CN106846924A - Air traffic control system for collision early warning - Google Patents
Air traffic control system for collision early warning Download PDFInfo
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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]
- G08G5/04—Anti-collision systems
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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]
- G08G5/0017—Arrangements for implementing traffic-related aircraft activities, e.g. arrangements for generating, displaying, acquiring or managing traffic information
- G08G5/0021—Arrangements for implementing traffic-related aircraft activities, e.g. arrangements for generating, displaying, acquiring or managing traffic information located in the aircraft
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Abstract
The invention relates to an air traffic control system for collision early warning, which comprises a data communication module, a monitoring data fusion module, an airborne terminal module and a control terminal module, wherein the monitoring data fusion module is used for realizing the fusion of monitoring data of an air traffic control radar and automatic related monitoring data and providing real-time flight path information for the control terminal module; the control terminal module comprises 3 submodules of conflict-free 4D track generation before flight, short-term and medium-term 4D track generation in flight, real-time flight conflict monitoring and warning; according to the conflict early warning method based on 4D track operation, flight plan data are processed by means of the control terminal module, the 4D track is generated by means of the hidden Markov model, and analysis of potential traffic conflicts in airspace traffic conditions is achieved. The invention can effectively early warn flight conflict and improve the safety of air traffic.
Description
The application is Application No.:201510007997.8, invention and created name is《The flight of air traffic control system
Conflict method for early warning》, the applying date is:The divisional application of the application for a patent for invention of on 01 07th, 2015.
Technical field
It is the present invention relates to a kind of air traffic control system and method more particularly to a kind of based on the aerial of 4D flight paths operation
Traffic control system and airborne vehicle track is predicted and to the method for flight collision early warning.
Background technology
With fast-developing the becoming increasingly conspicuous with spatial domain resource-constrained contradiction of World Airways transport service, traffic flow is close in the air
The complicated spatial domain of collection, the air traffic control mode for still combining interval allotment using flight plan gradually shows that it falls behind
Property, it is in particular in:(1) flight plan easily causes traffic flow tactics pipe not for airborne vehicle configures accurate blank pipe interval
It is crowded in reason, reduce spatial domain security;(2) reckoning of the air traffic control automation system centered on flight plan to flight profile, mission profile
With Trajectory Prediction low precision, conflict dissolution ability is caused;(3) job of air traffic control still lays particular emphasis on the single aviation of holding
Personal distance between device, it is difficult to rise to carry out strategic Management to traffic flow.Prediction for airborne vehicle track and thereby
And flight collision early warning is particularly important.
4D flight paths be in room and time form, in a certain airborne vehicle flight path each point locus (longitude, latitude and
Highly) and the time accurate description, the operation based on flight path refers to use " control arrival time " on the way point of 4D flight paths,
" time window " that i.e. control airborne vehicle passes through specific way point.In high density spatial domain the operation based on 4D flight paths
(Trajectory based Operation) as one of basic operating mechanism, be it is following to big flow, it is high density, closely-spaced
Under the conditions of spatial domain implement a kind of effective means of management, can significantly decrease the uncertainty of airborne vehicle flight path, improve spatial domain
With the security and utilization rate of Airport Resources.
The air traffic method of operation based on flight path operation needs to carry out single aircraft flight path on strategic level
Calculate and optimize, collaboration is implemented to the traffic flow that many airborne vehicles are constituted and is adjusted;By correcting traffic flow on pre- tactical level
In indivedual airborne vehicles flight path to solve congestion problems, and ensure the operational efficiency of all airborne vehicles in the traffic flow;And in war
In art aspect predict conflict and optimization free scheme, then be highly dependent on can be exactly to airborne vehicle track be predicted simultaneously
Early warning is carried out to flight collision, track that at present can not be accurately in real time to airborne vehicle is predicted, and that is done in real-time is outstanding
For difference.
The content of the invention
It is to overcome the deficiencies in the prior art that the technical problem to be solved in the present invention is, there is provided a kind of based on the operation of 4D flight paths
The air traffic control system for the early warning that conflicts, can effectively, accurately and real-time predict the track of airborne vehicle and predict flight
Conflict.
