CN104159293B - Towards the indoor orientation method of high speed unmanned rotary wing aircraft - Google Patents

Towards the indoor orientation method of high speed unmanned rotary wing aircraft Download PDF

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CN104159293B
CN104159293B CN201410322947.4A CN201410322947A CN104159293B CN 104159293 B CN104159293 B CN 104159293B CN 201410322947 A CN201410322947 A CN 201410322947A CN 104159293 B CN104159293 B CN 104159293B
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rotary wing
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CN104159293A (en
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于拓
周子龙
张阳
张哲慧
吴炜捷
杨峰
王新兵
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Shanghai Jiaotong University
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Abstract

The present invention discloses a kind of indoor orientation method towards high speed unmanned rotary wing aircraft, comprises the following steps:Multi-section wireless router is installed in the region that positioning service is provided;It is grid by region division, measures WiFi signal intensity in each grid;Aircraft is with Fixed Time Interval test constantly WiFi signal intensity;Aircraft asks to position and upload measurement data to server;Server calculating aircraft position, sends result to aircraft according to measurement result;Aircraft receives positioning result.This method can effectively improve the indoor position accuracy of unmanned rotary wing aircraft in high-speed mobile.

Description

Towards the indoor orientation method of high speed unmanned rotary wing aircraft
Technical field
The present invention relates to communication, technical field of navigation and positioning, in particular it relates to a kind of towards high speed unmanned rotary wing aircraft Indoor orientation method.
Background technology
With the popularization of unmanned vehicle, increasing unmanned vehicle navigation feature needs positional information to give branch Support, i.e., so-called location-based information service (LBS).Therefore location technology, which develops into unmanned vehicle navigation field, has There is the key technology of supportive.In outdoor, unmanned vehicle can be positioned using GPS technology, but GPS technology is indoors Positioning precision is extremely low, therefore limits the use of unmanned vehicle navigation indoors.As unmanned rotary wing aircraft is in large-scale room Interior venue becomes increasingly conspicuous with popularization, the indoor positioning problem of unmanned rotary wing aircraft, and without the business of comparative maturity Solution.
From 21 century from the beginning of many colleges and universities and research institution have had begun to be directed to the indoor positioning technologies of general user Research, and achieve larger breakthrough.Typical indoor locating system has:The Active that AT&T Cambridge are developed Badges systems, the RADAR system positioned using WLAN, positioned using the Cricket of ultrasonic wave location technology System, the SpotON systems based on RFID etc..
Wherein, have benefited from the fast development of present mobile intelligent terminal and the extensive use of wireless local area network technology, be based on The indoor positioning technologies of WiFi signal intensity have become the study hotspot of indoor positioning, navigation field in recent years.It is based on The indoor positioning technologies of WiFi signal intensity have advantages below:1) signal intensity is directly obtained by intelligent terminal (Received Signal Strength,RSS);2) positioning can be realized with the development scheme of pure application using signal intensity; 3) have alignment system cost low, the advantages that developing conveniently, while higher positioning accuracy can be provided.
However, the indoor orientation method based on WiFi can not directly apply on the unmanned rotary wing aircraft of high-speed mobile, Reason is that this method needs aircraft to stay for some time in situ (or so 1-2 seconds), and unmanned vehicle may within the period The position of script is had been moved off, therefore positioning precision receives the restriction of WiFi signal ionization meter and aircraft movement velocity.
The content of the invention
For technical problem present in above-mentioned prior art, the present invention provides a kind of towards high speed unmanned rotary wing aircraft Indoor orientation method, by making unmanned rotary wing aircraft continuous collecting location data in flight course, make location-server Historical location data can be obtained when performing location algorithm.By using kalman filter method, the history of aircraft is estimated Mobile route, so as to correct newest positioning result, improves positioning precision.
To reach above-mentioned purpose, the technical solution adopted in the present invention is as follows:
A kind of indoor orientation method towards high speed unmanned rotary wing aircraft, comprise the following steps:
Step 1:Multiple wireless routers are set in the region for needing to provide positioning service first;
Step 2:The region division for providing positioning service will be needed to be the square net of multiple length of side L rice, and measured each The WiFi signal intensity for coming from each wireless router in individual grid, and the result of measurement is uploaded to location-server;
Step 3:Unmanned rotary wing aircraft test constantly in flight course comes from the WiFi letters of each wireless router Number intensity, and it is stored in local;
Step 4:When aircraft needs positioning, ask to position to server, and upload WiFi signal intensity so far Measurement data;
Step 5:Server sends result to aircraft according to the measurement data of upload, calculating aircraft position;
Step 6:Aircraft receives positioning result.
