CN104504941A - Flight conflict resolution method of air traffic control system - Google Patents

Abstract

The invention relates to a flight conflict resolution method of an air traffic control system, wherein the air traffic control system comprises a data communication module, an airborne terminal module and a control terminal module; the control terminal module comprises 2 submodules of real-time flight conflict monitoring and warning, and flight conflict resolution 4D track optimization; the flight conflict resolution method of the system directly obtains the 4D track of each aircraft in the future time period through the air traffic control center, realizes the analysis of the potential traffic conflict of the airspace traffic condition, and provides an optimal resolution scheme by adopting a model prediction control theory method. The invention can effectively prevent flight conflict and improve the safety of air traffic.

Description

A kind of Solving Flight Conflicts method of air traffic control system

Technical field

The present invention relates to a kind of air traffic control system and method, particularly relate to a kind of Solving Flight Conflicts method of the air traffic control system based on the operation of 4D flight path.

Background technology

Along with fast-developing the becoming increasingly conspicuous with spatial domain resource-constrained contradiction of World Airways forwarding business, the complicated spatial domain that traffic flow is aloft intensive, still the air traffic control mode adopting flight planning to allocate in conjunction with interval demonstrates its lag gradually, be in particular in: (1) flight planning is not for aircraft configures accurate blank pipe interval, easily cause traffic flow tactics manage in crowded, reduce spatial domain security; (2) air traffic control automation system centered by flight planning, to the reckoning of flight profile, mission profile and Trajectory Prediction low precision, causes conflict dissolution ability; (3) job of air traffic control still lays particular emphasis on the personal distance kept between single aircraft, is difficult to rise to and carries out strategic Management to traffic flow.

4D flight path is with room and time form, to each point locus (longitude, latitude and height) in a certain aircraft flight path and the accurate description of time, operation based on flight path refers to that use on the way point of 4D flight path " controls time of arrival ", namely controls " time window " of aircraft by specific way point.In high density spatial domain using the operation (Trajectory based Operation) based on 4D flight path as one of basic operating mechanism, it is following a kind of effective means spatial domain under large discharge, high density, closely-spaced condition being implemented to management, the uncertainty of aircraft flight path can be reduced significantly, improve security and the utilization factor of spatial domain and Airport Resources.

The air traffic method of operation run based on flight path needs calculate single aircraft flight path and optimize on strategic level, implements collaborative and adjustment to the traffic flow that many aircrafts are formed; By revising the flight path of indivedual aircraft in traffic flow to solve congestion problems on pre-tactical level, and ensure the operational efficiency of all aircrafts in this traffic flow; And prediction conflicts and optimization solution off-square case on tactical level, change aircraft headway management factors such as into considering aircraft performance, regulation rule and environment in interior variable Separation control mode from fixing manual type, the operation therefore towards 4D flight path proposes new requirement to air traffic control.

Summary of the invention

The technical problem to be solved in the present invention is to overcome the deficiencies in the prior art, provides a kind of Solving Flight Conflicts method of the air traffic control system based on the operation of 4D flight path, effectively can prevent flight collision, improve the security of air traffic.

The technical scheme realizing the object of the invention is to provide a kind of Solving Flight Conflicts method of air traffic control system, and described air traffic control system comprises Airborne Terminal module, data communication module and control terminal module;

Described control terminal module comprises following submodule:

The continuous dynamic mapping of Air Traffic System, for setting up the dynamic continuously observer to discrete conflict logic from aircraft, is the conflict situation that discrete observation value is expressed by real-time flight conflict monitoring and alarm module; When system likely violates air traffic control rules, to the Hybrid dynamics behavior implementing monitoring of air traffic hybrid system, for controller provides warning information timely;

Solving Flight Conflicts 4D track optimization module, under the system of guarantee meets aircraft performance and regulation rule constraint condition, by selecting different to free objective function, adopting Model Predictive Control Theory method, calculating aircraft conflict Resolution 4D flight path; And send to Airborne Terminal module to perform aircraft conflict Resolution 4D flight path by data communication module;