Realize that the technical scheme of the object of the invention is to provide a kind of air traffic control system for the early warning that conflicts, including
Airborne Terminal module, data communication module, monitoring data fusion module and control terminal module;Monitoring data fusion module is used
In merging for air traffic control radar monitoring data and automatic dependent surveillance data is realized, believe for control terminal module provides real-time flight path
Breath;
The control terminal module includes following submodule:
Lothrus apterus 4D flight path generation modules before flight, according to flight plan and the forecast data of world area forecast system,
Airborne vehicle kinetic model is set up, then the pre- allotment theoretical model of flight path conflict, generation boat is set up according to flight collision Coupling point
Pocket Lothrus apterus 4D flight paths;
Flight middle or short term 4D flight path generation modules, according to the real-time flight path information that monitoring data fusion module is provided, utilize
HMM, thus it is speculated that the airborne vehicle 4D tracks in following certain hour window;
Real-time flight conflict monitoring and alarm module, for setting up from the continuous dynamic of airborne vehicle to discrete conflict logic
Observer, by the conflict situation that the continuous dynamic mapping of Air Traffic System is the expression of discrete observation value;When system is possible to separated
During anti-air traffic control rules, to the Hybrid dynamics behavior implementing monitoring of air traffic hybrid system, provide for controller and
When warning information;
The method that the air traffic control system for the early warning that conflicts carries out conflict early warning includes following several steps:
Forecast of the Lothrus apterus 4D flight paths generation module according to flight plan and world area forecast system before step A, flight
Data, set up airborne vehicle kinetic model, and set up the pre- allotment theoretical model of flight path conflict, generation according to flight collision Coupling point
Airborne vehicle Lothrus apterus 4D flight paths;
Step B, monitoring data fusion module are merged air traffic control radar monitoring data with automatic dependent surveillance data, raw
Into the real-time flight path information of airborne vehicle and it is supplied to control terminal module;Flight middle or short term 4D flight paths generation in control terminal module
Module speculates the airborne vehicle 4D tracks in following certain hour window according to the real-time flight path information of airborne vehicle and history flight path information;Institute
State the tool of the airborne vehicle 4D tracks speculated according to the real-time flight path information of airborne vehicle and history flight path information in following certain hour window
Body implementation process is as follows:
Step B6, to airborne vehicle track data pre-process, according to acquired in the original discrete two-dimensional position sequence x of airborne vehicle
=[x1,x2,...,xn] and y=[y1,y2,...,yn], treatment is carried out to it using first-order difference method and obtains new airborne vehicle
Discrete location sequence △ x=[△ x1,△x2,...,△xn-1] and △ y=[△ y1,△y2,...,△yn-1], wherein △ xb=
xb+1-xb,△yb=yb+1-yb(b=1,2 ..., n-1);
Step B7, to airborne vehicle track data cluster, to airborne vehicle discrete two-dimensional position sequence △ x and △ new after treatment
Y, by setting cluster number M', is clustered to it respectively using K-means clustering algorithms;
Step B8, parameter training is carried out using HMM to the airborne vehicle track data after cluster, by will
Airborne vehicle running orbit data △ x and △ y after treatment is considered as the aobvious observation of hidden Markov models, by setting hidden state
Number N ' and parameter update period ζ ', according to nearest T' position detection value and using the B-W algorithms rolling newest hidden horse of acquisition
Er Kefu model parameters λ ';
Step B9, foundation HMM parameter, are obtained corresponding to current time observation using Viterbi algorithm
Hidden state q;
Step B10, by set prediction time domain h', the hidden state q based on airborne vehicle current time, obtain future time period boat
The position prediction value O of pocket;
Step C, real-time flight conflict monitoring and alarm module are set up from the continuous dynamic of airborne vehicle to discrete conflict logic
Observer, by the continuous dynamic mapping of Air Traffic System be discrete observation value expression conflict situation;When system is possible to
When violating air traffic control rules, to the Hybrid dynamics behavior implementing monitoring of air traffic hybrid system, for controller provides
Timely warning information.
Further, in step B, the value of the cluster number M' is 4, and the value of hidden state number N' is 3, when parameter updates
Section ζ ' is 30 seconds, and T' is 10, and prediction time domain h' is 300 seconds.
Further, the B8 of step B is specifically referred to:By the flight path sequence data length for being obtained is dynamic change,
For the state change of real-time tracking airborne vehicle flight path, it is necessary to initial flight path HMM parameter lambda '=(π, A,
B it is readjusted on the basis of), more accurately to speculate airborne vehicle in the position at following certain moment;Every period ζ ', according to
According to T' observation (o of newest acquisition1,o2,...,oT') to flight path HMM parameter lambda '=(π, A, B) carry out weight
New estimation;
The B10 of step B is specifically referred to:Every the periodHMM parameter lambda according to newest acquisition '=(π,
A, B) and nearest H history observation (o1,o2,...,oH), the hidden state q based on airborne vehicle current time is predicted by setting
Time domain h', position prediction value O of the airborne vehicle in future time period h' is obtained in moment t.
Further, the periodIt is 4 seconds.