Preferably, the equal normal work of wireless router in the step 1 broadcasts visible mode in SSID, i.e., with fixed week Phase sends Beacon broadcast singals.
Preferably, the step 2 comprises the following steps:
Step 2.1:Each the WiFi signal strength test process in grid is:Each no circuit is directed in each grid Measure n times respectively by device and come from the WiFi signal radiation intensity of wireless router, and measurement result is uploaded to positioning service Device;
Step 2.2:Location-server carries out following calculate according to the measurement result of upload:
If grid sum is W in step 2, then for grid w, a series of function is calculated:
Wherein, pwjWhat () represented to receive at grid w comes from the signal intensity probability density point of j-th of router Cloth function, N are testing time in grid w, owjiIt is strong for the signal for coming from j-th of router that is received at grid w Value obtained by the ith test of degree, σ are constant, and M is the sum of wireless router, and o represents received signal strength;
Location-server calculates the function p of gained by more thanwj(o) it is stored in database.
Preferably, the step 3 comprises the following steps:
Step 3.1:Unmanned rotary wing aircraft comes from each nothing in flight course with Fixed Time Interval T test constantlies The WiFi signal intensity of line router, every time measurement can obtain one group of signal for coming from each wireless routerT=T, 2T ....WhereinWhen for the time being t, the signal intensity from j-th of router.M is The sum of wireless router.Time interval T minimum value is equal to unmanned vehicle and performs a WiFi signal ionization meter most It is small time-consuming.
Step 3.2:The unmanned rotary wing aircraft is provided with Cellular Networks or WiFi port devices, can via Cellular Networks or WiFi connection location-servers.
Preferably, the step 5 comprises the following steps:
Step 5.1:According to unmanned rotary wing aircraft upload obtained by all WiFi signal intensity measurement datas, carry out with Lower calculating:
For grid w, calculate with probability values:
Wherein PwtFor time t when the probability that is in grid w of unmanned rotary wing aircraft, M is the sum of wireless router, pwj() is gained function in step 2.2,Come from j-th for mobile terminal is measured in time t in step 3 The signal intensity of wireless router, KT are the time of unmanned rotary wing aircraft last time positioning.
Finally, for different t, from Pwt, w=1 ..., the net corresponding to one of value the maximum or the maximum is found out in W Lattice w, grid w are the position in time t where unmanned rotary wing aircraft being calculated, and are designated asT= T,2T,...KT.Wherein, x 't, y 'tFor the horizontal stroke of the grid element center, ordinate value.
Step 5.2:Using Kalman filtering to ztHandled, it is specific as follows:
Set unmanned rotary wing airplane motion state vector:
Wherein, xt, ytThe position transverse and longitudinal coordinate value for being unmanned rotary wing aircraft in time t, vxt, vytFor unmanned rotary wing aircraft Movement velocity vector in time t is in horizontal, longitudinal direction component value.
Set unmanned rotary wing airplane motion model matrix:
Setting motion variance matrix:
WhereinIt is constant to move variance.
Setting measurement matrix of consequence:
Setting measurement variance matrix:
WhereinIt is constant to measure variance.
Kalman filtering processing procedure is as follows:From t=T to t=KT, following cycle calculations are performed:
Wherein PtFor time t when filtering matrix,For time t when amendment filtering matrix, KtFor time t when filtering Weight matrix, E are unit matrix,For time t when filter result.FT、HTF and H transposed matrix is represented respectively.Circulation Initial value is arranged to
Thus, it is possible to obtain Kalman filtered resultsTakeExported as positioning result.
Indoor orientation method provided by the invention towards high speed unmanned rotary wing aircraft, using Kalman filtering, pass through The history WiFi signal intensity data gathered using unmanned rotary wing aircraft, is modified by server to newest positioning result, Position error caused by so as to reduce WiFi signal shake, it is effectively improved the indoor positioning essence of unmanned rotary wing aircraft Degree.
Compared with prior art, the present invention has following beneficial effect:
The existing indoor positioning technologies based on WiFi signal intensity typically require that user is strong to WiFi signal in same place Degree takes multiple measurements, and required time is longer.If these technologies are directly applied into unmanned rotary wing aircraft, aircraft is entering Rapid flight is will be unable to during row continuous positioning.If aircraft carries out rapid flight, system will use the knot of last time measurement Fruit is as basis on location, so as to seriously reduce the precision of positioning.In contrast, present invention utilizes the positioning of the history of aircraft Data, its movement line is estimated, so as to effectively have modified newest positioning result, reduce position error.