The Solving Flight Conflicts method of described air traffic control system comprises following several step:

Steps A, directly obtain its aircraft 4D track of each aircraft in future time period inferred in each sampling instant by air traffic controllers, air traffic controllers infers the 4D track of aircraft in future time period by the fusion of air traffic control radar monitoring data and automatic dependent surveillance data;

Step B, real-time flight conflict monitoring and alarm module set up the dynamic continuously observer to discrete conflict logic from aircraft, are the conflict situation that discrete observation value is expressed by the continuous dynamic mapping of Air Traffic System; When system likely violates air traffic control rules, to the Hybrid dynamics behavior implementing monitoring of air traffic hybrid system, for controller provides warning information timely;

Step C, Solving Flight Conflicts 4D track optimization module, under the system of guarantee meets aircraft performance and regulation rule constraint condition, by selecting different to free objective function, adopting Model Predictive Control Theory method, calculating aircraft conflict Resolution 4D flight path; And send to Airborne Terminal module to perform aircraft conflict Resolution 4D flight path by data communication module;

Step D, Airborne Terminal module receive and perform the 4D track data of control terminal module issue.

Further, the specific implementation process of described step C is as follows:

Step C1, to Solving Flight Conflicts process model building: conflict Resolution flight path is considered as continuous print three sections of smooth curves, given starting point and terminal of freeing flight path, according to flight path restrictive condition, set up comprise acceleration, climb or rate of descent, turning rate the optimum conflict Resolution model of multivariate;

Step C2, to conflict Resolution variable bound modeling under different flying condition: the variable bound that wherein t need implement conflict Resolution aircraft k can be described as: a _k(t)≤a _m, ω _k(t)≤ω _m, γ _k(t)≤γ _m, a _m, ω _m, γ _mbe respectively maximum acceleration, turning rate and climb or rate of descent;

Step C3, the termination reference point locations P of setting aircraft collision avoidance planning, collision avoidance planning control time domain Θ, trajectory predictions time domain Υ;

Step C4, in each sampling instant, the running status current based on aircraft and historical position observation sequence, obtain the numerical value of spatial domain wind field variable;

Step C5, be set in given optimizing index function prerequisite under, based on cooperative collision avoidance trajectory planning thought, by giving different weights and incorporate real-time wind field variable filtering numerical value to each aircraft, obtain the collision avoidance track of each aircraft and collision avoidance control strategy and its first Optimal Control Strategy only implemented by each aircraft in Rolling Planning interval;

Step C6, in next sampling instant, repeat step C4 to C5 free terminal until each aircraft all arrives it.

Further, in step C3: stop the next way point that reference point locations P is aircraft, collision avoidance planning control time domain Θ is 300 seconds, and trajectory predictions time domain Υ is 300 seconds;

The detailed process of step C4 is as follows:

C4.1) stop position setting aircraft is track reference coordinate initial point;

C4.2) when aircraft is in straight running condition and at the uniform velocity turning running status, build spatial domain wind field linear filtering model x (t+ Δ t)=F (t) x (t)+w (t) and z (t)=H (t) x (t)+v (t) and obtain wind field variable value, wherein Δ t represents sampling interval, x (t) represents the state vector of t, z (t) represents the observation vector of t, F (t) and H (t) represents state-transition matrix respectively and exports calculation matrix, w (t) and v (t) represents system noise vector sum measurement noises vector respectively, when aircraft is in speed change turning running status, build spatial domain wind field nonlinear filtering wave pattern

X (t+ Δ t)=Ψ (t, x (t), u (t))+w (t), z (t)=Ω (t, x (t))+v (t) and u (t)=[ω a (t), γ a (t)] ^t,

