CN104333903A - Indoor multi-object positioning system and method based on RSSI (receiver signal strength indicator) and inertia measurement - Google Patents

Indoor multi-object positioning system and method based on RSSI (receiver signal strength indicator) and inertia measurement Download PDF

Info

Publication number
CN104333903A
CN104333903A CN201410474704.2A CN201410474704A CN104333903A CN 104333903 A CN104333903 A CN 104333903A CN 201410474704 A CN201410474704 A CN 201410474704A CN 104333903 A CN104333903 A CN 104333903A
Authority
CN
China
Prior art keywords
anchor node
positioning
rssi
location
node
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN201410474704.2A
Other languages
Chinese (zh)
Inventor
冉静
袁东明
胡鹤飞
高锦春
谢刚
刘元安
刘宇杰
田亮亮
尚颖
周赟
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Beijing University of Posts and Telecommunications
Original Assignee
Beijing University of Posts and Telecommunications
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Beijing University of Posts and Telecommunications filed Critical Beijing University of Posts and Telecommunications
Priority to CN201410474704.2A priority Critical patent/CN104333903A/en
Publication of CN104333903A publication Critical patent/CN104333903A/en
Pending legal-status Critical Current

Links

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management
    • H04W64/006—Locating users or terminals or network equipment for network management purposes, e.g. mobility management with additional information processing, e.g. for direction or speed determination
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/10—Scheduling measurement reports ; Arrangements for measurement reports

Landscapes

  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Position Fixing By Use Of Radio Waves (AREA)

Abstract

The invention discloses an indoor multi-object positioning system and method based on an RSSI (receiver signal strength indicator) and inertia measurement. The system is provided with three components: a positioning server, positioning anchor anodes and positioners, integrates positioning data of an RSSI method and the positioning data of an inertia measurement method, and then executes dynamic correction on the positions of the positioning anchor nodes and the positioners so as to reduce system positioning errors, improve system positioning precision and enhance system positioning stability. According to the invention, by use of a characteristic that anchor node positions are relatively fixed in a progressive maximum positioning process, through increasing measuring time and reducing the influence of environment accidental factors on the RSSI, the RSSI measuring precision of the anchor nodes is improved. During a positioning measuring process, period correction is performed on the positions of each stage of anchor nodes by use of new range finding signal values so that the stability and the accuracy of the positioning system are improved. Besides, the two methods of a RSSI propagation model and the inertia measurement are utilized for data fusion and positioning, so that the strengths of the two can be integrated, and the positioning precision is higher.

