CN105469139A - Embedded control-based unmanned aerial vehicle air real-time cooperative guidance method - Google Patents

Abstract

The invention relates to an embedded control-based unmanned aerial vehicle air real-time cooperative guidance method, which belongs to the field of unmanned aerial vehicle guidance. The method comprises steps: A, an objective function and constraint conditions are made; B, the our unmanned aerial vehicle guidance priority and the enemy threat value are calculated; C, a particle swarm is initialized; D, the guidance right transfer price is calculated; E, the best fitness value of a single particle is calculated; F, the particle swarm is updated; G, the best fitness value of the overall particles is calculated; H, whether to be early mature is judged, if not, a step I is carried out, and if yes, the step F is carried out; and I, whether to meet a termination condition is judged, if not, the step F is carried out, and if yes, termination is carried out. In view of defects of the current domestic air-to-air missile guidance right transfer theory and the technical means, based on the improved particle swarm algorithm and the auction algorithm, a distributed particle swarm auction mixed algorithm with excellent dynamic performance, excellent real-time performance and excellent global optimization performance is brought forward, and the method can be applied to optimization solution to the large-sized air-to-air missile guidance right transfer problem.

Description

The aerial real-time collaborative method of guidance of a kind of unmanned plane based on embedded Control

Technical field

The present invention relates to the aerial real-time collaborative method of guidance of a kind of unmanned plane based on embedded Control, belong to unmanned plane guidance field.

Background technology

Along with the broad development of unmanned air vehicle technique, its purposes in war is also more and more crucial, and especially utilize unmanned plane to carry out dog fight, not only lethality is large, with low cost, and can effectively reduce one's own side's casualties.But time when guide unmanned plane be on the hazard time, in order to realize striking target and reduce self loss, need guidance power to transfer other wing planes to and continue to guide the guided missile launched, and select any frame wing plane to be key point in problem, its essence is a problem solving global optimum.

Summary of the invention

For unmanned plane guidance power hand-off problem, the invention provides the aerial real-time collaborative method of guidance of a kind of unmanned plane based on embedded Control.

Technical scheme of the present invention is: the aerial real-time collaborative method of guidance of a kind of unmanned plane based on embedded Control, comprises the steps:

A, set objectives function and constraint condition;

B, calculate our unmanned plane guidance right of priority and enemy's threat value;

C, initialization population;

D, calculating guidance power transfer price;

The best fitness value of E, calculating single particle;

F, renewal population;

The best fitness value of G, calculating integral particles;

H, judge whether precocity, then go to step I if not, if then go to step F;

I, whether meet end condition, then go to step F if not, if then terminate.

The concrete steps of described method are as follows:

Step1, set objectives function and constraint condition;

Adopt the auction algorithm based on greediness to calculate the function that sets objectives, the function that sets objectives is:

$F\left(x\right)=MAX\underset{j=1}{\overset{N}{\Σ}}\underset{i=1}{\overset{M}{\Σ}}{S}_{ij}\[1-{(1-p_{ij})}^{x_{ij}}\];$

Formulation constraint condition is:

(1) represent that we guides at most I piece of guided missile by the i-th frame unmanned plane, I is threshold value;

(2) represent that one piece of guided missile is guided by a frame unmanned plane at most;

(3) Δ (T, j)≤Δ _i, i=1,2,3...M, represent that the sensing range of unfriendly target T and jth piece guided missile must the radar range Δ of unmanned plane at this end _iin;

Wherein, N is the guided missile number needing cooperative guidance, and M is our unmanned plane number, S _ijfor our unmanned plane guidance right of priority, p _ijfor our the i-th frame unmanned plane is to the guidance ability of jth piece guided missile, x _ijfor our the i-th frame unmanned plane transfers the element weighed in decision matrix to the guidance of jth piece guided missile, represent whether the i-th frame unmanned plane participates in the guidance to jth piece guided missile, can only get 0 or 1,0 expression does not participate in, and 1 represents participation; Power decision matrix is transferred in guidance: $\left[\begin{array}{cccc}{x}_{11}& ...& ...& x_{1N}\\ \·& & & \·\\ \·& ...& ...& \·\\ \·& & & \·\\ x_{M1}& ...& ...& x_{MN}\end{array}\right];$ Get any frame in footmark i our M frame unmanned plane corresponding, footmark j correspondence N piece needs any one piece in the guided missile of cooperative guidance;

Step2, calculate our unmanned plane guidance right of priority and enemy's threat value;

Step2.1, first, we comprises the guidance right of priority to enemy plane and the guidance right of priority to guided missile at unmanned plane guidance right of priority:

Step2.1.1, the guidance right of priority of our unmanned plane to enemy plane are that our the i-th frame unmanned plane is to the guidance ability p of jth piece guided missile _ij;