Wherein Ψ () and Ω () represents state-transition matrix respectively and exports calculation matrix, ω _a(t) and γ _at () represents turning rate and rate of acceleration respectively;

C4.3) numerical value of wind field variable is obtained according to constructed Filtering Model;

The detailed process of step C5 is as follows: order

$d_{\mathrm{it}}^2={\left|\right|P_i\left(t\right)-{P_i}^f\left|\right|}_2^2={(x_{\mathrm{it}}-x_i^f)}^2+{(y_{\mathrm{it}}-y_i^f)}^2,$

Wherein represent the current position P of t aircraft i _i(t) and next way point P _i ^fbetween distance square, P _i(t)=(x _it, y _it), so the priority index of t aircraft i can be set as:

$L_{\mathrm{it}}=100\frac{d_{\mathrm{it}}^{-2}}{\underset{i=1}{\overset{n_t}{\mathrm{\Σ}}}{d}_{\mathrm{it}}^{-2}},$

Wherein n _irepresent the aircraft number that there is conflict in t spatial domain, from the implication of priority index, aircraft is nearer apart from its terminal, and its priority is higher;

Setting optimizing index

$\begin{array}{c}{J}^{\′}({u_1}^{\left(t\right)},{u_1}^{(t+\mathrm{\Δt})},...,{u_1}^{(t+\mathrm{p\Δt})},...,u_{n_t}^{\left(t\right)},u_{n_t}^{(t+\mathrm{\Δt})},...,u_{n_t}^{(t+\mathrm{p\Δt})})=\underset{s=1}{\overset{p}{\mathrm{\Σ}}}\underset{i=1}{\overset{n_t}{\mathrm{\Σ}}}{L}_{\mathrm{it}}{\left|\right|P_i(t+\mathrm{s\Δt})-{P_i}^f\left|\right|}_2^2\\ =\underset{s=1}{\overset{p}{\mathrm{\Σ}}}\underset{i=1}{\overset{n_t}{\mathrm{\Σ}}}{(P_i(t+\mathrm{s\Δt})-{P_i}^f)}^T{Q}_{\mathrm{it}}(P_i(t+\mathrm{s\Δt})-{P_i}^f)\end{array}$

, wherein i ∈ I (t) represent aircraft code and I (t)=1,2 ..., n _t, P _i(t+s Δ t) represents the position vector of aircraft at moment (t+s Δ t), P _i ^frepresent next way point of aircraft i, u _irepresent the optimal control sequence of aircraft i to be optimized, Q _itfor positive definite diagonal matrix, its diagonal element is the priority index L of aircraft i in t _it, and $Q_{\mathrm{it}}=\left[\begin{array}{cc}{L}_{\mathrm{it}}& 0\\ 0& L_{\mathrm{it}}\end{array}\right].$

Further, the specific implementation process of described step B is as follows:

Step B1, construct conflict hypersurface collection of functions based on regulation rule: set up hypersurface collection of functions in order to reflect the contention situation of system, wherein, continuous function relevant to single aircraft in conflict hypersurface be I type hypersurface, the continuous function relevant to two frame aircrafts it is II type hypersurface;

Step B2, to set up by aircraft continuous state to the observer of discrete conflict situation: need to set up observer according to control specification, the collision event that recording geometry system is passed through hypersurface and produced, so that corresponding control decision instruction made by controller; Observer ξ is used for the consecutive variations of aircraft position in recording geometry and produces collision event, claims be I type observer, it is II type observer;

Step B3, design from conflict to the discrete watch-dog of conflict Resolution means, this discrete watch-dog can be described as function wherein S is the space of observer observation vector generate, and D is the space of all decision vector d generates; When the discrete observation vector of observer shows that a certain unexpected state occurs, send corresponding alarm at once.

The present invention has positive effect: the Solving Flight Conflicts method of (1) a kind of air traffic control system of the present invention is in aircraft conflict Resolution process, incorporate the impact of high-altitude wind field, the rolling adopted is freed trajectory planning scheme and can be adjusted in time according to the change of wind field in high-altitude and free track, improves the robustness of aircraft conflict Resolution.