Further, the airborne vehicle Lothrus apterus 4D flight paths of the step A are generated in accordance with the following methods:
Step A1, aircraft states transfer modeling is carried out, according to the flying height section of airborne vehicle in flight plan, set up
The Petri net model that single airborne vehicle is shifted in different legs:E=(g, G, Pre, Post, m) for the airborne vehicle stage shifts mould
Type, wherein g represent flight leg, and G represents the transfer point of flight status parameter in vertical section, and Pre and Post represents boat respectively
Section is front and rear to annexation with way point,Represent the mission phase residing for airborne vehicle;
Step A2, to set up the full flight profile, mission profile hybrid model of airborne vehicle as follows,
vH=κ (vCAS,Mach,hp,tLOC),
vGS=μ (vCAS,Mach,hp,tLOC,vWS, α),
Wherein vCASIt is calibrated airspeed, Mach is Mach number, hpIt is pressure altitude, α is the angle of wind direction forecast and air route,
vWSIt is wind speed forecasting value, tLOCIt is temperature forecast value, vHIt is altitude rate, vGSIt is ground velocity;
Step A3, using hybrid system emulation by the way of speculate solution flight path:It is sharp using by the method for time subdivision
Voyage with the characteristic Recursive Solution any time airborne vehicle of state consecutive variations in a certain mission phase away from reference pointAnd heightWherein J0It is initial time airborne vehicle away from reference point
Voyage, △ τ are the numerical value of time window, and J (τ) is voyage of the τ moment airborne vehicle away from reference point, h0It is initial time airborne vehicle away from ginseng
The height of examination point, h (τ) is height of the τ moment airborne vehicle away from reference point, thereby it is assumed that the 4D flight paths for obtaining single airborne vehicle;
Step A4, to many airborne vehicle coupling models implement Lothrus apterus allotment:According to two airborne vehicles in advance up to the time in crosspoint,
According to air traffic control principle, the airborne vehicle 4D flight paths to being unsatisfactory for space requirement near crosspoint carry out quadratic programming, obtain
To Lothrus apterus 4D flight paths.
Further, monitor that air traffic control radar is monitored data and automatic dependent surveillance by data fusion module in the step B
Data are merged, and generate the real-time flight path information of airborne vehicle, specifically in accordance with the following methods:
Step B1, by coordinate unit and time unification;
Step B2, the point that will belong to same target using closest data association algorithm are associated, and extract targetpath;
Step B3, the track data that will be extracted from automatic dependent surveillance system and air traffic control radar respectively are joined from different space-time
Examine coordinate system conversion, be registered to the unified space-time reference coordinate system of control terminal;
Step B4, two coefficient correlations of flight path of calculating, if coefficient correlation is less than a certain predetermined threshold value, then it is assumed that two boats
Mark is uncorrelated;Otherwise two flight path correlations, can be merged;
Step B5, the flight path to correlation are merged.
Further, related flight path is merged in the step B5, it is flat using the weighting based on the sampling period
Equal algorithm, its weight coefficient determines according to sampling period and precision of information, recycle Weighted Average Algorithm by it is associated from
Dynamic dependent surveillance flight path and air traffic control radar Track Fusion are system flight path.
Further, the specific implementation process of the step C is as follows:
The conflict hypersurface collection of functions of step C1, construction based on regulation rule:Set up hypersurface collection of functions and be used to reflect and be
The contention situation of system, wherein, the continuous function related to single airborne vehicle in conflict hypersurfaceFor I types are super bent
Face, the continuous function related to two frame airborne vehiclesIt is Type-II hypersurface;
Step C2, set up by airborne vehicle continuous state to discrete conflict situation observer:Needs are built according to control specification
Vertical observer, the collision event that observation system system is passed through hypersurface and produced, so that controller makes corresponding control decision
Instruction;Observer ξ is used for the consecutive variations of aircraft position in observation system and produces collision event, claimsIt is I
Type observer,It is Type-II observer;
The discrete watch-dog of step C3, design from conflict to conflict Resolution means, the discrete watch-dog can be described as functionWherein S is the space that observer observation vector is transformed into, and D is the space that all decision vector d are transformed into;Work as observer
Discrete observation vector when showing that a certain unexpected state occurs, corresponding alarm is sent at once.
The present invention has positive effect:(1) air traffic control system for the early warning that conflicts of the invention is in aviation
During device real-time track speculates, the influence of enchancement factor is incorporated, the rolling track for being used speculates that scheme can be carried in time
The changing condition of extraneous enchancement factor is taken, the accuracy of airborne vehicle track supposition is improve.
(2) the conflict method for early warning based on the operation of 4D flight paths of the invention is preferable to the early warning effect of flight collision, can have
Flight collision is simultaneously predicted in effect, the accurately and real-time track of prediction airborne vehicle.