Brief description of the drawings
The detailed description made by reading with reference to the following drawings to non-limiting example, further feature of the invention, Objects and advantages will become more apparent upon:
Fig. 1 is the step flow chart of the present invention;
Fig. 2 is the execution structural representation of the present invention.
In figure:1 is location-server;2 be unmanned rotary wing aircraft;3 be wireless router.
Embodiment
With reference to specific embodiment, the present invention is described in detail.Following examples will be helpful to the technology of this area Personnel further understand the present invention, but the invention is not limited in any way.It should be pointed out that the ordinary skill to this area For personnel, without departing from the inventive concept of the premise, various modifications and improvements can be made.These belong to the present invention Protection domain.
Fig. 1 is a kind of flow chart of indoor orientation method towards high speed unmanned rotary wing aircraft provided by the present invention, Fig. 2 is the overall system design structure chart of the inventive method.The system is directed to unmanned rotary wing aircraft using provided by the invention The indoor orientation method of design, the system are mainly made up of three parts, are respectively:Location-server, router and unmanned rotary wing Aircraft.
In system, location-server is established with unmanned rotary wing aircraft by Cellular Networks or WLAN and connected.Nothing The control system acquiescence of people's rotor craft has been mounted with the application that the system provides and at least in a certain intelligent router Coverage within.In flight course, unmanned rotary wing aircraft is with Fixed Time Interval test constantly WiFi signal intensity. When unmanned rotary wing aircraft needs to position itself, user sends one by wireless connection to location-server first Location Request, and upload measurement data;Server estimates aircraft according to measurement result after being calculated by a series of algorithm Result is simultaneously informed into the aircraft in the position of most probable appearance.
The present invention utilizes history WiFi signal intensity measurement data of the unmanned rotary wing aircraft in motion process, to newest Positioning result be modified, reduce and asked because positioning precision caused by WiFi signal ionization meter number deficiency is low Topic.For it is currently a popular based on the indoor locating system of WiFi signal intensity for, due to most systems require user exist Not shift position, therefore be not suitable for the unmanned rotary wing aircraft of high-speed mobile in WiFi measurement process.But it is at us In system, meeting test constantly WiFi signal intensity in unmanned rotary wing aircraft motion process, therefore surveyed even in last time WiFi In the case of measuring number deficiency, its course can also be estimated by using history positioning result, so as to reduce positioning Error.
The present embodiment is described further below in conjunction with the accompanying drawings.
As shown in figure 1, the present embodiment comprises the following steps:
Step 1:Multiple wireless routers are set in the region for needing to provide positioning service first, wherein, it is described wireless The equal normal work of router broadcasts visible mode in SSID, i.e., sends Beacon broadcast singals with the fixed cycle.
Step 2:The region division for providing positioning service will be needed to be the square net of multiple length of side L rice, and measured each The WiFi signal intensity for coming from each wireless router in individual grid.WiFi signal strength test process in each grid For:N times are measured respectively for each wireless router in each grid comes from the WiFi signal radiation of wireless router by force Degree, and measurement result is uploaded to location-server.Location-server carries out following calculate according to the measurement result of upload:
If grid sum is W in step 2, then for grid w, a series of function is calculated:
Wherein, pwjWhat () represented to receive at grid w comes from the signal intensity probability density point of j-th of router Cloth function, N are testing time in grid w, owjiIt is strong for the signal for coming from j-th of router that is received at grid w Value obtained by the ith test of degree, σ are constant, and M is the sum of wireless router, and o represents received signal strength;
Location-server calculates the function p of gained by more thanwj(o) it is stored in database.
Step 3:Unmanned rotary wing aircraft is come from each wireless in flight course with Fixed Time Interval T test constantlies The WiFi signal intensity of router, every time measurement can obtain one group of signal for coming from each wireless routerT=T, 2T ....WhereinWhen for the time being t, the signal intensity from j-th of router.M is The sum of wireless router.Time interval T minimum value is equal to unmanned vehicle and performs a WiFi signal ionization meter most It is small time-consuming.Measured all results are stored in unmanned rotary wing aircraft local.Pay attention to, the unmanned rotary wing aircraft installation There are Cellular Networks or WiFi port devices, can be via Cellular Networks or WiFi connection location-servers.