Description

Based on the multiobject navigation system in indoor and the method for RSSI and inertia measurement
Technical field
The present invention relates to a kind of location technology solving indoor environment, exactly, relate to a kind of multiobject navigation system in indoor based on RSSI and inertia measurement and method, belong to the technical field of indoor positioning.
Background technology
Wireless indoor location technology all has the prospect of wide application because of it in indoor navigation, trajectory track, mobile office, emergency position circular etc., become the strategic development emphasis of the Invention service provider such as Google, Foursquare and the mobile operator such as China Mobile, China Telecom, and become a requisite part in nowadays mobile Internet business.GPS because it is with high costs, to search star speed slow, and the problem such as cannot to locate by barrier obstruction, be not suitable for being directly used in indoor positioning, other alternative methods must be found.The research origin of indoor positioning is in the 1990s age, the research of current indoor positioning comprises GSM location, infrared ray location (Active Badge), ultrasonic wave location (Cricket System and Active Bat), ultra broadband (UWB) is located, radio frequency identification (RFID) location (LANDMARK) etc.The location technology that the present invention uses comprises: received signal strength indicator RSSI (Receive Signal Strength Indicator) propagation model location technology and inertia measurement location technology.Below, first these two kinds of technical background situations of brief introduction:
(1) RSSI propagation model location is a kind of location algorithm of classics, because it calculates simple, therefore in current wireless location system still extensive application.The method is the distance indirectly obtaining between signal sending point and acceptance point by propagation model, the position of recycling geometrical relationship determination target.
The relation of the received signal strength RSSI of wireless signal and the transmission range of signal can simply be expressed as: RSSI=-(A+10nlgd)+pt; Wherein, RSSI value when A is signal propagation 1m, n is the path attenuation factor, and d is the spacing of transmitting terminal and receiving terminal, and pt obeys the factor of influence that average is the Gaussian Profile of 0.According to above-mentioned formula, ignore pt item, the distance d of receiving terminal and transmitting terminal can be calculated by the RSSI value of receiving terminal.
The following describes RSSI propagation model method at three-dimensional position fixing process.
In three dimensions, unknown node can determine the coordinate of self according to the range information between itself and 4 not coplanar neighbours' reference nodes.Suppose unknown node E (x, y, z) according to 4 not coplanar neighbours' reference node A (x 1, y 1, z 1), B (x 2, y 2, z 2), C (x 3, y 3, z 3) and D (x 4, y 4, z 4) between distance be respectively d 1, d 2, d 3, d 4.That is: d 1 2 = ( x - x 1 ) 2 + ( y - y 1 ) 2 + ( z - z 1 2 ) d 2 2 = ( x - x 2 ) 2 + ( y - y 2 ) 2 + ( z - z 2 2 ) d 3 2 = ( x - x 3 ) 2 + ( y - y 3 ) 2 + ( z - z 3 2 ) d 4 2 = ( x - x 4 ) 2 + ( y - y 4 ) 2 + ( z - z 4 2 ) ; Arrange again: r i 2 = d i 2 - x i 2 - y i 2 - z i 2 r i 2 = d i 2 - x i 2 - y i 2 , And i=1,2,3,4, then deduct the 4th equation respectively by front 3 equations, can obtain: 2 x 4 - 2 x 1 2 y 4 - 2 y 1 2 z 4 - 2 z 1 2 x 4 - 2 x 2 2 y 4 - 2 y 2 2 z 4 - 2 z 2 2 x 4 - 2 x 3 2 y 4 - 2 y 3 2 z 4 - 2 z 3 x y z = r 1 2 - r 4 2 r 2 2 - r 4 2 r 3 2 - r 4 2 . Establish again: Q = 2 x 4 - 2 x 1 2 y 4 - 2 y 1 2 z 4 - 2 z 1 2 x 4 - 2 x 2 2 y 4 - 2 y 2 2 z 4 - 2 z 2 2 x 4 - 2 x 3 2 y 4 - 2 y 3 2 z 4 - 2 z 3 , θ = x y z , b = r 1 2 - r 4 2 r 2 2 - r 4 2 r 3 2 - r 4 2 ; Then above-mentioned formula can be exchanged into: Q θ=b, obtains least square solution: in formula, for unknown node E (x, y, the z) position coordinates calculated by least square method.
From analyzing above, when rssi measurement accuracy is higher, the distance between node calculates will be more accurate, and the positioning precision of propagation model method is also higher.
But, rssi measurement and indoor environment Relationship Comparison close.For outdoor, the interior space is less, layout is complicated, the multiple accidentalia such as to walk about of wall, door and window, electrical equipment, personnel all can be propagated signal and have an impact, and cause such as reflect, reflect, diffraction and scattering phenomenon, and then cause the multipath transmisstion effect of wireless signal, therefore, the shake of RSSI real-time measurement values is very large, makes the error of the real-time positioning mode of RSSI propagation model larger.
But, if RSSI effective sample is enough large, by parameter optimization and filtering process, the measure error of RSSI can be reduced.Therefore the sampling time is longer, and the RSSI effective sample quantity of acquisition is more, and RSSI propagation model method location is more stable, and accuracy also can be higher.
(2) inertia measurement location technology is a kind of independent positioning technology not relying on external information, by measuring carrier in the acceleration of inertial reference system and direction, it is carried out integration to the time, just can obtain the information such as the speed of localizing objects in reference frame, yaw angle and position.Along with popularizing of inertia measurement equipment, inertia measurement location technology is also used to indoor positioning more and more.
Pedestrian's reckoning algorithm is a kind of conventional inertia measurement location algorithm, and this algorithm general principle utilizes home position, displacement and direction to calculate pedestrian position.Concrete grammar is: adopt the product of step number and step-length as the distance of walking, then calculate the displacement of walking in conjunction with direction of travel, then according to the initial position of pedestrian, just can calculate pedestrian move after position.
The process of reckoning algorithm can be expressed as: in formula, (x n, y n, z n) be initial position, (x n+1, y n+1, z n+1) be the position of subsequent time, k, l are step number, the step-length of movement respectively, it is three-dimensional moving direction vector.
The reckoning algorithm of inertial sensor has completely autonomous location, a dependence transducer and by the advantage such as outer signals and environmental impact, can be user-provided location information in the short time very flexibly, whenever and wherever possible.
In reckoning algorithm, step number, direction and step-length are three principal elements affecting positioning precision, wherein, step number is that the data analysis gathered by acceleration transducer is drawn, direction can be obtained by electronic compass, step-length directly cannot be measured because of it and draw, general use experience estimated value.Step-length due to user has very large randomness and variability, and the step number drawn by sensing data and directional information also exist error, and therefore, along with the increase of time, the position error of pedestrian's reckoning algorithm also can constantly increase.
Summary of the invention
In view of this, the object of this invention is to provide a kind of for solve Multi-target position in indoor environment, based on the multiobject navigation system in indoor of RSSI and inertia measurement and method, the present invention combines the feature that RSSI long-term tillage has been stablized and the advantage that inertial navigation location technology short-term positioning precision is high, continuity is good, has better positioning precision.
In order to achieve the above object, the invention provides a kind of multiobject navigation system in indoor based on received signal strength indicator RSSI (Receive Signal Strength Indicator) and inertia measurement, it is characterized in that: described system is the locator data merging RSSI and inertia measurement two kinds of method of measurement, and dynamic calibration is carried out to the position of positioning anchor node and locator, make the stability that system position error reduces and increase system is located; This system is provided with three building blocks: location-server, positioning anchor node and locator, wherein:
Location-server, is responsible for the location measurement information sent according to positioning anchor node and locator, the position of compute location anchor node and locator, and positioning result is sent to locator by positioning anchor node; Be provided with four comprising modules: communication interface, system locating module, data memory module and data disaply moudle;
