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 PDFInfo
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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
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：
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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：
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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>&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>&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>&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>&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>&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>&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>&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>&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>&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>&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 |
| CN107291092B (en) * | 2017-06-15 | 2021-01-22 | 上海工程技术大学 | WiFi-supported air-ground cooperative unmanned aerial vehicle system |
| 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 |
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