Step 4:When aircraft needs positioning, ask to position to server, and upload WiFi signal intensity so far Measurement data;
Step 5:Location-server uploads resulting all WiFi signal ionization meter numbers according to unmanned rotary wing aircraft According to progress is following to be calculated:
For grid w, calculate with probability values:
Wherein PwtFor time t when the probability that is in grid w of unmanned rotary wing aircraft, M is the sum of wireless router, pwj() is gained function in step 2,Come from j-th of nothing for mobile terminal is measured in time t in step 3 The signal intensity of line router, KT are the time of unmanned rotary wing aircraft last time positioning.
Finally, for different t, from Pwt, w=1 ..., the net corresponding to one of value the maximum or the maximum is found out in W Lattice w, grid w are the position in time t where unmanned rotary wing aircraft being calculated, and are designated asT= T,2T,...KT.Wherein, x 't, y 'tFor the horizontal stroke of the grid element center, ordinate value.
Thereafter, using Kalman filtering to zt, t=T, 2T ... KT processing, it is specific as follows:
Set unmanned rotary wing airplane motion state vector:
Wherein, xt, ytThe position transverse and longitudinal coordinate value for being unmanned rotary wing aircraft in time t, vxt, vytFor unmanned rotary wing aircraft Movement velocity vector in time t is in horizontal, longitudinal direction component value.
Set unmanned rotary wing airplane motion model matrix:
Setting motion variance matrix:
WhereinIt is constant to move variance.
Setting measurement matrix of consequence:
Setting measurement variance matrix:
WhereinIt is constant to measure variance.
Kalman filtering processing procedure is as follows:From t=T to t=KT, following cycle calculations are performed:
Wherein PtFor time t when filtering matrix,For time t when amendment filtering matrix, KtFor time t when filtering Weight matrix, E are unit matrix,For time t when filter result.FT、HTF and H transposed matrix is represented respectively.Circulation Initial value is arranged to
Thus, it is possible to obtain Kalman filtered resultsTakeExported as positioning result, and The result is sent back into aircraft.
Step 6:Aircraft receives positioning result.
It can be seen that the system, by Kalman filter, the historical data gathered to aircraft in flight course is carried out Processing, so as to have modified the result of last time positioning, reduce position error.
The ambient parameter of the present embodiment is:
Unmanned rotary wing aircraft:The power edition of Parrot AR.Drone 2.0, control system are based on Android Jelly Bean (4.2), there is WiFi function, wireless connection can be established by WiFi interfaces, or complete WiFi signal intensity Measurement.
Wireless router:Use five TP-LINK TL-WR842N, network standard IEEE 802.11n, frequency range:It is single Frequently (2.4-2.4835GHz).
Location-server:Grand base 4930G notebook computers, Duo dual core processor, 2G internal memory, 2G dominant frequency.Service Device is connected by wired network with five Intelligent wireless routers, and can be via internet, wireless network and unmanned rotary wing aircraft Communication.
The present embodiment comprises the following specific steps that:
Step 1:Staff is that M=5 are installed in 1000 square metres of large-scale experiment rooms without circuit first in an area By device.
Step 2:The ground region of this large-scale experiment room is being divided into W=1000 length of side L=1 rice just by staff Square net.Each the WiFi signal strength test process in grid is:Measure N=10 times and come from respectively in each grid The WiFi signal radiation intensity (measuring altogether 50 times) of each Intelligent wireless router, and result is uploaded onto the server.Clothes Business device carries out following calculate according to the measurement result of upload:
If grid sum is 1000, then for w (1≤w≤1000) individual grid, a series of function is calculated:
Wherein, pwj() represents the signal intensity probability for coming from 1≤j≤5 router received at grid w Density fonction.N=10 be at grid w in testing time, owjiCome from j-th of tunnel for what is received at grid w By the value obtained by the ith test of the signal intensity of device, σ is constant, σ=10.M=5 be wireless router sum, o tables Show received signal strength;Location-server calculates the function p of gained by more thanwj(o) it is stored in database.
Step 3:Unmanned rotary wing aircraft is come from respectively in flight course with Fixed Time Interval T=2 second test constantlies The WiFi signal intensity of individual wireless router, every time measurement can obtain one group of signal for coming from each wireless routerT=T, 2T ....WhereinWhen for the time being t, the signal intensity from j-th of router.M is The sum of wireless router.Measured all results are stored in unmanned rotary wing aircraft local.
Step 4:Time when aircraft needs to position is t=50 × 2 second (i.e. K=50), asks to position to server, and Upload WiFi signal intensity measurement data so farT=T, 2T ..., 50T.