Positioning anchor node, as the via node of the two-way communication path of location-server and locator, had both been responsible for the operational order of location-server to send to locator; Simultaneously also for for providing position reference data when locator is located, performing and measuring operation, and forwarding positioning result data to location-server; Positioning anchor node divides into the anchor node of multiple grade according to the sequencing that it is placed: the known positioning anchor node in position is anchor node, one-level anchor node, secondary anchor node and follow-up corresponding anchor node; This navigation system is the position of the position calculation determination next stage anchor node according to upper level anchor node: the position first obtaining one-level anchor node according to the position calculation of anchor node, the position of secondary anchor node is obtained again according to the position calculation of one-level anchor node, the like, form multistage anchor node; Each positioning anchor node is respectively equipped with three comprising modules: communication interface, data memory module and rssi measurement module;
Locator, is responsible for gathering RSSI data and inertia measurement data, and sends to location-server, and receive and show the positioning result of location-server; Be provided with four comprising modules: communication interface, data memory module, sensor assembly and display module.
In order to achieve the above object, present invention also offers a kind of multi-target orientation method adopting the indoor multiobject navigation system of the present invention, it is characterized in that: the locator data of two kinds of method of measurement of received signal strength indicator RSSI and inertia measurement is merged, again dynamic corrections is performed to the position of positioning anchor node and locator, with the stability of the positioning precision and increase system location that improve system; Described method comprises following operative step:
Step 1, the initial position of positioning anchor node is set: when starting to locate, first the initial position of positioning anchor node is set in location-server, again before location starts, first the position coordinates of known initial anchor node is input in location-server, and obtains the position of the positioning anchor node of subsequent stages according to the position step-by-step calculation of anchor node;
Step 2, the target of location movement: after target moves a segment distance, the locator placed on the object sends to location-server the RSSI value received and the inertia measurement parameter of itself, before maximum in the RSSI numerical value that location-server receives using locator, k anchor node is as with reference to node, in conjunction with inertia measurement data, data fusion positioning is carried out to locator; Wherein, natural number k should be more than or equal to 4.
The advantage of the multiobject navigation system in indoor and method that the present invention is based on RSSI and inertia measurement is:
The present invention utilizes the incrementally relatively-stationary feature in anchor node position in position fixing process, by increasing Measuring Time and reducing environment accidentalia to the impact of RSSI, improves anchor node rssi measurement precision.
The present invention, in aligner measurements, uses new ranging signal value periodically to revise every one-level anchor node position, increases stability and the accuracy of navigation system.
The present invention uses RSSI propagation model and inertia measurement two kinds of methods to carry out data fusion positioning, is compared to single RSSI location or inertial navigation location, has better positioning precision.
Innovation key technology of the present invention comprises: the relatively-stationary feature in position utilizing anchor node at different levels in incrementally position fixing process, by increasing Measuring Time, reducing the accidentalia of environment to the impact of RSSI, improving anchor node rssi measurement precision.Also in aligner measurements, use new ranging signal value to carry out periodicity correction to every one-level anchor node position, increase stability and the accuracy of navigation system.In a word, the data that the present invention uses RSSI propagation model and inertia measurement two kinds of method of measurement to obtain carry out fusion location, compare be used alone wherein RSSI location or inertial navigation location all have better, more stable positioning precision.
Accompanying drawing explanation
Fig. 1 is the indoor multiobject positioning system network structure composition schematic diagram that the present invention is based on RSSI and inertia measurement.
Fig. 2 is the location-server structure composition schematic diagram in the indoor multiobject navigation system of the present invention.
Fig. 3 is the positioning anchor node structure composition schematic diagram in the indoor multiobject navigation system of the present invention.
Fig. 4 is the locator structure composition schematic diagram in the indoor multiobject navigation system of the present invention.
Fig. 5 is the localization method operating procedure flow chart of the multiobject navigation system in indoor that the present invention is based on RSSI and inertia measurement.
Embodiment
For making the object, technical solutions and advantages of the present invention clearly, below in conjunction with drawings and Examples, the present invention is described in further detail.
The present invention, in conjunction with RSSI propagation model positioning mode and inertia measurement two kinds of indoor orientation methods, proposes a kind of indoor multi-target positioning system based on RSSI and inertia measurement.The core concept of this system is the locator data by merging RSSI and inertia measurement two kinds of method of measurement, and carries out dynamic calibration to the position of positioning anchor node and locator, makes the stability that system position error reduces and increase system is located.
See Fig. 1 ~ Fig. 4, introduce three parts of present system: location-server, positioning anchor node and locator, wherein positioning anchor node can be divided into anchor node, one-level anchor node, secondary anchor node etc. according to its sequencing placed.This system block diagram as shown in Figure 1.Introduce this three building blocks below respectively:
(1) location-server: be responsible for the location measurement information sent according to positioning anchor node and locator, the position of compute location anchor node and locator, and positioning result is sent to locator by positioning anchor node.Be provided with four comprising modules (see Fig. 2): communication interface, system locating module, data memory module and data disaply moudle.Location-server modules function is as follows:
Communication interface, as the reception of location-server and the communication interface of transmission data, uses the interactive communication of the maintenance of WLAN communication protocol and locator and positioning anchor node, completes the transmission-receiving function of locator data.The two-way communication path of location-server and locator is all using positioning anchor node as via node.
Data memory module, the locating information received for storage networking communication module and system locating module calculate the positional information of each node generated, and call for other modules.
System locating module, for the locating information according to data memory module, runs location algorithm, calculates the positional information of each node, then pass to data memory module.
Information display module, is responsible for reading locating information from data memory module, and shows to user.
(2) positioning anchor node: as the via node of the two-way communication path of location-server and locator, had both been responsible for the operational order of location-server to send to locator; Simultaneously also for for providing position reference data when locator is located, performing and measuring operation, and forwarding positioning result data to location-server.Positioning anchor node divides into the anchor node of multiple grade according to the sequencing that it is placed: the known positioning anchor node in position is anchor node, one-level anchor node, secondary anchor node and follow-up corresponding anchor node.This navigation system is the position of the position calculation determination next stage anchor node according to upper level anchor node: the position first obtaining one-level anchor node according to the position calculation of anchor node, the position of secondary anchor node is obtained again according to the position calculation of one-level anchor node, the like, form multistage anchor node.Each positioning anchor node is respectively equipped with three comprising modules (see Fig. 3): communication interface, data memory module and rssi measurement module.Three functions of modules are described below:
