CN110536233A - A kind of real-time unmanned plane supervisory systems - Google Patents
A kind of real-time unmanned plane supervisory systems Download PDFInfo
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- CN110536233A CN110536233A CN201910716123.8A CN201910716123A CN110536233A CN 110536233 A CN110536233 A CN 110536233A CN 201910716123 A CN201910716123 A CN 201910716123A CN 110536233 A CN110536233 A CN 110536233A
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G5/00—Traffic control systems for aircraft, e.g. air-traffic control [ATC]
- G08G5/003—Flight plan management
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G5/00—Traffic control systems for aircraft, e.g. air-traffic control [ATC]
- G08G5/0073—Surveillance aids
- G08G5/0082—Surveillance aids for monitoring traffic from a ground station
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
- H04W4/025—Services making use of location information using location based information parameters
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
- H04W4/025—Services making use of location information using location based information parameters
- H04W4/027—Services making use of location information using location based information parameters using movement velocity, acceleration information
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
- H04W4/029—Location-based management or tracking services
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/38—Services specially adapted for particular environments, situations or purposes for collecting sensor information
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/40—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]
- H04W4/44—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]
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Abstract
The invention discloses a kind of real-time unmanned plane supervisory systems, belong to sensor related fields, it include: effectively to be tracked to drone flying height and unmanned plane travel track, to no signal, crucially band passes through the progress effective information transmission of the deployment base station LORA, unmanned plane during flying mode is effectively supervised and alarmed, unmanned plane during flying data are effectively analyzed and data mining, drone flying height DATA REASONING algorithm, track correct algorithm.
Description
Technical field
The invention discloses a kind of real-time unmanned plane supervisory systems, belong to sensor related fields.
Background technique
Currently, with unmanned air vehicle technique high speed development and information communication, internet etc. technologies progress, unmanned plane
Supervision has been brought into schedule, and unmanned plane has application range in each field, in crucial region such as place of military importance, has to unmanned plane
The control of effect is more and more important.The associated documents of unmanned plane management are also gradually put into effect, at present on the market without the nothing of a set of maturation
Man-machine supervisory systems, the prior art mainly come from the optimization of vehicle networked Managed Solution, and existing technologies are more cartographic informations pair
GPS data is modified, and can not effectively be tracked to unmanned plane position and height, covers zone data in no 4G network signal
It can not be transmitted.
Summary of the invention
Data supervision is carried out to unmanned plane the object of the present invention is to provide an active platform and data are analyzed.
In order to achieve the above object, the technical solution of the present invention is to provide a kind of real-time unmanned plane supervisory systems, special
Sign is, including flight management module and server system, in which:
Flight management module includes remote communication module, data acquisition module, power management module and the base station LORA；Remotely
Communication module includes 4G communication module and LORA communication module, if LORA signal is strong compared with 4G signal, uses LORA communication module
Server system is sent data to, if 4G signal is strong compared with LORA signal, service is sent data to using 4G communication module
Device system；Data acquisition module is used to acquire all data of unmanned plane during flying, including longitude and latitude, flying speed, flying height,
Flight attitude, temperature, humidity and air pressure obtain unmanned plane during flying posture, geographical position by the data of data collecting module collected
It sets and flying height；Each data acquisition module is used to unique identifier, identification code and corresponding unmanned plane during flying posture,
Geographical location and flying height are transmitted to server system by remote communication module；LORA base station deployment is needing to be monitored
Key area；
Server system includes back-end data base and front end real-time display system, and server system is according to received from tof tube
The identification code and corresponding unmanned plane during flying posture, geographical location and flying height for managing module determine whether that unmanned plane rises
Fly, and judgement conclusion is fed back into flight management module, meanwhile, server system receives to send the data from flight management module
And it is stored in back-end data base, and shown after drawing 3D flight path in front end real-time display system.
Local is saved the data in preferably for flight management module described in the location of no 4G signal and LORA signal,
To thering is 4G signal or LORA signal location to be sent to the server system for local data are stored in.
Preferably, the data acquisition module acquires the air pressure by barometer, and air pressure is carried out using temperature and humidity
Amendment.
Preferably, formula air pressure being modified are as follows:
P=P0+α(T-T0)+β(h-h0)+λ, in formula, P is revised air pressure, P0For actually measured air pressure numerical value, T
For Current Temperatures, T0For surface temperature, h is current humidity, h0For surface humidity, α, β, λ are constant.