Step 5:Location-server uploads resulting all WiFi signal ionization meter numbers according to unmanned rotary wing aircraft According to progress is following to be calculated:
For grid w, calculate with probability values:
Wherein PwtFor time t when the probability that is in grid w of unmanned rotary wing aircraft, pwj() is gained letter in step 2 Number,For the mobile terminal signal intensity that comes from j-th wireless router measured in time t in step 3,50T For the time of unmanned rotary wing aircraft last time positioning.
Finally, for different t, from Pwt, w=1 ..., found out in 1000 corresponding to one of value the maximum or the maximum Grid w, grid w are the position in time t where unmanned rotary wing aircraft being calculated, and are designated ast =T, 2T ... 50T.Wherein, x 't, y 'tFor the horizontal stroke of the grid element center, ordinate value.
Thereafter, using Kalman filtering to zt, t=T, 2T ... 50T processing, it is specific as follows:
Set unmanned rotary wing airplane motion state vector:
Wherein, xt, ytThe position transverse and longitudinal coordinate value for being unmanned rotary wing aircraft in time t, vxt, vytFor unmanned rotary wing aircraft Movement velocity vector in time t is in horizontal, longitudinal direction component value.
Set unmanned rotary wing airplane motion model matrix:
Setting motion variance matrix:
Setting measurement matrix of consequence:
Setting measurement variance matrix:
Kalman filtering processing procedure is as follows:From t=T to t=50T, following cycle calculations are performed:
Wherein PtFor time t when filtering matrix,For time t when amendment filtering matrix, KtFor time t when filtering Weight matrix, E are unit matrix,For time t when filter result.FT、HTF and H transposed matrix is represented respectively.Circulation Initial value is arranged to
Thus, it is possible to obtain Kalman filtered resultsTakeExported as positioning result, And the result is sent back into aircraft.
Step 6:Aircraft receives positioning result.
Although present disclosure is discussed in detail by above-described embodiment, but it should be appreciated that the description above It is not considered as limitation of the present invention.After those skilled in the art have read the above, for a variety of of the present invention Modifications and substitutions all will be apparent.Therefore, protection scope of the present invention should be limited to the appended claims.

Claims (5)

1. a kind of indoor orientation method towards high speed unmanned rotary wing aircraft, it is characterised in that comprise the following steps:
Step 1:Multiple wireless routers are set in the region for needing to provide positioning service;
Step 2:It is multiple square nets by the region division for needing to provide positioning service, and measures coming from each grid Location-server is uploaded in the WiFi signal intensity of each wireless router, and by the result of measurement;
Step 3:The WiFi signal that unmanned rotary wing aircraft test constantly in flight course comes from each wireless router is strong Degree, and it is stored in local;
Step 4:When aircraft needs positioning, ask to position to server, and upload WiFi signal ionization meter so far Data;
Step 5:Server is according to the measurement data of upload, the probability P that aircraft is in grid w when calculating time twt;For Different t, from PwtIn find out grid w corresponding to one of value the maximum or the maximum, grid w be calculated Position z during time t where aircraftt, using Kalman filtering to ztHandled, and result is sent to aircraft;
Step 6:Aircraft receives positioning result.
2. the indoor orientation method according to claim 1 towards high speed unmanned rotary wing aircraft, it is characterised in that described The equal normal work of wireless router in step 1 broadcasts visible mode in SSID, i.e., sends Beacon broadcast letters with the fixed cycle Number.
3. the indoor orientation method according to claim 1 towards high speed unmanned rotary wing aircraft, it is characterised in that described Step 2 comprises the following steps:
Step 2.1:Each the WiFi signal strength test process in grid is:Each wireless router is directed in each grid Measurement n times come from the WiFi signal radiation intensity of wireless router respectively, and measurement result is uploaded into location-server;
Step 2.2:Location-server carries out following calculate according to the measurement result of upload:
If grid sum is W in step 2, then for grid w, a series of function is calculated:
<mrow> <msub> <mi>p</mi> <mrow> <mi>w</mi> <mi>j</mi> </mrow> </msub> <mrow> <mo>(</mo> <mi>o</mi> <mo>)</mo> </mrow> <mo>=</mo> <mfrac> <mn>1</mn> <mi>N</mi> </mfrac> <munderover> <mi>&amp;Sigma;</mi> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>N</mi> </munderover> <mfrac> <mn>1</mn> <mrow> <msqrt> <mrow> <mn>2</mn> <mi>&amp;pi;</mi> </mrow> </msqrt> <mi>&amp;sigma;</mi> </mrow> </mfrac> <mi>exp</mi> <mrow> <mo>(</mo> <mo>-</mo> <mfrac> <mrow> <mo>(</mo> <mi>o</mi> <mo>-</mo> <msub> <mi>o</mi> <mrow> <mi>w</mi> <mi>j</mi> <mi>i</mi> </mrow> </msub> <mo>)</mo> </mrow> <mrow> <mn>2</mn> <msup> <mi>&amp;sigma;</mi> <mn>2</mn> </msup> </mrow> </mfrac> <mo>)</mo> </mrow> <mo>,</mo> <mi>j</mi> <mo>=</mo> <mn>1</mn> <mo>,</mo> <mn>2</mn> <mo>,</mo> <mn>...</mn> <mo>,</mo> <mi>M</mi> <mo>,</mo> <mi>w</mi> <mo>=</mo> <mn>1</mn> <mo>,</mo> <mn>2</mn> <mo>,</mo> <mn>...</mn> <mo>,</mo> <mi>W</mi> </mrow>
Wherein, pwj() represents the signal intensity probability density distribution letter for coming from j-th of router received at grid w Number, N are testing time in grid w, owjiFor the signal intensity for coming from j-th of router that is received at grid w Value obtained by ith test, σ are constant, and M is the sum of wireless router, and o represents received signal strength;
Location-server calculates the function p of gained by more thanwj(o) it is stored in database.