(3) reckoning and Trajectory Prediction precision of the conflict method for early warning based on the operation of 4D flight paths of the invention to flight profile, mission profile
Height, and then cause that conflict dissolution ability and automatization level are improved, reduce the live load of controller.
Brief description of the drawings
Fig. 1 is Lothrus apterus 4D flight path generation method schematic flow sheets before flight;
Fig. 2 is flight middle or short term 4D flying track conjecture method flow schematic diagrams;
Fig. 3 is airborne vehicle flight path conflict monitoring and alarm method schematic flow sheet.
Specific embodiment
(embodiment 1)
The air traffic control system for the early warning that conflicts based on the operation of 4D flight paths of the present embodiment, including Airborne Terminal
Module 101, data communication module 102, monitoring data fusion module 103 and control terminal module 104.Below to each several part
Specific embodiment is described in detail respectively.
1. Airborne Terminal module
Airborne Terminal module 101 be pilot obtain ground control order, with reference to 4D flight paths, and input flight intent
Interface, while still gathering the interface of current aerospace device position data.
Its specific embodiment is as follows:
Airborne Terminal module 101 receives following information input:(1) ADS-B information acquisition units 201 pass through Airborne GPS
The aircraft position vector of collection, velocity vector, and this airborne vehicle catchword, by information and data transfer to machine after coding
Carry data communication module 102;(2) airborne vehicle driver is needed the flight intent inconsistent with ground control order, by people
Machine inputting interface, and the form that the ground controller for arranging can recognize passes through information and data transfer to airborne data communication
Module 102.Other Airborne Terminal module 101 realizes following information output:(1) by terminal display, receive and show
The air traffic control instruction that pilot can recognize;(2) receive and show ground line terminal flight previous existence into Lothrus apterus 4D boat
Mark, and the optimal of calculating frees 4D flight paths after ground line end-probing is to conflict.
2. data communication module
Data communication module 102 can realize vacant lot bidirectional data communication, realize airborne real time position data and flight intent
The downlink transfer and ground control command unit 203 of data cell 202, and with reference to the uplink of 4D flight paths unit 204.
Its specific embodiment is as follows:
Downlink data communication:Airborne Terminal 101 passes through airborne secondary radar answering machine by aircraft identification mark and 4D
Confidence ceases, and other additional datas, and such as flight intent, flying speed, meteorology information transfer gives ground secondary radar
(SSR) data message is parsed after secondary radar reception, and is transferred to central data processing assembly 301 and decoded, by referring to
Track data interface is made to be transferred to control terminal 104;Upstream data communication:Control terminal 104 in ground is by instructing track data
Interface, after being encoded through central data processing assembly 301, the inquisitor just ground control order of ground secondary radar or refers to 4D
Flight path information transmission is simultaneously displayed in Airborne Terminal 101.
3. data fusion module is monitored
Monitoring data fusion module 103 realizes that air traffic control radar monitoring is merged with automatic dependent surveillance ADS-B data, is to manage
Flight middle or short term 4D flight paths generation submodule and real-time flight conflict monitoring in terminal module processed 104 are provided with alarm submodule
Real-time flight path information.
Its specific embodiment is as follows:
(1) in pretreatment stage by coordinate unit and time unification, it is assumed that extracted from ADS-B and air traffic control radar respectively
Data are the coordinate (such as longitude, latitude, height above sea level) of series of discrete point, each point correspondence acquisition time;(2) using closest
The point that data association algorithm will belong to same target is associated, and extracts targetpath;(3) will respectively from ADS-B and blank pipe thunder
Up to the track data of middle extraction from different space-time reference coordinate system conversion, the unified space-time of control terminal is registered to reference to seat
Mark system;(4) two coefficient correlations of flight path are calculated, if coefficient correlation is less than a certain predetermined threshold value, then it is assumed that two flight paths are not
Correlation, otherwise two flight path correlations, can be merged;(5) related flight path is merged.Due to ADS-B and blank pipe
The precision of radar is different with the sampling period, the system using based on the sampling period Weighted Average Algorithm, its weight coefficient according to
Sampling period and precision of information determination, recycle Weighted Average Algorithm by associated ADS-B flight paths and air traffic control radar flight path
It is fused to system flight path.
4. control terminal module
Control terminal module 104 includes that Lothrus apterus 4D flight paths are generated, flight middle or short term 4D flight paths are generated before flight, flies in real time
Row conflict monitoring and this 3 submodules of alarm.
(1) Lothrus apterus 4D flight paths generation before flying
Flight plan and world area forecast system (WAFS) issue obtained according to Flight Data Processing System (FDP)
The GRIB lattice point forecast datas of wind, temperature, the hybrid model of stratification is set up to Air Traffic System, by system in peace
The evolution of total state, describes the time locus of state evolution, generates airborne vehicle flight path.
