling period one skilled in the art.Usually, it is known that initial position (x0, y0), what is speculated after we are oriented passs
Pushing-type,
K=1,2,3 ...
There are two key factors in the hypothetical system：Travel distance D and course angle ψ.Herein course angle is defined as walking side
To the angle with magnetic north direction.Similarly, we can have supposition stepping type forward.
Positioned using Geomagnetic signal and increasingly received publicity in recent years.Geomagnetic field has preferable stability.
But Partial Perimeter environment (iron mine nearby, reinforcing bar in ferrous metal material such as iron content plant equipment, building) can be right
Magnetic field produces a range of interference, makes field signal be distorted.Although surrounding enviroment produce interference to magnetic field, when one
Various erection of equipment are finished in building, after working environment is stable, the earth magnetism containing noisy distortion of each point in building
Signal is also stable.
Newton's algorithm list of references：Hagan, Martin T., Demuth, Howard B., Beale, Mark, Neural
Network Design, PWS Publishing Company, Boston 1995.
Direction calculating list of references：J.L.Marins, X.Yun, E.R.Bachmann, R.B.McGhee, and
M.J.Zyda, " An Extended Kalman Filtter for Quaternion-based Orientation
Estimation Using MARG Sensors ", in Proc.IEEE/RSJ Int.Conf.Intell.Robots Syst.,
Maui, HI, Oct.2001, pp.2003-2011.
The content of the invention
The present invention provides a kind of based on Kalman filter and the nuclear power station wireless location system of dead reckoning.The positioning
System completes location Calculation not merely with wireless signal strength data (RSSI value), also uses Geomagnetic signal data.The present invention
Using the result of calculation of personal dead reckoning (PDR), the state of the Kalman filter of " prediction " its construction, it is re-introduced into new
Observation, the artificial neural network that Jing is constructed in advance is that observational equation calculates " amendment " its state outcome.The purpose of the present invention
It is to overcome the defect individually having using above-mentioned various technologies, so as to avoid aforesaid limitation.System of the present invention
System also provides particular for nuclear power station particular job environment and stays overtime, static time-out, various safety, the accident announcement such as falls
Alert function.
The element of this alignment system includes：Built-in WIFI module and MEMS sensor and the special sensing of industry
The Specialised mobile terminal of device, it is mounted with the built-in WIFI module of specific application services and the smart mobile phone of MEMS sensor
(Android platform, iOS platforms or Windows Phone), location-server and positioning graphic user interface client.Special shifting
MEMS sensor mainly includes accelerometer, gyroscope, magnetometer in dynamic terminal.
The rely wireless network environment of operation of this alignment system is requisite, but be not belonging to the system comprising scope it
It is interior.
Before this alignment system can be with real time operation, it is necessary first to carry out exploration work.According to room in positioning region
Interior topological structure and arrangement choose some exploration point gathered datas.Each exploration point needs to gather the number of all directions four direction
According to.Gathered data includes：Exploration point coordinates (x, y), wireless signal strength data (RSSI value) at exploration point, and Geomagnetic signal
Data.(belong to one kind of artificial neural network, because of its activation primitive using one radial primary function network of these data genarations
Gained the name using RBF) RBF, realize to the signal strength values RSSI of positioning region coordinate of ground point to access point AP with
The mapping of Geomagnetic signal.By this mapping, necessary other finger print datas are generated, to reduce exploration workload.
Alignment system of the present invention is as shown in Figure 1；Its course of work and data flow are as shown in Figure 3.The step of concrete positioning
It is rapid as follows.
Step 1：By the output valve of each moment MEMS sensor of Specialised mobile terminal, Specialised mobile terminal wearer is calculated
Motion morphology, including it is static, mobile, fall etc..Now triggering alarm can be judged whether according to various alarm conditions.
Step 2：By the output valve of each moment MEMS sensor of Specialised mobile terminal, travel distance D is calculated.This alignment system
Two key factors are travel distance D and course angle ψ in adopted PDR algorithms.We realize that pedometer calculates walking with algorithm
Step number, then estimate step-length, that is, obtain apart from D.The big position excursion that double integral brings can be avoided with such method.