Preferably, flying height is modified using revised air pressure P, comprising the following steps:
The height above sea level H of standard isobaric surface is calculated first with revised air pressure Ps, then have:
Hs=H0+R/g×Tm×ln(P0/Ps), in formula, HsFor the height above sea level of standard isobaric surface, H0For the height above sea level of survey station
Highly, P is surface pressure, PsFor the air column average height obtained according to revised air pressure P, Tm is Current Temperatures, and R, g are normal
Number；
Then use following formula by height above sea level HsIt blends, is melted with the real-time flight height obtained by GPS
Flying height H after conjunction:
In formula, HgFor the real-time flight height obtained by GPS, Δ HgThe moment is acquired for current time and previous secondary data
Calculate resulting difference in height.
Preferably, the flight attitude is obtained using gyroscope, is obtained using revised flying height H removal with gyroscope
The data wander point of the flight attitude obtained, formula are as follows:
In formula, Δ H is the height changed in the sampling time, and Δ t is data collection interval, and v obtains for gyroscope to hang down
Straight speed.
Preferably, when the server system draws 3D flight path, flight path is modified, when amendment uses rail
Mark correction algorithm:
In formula, (xj,yj) it is coordinate points corresponding to the current j moment, i ∈ (j-
It 3, j+3) is 3 before j moment corresponding sequence number to rear 3 sequence numbers, j is sequence number corresponding to current time；
The track data of relative smooth is obtained using mean filter, data consider point set nearby, effective to cross rate error number
According to then using Kalman by the status predication current state of last moment:
In formula,For current data state,For the data mode at k-1 moment, uk-1For k-1
Moment corresponding system control amount, A, B are system parameter；
Prediction process increases new uncertain Q:
In formula,ForCorresponding covariance, Pk-1ForCorresponding covariance；
By the uncertainty of prediction resultKalman gain is calculated with the uncertain R of observed result:
In formula, KkFor kalman gain, H is the parameter of measuring system；
Prediction result and observed result are weighted and averaged, the state estimation at current time is obtained:
In formula,For estimated value optimal under k-state, KkFor kalman gain, zkIt is yes
The measured value at k moment；
Update Pk,
Finally modified path is judged using track correct algorithm, show that a relatively smooth path is bent
Line.
Compared with prior art, the invention has the advantages that can advance to drone flying height and unmanned plane
Track is effectively tracked, and to no signal, crucially band flies unmanned plane by the progress effective information transmission of the deployment base station LORA
Line mode is effectively supervised and is alarmed, and is effectively analyzed unmanned plane during flying data and data mining.
Detailed description of the invention
Fig. 1 is the overall framework figure of this system；
Fig. 2 is flight management module frame figure；
Fig. 3 is altitude information correction algorithm flow chart；
Fig. 4 is server system frame diagram；
Fig. 5 is track correct algorithm flow chart.
Specific embodiment
Present invention will be further explained below with reference to specific examples.It should be understood that these embodiments are merely to illustrate the present invention
Rather than it limits the scope of the invention.In addition, it should also be understood that, after reading the content taught by the present invention, those skilled in the art
Member can make various changes or modifications the present invention, and such equivalent forms equally fall within the application the appended claims and limited
Range.
The present invention acquires all data of unmanned plane during flying, including longitude and latitude using flight management module, and flying speed flies
Row height, flight attitude.And carried out data transmission by 4G/LORA, data are reached into system server.It is preferable for 4G network
Region carried out data transmission using 4G module, local preservation is carried out using data for no signal location, until there is signal location
Data transmission is carried out, the base station LORA is disposed to the key area that needs are monitored, meets the needs of data transmission；Flight management
Module is using GPS and air pressure meter difference computed altitude and by data back.Wherein barometer is modified using temperature, using equal
Value filtering removes shift point；Server system combines the GPS data of passback using median filtering and Kalman filtering
Mode removes GPS data shift point, corrects GPS data, and draw 3D flight map.It is advised according to real time data to flight is not met
The unmanned plane of model is alarmed by flight management module, and is alarmed to relevant staff.Back-end system periodically uses
Analytic hierarchy process (AHP) carries out basis effectively analysis to data, classify to data using machine learning algorithm and then analyze nobody
Machine flies the flight habit of hand.