As shown in figure 1, its specific implementation process is as follows:
First, aircraft states transfer modeling is carried out.Airborne vehicle shows as being moved between leg along the process of track flight
State handoff procedure, according to the flying height section of airborne vehicle in flight plan, sets up what single airborne vehicle was shifted in different legs
Petri net model:(g, G, Pre, Post, are m) airborne vehicle stage metastasis model to E=, and wherein g represents flight leg, and G represents vertical
The transfer point of flight status parameter (including air speed, height, configuration) in straight section, Pre and Post represents leg and air route respectively
That puts is front and rear to annexation,Represent the mission phase residing for airborne vehicle.
Secondly, the full flight profile, mission profile hybrid model of airborne vehicle is set up.Flight of the airborne vehicle in single leg is considered as company
Continuous process, according to particle energy model, derives airborne vehicle dynamics of the airborne vehicle in the case where the different operation phase is with meteorological condition
Equation, vH=κ (vCAS,Mach,hp,tLOC), vGS=μ (vCAS,Mach,hp,tLOC,vWS, α), wherein vCASIt is calibrated airspeed,
Mach is Mach number, hpIt is pressure altitude, α is the angle of wind direction forecast and air route, vWSIt is wind speed forecasting value, tLOCFor temperature is pre-
Report value, vHIt is altitude rate, vGSIt is ground velocity.
Then, solution flight path is speculated by the way of hybrid system emulation.It is sharp using by the method for time subdivision
Voyage with the characteristic Recursive Solution any time airborne vehicle of state consecutive variations in a certain mission phase away from reference pointAnd heightWherein J0It is initial time airborne vehicle away from reference point
Voyage, △ τ are the numerical value of time window, and J (τ) is voyage of the τ moment airborne vehicle away from reference point, h0It is initial time airborne vehicle away from ginseng
The height of examination point, h (τ) is height of the τ moment airborne vehicle away from reference point, thereby it is assumed that the 4D flight paths for obtaining single airborne vehicle.
Finally, many airborne vehicle coupling models are implemented with Lothrus apterus allotment.According to two airborne vehicles in advance up to the time in crosspoint, press
According to air traffic control principle, the airborne vehicle 4D flight paths to being unsatisfactory for space requirement near crosspoint carry out quadratic programming, obtain
Lothrus apterus 4D flight paths.
(2) flight middle or short term 4D flight paths generation
The real-time track data of airborne vehicle is obtained after implementing fusion according to control radar and automatic dependent surveillance system ADS-B,
Using HMM, thus it is speculated that the airborne vehicle 4D tracks in following 5 minutes window.
As shown in Fig. 2 its specific implementation process is as follows:
First, airborne vehicle track data is pre-processed, the original discrete two-dimensional position sequence x=of airborne vehicle acquired in
[x1,x2,...,xn] and y=[y1,y2,...,yn], using first-order difference method it is carried out treatment obtain new airborne vehicle from
Dissipate position sequence △ x=[△ x1,△x2,...,△xn-1] and △ y=[△ y1,△y2,...,△yn-1], wherein △ xb=xb+1-
xb,△yb=yb+1-yb(b=1,2 ..., n-1).
Secondly, airborne vehicle track data is clustered.To airborne vehicle discrete two-dimensional position sequence △ x and △ y new after treatment,
By setting cluster number M', it is clustered respectively using K-means clustering algorithms.
Then, parameter training is carried out using HMM to the airborne vehicle track data after cluster.By that will locate
Airborne vehicle running orbit data △ x and △ y after reason is considered as the aobvious observation of hidden Markov models, by setting hidden status number
Mesh N' and parameter update period ζ ', roll and obtain newest hidden Ma Er according to T' nearest position detection value and use B-W algorithms
Section husband model parameter λ ':By the flight path sequence data length for being obtained is dynamic change, in order to real-time tracking airborne vehicle navigates
The state change of mark, it is necessary to initial flight path HMM parameter lambda '=(π, A, B) on the basis of it is adjusted again
It is whole, more accurately to speculate airborne vehicle in the position at following certain moment.Every period ζ ', according to T' observation of newest acquisition
Value (o1,o2,...,oT') to flight path HMM parameter lambda '=(π, A, B) reevaluated.
Again and, according to HMM parameter, obtained corresponding to current time observation using Viterbi algorithm
Hidden state q.
Finally, every the periodHMM parameter lambda according to newest acquisition '=(π, A, B) and nearest H
History observation (o1,o2,...,oH), the hidden state q based on airborne vehicle current time, by setting prediction time domain h', at the moment
T obtains position prediction value O of the airborne vehicle in future time period h'.