The factor that step-size estimation considers has：(1) usually, the step-length of people is the 37%-45% of height；(2) height information takes from employee
Data base, when height information is lacked, by sex average height is taken；(3) step-length changes with variation in pace speed；(4) strength is walked
Step-length can be bigger (tending to 45%) when (now the output valve deviation average of accelerometer is more)；(5) interior is (especially in working area
It is indoor) walking do not consider jump, quickly runs, very big etc. non-common factors of left and right lower limb step-length discrepancy.
Step 3：By the output valve of each moment MEMS sensor of Specialised mobile terminal, course angle ψ, pitching angle theta and horizontal stroke are calculated
Roll angleFor convenience of calculating, our wearing modes of special specification Specialised mobile terminal in nuclear power station are (such as：It is worn on waist
Between, front panel points to the front of wearer).So, course angle is Specialised mobile terminal front panel direction and magnetic north side
To angle.We are by first seeking the quaternary number related to course angle, the angle of pitch and roll angle, then to be changed by quaternary number
To course angle, the angle of pitch and roll angle.Fig. 2 is to solve for the schematic diagram of corresponding quaternary number.In figureBg、BM represents that respectively MEMS is sensed
The vector acceleration and magnetic field vector of the carrier coordinate system of device；Eg、EM represents respectively the vector acceleration of inertial coodinate system and magnetic field
Vector.ByBg、BM andEg、EM Jing Newton's algorithms calculate quaternary number q=(a, b, c, d) of correlation, the same gyroscopes of this quaternary number q
Measurement data (p, q, r) together as Kalman filter observation calculate estimated value () and ().Profit
The conversion formula for counting to Eulerian angles with quaternary can obtain course angle ψ, pitching angle theta and roll angle(Newton's algorithm sees reference document：
Hagan, Martin T., Demuth, Howard B., Beale, Mark, Neural Network Design, PWS
Publishing Company, Boston 1995.Direction calculating sees reference document：J.L.Marins, X.Yun,
E.R.Bachmann, R.B.McGhee, and M.J.Zyda, " An Extended Kalman Filter for Qua
Ternion-based Orientation Estima tion Using MARG Sensors ", in Proc.IEEE/RSJ
Int.Conf.Intell.Robots Syst., Maui, HI, Oct.2001, pp.2003-2011.)
Step 4：Build Kalman filter.Its dynamic model is, using position coordinateses (x, y) as state vector, karr
The state equation of graceful wave filter is
xk+1=xk+D sinψ
yk+1=yk+D cosψ
Wherein D and ψ are that Jing steps 2 and step 3 are obtained.Its observation model is to be obtained with Specialised mobile terminal measurement
A series of magnetometer output valve of RSSI values and Specialised mobile terminal is observed quantity, using aforementioned RBF RBF, Kalman
The observational equation of wave filter is,
zM, k=RBFM, k(xk, yk)+nM, k
Wherein zM, kThe RSSI value (1≤m≤M) of m-th AP for observing, or measurement to magnetometer data (M+1≤m
≤M+3)；nM, kFor the random noise of Gaussian distributed, its average is zero, and standard deviation is determined (i.e. by the variability of survey data
The standard deviation of survey data).The position coordinateses of Specialised mobile terminal wearer are calculated by the Kalman filter.
Description of the drawings
Fig. 1 is a simplified wireless indoor alignment system schematic diagram based on WIFI.
Fig. 2 is to solve for the schematic diagram of corresponding quaternary number.
Fig. 3 is the system course of work and data flow diagram.
Specific embodiment
It is exemplary below by way of the embodiment being described with reference to the drawings, is only used for explaining the present invention, and can not be construed to
Limitation of the present invention.
The real-time calculating process of items when being embodied as not only including positioning of the present invention, also including on-site land survey and by surveying
Survey the process (commonly referred to training process or learning process) of data configuration RBF networks.For being consistent property, while not losing complete
Property, this process number is step 0 by we.Specific implementation step is as follows.