Communication interface, as the communication interface of the digital received and sent of positioning anchor node, use WLAN communication protocol keeps the communication interaction with location-server and locator respectively, completes the transmission-receiving function of locating information.
Data memory module, the locating information received for storage networking communication module and rssi measurement module calculate the rssi measurement positional information of each node generated, and call for other modules.
Rssi measurement module, be responsible for gather statistics receive from other positioning anchors node R SSI information.
(3) locator: be responsible for gathering RSSI data and inertia measurement data, and send to location-server, and receive and show the positioning result of location-server.Be provided with four comprising modules (see Fig. 4): communication interface, data memory module, sensor assembly and display module.Four functions of modules are described below:
Communication interface, as the communication interface of the digital received and sent of locator, uses WLAN communication protocol to carry out interactive communication with location-server device and positioning anchor node respectively, completes the transmission-receiving function of locating information.
Data memory module, the locating information received for storage networking communication module and rssi measurement module calculate the rssi measurement information of each node generated.
Transducer, is provided with two assemblies: rssi measurement unit and Inertial Measurement Unit, gathers the relevant position information of locator respectively: rssi measurement unit be responsible for gather with statistics receive from other positioning anchors node R SSI information; Inertia measuring module be responsible for gather locator self measure obtain comprise: the multi-motion information at moving step length, mobile step number, moving direction angle.
Information display module, for reading locating information from data memory module, and shows current location and the movement locus of locator to user.
The present invention is based on the multi-target orientation method of the indoor multi-target positioning system of RSSI and inertia measurement, its core concept is mainly: the locator data of two kinds of method of measurement of received signal strength indicator RSSI and inertia measurement merged, again dynamic corrections is performed to the position of positioning anchor node and locator, with the stability of the positioning precision and increase system location that improve system.
See Fig. 5, introduce the following operative step of multi-target orientation method of the present invention:
Step 1, the initial position of positioning anchor node is set: when starting to locate, first the initial position of positioning anchor node is set in location-server, again before location starts, first the position coordinates of known initial anchor node is input in location-server, and obtains the position of the positioning anchor node of subsequent stages according to the position step-by-step calculation of anchor node.
Step 2, the target of location movement: after target moves a segment distance, the locator placed on the object sends to location-server the RSSI value received and the inertia measurement parameter of itself, before maximum in the RSSI numerical value that location-server receives using locator, k anchor node is as with reference to node, in conjunction with inertia measurement data, data fusion positioning is carried out to locator; Wherein, natural number k should be more than or equal to 4.
In this step, front k anchor node maximum in the RSSI numerical value utilizing locator to receive as with reference to node, in conjunction with inertia measurement data, the method of locator being carried out to data fusion positioning is by coefficient weighting, according to the following equation: (x, y, z)=λ 0(x i, y i, z i)+(1-λ 0) (x r, y r, z r) calculate the three-dimensional position coordinates (x, y, z) of unknown node; Wherein, (x i, y i, z i) be measure the Nodes Three-dimensional locus calculated by pedestrian's reckoning algorithm, (x according to inertial navigation r, y r, z r) be the Nodes Three-dimensional locus adopting RSSI propagation model location Calculation to obtain, λ 0inertial navigation measuring position coordinate (x i, y i, z i) fixed weight coefficient.
In conjunction with inertia measurement data in this step, the method for locator being carried out to data fusion positioning comprises following content of operation:
(21) because of in three dimensions, unknown node E (x, y, z) is according to the not coplanar neighbours' reference node A (x of itself and 4 1, y 1, z 1), B (x 2, y 2, z 2), C (x 3, y 3, z 3) and D (x 4, y 4, z 4) between range information determine that the formula of self three dimensional space coordinate is: establish these four not coplanar neighbor nodes (x respectively i, y i, z i) to the distance of unknown node E (x, y, z) be d i: d 1 2 = ( x - x 1 ) 2 + ( y - y 1 ) 2 + ( z - z 1 2 ) d 2 2 = ( x - x 2 ) 2 + ( y - y 2 ) 2 + ( z - z 2 2 ) d 3 2 = ( x - x 3 ) 2 + ( y - y 3 ) 2 + ( z - z 3 2 ) d 4 2 = ( x - x 4 ) 2 + ( y - y 4 ) 2 + ( z - z 4 2 ) ; Arrange again: r i 2 = d i 2 - x i 2 - y i 2 - z i 2 , Then deduct the 4th equation respectively by front 3 equations, obtain: 2 x 4 - 2 x 1 2 y 4 - 2 y 1 2 z 4 - 2 z 1 2 x 4 - 2 x 2 2 y 4 - 2 y 2 2 z 4 - 2 z 2 2 x 4 - 2 x 3 2 y 4 - 2 y 3 2 z 4 - 2 z 3 x y z = r 1 2 - r 4 2 r 2 2 - r 4 2 r 3 2 - r 4 2 ; In formula, natural number i is four not coplanar neighbor node sequence numbers, therefore its value is respectively: 1,2,3 and 4.
(22) arrange: Q = 2 x 4 - 2 x 1 2 y 4 - 2 y 1 2 z 4 - 2 z 1 2 x 4 - 2 x 2 2 y 4 - 2 y 2 2 z 4 - 2 z 2 2 x 4 - 2 x 3 2 y 4 - 2 y 3 2 z 4 - 2 z 3 , θ = x y z , b = r 1 2 - r 4 2 r 2 2 - r 4 2 r 3 2 - r 4 2 ; Then left side formula can be exchanged into: Q θ=b, obtains least square solution: wherein, r i, Q, b be the intermediate variable of formulae discovery derivation, it is the position coordinates of the unknown node E (x, y, z) calculated by least square method; And when rssi measurement accuracy is higher, the distance between node calculates will be more accurate, and the positioning precision of propagation model method is also higher.
(23) increase and record the position of new anchor node: if when the total quantity of anchor node is less than the maximum S that system allows, then arrange new anchor node in the current position of measurement target, and the anchor node position that record is newly-increased, anchor node number adds 1.
(24) revise anchor node rssi measurement value: from one-level anchor node, adopt middle position value filtering algorithm to revise the node R SSI value of every one-level positioning anchor node step by step.Wherein, meta algorithm filtering algorithm is after gathering N number of effective RSSI value, by this N number of RSSI value according to the arrangement of numerical values recited order, choose the RSSI value being wherein positioned at middle and export as filtering, that is: the median RSSI obtained when n-th RSSI of anchor node revises medn=Med (RSSI 1, RSSI 2, RSSI 3...., RSSI n); Wherein, natural number N is odd number.If the sample size gathered is larger, middle position value filtering method more effectively can overcome the fluctuation interference that accidentalia causes.
(25) anchor node position is revised: use step (24) revised RSSI value, step by step the position of anchor node at different levels is revised according to anchor node position correction algorithm.Wherein, the computing formula of anchor node position correction algorithm is: by coefficient weighting, anchor node z after revising for n-th time nposition three dimensional space coordinate (x n, y n, z n)=(λ 0+ ε (n)) (x i, y i, z i)+(1-λ 0-ε (n)) (x rn, y rn, z rn); In formula, (x i, y i, z i) be the three-dimensional space position coordinate of anchor node using track Calculation to obtain, (x rn, y rn, z rn) be according to n-th revised signal receiving strength value RSSI mednwith the three-dimensional space position coordinate of the anchor node that propagation model method calculates, λ 0inertial navigation surving coordinate (x i, y i, z i) fixed weight coefficient, additional weight coefficient function ε (n) is the subtraction function of variable about rssi measurement frequency n, and ε (n) <1-λ 0,
(26) location-server judges whether to receive the instruction stopping location survey, if receive, then exits location, terminates the whole flow process in location.Otherwise, return step 2, continue to perform next round positioning action.
Inventions have been and repeatedly implement test, the result of test is successful, achieves goal of the invention.