The value of the cluster number M' is 4, and the value of hidden state number N' is 3, and parameter renewal period ζ ' is 30 seconds, and T' is
10, prediction time domain h' is 300 seconds, periodIt is 4 seconds.
(3) real-time flight conflict monitoring and alarm
When system is possible to occur violating the state of safe condition collection, condition monitoring is implemented by controller, to aviation
Device implements effective measure of control, it is to avoid the generation of flight collision.
As shown in figure 3, its specific implementation process is as follows:
First, conflict hypersurface collection of functions of the construction based on regulation rule.The violation of air traffic control constraint can
It is considered as controlled device (the multi rack airborne vehicle of control zone flight) event that composition system is passed through hypersurface and produced, sets up super bent
Surface function collection is used to reflect the contention situation of system.Wherein, continuous function related to single airborne vehicle in conflict hypersurfaceIt is I type hypersurfaces, and by the continuous function related to two frame airborne vehiclesFor Type-II is super bent
Face.
Then, set up by the observer of airborne vehicle continuous state to discrete conflict situation.Need to be set up according to control specification
Observer, the collision event that observation system system is passed through hypersurface and produced is made corresponding control decision and is referred to so as to controller
Order.Observer ξ is used for the consecutive variations of aircraft position in observation system and produces collision event, claimsIt is I types
Observer,It is Type-II observer.
Finally, discrete watch-dog of the design from conflict to conflict Resolution means.When the discrete observation vector of observer shows
When a certain unexpected state occurs, corresponding alarm is sent at once.The discrete watch-dog can be described as functionIts
Middle S is the space that observer observation vector is transformed into, and D is the space that all decision vector d are transformed into.
Obviously, above-described embodiment is only intended to clearly illustrate example of the present invention, and is not to of the invention
The restriction of implementation method.For those of ordinary skill in the field, it can also be made on the basis of the above description
The change or variation of its multi-form.There is no need and unable to be exhaustive to all of implementation method.And these belong to this hair
Obvious change that bright spirit is extended out or among changing still in protection scope of the present invention.
Claims (1)
1. a kind of air traffic control system for the early warning that conflicts, it is characterised in that:Including Airborne Terminal module, data communication
Module, monitoring data fusion module and control terminal module;Monitoring data fusion module is used to realize that air traffic control radar monitors number
Merged according to automatic dependent surveillance data, for control terminal module provides real-time flight path information;
The control terminal module includes following submodule:
Lothrus apterus 4D flight path generation modules before flight, according to flight plan and the forecast data of world area forecast system, set up
Airborne vehicle kinetic model, then sets up the pre- allotment theoretical model of flight path conflict according to flight collision Coupling point, generates airborne vehicle
Lothrus apterus 4D flight paths;
Flight middle or short term 4D flight path generation modules, according to the real-time flight path information that monitoring data fusion module is provided, using hidden horse
Er Kefu models, thus it is speculated that the airborne vehicle 4D tracks in following certain hour window;
Real-time flight conflict monitoring and alarm module, for setting up from the continuous dynamic of airborne vehicle to the observation of discrete conflict logic
Device, by the conflict situation that the continuous dynamic mapping of Air Traffic System is the expression of discrete observation value;When system is possible to violate empty
During middle traffic control rule, to the Hybrid dynamics behavior implementing monitoring of air traffic hybrid system, for controller provides timely
Warning information;The method that the air traffic control system for the early warning that conflicts carries out conflict early warning includes following several steps
Suddenly:
Step A, flight before Lothrus apterus 4D flight paths generation module according to flight plan and the forecast data of world area forecast system,
Airborne vehicle kinetic model is set up, and the pre- allotment theoretical model of flight path conflict is set up according to flight collision Coupling point, generate aviation
Device Lothrus apterus 4D flight paths;
Step B, monitoring data fusion module are merged air traffic control radar monitoring data with automatic dependent surveillance data, generation boat
The real-time flight path information of pocket is simultaneously supplied to control terminal module;Flight middle or short term 4D flight path generation modules in control terminal module
Speculate the airborne vehicle 4D tracks in following certain hour window according to the real-time flight path information of airborne vehicle and history flight path information;It is described according to
The specific reality of the airborne vehicle 4D tracks in following certain hour window is speculated according to the real-time flight path information of airborne vehicle and history flight path information