4. the indoor orientation method according to claim 1 towards high speed unmanned rotary wing aircraft, it is characterised in that described Step 3 comprises the following steps:
Step 3.1:Unmanned rotary wing aircraft comes from each no circuit in flight course with Fixed Time Interval T test constantlies By the WiFi signal intensity of device, measurement every time can obtain one group of signal for coming from each wireless routerWhereinWhen to be the time be t, the signal intensity from j-th of router, M is nothing The sum of line router, time interval T minimum value are equal to the minimum that unmanned vehicle performs a WiFi signal ionization meter It is time-consuming;
Step 3.2:The unmanned rotary wing aircraft is provided with Cellular Networks or WiFi port devices, can be via Cellular Networks or WiFi Connect location-server.
5. the indoor orientation method according to claim 3 towards high speed unmanned rotary wing aircraft, it is characterised in that described Step 5 comprises the following steps:
Step 5.1:All WiFi signal intensity measurement datas obtained by being uploaded according to unmanned rotary wing aircraft, carry out following count Calculate:
For grid w, calculate with probability values:
<mrow> <msub> <mi>P</mi> <mrow> <mi>w</mi> <mi>t</mi> </mrow> </msub> <mo>=</mo> <munder> <mo>&amp;Pi;</mo> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> <mo>,</mo> <mo>...</mo> <mo>,</mo> <mi>M</mi> </mrow> </munder> <msub> <mi>p</mi> <mrow> <mi>w</mi> <mi>j</mi> </mrow> </msub> <mrow> <mo>(</mo> <msub> <mover> <mi>o</mi> <mo>~</mo> </mover> <mrow> <mi>j</mi> <mi>t</mi> </mrow> </msub> <mo>)</mo> </mrow> <mo>,</mo> <mi>w</mi> <mo>=</mo> <mn>1</mn> <mo>,</mo> <mo>...</mo> <mo>,</mo> <mi>W</mi> <mo>;</mo> <mi>t</mi> <mo>=</mo> <mi>T</mi> <mo>,</mo> <mn>2</mn> <mi>T</mi> <mo>,</mo> <mo>...</mo> <mi>K</mi> <mi>T</mi> </mrow>
Wherein PwtFor time t when the probability that is in grid w of unmanned rotary wing aircraft, M is the sum of wireless router, pwj(·) For in step 2.2 gained function,Come from j-th of wireless routing for mobile terminal is measured in time t in step 3 The signal intensity of device, KT are the time of unmanned rotary wing aircraft last time positioning;
Finally, for different t, from Pwt, the grid w corresponding to one of value the maximum or the maximum is found out in w=1 ..., W, Grid w is the position in time t where unmanned rotary wing aircraft being calculated, and is designated asT=T, 2T ... KT, wherein, x 't, y 'tFor the horizontal stroke of the grid element center, ordinate value;
Step 5.2:Using Kalman filtering to ztHandled, it is specific as follows:
Set unmanned rotary wing airplane motion state vector:
<mrow> <msub> <mi>s</mi> <mi>t</mi> </msub> <mo>=</mo> <mfenced open = "[" close = "]"> <mtable> <mtr> <mtd> <msub> <mi>x</mi> <mi>t</mi> </msub> </mtd> </mtr> <mtr> <mtd> <msub> <mi>y</mi> <mi>t</mi> </msub> </mtd> </mtr> <mtr> <mtd> <msub> <mi>v</mi> <mrow> <mi>x</mi> <mi>t</mi> </mrow> </msub> </mtd> </mtr> <mtr> <mtd> <msub> <mi>v</mi> <mrow> <mi>y</mi> <mi>t</mi> </mrow> </msub> </mtd> </mtr> </mtable> </mfenced> </mrow>