Claims (9)

1. the multiobject navigation system in indoor based on received signal strength indicator RSSI (Receive Signal Strength Indicator) and inertia measurement, it is characterized in that: described system is the locator data merging RSSI and inertia measurement two kinds of method of measurement, and dynamic calibration is carried out to the position of positioning anchor node and locator, make the stability that system position error reduces and increase system is located; This system is provided with three building blocks: location-server, positioning anchor node and locator, wherein:
Location-server, is responsible for the location measurement information sent according to positioning anchor node and locator, the position of compute location anchor node and locator, and positioning result is sent to locator by positioning anchor node; Be provided with four comprising modules: communication interface, system locating module, data memory module and data disaply moudle;
Positioning anchor node, as the via node of the two-way communication path of location-server and locator, had both been responsible for the operational order of location-server to send to locator; Simultaneously also for for providing position reference data when locator is located, performing and measuring operation, and forwarding positioning result data to location-server; Positioning anchor node divides into the anchor node of multiple grade according to the sequencing that it is placed: the known positioning anchor node in position is anchor node, one-level anchor node, secondary anchor node and follow-up corresponding anchor node; This navigation system is the position of the position calculation determination next stage anchor node according to upper level anchor node: the position first obtaining one-level anchor node according to the position calculation of anchor node, the position of secondary anchor node is obtained again according to the position calculation of one-level anchor node, the like, form multistage anchor node; Each positioning anchor node is respectively equipped with three comprising modules: communication interface, data memory module and rssi measurement module;
Locator, is responsible for gathering RSSI data and inertia measurement data, and sends to location-server, and receive and show the positioning result of location-server; Be provided with four comprising modules: communication interface, data memory module, sensor assembly and display module.
2. system according to claim 1, is characterized in that: each building block function of described location-server is as follows:
Communication interface, as the reception of location-server and the communication interface of transmission data, uses the interactive communication of the maintenance of WLAN communication protocol and locator and positioning anchor node, completes the transmission-receiving function of locator data; The two-way communication path of location-server and locator is all using positioning anchor node as via node;
Data memory module, the locating information received for storage networking communication module and system locating module calculate the positional information of each node generated, and call for other modules;
System locating module, for the locating information according to data memory module, runs location algorithm, calculates the positional information of each node, then pass to data memory module;
Information display module, is responsible for reading locating information from data memory module, and shows to user.
3. system according to claim 1, is characterized in that: three building block functions of described positioning anchor node are as follows:
Communication interface, as the communication interface of the digital received and sent of positioning anchor node, use WLAN communication protocol keeps the communication interaction with location-server and locator respectively, completes the transmission-receiving function of locating information;
Data memory module, the locating information received for storage networking communication module and rssi measurement module calculate the rssi measurement positional information of each node generated, and call for other modules;
Rssi measurement module, be responsible for gather statistics receive from other positioning anchors node R SSI information.
4. system according to claim 1, is characterized in that: four building block functions of described locator are as follows:
Communication interface, as the communication interface of the digital received and sent of locator, uses WLAN communication protocol to carry out interactive communication with location-server device and positioning anchor node respectively, completes the transmission-receiving function of locating information;
Data memory module, the locating information received for storage networking communication module and rssi measurement module calculate the rssi measurement information of each node generated;
Transducer, is provided with two assemblies: rssi measurement unit and Inertial Measurement Unit, gathers the relevant position information of locator respectively: rssi measurement unit be responsible for gather with statistics receive from other positioning anchors node R SSI information; Inertia measuring module be responsible for gather locator self measure obtain comprise: the multi-motion information at moving step length, mobile step number, moving direction angle;
Information display module, for reading locating information from data memory module, and shows current location and the movement locus of locator to user.
5. one kind adopts the multi-target orientation method of indoor multiobject navigation system described in claim 1, it is characterized in that: the locator data of two kinds of method of measurement of received signal strength indicator RSSI and inertia measurement is merged, again dynamic corrections is performed to the position of positioning anchor node and locator, with the stability of the positioning precision and increase system location that improve system; Described method comprises following operative step:
Step 1, the initial position of positioning anchor node is set: when starting to locate, first the initial position of positioning anchor node is set in location-server, again before location starts, first the position coordinates of known initial anchor node is input in location-server, and obtains the position of the positioning anchor node of subsequent stages according to the position step-by-step calculation of anchor node;