Apply process as follows:
Step B6, to airborne vehicle track data pre-process, according to acquired in the original discrete two-dimensional position sequence x=of airborne vehicle
[x1,x2,...,xn] and y=[y1,y2,...,yn], using first-order difference method it is carried out treatment obtain new airborne vehicle from
Dissipate position sequence △ x=[△ x1,△x2,...,△xn-1] and △ y=[△ y1,△y2,...,△yn-1], wherein △ xb=xb+1-
xb,△yb=yb+1-yb(b=1,2 ..., n-1);
Step B7, to airborne vehicle track data cluster, to airborne vehicle discrete two-dimensional position sequence △ x and △ y new after treatment, lead to
Setting cluster number M' is crossed, it is clustered respectively using K-means clustering algorithms;
Step B8, parameter training is carried out using HMM to the airborne vehicle track data after cluster, by will treatment
Airborne vehicle running orbit data △ x and △ y afterwards is considered as the aobvious observation of hidden Markov models, by setting hidden state number
N' and parameter update period ζ ', roll and obtain newest hidden Ma Erke according to T' nearest position detection value and use B-W algorithms
Husband's model parameter λ ';
Step B9, foundation HMM parameter, obtain hidden corresponding to current time observation using Viterbi algorithm
State q;
Step B10, by set prediction time domain h', the hidden state q based on airborne vehicle current time, obtain future time period airborne vehicle
Position prediction value O;
Step C, real-time flight conflict monitoring and alarm module are set up from the continuous dynamic of airborne vehicle to the sight of discrete conflict logic
Device is surveyed, by the conflict situation that the continuous dynamic mapping of Air Traffic System is the expression of discrete observation value;When system is possible to violate
During air traffic control rules, to the Hybrid dynamics behavior implementing monitoring of air traffic hybrid system, for controller provides in time
Warning information;
The airborne vehicle Lothrus apterus 4D flight paths of the step A are generated in accordance with the following methods:
Step A1, carry out aircraft states transfer modeling, according to the flying height section of airborne vehicle in flight plan, set up single
The Petri net model that airborne vehicle is shifted in different legs:E=(g, G, Pre, Post, m) are airborne vehicle stage metastasis model, its
Middle g represents flight leg, and G represents the transfer point of flight status parameter in vertical section, and Pre and Post represents leg and boat respectively
Waypoint it is front and rear to annexation,Represent the mission phase residing for airborne vehicle;
Step A2, to set up the full flight profile, mission profile hybrid model of airborne vehicle as follows,
vH=κ (vCAS,Mach,hp,tLOC),
vGS=μ (vCAS,Mach,hp,tLOC,vWS, α),
Wherein vCASIt is calibrated airspeed, Mach is Mach number, hpIt is pressure altitude, α is the angle of wind direction forecast and air route, vWSFor
Wind speed forecasting value, tLOCIt is temperature forecast value, vHIt is altitude rate, vGSIt is ground velocity;
Step A3, using hybrid system emulation by the way of speculate solution flight path:It is sharp using by the method for time subdivision
Voyage with the characteristic Recursive Solution any time airborne vehicle of state consecutive variations in a certain mission phase away from reference pointAnd heightWherein J0It is initial time airborne vehicle away from reference point
Voyage, △ τ are the numerical value of time window, and J (τ) is voyage of the τ moment airborne vehicle away from reference point, h0It is initial time airborne vehicle away from ginseng
The height of examination point, h (τ) is height of the τ moment airborne vehicle away from reference point, thereby it is assumed that the 4D flight paths for obtaining single airborne vehicle;
Step A4, to many airborne vehicle coupling models implement Lothrus apterus allotment:Reach the time in crosspoint in advance according to two airborne vehicles, according to
Air traffic control principle, the airborne vehicle 4D flight paths to being unsatisfactory for space requirement near crosspoint carry out quadratic programming, obtain nothing
Conflict 4D flight paths;
The specific implementation process of the step C is as follows:
The conflict hypersurface collection of functions of step C1, construction based on regulation rule:Hypersurface collection of functions is set up to be used to reflect system
Contention situation, wherein, the continuous function related to single airborne vehicle in conflict hypersurfaceIt is I type hypersurfaces, with
The related continuous function of two frame airborne vehiclesIt is Type-II hypersurface;
Step C2, set up by airborne vehicle continuous state to discrete conflict situation observer:Need to be set up according to control specification and see
Survey device, the collision event that observation system system is passed through hypersurface and produced, so that controller makes corresponding control decision instruction;
Observer ξ is used for the consecutive variations of aircraft position in observation system and produces collision event, claimsFor I types are seen
Survey device,It is Type-II observer;
The discrete watch-dog of step C3, design from conflict to conflict Resolution means, the discrete watch-dog can be described as functionWherein S is the space that observer observation vector is transformed into, and D is the space that all decision vector d are transformed into;Work as observer
Discrete observation vector when showing that a certain unexpected state occurs, corresponding alarm is sent at once.