(2) the Solving Flight Conflicts method of a kind of air traffic control system of the present invention is that aircraft configures accurate blank pipe interval, and the strict aircraft that controls, by the time window of way point, reduces traffic flow randomness, improves spatial domain security.

(3) the Solving Flight Conflicts method of a kind of air traffic control system of the present invention is no longer confined to keep the personal distance between single aircraft, but from macroscopically implementing effectively to control to the traffic flow in spatial domain, control work can more transfer to departure time of aircraft, sequence of marching into the arena, inclement weather change the aspects such as boat.

(4) the Solving Flight Conflicts method of a kind of air traffic control system of the present invention frees based on the aircraft optimum of different performance index the economy that flight path can improve aircraft operation significantly, and the utilization factor in spatial domain.

Accompanying drawing explanation

Fig. 1 is that 4D route optimization method schematic flow sheet freed by aircraft.

Embodiment

(embodiment 1)

The air traffic control system run based on 4D flight path of the present embodiment, comprises Airborne Terminal module 101, data communication module 102 and control terminal module 104.Below the embodiment of each several part is described in detail respectively.

1. Airborne Terminal module

Airborne Terminal module 101 is that pilot obtains ground control order, reference 4D flight path, and the interface of input flight intent, still gathers the interface of current aerospace device position data simultaneously.

Its specific embodiments is as follows:

Airborne Terminal module 101 receives following information input: aircraft position vector, velocity vector that (1) ADSB information acquisition unit 201 is gathered by Airborne GPS, and the catchword of this aircraft, pass to airborne data communication module 102 by information and data after coding; (2) aircraft driver needs the flight intent inconsistent with ground control order, and by man-machine inputting interface, and the form that the ground controller of agreement can identify passes to airborne data communication module 102 by information and data.Airborne Terminal module 101 realizes following information output in addition: (1), by terminal display, receives and show the air traffic control instruction that pilot can identify; (2) the Lothrus apterus 4D flight path with the explicitly front generation of facial canal terminal flight is received, and when the optimum of calculating after ground line end-probing to conflict frees 4D flight path.

2. data communication module

Data communication module 102 can realize vacant lot bidirectional data communication, realizes downlink transfer and the ground control command unit 203 of airborne real time position data and flight intent data cell 202, and the uplink of reference 4D flight path unit 204.

Its specific embodiments is as follows:

Downlink data communication: Airborne Terminal 101 passes through airborne secondary radar answering machine by aircraft identification mark and 4D positional information, and other additional datas, if the information transmission such as flight intent, flying speed, meteorology are to ground secondary radar (SSR), secondary radar is resolved data message after receiving, and be transferred to central data processing components 301 and decode, be transferred to control terminal 104 by instruction track data interface; Upstream data communication: ground control terminal 104 by instruction track data interface, after central data processing components 301 is encoded, the inquisitor of ground secondary radar just ground control order or be presented at Airborne Terminal 101 with reference to 4D flight path information transmission.

3. control terminal module

Control terminal module 104 comprises real-time flight conflict monitoring and alarm, these 2 submodules of Solving Flight Conflicts 4D track optimization.

(2) real-time flight conflict monitoring and alarm

First directly obtain its aircraft 4D track of each aircraft in future time period inferred in each sampling instant by air traffic controllers, air traffic controllers infers the 4D track of aircraft in future time period by the fusion of air traffic control radar monitoring data and automatic dependent surveillance data.

When the state violating safe condition collection likely appears in system, implement condition monitoring by controller, effective measure of control is implemented to aircraft, avoid the generation of flight collision.