Step 2, the target of location movement: after target moves a segment distance, the locator placed on the object sends to location-server the RSSI value received and the inertia measurement parameter of itself, before maximum in the RSSI numerical value that location-server receives using locator, k anchor node is as with reference to node, in conjunction with inertia measurement data, data fusion positioning is carried out to locator; Wherein, natural number k should be more than or equal to 4.
6. method according to claim 5, it is characterized in that: in described step 2, front k anchor node maximum in the RSSI numerical value utilizing locator to receive is as reference node, in conjunction with inertia measurement data, the method of locator being carried out to data fusion positioning is by coefficient weighting, according to the following equation:
(x, y, z)=λ 0(x i, y i, z i)+(1-λ 0) (x r, y r, z r) calculate the three-dimensional position coordinates (x, y, z) of unknown node; Wherein, (x i, y i, z i) be measure the Nodes Three-dimensional locus calculated by pedestrian's reckoning algorithm, (x according to inertial navigation r, y r, z r) be the Nodes Three-dimensional locus adopting RSSI propagation model location Calculation to obtain, λ 0inertial navigation measuring position coordinate (x i, y i, z i) fixed weight coefficient.
7. method according to claim 6, is characterized in that: in described step 2 in conjunction with inertia measurement data, the method for locator being carried out to data fusion positioning comprises following content of operation:
(21) because of in three dimensions, unknown node E (x, y, z) is according to the not coplanar neighbours' reference node A (x of itself and 4 1, y 1, z 1), B (x 2, y 2, z 2), C (x 3, y 3, z 3) and D (x 4, y 4, z 4) between range information determine that the formula of self three dimensional space coordinate is: establish these four not coplanar neighbor nodes (x respectively i, y i, z i) to the distance of unknown node E (x, y, z) be d i: d 1 2 = ( x - x 1 ) 2 + ( y - y 1 ) 2 + ( z - z 1 2 ) d 2 2 = ( x - x 2 ) 2 + ( y - y 2 ) 2 + ( z - z 2 2 ) d 3 2 = ( x - x 3 ) 2 + ( y - y 3 ) 2 + ( z - z 3 2 ) d 4 2 = ( x - x 4 ) 2 + ( y - y 4 ) 2 + ( z - z 4 2 ) ; Arrange again: r i 2 = d i 2 - x i 2 - y i 2 - z i 2 , Then deduct the 4th equation respectively by front 3 equations, obtain: 2 x 4 - 2 x 1 2 y 4 - 2 y 1 2 z 4 - 2 z 1 2 x 4 - 2 x 2 2 y 4 - 2 y 2 2 z 4 - 2 z 2 2 x 4 - 2 x 3 2 y 4 - 2 y 3 2 z 4 - 2 z 3 x y z = r 1 2 - r 4 2 r 2 2 - r 4 2 r 3 2 - r 4 2 ; In formula, natural number i is four not coplanar neighbor node sequence numbers, therefore its value is respectively: 1,2,3 and 4;
(22) arrange: Q = 2 x 4 - 2 x 1 2 y 4 - 2 y 1 2 z 4 - 2 z 1 2 x 4 - 2 x 2 2 y 4 - 2 y 2 2 z 4 - 2 z 2 2 x 4 - 2 x 3 2 y 4 - 2 y 3 2 z 4 - 2 z 3 , &theta; = x y z , b = r 1 2 - r 4 2 r 2 2 - r 4 2 r 3 2 - r 4 2 ; Then left side formula can be exchanged into: Q θ=b, obtains least square solution: wherein, r i, Q, b be the intermediate variable of formulae discovery derivation, it is the position coordinates of the unknown node E (x, y, z) calculated by least square method; And when rssi measurement accuracy is higher, the distance between node calculates will be more accurate, and the positioning precision of propagation model method is also higher;
(23) increase and record the position of new anchor node: if when the total quantity of anchor node is less than the maximum S that system allows, then arrange new anchor node in the current position of measurement target, and the anchor node position that record is newly-increased, anchor node number adds 1;
(24) revise anchor node rssi measurement value: from one-level anchor node, adopt middle position value filtering algorithm to revise the node R SSI value of every one-level positioning anchor node step by step;
(25) anchor node position is revised: use step (24) revised RSSI value, step by step the position of anchor node at different levels is revised according to anchor node position correction algorithm;
(26) location-server judges whether to receive the instruction stopping location survey, if receive, then exits location, terminates the whole flow process in location; Otherwise, return step 2, continue to perform next round positioning action.
8. method according to claim 5, it is characterized in that: in described step (24), meta algorithm filtering algorithm is after gathering N number of effective RSSI value, this N number of RSSI value is arranged according to numerical values recited order, choose the RSSI value being wherein positioned at middle to export as filtering, that is: the median RSSI obtained when n-th RSSI of anchor node revises medn=Med (RSSI 1, RSSI 2, RSSI 3...., RSSI n); Wherein, natural number N is odd number; If the sample size gathered is larger, middle position value filtering method more effectively can overcome the fluctuation interference that accidentalia causes.
9. method according to claim 5, is characterized in that: in described step (25), and the computing formula of anchor node position correction algorithm is: by coefficient weighting, anchor node z after revising for n-th time nposition three dimensional space coordinate (x n, y n, z n)=(λ 0+ ε (n)) (x i, y i, z i)+(1-λ 0-ε (n)) (x rn, y rn, z rn); In formula, (x i, y i, z i) be the three-dimensional space position coordinate of anchor node using track Calculation to obtain, (x rn, y rn, z rn) be according to n-th revised signal receiving strength value RSSI mednwith the three-dimensional space position coordinate of the anchor node that propagation model method calculates, λ 0inertial navigation surving coordinate (x i, y i, z i) fixed weight coefficient, additional weight coefficient function ε (n) is the subtraction function of variable about rssi measurement frequency n, and ε (n) <1-λ 0,
CN201410474704.2A 2014-09-17 2014-09-17 Indoor multi-object positioning system and method based on RSSI (receiver signal strength indicator) and inertia measurement Pending CN104333903A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201410474704.2A CN104333903A (en) 2014-09-17 2014-09-17 Indoor multi-object positioning system and method based on RSSI (receiver signal strength indicator) and inertia measurement