As shown in Figure 1, the present invention is specifically made of flight management module and server system two parts in real time.Such as Fig. 2 institute
Show that flight management module is made of MCU, power module and sensor module and communication module.Sensor module mainly by
Barometer thermometer module, locating module and gyroscope composition.Control chip by bus acquisition location information and air pressure and
Temperature data is modified air pressure by algorithm temperature as shown in Figure 3, and converts and altitude information is calculated, and passes through LORA/
4G network is carried out data transmission by ICP/IP protocol.The data received are decoded by server as shown in Figure 4, and will solution
Data after code are stored into correspondence database, are shown to wrong data and warning data in front end, when access services
When the webpage of device front end, the data in background data base are obtained, algorithm analysis removal exception error point is carried out to data, merges GPS
Data and air pressure count to obtain reliable data in real time and drawing three-dimensional map, algorithm flow are as shown in Figure 5.Server is fixed
Phase analyzes big data by machine learning scheme according to existing data, extracts data characteristics, and tie to analysis in front end
Fruit is shown.
Data acquisition module of the invention acquires the air pressure by barometer, and air pressure is repaired using temperature and humidity
Just, formula air pressure being modified are as follows:
P=P0+α(T-T0)+β(h-h0)+λ, in formula, P is revised air pressure, P0For actually measured air pressure numerical value, T
For Current Temperatures, T0For surface temperature, h is current humidity, h0For surface humidity, α, β, λ are constant.
Flying height is modified using revised air pressure P, comprising the following steps:
The height above sea level H of standard isobaric surface is calculated first with revised air pressure Ps, then have:
Hs=H0+R/g×Tm×ln(P0/Ps), in formula, HsFor the height above sea level of standard isobaric surface, H0For the height above sea level of survey station
Highly, P is surface pressure, PsFor the air column average height obtained according to revised air pressure P, Tm is Current Temperatures, and R, g are normal
Number；
Then use following formula by height above sea level HsIt blends, is melted with the real-time flight height obtained by GPS
Flying height H after conjunction:
In formula, HgFor the real-time flight height obtained by GPS, Δ HgThe moment is acquired for current time and previous secondary data
Calculate resulting difference in height.
The flight attitude, the institute obtained using revised flying height H removal gyroscope are obtained using gyroscope
The data wander point of flight attitude is stated, formula is as follows:
In formula, Δ H is the height changed in the sampling time, and Δ t is data collection interval, and v obtains for gyroscope to hang down
Straight speed.
When server system draws 3D flight path, flight path is modified, track correct algorithm is used when amendment:
In formula, (xj,yj) it is coordinate points corresponding to the current j moment, i ∈ (j-
It 3, j+3) is j moment corresponding sequenceIn formula, (xj,yj) it is corresponding to the current j moment
Coordinate points, i ∈ (j-3, j+3) are 3 before j moment corresponding sequence number to rear 3 sequence numbers, and j is corresponding to current time
Sequence number；
The track data of relative smooth is obtained using mean filter, data consider point set nearby, effective to cross rate error number
According to then using Kalman by the status predication current state of last moment:
In formula,For current data state,For the data mode at k-1 moment, uk-1For k-1
Moment corresponding system control amount, A, B are system parameter；
Prediction process increases new uncertain Q:
In formula,ForCorresponding covariance, Pk-1ForCorresponding covariance；
By the uncertainty of prediction resultKalman gain is calculated with the uncertain R of observed result:
In formula, KkFor kalman gain, H is the parameter of measuring system；
Prediction result and observed result are weighted and averaged, the state estimation at current time is obtained:
In formula,For estimated value optimal under k-state, KkFor kalman gain, zkIt is yes
The measured value at k moment；
First 3 are counted to rear 3 sequence numbers, j is sequence number corresponding to current time；
The track data of relative smooth is obtained using mean filter, data consider point set nearby, effective to cross rate error number
According to then using Kalman by the status predication current state of last moment:
In formula,For current data state,For the data mode of last moment, uk-1For k-
Control amount of 1 moment to system, A, B are system parameter；
Prediction process increases new uncertain Q:
In formula,For the uncertainty of prediction result, Pk-1Most for k-1 moment status predication
Excellent result；
By the uncertainty of prediction resultKalman gain is calculated with the uncertain R of observed result:
In formula, KkFor kalman gain, H is the parameter of measuring system；
Prediction result and observed result are weighted and averaged, the state estimation at current time is obtained:
In formula,For estimated value optimal under k-state, KkFor kalman gain, zkIt is yes
The measured value at k moment；
Update Pk,
Finally modified path is judged using track correct algorithm, show that a relatively smooth path is bent
Line.