Its specific implementation process is as follows:

First, according to the aircraft 4D track of each aircraft obtained from air traffic controllers in future time period, the conflict hypersurface collection of functions based on regulation rule is constructed.The violation of air traffic control constraint can be considered as controlled device (the multi rack aircraft of the control zone flight) event that construction system passes through hypersurface and produces, and sets up hypersurface collection of functions in order to reflect the contention situation of system.Wherein, relevant to single aircraft in conflict hypersurface continuous function be I type hypersurface, and by the continuous function relevant to two frame aircrafts it is II type hypersurface.

Then, set up by aircraft continuous state to the observer of discrete conflict situation.Need to set up observer according to control specification, the collision event that recording geometry system is passed through hypersurface and produced, so that corresponding control decision instruction made by controller.Observer ξ is used for the consecutive variations of aircraft position in recording geometry and produces collision event, claims be I type observer, it is II type observer.

Finally, the discrete watch-dog from conflict to conflict Resolution means is designed.When the discrete observation vector of observer shows that a certain unexpected state occurs, send corresponding alarm at once.This discrete watch-dog can be described as function wherein S is the space of observer observation vector generate, and D is the space of all decision vector d generates.

(2) Solving Flight Conflicts 4D track optimization

Under ensureing to make system meet the condition controlling specification, by selecting different to free objective function, adopt theory of optimal control method, the control inputs that controller is provided can reach optimum.

As shown in Figure 1, its specific implementation process is as follows:

Step C1, to Solving Flight Conflicts process model building: conflict Resolution flight path is considered as continuous print three sections of smooth curves, given starting point and terminal of freeing flight path, according to flight path restrictive condition, sets up and comprise acceleration a _i(t), climb or rate of descent γ _i(t), turning rate ω _ithe optimum conflict Resolution model of multivariate of (t).

Step C2, to conflict Resolution variable bound modeling under different flying condition: the variable bound that wherein t need implement conflict Resolution aircraft k can be described as: a _k(t)≤a _m, ω _k(t)≤ω _m, γ _k(t)≤γ _m, a _m, ω _m, γ _mbe respectively maximum acceleration, turning rate and climb or rate of descent.

Step C3, the termination reference point locations P of setting aircraft collision avoidance planning, collision avoidance planning control time domain Θ, trajectory predictions time domain Υ, stop the next way point that reference point locations P is aircraft, collision avoidance planning control time domain Θ is 300 seconds, and trajectory predictions time domain Υ is 300 seconds.

Step C4, at each sampling instant t, the running status current based on aircraft and historical position observation sequence, obtain the numerical value of spatial domain wind field variable, its detailed process is as follows:

C4.1) stop position setting aircraft is track reference coordinate initial point;

C4.2) when aircraft is in straight running condition and at the uniform velocity turning running status, build spatial domain wind field linear filtering model x (t+ Δ t)=F (t) x (t)+w (t) and z (t)=H (t) x (t)+v (t) and obtain wind field variable value, wherein Δ t represents sampling interval, x (t) represents the state vector of t, z (t) represents the observation vector of t, F (t) and H (t) represents state-transition matrix respectively and exports calculation matrix, w (t) and v (t) represents system noise vector sum measurement noises vector respectively, when aircraft is in speed change turning running status, build spatial domain wind field nonlinear filtering wave pattern

X (t+ Δ t)=Ψ (t, x (t), u (t))+w (t), z (t)=Ω (t, x (t))+v (t) and u (t)=[ω a (t), γ a (t)] ^t, wherein Ψ () and Ω () represents state-transition matrix respectively and exports calculation matrix, ω _a(t) and γ _at () represents turning rate and rate of acceleration respectively;

C4.3) numerical value of wind field variable is obtained according to constructed Filtering Model.