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201410474704.2A CN104333903A (en) 2014-09-17 2014-09-17 Indoor multi-object positioning system and method based on RSSI (receiver signal strength indicator) and inertia measurement

Publications (1)

Publication Number Publication Date
CN104333903A true CN104333903A (en) 2015-02-04

Family

ID=52408526

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201410474704.2A Pending CN104333903A (en) 2014-09-17 2014-09-17 Indoor multi-object positioning system and method based on RSSI (receiver signal strength indicator) and inertia measurement

Country Status (1)

Country Link
CN (1) CN104333903A (en)

Cited By (24)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105021200A (en) * 2015-07-27 2015-11-04 北京博阳世通信息技术有限公司 Indoor location service information generation system and method
CN105115487A (en) * 2015-05-18 2015-12-02 陈希 Positioning and navigation method in supermarket based on information fusion
CN105357753A (en) * 2015-10-16 2016-02-24 杭州电子科技大学 Multimode fusion recursion iteration based indoor positioning method
CN105510876A (en) * 2015-12-25 2016-04-20 武汉大学 Electromagnetic wave propagation characteristic-based indoor distance measurement positioning method
WO2016180060A1 (en) * 2015-05-08 2016-11-17 深圳市华颖泰科电子技术有限公司 Calibration method
CN106197406A (en) * 2016-06-20 2016-12-07 天津大学 A kind of based on inertial navigation with the fusion method of RSSI wireless location
WO2017079975A1 (en) * 2015-11-13 2017-05-18 华为技术有限公司 Method and device for indoor positioning
WO2017088196A1 (en) * 2015-11-24 2017-06-01 东南大学 Fusion navigation device and method based on wireless fingerprints and mems sensor
CN106937377A (en) * 2015-12-29 2017-07-07 中国移动通信集团公司 A kind of method, device and equipment that classification positioning is realized for monitoring objective
CN106993292A (en) * 2017-03-21 2017-07-28 上海优璞信息科技有限公司 Emergent alignment system and its distribution method based on ultra wide band
CN107101616A (en) * 2017-05-23 2017-08-29 北京小鸟看看科技有限公司 A kind of personal identification method for positioning object, device and system
CN107888289A (en) * 2017-11-14 2018-04-06 东南大学 The indoor orientation method and platform merged based on visible light communication with inertial sensor
WO2018133264A1 (en) * 2017-01-18 2018-07-26 深圳大学 Indoor automatic human body positioning detection method and system
CN108419216A (en) * 2018-05-14 2018-08-17 深圳践行智能科技有限公司 Indoor positioning wireless medical monitoring system and its monitoring method
CN108696820A (en) * 2018-05-23 2018-10-23 苏州博联科技有限公司 Indoor orientation method based on iBeacon ranging technologies
CN109362027A (en) * 2018-10-19 2019-02-19 广州杰赛科技股份有限公司 Localization method, device, equipment and storage medium
CN109633544A (en) * 2018-12-26 2019-04-16 奇点新源国际技术开发(北京)有限公司 A kind of anchor point coordinate scaling method, anchor point localization method and device
CN110049550A (en) * 2019-03-06 2019-07-23 上海交通大学 Wireless indoor positioning and cognitive method, system and storage medium
CN110366104A (en) * 2019-08-12 2019-10-22 中南大学湘雅医院 Localization method, device, system and electronic equipment and computer readable storage medium
CN110572779A (en) * 2019-08-30 2019-12-13 南京沃旭通讯科技有限公司 System error estimation method of base station based on ToF model
CN111829519A (en) * 2019-05-29 2020-10-27 北京骑胜科技有限公司 Positioning method, positioning device, electronic equipment and storage medium
CN112098925A (en) * 2019-06-17 2020-12-18 群光电子股份有限公司 Electronic device, tracking system and tracking method
CN114175773A (en) * 2019-07-19 2022-03-11 松下知识产权经营株式会社 Area determination system, area determination method, and program
CN117499861A (en) * 2023-12-29 2024-02-02 济宁勤昌工贸有限公司 Side slope anchoring drilling machine construction drill bit positioning method based on sensor acquisition

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20060217132A1 (en) * 2005-03-23 2006-09-28 3Com Corporation High resolution localization for indoor environments
US7660591B1 (en) * 2005-09-09 2010-02-09 Avaya Inc. Propagation loss model based indoor wireless location of stations
CN102419180A (en) * 2011-09-02 2012-04-18 无锡智感星际科技有限公司 Indoor positioning method based on inertial navigation system and WIFI (wireless fidelity)
CN103415071A (en) * 2013-07-23 2013-11-27 南京邮电大学 Underwater wireless sensor network positioning method

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20060217132A1 (en) * 2005-03-23 2006-09-28 3Com Corporation High resolution localization for indoor environments
US7660591B1 (en) * 2005-09-09 2010-02-09 Avaya Inc. Propagation loss model based indoor wireless location of stations
CN102419180A (en) * 2011-09-02 2012-04-18 无锡智感星际科技有限公司 Indoor positioning method based on inertial navigation system and WIFI (wireless fidelity)
CN103415071A (en) * 2013-07-23 2013-11-27 南京邮电大学 Underwater wireless sensor network positioning method

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
胡伟娅: "基于RSSI与惯性测量的室内定位系统", 《计算机工程》 *