Claims (7)
1. a kind of real-time unmanned plane supervisory systems, which is characterized in that including flight management module and server system, in which:
Flight management module includes remote communication module, data acquisition module, power management module and the base station LORA；Telecommunication
Module includes 4G communication module and LORA communication module, if LORA signal is strong compared with 4G signal, will be counted using LORA communication module
According to server system is sent to, if 4G signal is strong compared with LORA signal, server system is sent data to using 4G communication module
System；Data acquisition module is used to acquire all data of unmanned plane during flying, including longitude and latitude, flying speed, flying height, flight
Posture, temperature, humidity and air pressure, by the data of data collecting module collected obtain unmanned plane during flying posture, geographical location and
Flying height；Each data acquisition module is used to unique identifier, identification code and corresponding unmanned plane during flying posture, geography
Position and flying height are transmitted to server system by remote communication module；LORA base station deployment is in the pass that needs are monitored
Key area；
Server system includes back-end data base and front end real-time display system, and server system is according to received from flight management mould
The identification code of block and corresponding unmanned plane during flying posture, geographical location and flying height determine whether that unmanned plane takes off,
And judgement conclusion is fed back into flight management module, meanwhile, server system receives to send from the data of flight management module simultaneously
It is stored in back-end data base, and is shown after drawing 3D flight path in front end real-time display system.
2. a kind of real-time unmanned plane supervisory systems as described in claim 1, which is characterized in that no 4G signal and LORA are believed
Number location described in flight management module save the data in local, until having 4G signal or LORA signal location that will be stored in local
Data be sent to the server system.
3. a kind of real-time unmanned plane supervisory systems as described in claim 1, which is characterized in that the data acquisition module passes through
Barometer acquires the air pressure, and air pressure is modified using temperature and humidity.
4. a kind of real-time unmanned plane supervisory systems as claimed in claim 3, which is characterized in that the formula being modified to air pressure
Are as follows:
P=P0+α(T-T0)+β(h-h0)+λ, in formula, P is revised air pressure, P0For actually measured air pressure numerical value, T is current
Temperature, T0For surface temperature, h is current humidity, h0For surface humidity, α, β, λ are constant.
5. a kind of real-time unmanned plane supervisory systems as claimed in claim 3, which is characterized in that utilize revised P pairs of air pressure
Flying height is modified, comprising the following steps:
The height above sea level H of standard isobaric surface is calculated first with revised air pressure Ps, then have:
Hs=H0+R/g×Tm×ln(P0/Ps), in formula, HsFor the height above sea level of standard isobaric surface, H0For the height above sea level of survey station,
P is surface pressure, PsFor the air column average height obtained according to revised air pressure P, Tm is Current Temperatures, and R, g are constant；
Then use following formula by height above sea level HsIt blends, obtains fused with the real-time flight height obtained by GPS
Flying height H:
In formula, HgFor the real-time flight height obtained by GPS, Δ HgMoment calculating is acquired for current time and previous secondary data
Resulting difference in height.
6. a kind of real-time unmanned plane supervisory systems as claimed in claim 5, which is characterized in that obtain described fly using gyroscope
Row posture, using the data wander point for the flight attitude that revised flying height H removal gyroscope obtains, formula is such as
Under:
In formula, Δ H is the height changed in the sampling time, and Δ t is data collection interval, and v is that gyroscope obtains vertical speed
Degree.
7. a kind of real-time unmanned plane supervisory systems as described in claim 1, which is characterized in that the server system draws 3D
When flight path, flight path is modified, track correct algorithm is used when amendment:
In formula, (xj,yj) it is coordinate points corresponding to the current j moment, i ∈ (j-3, j+
It 3) is 3 before j moment corresponding sequence number to rear 3 sequence numbers, j is sequence number corresponding to current time；
The track data of relative smooth is obtained using mean filter, data consider point set nearby, it is effective to cross rate wrong data, with
Afterwards using Kalman by the status predication current state of last moment:
In formula,For current data state,For the data mode at k-1 moment, uk-1For the k-1 moment
Corresponding system control amount, A, B are system parameter；
Prediction process increases new uncertain Q:
In formula,ForCorresponding covariance, Pk-1ForCorresponding covariance；
By the uncertainty of prediction resultKalman gain is calculated with the uncertain R of observed result:
In formula, KkFor kalman gain, H is the parameter of measuring system；
Prediction result and observed result are weighted and averaged, the state estimation at current time is obtained:
In formula,For estimated value optimal under k-state, KkFor kalman gain, zkWhen to be k
The measured value at quarter；
Update Pk,
Finally modified path is judged using track correct algorithm, obtains a relatively smooth path curve.
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| CN110536233B (en) | 2021-04-20 |
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