Step 0：On-site land survey, using survey data RBF networks are constructed.
Some exploration point gathered datas are chosen according to indoor topological structure and arrangement in positioning region.Each exploration point is needed
Gather the data of all directions four direction.Gathered data includes：Exploration point coordinates (x, y), wireless signal is strong at exploration point
Degrees of data, and Geomagnetic signal data.(belong to artificial neural network using one radial primary function network of these data genarations
One kind, because its activation primitive is gained the name using RBF) RBF, realize to positioning region coordinate of ground point to access point
The signal strength values RSSI of AP and the mapping of Geomagnetic signal.
Step 1：By the output valve of each moment MEMS sensor of Specialised mobile terminal, Specialised mobile terminal wearer is calculated
Motion morphology, including it is static, mobile, fall etc..Now triggering alarm can be judged whether according to various alarm conditions.
Step 2：By the output valve of each moment MEMS sensor of Specialised mobile terminal, travel distance D is calculated.This alignment system
Two key factors are travel distance D and course angle ψ in adopted PDR algorithms.We realize that pedometer calculates walking with algorithm
Step number, then estimate step-length, that is, obtain apart from D.The big position excursion that double integral brings can be avoided with such method.
The factor that step-size estimation considers has：(1) usually, the step-length of people is the 37%-45% of height；(2) height information takes from employee
Data base, when height information is lacked, by sex average height is taken；(3) step-length changes with variation in pace speed；(4) strength is walked
Step-length can be bigger (tending to 45%) when (now the output valve deviation average of accelerometer is more)；(5) interior is (especially in working area
It is indoor) walking do not consider jump, quickly runs, very big etc. non-common factors of left and right lower limb step-length discrepancy.
Step 3：By the output valve of each moment MEMS sensor of Specialised mobile terminal, course angle ψ, pitching angle theta and horizontal stroke are calculated
Roll angleFor convenience of calculating, our wearing modes of special specification Specialised mobile terminal in nuclear power station are (such as：It is worn on waist
Between, front panel points to the front of wearer).So, course angle is Specialised mobile terminal front panel direction and magnetic north side
To angle.We are by first seeking the quaternary number related to course angle, the angle of pitch and roll angle, then to be changed by quaternary number
To course angle, the angle of pitch and roll angle.Fig. 2 is to solve for the schematic diagram of corresponding quaternary number.In figureBg、BM represents that respectively MEMS is sensed
The vector acceleration and magnetic field vector of the carrier coordinate system of device；Eg、EM represents respectively the vector acceleration of inertial coodinate system and magnetic field
Vector.ByBg、BM andEg、EM Jing Newton's algorithms calculate quaternary number q=(a, b, c, d) of correlation, the same gyroscopes of this quaternary number q
Measurement data (p, q, r) together as Kalman filter observation calculate estimated value () and ().Profit
The conversion formula for counting to Eulerian angles with quaternary can obtain course angle ψ, pitching angle theta and roll angle
Step 4：Build Kalman filter.Its dynamic model is, using position coordinateses (x, y) as state vector, karr
The state equation of graceful wave filter is
xk+1=xk+D sinψ
yk+1=yk+D cosψ
Wherein D and ψ are that Jing steps 2 and step 3 are obtained.Its observation model is to be obtained with Specialised mobile terminal measurement
A series of magnetometer output valve of RSSI values and Specialised mobile terminal is observed quantity, using aforementioned RBF RBF, Kalman
The observational equation of wave filter is,
zM, k=RBFM, k(xk, yk)+nM, k
Wherein zM, kThe RSSI value (1≤m≤M) of m-th AP for observing, or measurement to magnetometer data (M+1≤m
≤M+3)；nM, kFor the random noise of Gaussian distributed, its average is zero, and standard deviation is determined (i.e. by the variability of survey data
The standard deviation of survey data).The position coordinateses of Specialised mobile terminal wearer are calculated by the Kalman filter.
The content that description is not described in detail belongs to prior art known to professional and technical personnel in the field.