Step C5, be set in given optimizing index function prerequisite under, based on cooperative collision avoidance trajectory planning thought, give different weights by giving each aircraft and incorporate real-time wind field variable filtering numerical value, obtain the collision avoidance track of each aircraft and collision avoidance control strategy and its first Optimal Control Strategy only implemented by each aircraft in Rolling Planning interval, detailed process is as follows: order $d_{\mathrm{it}}^2={\left|\right|P_i\left(t\right)-{P_i}^f\left|\right|}_2^2={(x_{\mathrm{it}}-x_i^f)}^2+{(y_{\mathrm{it}}-y_i^f)}^2,$

Wherein represent the current position P of t aircraft i _i(t) and next way point P _i ^fbetween distance square, P _i(t)=(x _it, y _it), so the priority index of t aircraft i can be set as:

$L_{\mathrm{it}}=100\frac{d_{\mathrm{it}}^{-2}}{\underset{i=1}{\overset{n_t}{\mathrm{\Σ}}}{d}_{\mathrm{it}}^{-2}},$

Wherein n _trepresent the aircraft number that there is conflict in t spatial domain, from the implication of priority index, aircraft is nearer apart from its next way point, and its priority is higher.

Setting optimizing index

$\begin{array}{c}{J}^{\′}({u_1}^{\left(t\right)},{u_1}^{(t+\mathrm{\Δt})},...,{u_1}^{(t+\mathrm{p\Δt})},...,u_{n_t}^{\left(t\right)},u_{n_t}^{(t+\mathrm{\Δt})},...,u_{n_t}^{(t+\mathrm{p\Δt})})=\underset{s=1}{\overset{p}{\mathrm{\Σ}}}\underset{i=1}{\overset{n_t}{\mathrm{\Σ}}}{L}_{\mathrm{it}}{\left|\right|P_i(t+\mathrm{s\Δt})-{P_i}^f\left|\right|}_2^2\\ =\underset{s=1}{\overset{p}{\mathrm{\Σ}}}\underset{i=1}{\overset{n_t}{\mathrm{\Σ}}}{(P_i(t+\mathrm{s\Δt})-{P_i}^f)}^T{Q}_{\mathrm{it}}(P_i(t+\mathrm{s\Δt})-{P_i}^f)\end{array}$

, wherein i ∈ I (t) represent aircraft code and I (t)=1,2 ..., n _t, P _i(t+s Δ t) represents the position vector of aircraft at moment (t+s Δ t), P _i ^frepresent next way point of aircraft i, u _irepresent the optimal control sequence of aircraft i to be optimized, Q _itfor positive definite diagonal matrix, its diagonal element is the priority index L of aircraft i in t _it, and $Q_{\mathrm{it}}=\left[\begin{array}{cc}{L}_{\mathrm{it}}& 0\\ 0& L_{\mathrm{it}}\end{array}\right].$

Step C6, in next sampling instant, repeat step C4 to C5 free terminal until each aircraft all arrives it.

Airborne Terminal module receives and performs the 4D track data of control terminal module issue.

Obviously, above-described embodiment is only for example of the present invention is clearly described, and is not the restriction to embodiments of the present invention.For those of ordinary skill in the field, can also make other changes in different forms on the basis of the above description.Here exhaustive without the need to also giving all embodiments.And these belong to spirit institute's apparent change of extending out of the present invention or change and are still among protection scope of the present invention.

Claims (4)

1. a Solving Flight Conflicts method for air traffic control system, described air traffic control system comprises Airborne Terminal module, data communication module and control terminal module; It is characterized in that:

Described control terminal module comprises following submodule:

The continuous dynamic mapping of Air Traffic System, for setting up the dynamic continuously observer to discrete conflict logic from aircraft, is the conflict situation that discrete observation value is expressed by real-time flight conflict monitoring and alarm module; When system likely violates air traffic control rules, to the Hybrid dynamics behavior implementing monitoring of air traffic hybrid system, for controller provides warning information timely;

Solving Flight Conflicts 4D track optimization module, under the system of guarantee meets aircraft performance and regulation rule constraint condition, by selecting different to free objective function, adopting Model Predictive Control Theory method, calculating aircraft conflict Resolution 4D flight path; And send to Airborne Terminal module to perform aircraft conflict Resolution 4D flight path by data communication module;