Wherein, xt, ytThe position transverse and longitudinal coordinate value for being unmanned rotary wing aircraft in time t, vxt, vytFor unmanned rotary wing aircraft when Between t when movement velocity vector in horizontal, longitudinal direction component value;
Set unmanned rotary wing airplane motion model matrix:
<mrow> <mi>F</mi> <mo>=</mo> <mfenced open = "[" close = "]"> <mtable> <mtr> <mtd> <mn>1</mn> </mtd> <mtd> <mn>0</mn> </mtd> <mtd> <mi>T</mi> </mtd> <mtd> <mn>0</mn> </mtd> </mtr> <mtr> <mtd> <mn>0</mn> </mtd> <mtd> <mn>1</mn> </mtd> <mtd> <mn>0</mn> </mtd> <mtd> <mi>T</mi> </mtd> </mtr> <mtr> <mtd> <mn>0</mn> </mtd> <mtd> <mn>0</mn> </mtd> <mtd> <mn>1</mn> </mtd> <mtd> <mn>0</mn> </mtd> </mtr> <mtr> <mtd> <mn>0</mn> </mtd> <mtd> <mn>0</mn> </mtd> <mtd> <mn>0</mn> </mtd> <mtd> <mn>1</mn> </mtd> </mtr> </mtable> </mfenced> </mrow>
Setting motion variance matrix:
<mrow> <mi>Q</mi> <mo>=</mo> <mfenced open = "[" close = "]"> <mtable> <mtr> <mtd> <msubsup> <mi>&amp;sigma;</mi> <mn>1</mn> <mn>2</mn> </msubsup> </mtd> <mtd> <mn>0</mn> </mtd> <mtd> <mn>0</mn> </mtd> <mtd> <mn>0</mn> </mtd> </mtr> <mtr> <mtd> <mn>0</mn> </mtd> <mtd> <msubsup> <mi>&amp;sigma;</mi> <mn>1</mn> <mn>2</mn> </msubsup> </mtd> <mtd> <mn>0</mn> </mtd> <mtd> <mn>0</mn> </mtd> </mtr> <mtr> <mtd> <mn>0</mn> </mtd> <mtd> <mn>0</mn> </mtd> <mtd> <msubsup> <mi>&amp;sigma;</mi> <mn>1</mn> <mn>2</mn> </msubsup> </mtd> <mtd> <mn>0</mn> </mtd> </mtr> <mtr> <mtd> <mn>0</mn> </mtd> <mtd> <mn>0</mn> </mtd> <mtd> <mn>0</mn> </mtd> <mtd> <msubsup> <mi>&amp;sigma;</mi> <mn>1</mn> <mn>2</mn> </msubsup> </mtd> </mtr> </mtable> </mfenced> </mrow>
WhereinIt is constant to move variance;
Setting measurement matrix of consequence:
<mrow> <mi>H</mi> <mo>=</mo> <mfenced open = "[" close = "]"> <mtable> <mtr> <mtd> <mn>1</mn> </mtd> <mtd> <mn>0</mn> </mtd> <mtd> <mn>0</mn> </mtd> <mtd> <mn>0</mn> </mtd> </mtr> <mtr> <mtd> <mn>0</mn> </mtd> <mtd> <mn>1</mn> </mtd> <mtd> <mn>0</mn> </mtd> <mtd> <mn>0</mn> </mtd> </mtr> </mtable> </mfenced> </mrow>
Setting measurement variance matrix:
<mrow> <mi>R</mi> <mo>=</mo> <mfenced open = "[" close = "]"> <mtable> <mtr> <mtd> <msubsup> <mi>&amp;sigma;</mi> <mn>2</mn> <mn>2</mn> </msubsup> </mtd> <mtd> <mn>0</mn> </mtd> </mtr> <mtr> <mtd> <mn>0</mn> </mtd> <mtd> <msubsup> <mi>&amp;sigma;</mi> <mn>2</mn> <mn>2</mn> </msubsup> </mtd> </mtr> </mtable> </mfenced> </mrow>
WhereinIt is constant to measure variance;
Kalman filtering processing procedure is as follows:From t=T to t=KT, following cycle calculations are performed:
<mrow> <msub> <mover> <mi>P</mi> <mo>&amp;OverBar;</mo> </mover> <mi>t</mi> </msub> <mo>=</mo> <msub> <mi>FP</mi> <mrow> <mi>t</mi> <mo>-</mo> <mi>T</mi> </mrow> </msub> <msup> <mi>F</mi> <mi>T</mi> </msup> <mo>+</mo> <mi>Q</mi> </mrow>
<mrow> <msub> <mi>K</mi> <mi>t</mi> </msub> <mo>=</mo> <msub> <mover> <mi>P</mi> <mo>&amp;OverBar;</mo> </mover> <mi>t</mi> </msub> <msup> <mi>H</mi> <mi>T</mi> </msup> <msup> <mrow> <mo>(</mo> <mi>H</mi> <msub> <mover> <mi>P</mi> <mo>&amp;OverBar;</mo> </mover> <mi>t</mi> </msub> <msup> <mi>H</mi> <mi>T</mi> </msup> <mo>+</mo> <mi>R</mi> <mo>)</mo> </mrow> <mrow> <mo>-</mo> <mn>1</mn> </mrow> </msup> </mrow>