Cited By (40)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2016180060A1 (en) * 2015-05-08 2016-11-17 深圳市华颖泰科电子技术有限公司 Calibration method
CN105115487A (en) * 2015-05-18 2015-12-02 陈希 Positioning and navigation method in supermarket based on information fusion
CN105115487B (en) * 2015-05-18 2017-09-01 陈希 Positioning navigation method in a kind of supermarket based on information fusion
CN105021200A (en) * 2015-07-27 2015-11-04 北京博阳世通信息技术有限公司 Indoor location service information generation system and method
CN105021200B (en) * 2015-07-27 2018-06-05 北京博阳世通信息技术有限公司 A kind of generation system and method for indoor location information on services
CN105357753A (en) * 2015-10-16 2016-02-24 杭州电子科技大学 Multimode fusion recursion iteration based indoor positioning method
CN105357753B (en) * 2015-10-16 2018-09-18 杭州电子科技大学 A kind of indoor orientation method based on multimodality fusion recursive iteration
WO2017079975A1 (en) * 2015-11-13 2017-05-18 华为技术有限公司 Method and device for indoor positioning
US10228453B2 (en) 2015-11-13 2019-03-12 Huawei Technologies Co., Ltd. Indoor positioning method and device
US10648816B2 (en) 2015-11-24 2020-05-12 Southeast University Device and method for integrated navigation based on wireless fingerprints and MEMS sensors
WO2017088196A1 (en) * 2015-11-24 2017-06-01 东南大学 Fusion navigation device and method based on wireless fingerprints and mems sensor
CN105424030B (en) * 2015-11-24 2018-11-09 东南大学 Fusion navigation device and method based on wireless fingerprint and MEMS sensor
CN105510876A (en) * 2015-12-25 2016-04-20 武汉大学 Electromagnetic wave propagation characteristic-based indoor distance measurement positioning method
CN106937377A (en) * 2015-12-29 2017-07-07 中国移动通信集团公司 A kind of method, device and equipment that classification positioning is realized for monitoring objective
CN106937377B (en) * 2015-12-29 2020-04-21 中国移动通信集团公司 Method, device and equipment for realizing graded positioning aiming at monitoring target
CN106197406A (en) * 2016-06-20 2016-12-07 天津大学 A kind of based on inertial navigation with the fusion method of RSSI wireless location
CN106197406B (en) * 2016-06-20 2019-06-25 天津大学 A kind of fusion method based on inertial navigation and RSSI wireless location
WO2018133264A1 (en) * 2017-01-18 2018-07-26 深圳大学 Indoor automatic human body positioning detection method and system
CN106993292A (en) * 2017-03-21 2017-07-28 上海优璞信息科技有限公司 Emergent alignment system and its distribution method based on ultra wide band
CN107101616A (en) * 2017-05-23 2017-08-29 北京小鸟看看科技有限公司 A kind of personal identification method for positioning object, device and system
CN107101616B (en) * 2017-05-23 2019-09-27 北京小鸟看看科技有限公司 It is a kind of to position the personal identification method of object, device and system
CN107888289A (en) * 2017-11-14 2018-04-06 东南大学 The indoor orientation method and platform merged based on visible light communication with inertial sensor
CN107888289B (en) * 2017-11-14 2020-08-11 东南大学 Indoor positioning method and platform based on fusion of visible light communication and inertial sensor
CN108419216A (en) * 2018-05-14 2018-08-17 深圳践行智能科技有限公司 Indoor positioning wireless medical monitoring system and its monitoring method
CN108696820A (en) * 2018-05-23 2018-10-23 苏州博联科技有限公司 Indoor orientation method based on iBeacon ranging technologies
CN109362027A (en) * 2018-10-19 2019-02-19 广州杰赛科技股份有限公司 Localization method, device, equipment and storage medium
CN109362027B (en) * 2018-10-19 2021-04-09 广州杰赛科技股份有限公司 Positioning method, device, equipment and storage medium
CN109633544A (en) * 2018-12-26 2019-04-16 奇点新源国际技术开发(北京)有限公司 A kind of anchor point coordinate scaling method, anchor point localization method and device
CN109633544B (en) * 2018-12-26 2021-04-06 奇点新源国际技术开发(北京)有限公司 Anchor point coordinate calibration method, anchor point positioning method and device
CN110049550A (en) * 2019-03-06 2019-07-23 上海交通大学 Wireless indoor positioning and cognitive method, system and storage medium
US11924805B2 (en) 2019-05-29 2024-03-05 Beijing Qisheng Science And Technology Co., Ltd. Positioning method and device, electronic device and storage medium
CN111829519A (en) * 2019-05-29 2020-10-27 北京骑胜科技有限公司 Positioning method, positioning device, electronic equipment and storage medium
CN112098925A (en) * 2019-06-17 2020-12-18 群光电子股份有限公司 Electronic device, tracking system and tracking method
CN112098925B (en) * 2019-06-17 2024-03-08 群光电子股份有限公司 Electronic device, tracking system and tracking method
CN114175773B (en) * 2019-07-19 2024-06-11 松下知识产权经营株式会社 Area judgment system, area judgment method, and non-transitory storage medium
CN114175773A (en) * 2019-07-19 2022-03-11 松下知识产权经营株式会社 Area determination system, area determination method, and program
CN110366104A (en) * 2019-08-12 2019-10-22 中南大学湘雅医院 Localization method, device, system and electronic equipment and computer readable storage medium
CN110572779A (en) * 2019-08-30 2019-12-13 南京沃旭通讯科技有限公司 System error estimation method of base station based on ToF model
CN117499861A (en) * 2023-12-29 2024-02-02 济宁勤昌工贸有限公司 Side slope anchoring drilling machine construction drill bit positioning method based on sensor acquisition
CN117499861B (en) * 2023-12-29 2024-03-22 济宁勤昌工贸有限公司 Side slope anchoring drilling machine construction drill bit positioning method based on sensor acquisition

Similar Documents

Publication Publication Date Title
CN104333903A (en) Indoor multi-object positioning system and method based on RSSI (receiver signal strength indicator) and inertia measurement
Li et al. Toward location-enabled IoT (LE-IoT): IoT positioning techniques, error sources, and error mitigation
WO2019136918A1 (en) Indoor positioning method, server and positioning system
Woo et al. Application of WiFi-based indoor positioning system for labor tracking at construction sites: A case study in Guangzhou MTR
CN105072581B (en) A kind of indoor orientation method that storehouse is built based on path attenuation coefficient
CN109195099A (en) A kind of indoor orientation method merged based on iBeacon and PDR
CN105004340A (en) Inertial navigation-fingerprint location-combined positioning error correction method
KR20150059718A (en) Sysem and method for position estimation using uplink access point
AU2012248121B2 (en) Communications
CN105203996A (en) Mobile device and indoor positioning method, system and device as well as anchor nodes thereof
KR101415191B1 (en) Pedestrian Navigation Apparatus
Zhang et al. Three‐dimensional localization algorithm of WSN nodes based on RSSI‐TOA and single mobile anchor node
Eldeeb et al. Optimal placement of access points for indoor positioning using a genetic algorithm
CN104507097A (en) Semi-supervised training method based on WiFi (wireless fidelity) position fingerprints
Souli et al. Relative positioning of autonomous systems using signals of opportunity
Rose et al. 3D trilateration localization using RSSI in indoor environment
Song et al. Fingerprinting localization method based on toa and particle filtering for mines
CN107356902B (en) WiFi positioning fingerprint data automatic acquisition method
Guo et al. Multi-channel and Multi-RSS based BLE Range Estimation for Indoor Tracking of Commercial Smartphones
Vaščák et al. Radio beacons in indoor navigation
Kim et al. Exploiting ultrasonic reflections for improving accuracy of indoor location tracking
CN116449406A (en) Seamless switching method for GNSS positioning and indoor positioning
Jamâa et al. Easyloc: Plug-and-play RSS-based localization in wireless sensor networks
Abd Shukur Ja’afar et al. Development of real-time monitoring BLE-LoRa positioning system based on RSSI for non-line-of-sight condition
KR20140051188A (en) Pedestrian navigation apparatus

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
C10 Entry into substantive examination
SE01 Entry into force of request for substantive examination
WD01 Invention patent application deemed withdrawn after publication

Application publication date: 20150204

WD01 Invention patent application deemed withdrawn after publication