The Solving Flight Conflicts method of described air traffic control system comprises following several step:

Steps A, directly to be obtained the aircraft 4D track of each aircraft in future time period that air traffic controllers infers in each sampling instant by air traffic controllers;

Step B, real-time flight conflict monitoring and alarm module set up the dynamic continuously observer to discrete conflict logic from aircraft according to the aircraft 4D track of each aircraft in future time period that steps A obtains, and are the conflict situation that discrete observation value is expressed by the continuous dynamic mapping of Air Traffic System; When system likely violates air traffic control rules, to the Hybrid dynamics behavior implementing monitoring of air traffic hybrid system, for controller provides warning information timely;

Step C, Solving Flight Conflicts 4D track optimization module, under the system of guarantee meets aircraft performance and regulation rule constraint condition, by selecting different to free objective function, adopting Model Predictive Control Theory method, calculating aircraft conflict Resolution 4D flight path; And send to Airborne Terminal module to perform aircraft conflict Resolution 4D flight path by data communication module; Its specific implementation process is as follows:

Step C1, to Solving Flight Conflicts process model building: conflict Resolution flight path is considered as continuous print three sections of smooth curves, given starting point and terminal of freeing flight path, according to flight path restrictive condition, set up comprise acceleration, climb or rate of descent, turning rate the optimum conflict Resolution model of multivariate;

Step C2, to conflict Resolution variable bound modeling under different flying condition: the variable bound that wherein t need implement conflict Resolution aircraft k can be described as: a _k(t)≤a _m, ω _k(t)≤ω _m, γ _k(t)≤γ _m, a _m, ω _m, γ _mbe respectively maximum acceleration, turning rate and climb or rate of descent;

Step C3, the termination reference point locations P of setting aircraft collision avoidance planning, collision avoidance planning control time domain Θ, trajectory predictions time domain γ;

Step C4, at each sampling instant t, the running status current based on aircraft and historical position observation sequence, obtain the numerical value of spatial domain wind field variable;

Step C5, be set in given optimizing index function prerequisite under, based on cooperative collision avoidance trajectory planning thought, by giving different weights and incorporate real-time wind field variable filtering numerical value to each aircraft, obtain the collision avoidance track of each aircraft and collision avoidance control strategy and its first Optimal Control Strategy only implemented by each aircraft in Rolling Planning interval;

Step C6, in next sampling instant, repeat step C4 to C5 free terminal until each aircraft all arrives it;

Step D, Airborne Terminal module receive and perform the 4D track data of control terminal module issue.

2. the Solving Flight Conflicts method of a kind of air traffic control system according to claim 1, it is characterized in that: in step C3: stop the next way point that reference point locations P is aircraft, collision avoidance planning control time domain Θ is 300 seconds, and trajectory predictions time domain γ is 300 seconds;

The detailed process of step C4 is as follows:

C4.1) stop position setting aircraft is track reference coordinate initial point;

C4.2) when aircraft is in straight running condition and at the uniform velocity turning running status, build spatial domain wind field linear filtering model x (t+ Δ t)=F (t) x (t)+w (t) and z (t)=H (t) x (t)+v (t) and obtain wind field variable value, wherein Δ t represents sampling interval, x (t) represents the state vector of t, z (t) represents the observation vector of t, F (t) and H (t) represents state-transition matrix respectively and exports calculation matrix, w (t) and v (t) represents system noise vector sum measurement noises vector respectively, when aircraft is in speed change turning running status, build spatial domain wind field nonlinear filtering wave pattern

X (t+ Δ t)=Ψ (t, x (t), u (t))+w (t), z (t)=Ω (t, x (t))+v (t) and u (t)=[ω _a(t), γ _a(t)] ^t,

Wherein Ψ () and Ω () represents state-transition matrix respectively and exports calculation matrix, ω _a(t) and γ _at () represents turning rate and rate of acceleration respectively;

C4.3) numerical value of wind field variable is obtained according to constructed Filtering Model.