The preferred embodiments of the present invention are the foregoing is only, the present invention is not limited to, for those skilled in the art
For, the present invention can have various changes and change.All any modification, equivalents made within spirit and principles of the present invention
Replace, improve etc., all should belong within the scope of the claims of the present invention.
Claims (1)
1. it is a kind of based on Kalman filter and the nuclear power station WIFI wireless location systems of dead reckoning, it is characterised in that should
The element of system includes：
Mobile terminal, is worn on detected personnel, built-in WIFI module and MEMS sensor, and wherein MEMS sensor includes
Accelerometer, gyroscope and magnetometer；
Smart mobile phone, including application services, built-in WIFI module and MEMS sensor；
Location-server, receives the various signal datas of mobile terminal and smart mobile phone collection, and position result is calculated in real time；Positioning
Graphic user interface client, to real-time display location result；
The localization method that the alignment system is adopted is divided into two stages：
1) the early stage exploration stage：Some exploration point gathered datas are chosen according to indoor topological structure and arrangement in positioning region,
Wherein gathered data includes：Exploration point coordinates (x, y), wireless signal strength data at exploration point, and Geomagnetic signal data, profit
It is one radial primary function network of each access point AP and every kind of Geomagnetic signal data genaration with the data, realizes by positioning area
Signal strength values RSSI and the mapping of Geomagnetic signal of the domain coordinate of ground point to AP；
2) the real-time positioning stage, comprise the following steps：
Step 1：By the output valve of each moment MEMS sensor of mobile terminal, the motion morphology of mobile terminal wearer is calculated；
Step 2：By the output valve of each moment MEMS sensor of mobile terminal, obtained apart from D according to the step number and step-length of walking；
Step 3：By the output valve of each moment MEMS sensor of mobile terminal, first ask related to course angle, the angle of pitch and roll angle
Quaternary number（A, b, c, d), this quaternary number is with gyroscope measurement data (p, q, r) together as the observation of Kalman filter
Calculate estimated valueWithAgain course angle ψ, pitching angle theta and roll angle are converted to by quaternary number
Step 4：Build Kalman filter：
Dynamic model is that, using position coordinateses (x, y) as state vector, the state equation of Kalman filter is：
xk+1=xk+D sinψ
yk+1=yk+D cosψ
Wherein, D and ψ are that Jing steps 2 and step 3 are obtained；
Observation model is a series of RSSI values and the magnetometer output valve of mobile terminal obtained with mobile terminal measurement as observation
Amount, using the radial primary function network that stage generation is surveyed in early stage, the observational equation of Kalman filter is：
zM, k=RBFM, k(xk, yk)+nM, k
Wherein, zM,K is the RSSI value of m-th AP observed at the k moment, 1≤m≤M, or the magnetometer data for measuring, M+1
≤m≤M+3；M is the number of observable wireless access point AP in positioning region；nM, kMaking an uproar at random for Gaussian distributed
Sound；RBFM, kRepresent the radial primary function network of m-th AP, or the radial primary function network of certain Geomagnetic signal data；(xk, yk)
The position coordinateses at the k moment are represented, the position coordinateses of mobile terminal wearer are calculated by the Kalman filter.
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| CN105783924A (en) * | 2016-01-29 | 2016-07-20 | 广东工业大学 | Indoor positioning method based on magnetic field intensity |
| CN105611630A (en) * | 2016-02-19 | 2016-05-25 | 徐州坤泰电子科技有限公司 | Gyroscope positioning system for smartphone |
| CN107229331A (en) * | 2017-04-27 | 2017-10-03 | 北京英贝思科技有限公司 | It is a kind of to make to move the method that VR equipment realizes simple motion function |
| CN107182036A (en) * | 2017-06-19 | 2017-09-19 | 重庆邮电大学 | The adaptive location fingerprint positioning method merged based on multidimensional characteristic |
| CN108894825A (en) * | 2018-08-16 | 2018-11-27 | 深圳市炬视科技有限公司 | A kind of tunnel defect intelligent analysis method |
| CN109085564B (en) * | 2018-08-31 | 2020-09-18 | 北京邮电大学 | Positioning method and device |
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