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Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110853412A (en) * | 2019-11-12 | 2020-02-28 | 上海眼控科技股份有限公司 | Method and device for identifying abnormal track point |
CN112258898A (en) * | 2020-10-16 | 2021-01-22 | 中国民用航空华东地区空中交通管理局 | Air traffic control method, system, electronic device and storage medium based on digital twin technology |
CN115482688A (en) * | 2022-08-30 | 2022-12-16 | 南京航空航天大学 | Aircraft traffic conflict resolution method and system based on multiple cluster |
Families Citing this family (13)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN105489068B (en) * | 2015-12-14 | 2018-04-13 | 青岛民航空管实业发展有限公司 | A kind of control order error correction method |
CN106205219B (en) * | 2016-08-31 | 2019-03-05 | 北京招通致晟科技有限公司 | Aircraft monitoring method and device based on fusion of multiple radar information |
US10332409B2 (en) * | 2016-09-27 | 2019-06-25 | Rockwell Collins, Inc. | Midair collision threat detection and assessment using visual information |
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CN110689763A (en) * | 2019-09-20 | 2020-01-14 | 中国飞行试验研究院 | Airborne auxiliary navigation method, device and system based on wireless reception |
CN112330982B (en) * | 2020-10-15 | 2024-06-21 | 中国民用航空中南地区空中交通管理局 | Mid-term conflict early warning method, device and storage medium applied to terminal area |
CN112596538B (en) * | 2020-11-26 | 2023-06-16 | 中国电子科技集团公司第十五研究所 | Large unmanned aerial vehicle conflict detection and avoidance decision device and use method |
CN114440891B (en) * | 2022-01-25 | 2023-08-25 | 深圳技术大学 | Four-dimensional flight path planning method, system and equipment for air traffic management |
Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20070210953A1 (en) * | 2006-03-13 | 2007-09-13 | Abraham Michael R | Aircraft collision sense and avoidance system and method |
CN102509475A (en) * | 2011-10-26 | 2012-06-20 | 南京航空航天大学 | Air traffic control system and method for four-dimensional (4D)-trajectory-based operation |
CN103050024A (en) * | 2013-01-09 | 2013-04-17 | 成都民航空管科技发展有限公司 | System and method for rapid real-time detection of air traffic service safety |
CN103226899A (en) * | 2013-03-19 | 2013-07-31 | 北京工业大学 | Method for dynamically dividing sector based on airspace traffic characteristics |
Family Cites Families (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5961568A (en) * | 1997-07-01 | 1999-10-05 | Farahat; Ayman | Cooperative resolution of air traffic conflicts |
CN103336863B (en) * | 2013-06-24 | 2016-06-01 | 北京航空航天大学 | The flight intent recognition methods of flight path observed data of flying based on radar |
-
2015
- 2015-01-07 CN CN201710189243.8A patent/CN106846924A/en active Pending
- 2015-01-07 CN CN201710189244.2A patent/CN106875757A/en active Pending
- 2015-01-07 CN CN201710189245.7A patent/CN106846925A/en active Pending
- 2015-01-07 CN CN201510007997.8A patent/CN104485025B/en active Active
Patent Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20070210953A1 (en) * | 2006-03-13 | 2007-09-13 | Abraham Michael R | Aircraft collision sense and avoidance system and method |
CN102509475A (en) * | 2011-10-26 | 2012-06-20 | 南京航空航天大学 | Air traffic control system and method for four-dimensional (4D)-trajectory-based operation |
CN103050024A (en) * | 2013-01-09 | 2013-04-17 | 成都民航空管科技发展有限公司 | System and method for rapid real-time detection of air traffic service safety |
CN103226899A (en) * | 2013-03-19 | 2013-07-31 | 北京工业大学 | Method for dynamically dividing sector based on airspace traffic characteristics |
Non-Patent Citations (1)
Title |
---|
潘奇明 等: ""基于隐马尔可夫模型的运动目标轨迹识别"", 《计算机应用研究》 * |
Cited By (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110853412A (en) * | 2019-11-12 | 2020-02-28 | 上海眼控科技股份有限公司 | Method and device for identifying abnormal track point |
CN110853412B (en) * | 2019-11-12 | 2021-06-01 | 上海眼控科技股份有限公司 | Method and device for identifying abnormal track point |
CN112258898A (en) * | 2020-10-16 | 2021-01-22 | 中国民用航空华东地区空中交通管理局 | Air traffic control method, system, electronic device and storage medium based on digital twin technology |
CN115482688A (en) * | 2022-08-30 | 2022-12-16 | 南京航空航天大学 | Aircraft traffic conflict resolution method and system based on multiple cluster |
CN115482688B (en) * | 2022-08-30 | 2024-05-03 | 南京航空航天大学 | Aircraft traffic conflict resolution method and system based on multiple clusters |
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