3. the Solving Flight Conflicts method of a kind of air traffic control system according to claim 1 and 2, is characterized in that: the detailed process of step C5 is as follows: order

$d_{\mathrm{it}}^2={\left|\right|P_i\left(t\right)-P_i^f\left|\right|}_2^2={(x_{\mathrm{it}}-x_i^f)}^2+{(y_{\mathrm{it}}-y_i^f)}^2,$

Wherein represent the current position P of t aircraft i _i(t) and next way point between distance square, P _i(t)=(x _it, y _it), so the priority index of t aircraft i can be set as:

$L_{\mathrm{it}}=100\frac{d_{\mathrm{it}}^{-2}}{\underset{i=1}{\overset{n_t}{\mathrm{\Σ}}}{d}_{\mathrm{it}}^{-2}},$

Wherein n _trepresent the aircraft number that there is conflict in t spatial domain, from the implication of priority index, aircraft is nearer apart from its next way point, and its priority is higher;

Setting optimizing index

$\begin{array}{c}{J}^{\′(u_1^{\left(t\right)},u_1^{(t+\mathrm{\Δt})},...,u_1^{(t+\mathrm{p\Δt})},...,u_{n_t}^{\left(t\right)},u_{n_t}^{(t+\mathrm{\Δt})},u_{n_t}^{(t+\mathrm{p\Δt})})=\underset{s=1}{\overset{p}{\mathrm{\Σ}}}\underset{i=1}{\overset{n_t}{\mathrm{\Σ}}}{L}_{\mathrm{it}}{\left|\right|P_i(t+\mathrm{s\Δt})-P_i^f\left|\right|}_2^2}\\ =\underset{s=1}{\overset{p}{\mathrm{\Σ}}}\underset{i=1}{\overset{n_t}{\mathrm{\Σ}}}{(P_i(t+\mathrm{s\Δt})-P_i^f)}^T{Q}_{\mathrm{it}}(P_i(t+\mathrm{s\Δt})-P_i^f)\end{array}$ , wherein i ∈ I (t) represent aircraft code and I (t)=1,2 ..., n _t, P _i(t+s Δ t) represents the position vector of aircraft at moment (t+s Δ t), represent next way point of aircraft i, u _irepresent the optimal control sequence of aircraft i to be optimized, Q _itfor positive definite diagonal matrix, its diagonal element is the priority index L of aircraft i in t _it, and $Q_{\mathrm{it}}=\left[\begin{array}{cc}{L}_{\mathrm{it}}& 0\\ 0& L_{\mathrm{it}}\end{array}\right].$

4. according to the Solving Flight Conflicts method of a kind of air traffic control system one of claims 1 to 3 Suo Shu, it is characterized in that: the specific implementation process of described step B is as follows:

Step B1, construct conflict hypersurface collection of functions based on regulation rule: set up hypersurface collection of functions in order to reflect the contention situation of system, wherein, continuous function relevant to single aircraft in conflict hypersurface be I type hypersurface, the continuous function relevant to two frame aircrafts it is II type hypersurface;

Step B2, to set up by aircraft continuous state to the observer of discrete conflict situation: need to set up observer according to control specification, the collision event that recording geometry system is passed through hypersurface and produced, so that corresponding control decision instruction made by controller; Observer ξ is used for the consecutive variations of aircraft position in recording geometry and produces collision event, claims be I type observer, it is II type observer;

Step B3, design from conflict to the discrete watch-dog of conflict Resolution means, this discrete watch-dog can be described as function wherein S is the space of observer observation vector generate, and D is the space of all decision vector d generates; When the discrete observation vector of observer shows that a certain unexpected state occurs, send corresponding alarm at once.