<mrow> <msub> <mi>P</mi> <mi>t</mi> </msub> <mo>=</mo> <mrow> <mo>(</mo> <mi>E</mi> <mo>-</mo> <msub> <mi>K</mi> <mi>t</mi> </msub> <mi>H</mi> <mo>)</mo> </mrow> <msub> <mover> <mi>P</mi> <mo>&amp;OverBar;</mo> </mover> <mi>t</mi> </msub> </mrow>
Wherein PtFor time t when filtering matrix,For time t when amendment filtering matrix, KtFor time t when filtering weighting square Battle array, E is unit matrix,For time t when filter result, FT、HTF and H transposed matrix, the initial value of circulation are represented respectively It is arranged to
Thus, it is possible to obtain Kalman filtered resultsTakeExported as positioning result.
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CN104684080B (en) * 2015-02-10 2018-04-27 同济大学 A kind of three-dimensional WLAN indoor orientation methods
CN105425208A (en) * 2015-12-21 2016-03-23 深圳思科尼亚科技有限公司 Positioning system and method used for accurate navigation of unmanned aerial vehicle
CN107801241A (en) * 2016-09-07 2018-03-13 黄大卫 Indoor orientation method and system based on wifi equipment
CN108260076B (en) * 2016-12-28 2020-10-09 中国电信股份有限公司 Method, platform and system for monitoring unmanned aerial vehicle running track
CN107272729B (en) * 2017-06-06 2021-01-22 上海工程技术大学 Unmanned aerial vehicle system of cruising based on router
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CN110087179B (en) * 2019-03-26 2020-07-21 深圳先进技术研究院 Indoor positioning control method and system and electronic equipment
CN112925335B (en) * 2019-12-06 2024-10-01 丰翼科技(深圳)有限公司 Unmanned aerial vehicle communication method, unmanned aerial vehicle communication device, computer readable storage medium and computer readable storage device
CN111065054B (en) * 2019-12-11 2021-09-03 Tcl移动通信科技(宁波)有限公司 Method, device, storage medium and terminal for positioning unmanned aerial vehicle

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2008057737A2 (en) * 2006-11-07 2008-05-15 Skyhook Wireless, Inc. System and method for estimating positioning error within a wlan-based positioning system
CN101620267A (en) * 2007-12-07 2010-01-06 中国移动通信集团广东有限公司 Indoor wireless locating system and arithmetic
CN102821463A (en) * 2012-08-13 2012-12-12 西北工业大学 Signal-strength-based indoor wireless local area network mobile user positioning method
CN103686999A (en) * 2013-12-12 2014-03-26 中国石油大学(华东) Indoor wireless locating method based on WiFi signals
CN103841642A (en) * 2014-03-10 2014-06-04 北京工业大学 Three-dimensional positioning method in a room

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2008057737A2 (en) * 2006-11-07 2008-05-15 Skyhook Wireless, Inc. System and method for estimating positioning error within a wlan-based positioning system
CN101620267A (en) * 2007-12-07 2010-01-06 中国移动通信集团广东有限公司 Indoor wireless locating system and arithmetic
CN102821463A (en) * 2012-08-13 2012-12-12 西北工业大学 Signal-strength-based indoor wireless local area network mobile user positioning method
CN103686999A (en) * 2013-12-12 2014-03-26 中国石油大学(华东) Indoor wireless locating method based on WiFi signals
CN103841642A (en) * 2014-03-10 2014-06-04 北京工业大学 Three-dimensional positioning method in a room

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