Step2.1.2, the guidance right of priority of our unmanned plane to guided missile comprise angle advantage and distance advantage:

Angle advantage: wherein, θ _ijfor we the i-th frame unmanned plane speed V _iscore d is departed from direction _ijangle; σ _ijfor jth piece missile velocity V _jscore d is departed from direction _ijthe angle of extended line; for the effective working cone angle of jth piece missile's rearward-facing antenna, δ _ifor our the i-th frame unmanned plane radar maximum search cone angle; d _ijfor the score of our the i-th frame unmanned plane and jth piece guided missile;

Distance advantage: ${\mathrm{\ρ}}_{ij}=\left\{\begin{array}{cc}{e}^{\frac{-3d_{ij}}{r_i}}& d_{ij}\≤r_i\\ 0& d_{ij}>r_i\end{array}\right\};$ Wherein, r _ifor our the i-th frame unmanned plane radar is to the maximum guidance range of guided missile, e is exponential constant;

Comprehensive angle advantage, distance advantage can obtain the guidance right of priority of our unmanned plane to guided missile and be: wherein, e ₁, e ₂for weight coefficient and e ₁+ e ₂=1;

Draw, we guides right of priority by unmanned plane wherein, u ₁, u ₂for weight coefficient and u ₁+ u ₂=1;

Step2.2, enemy's threat value comprise threat and kill probability; Wherein, A is the threat of enemy plane to our unmanned plane, and g is the kill probability of enemy plane guided missile;

Step3, initialization population:

Element x ij arbitrary in decision matrix being mapped to arbitrary particle xij in population is PP at the positional representation of E dimension space _ij=(pp _ij1, pp _ij2... pp _ijE), the desired positions of arbitrary particle xij process is PP, i.e. the best fitness value of single particle, and the desired positions of integral particles process is PP _best, i.e. the best fitness value of integral particles; Wherein, pp _ij1, pp _ij2... pp _ijErepresent arbitrary particle x _ijthe component of position in E dimension coordinate system in E coordinate axis;

Step4, calculating guidance power transfer price:

Adopt based on greediness auction algorithm calculate guidance power transfer price (auction algorithm need auction the both sides i.e. side of auction and auction side, auction side for we send transfer guidance power unmanned plane, auction side be we participate in guide weigh transfer unmanned plane.), calculating our the guidance power transfer price of the i-th frame unmanned plane participation jth piece guided missile is J _ij=a ₁* V _ij-a ₂* K _ij; Wherein, a ₁, a ₂for weight coefficient, for adjusting the ratio of interests and cost, and a ₁+ a ₂=1; The benefit that the guidance power that our the i-th frame unmanned plane participates in jth piece guided missile is transferred is e is exponential constant; The cost that the guidance power that our the i-th frame unmanned plane participates in jth piece guided missile is transferred is K _ij=A*g;

The best fitness value of Step5, calculating single particle:

First, the fitness function defining particle is

Secondly, price J is transferred by guidance power _ijinput as fitness function calculates the best fitness value PP of single particle;

Step6, renewal population;

After by Step3 initialization being carried out to population, define every generation particle and upgrade the speed of oneself and the formula of position is:

Speed: pv _ijk=cpv _ijk+ d ₁r ₁pp _ijk+ d ₂r ₂pp _ijk; Wherein, c is inertia weight, value between [0.1,0.9], d ₁, d ₂for Studying factors, r ₁, r ₂for coefficient value is between [0,1], footmark k represents each component in E dimension coordinate system in each coordinate axis, k=1,2,3...E, pv _ijkrepresent the component of the speed of arbitrary particle xij in E dimension coordinate system in E coordinate axis;

(2) position: pp _ijk=pp _ijk+ tpv _ijkrepresent the position pp of previous generation particle _ijkwith previous generation particle in refresh time t with speed pv _ijkthe position sum changed is as the position pp of particle of future generation _ijk;

The best fitness value of Step7, calculating integral particles:

The fitness function of definition particle is price J is transferred by guidance power _ijinput as fitness function calculates the best fitness value PP of integral particles _best;

Step8, judge whether precocity:

When having a particle x _ijbest fitness value PP be greater than the best fitness value PP of integral particles _best, then become precocious, then forward Step6 to and continue to upgrade population; Otherwise represent and do not occur precocity, so enter Step9;

Step9, judge whether to meet end condition:

By step Step8, draw in population and do not occur precocity, then obtain and particle x _ijthe particle position PP corresponding to best fitness value PP _ij, according to PP _ijobtain element x in corresponding decision matrix _ijvalue as transfer program, then whether meet according to step Step1 constraint IF condition:

If do not meet constraint condition, then forward Step6 to and continue to upgrade population;

If meet constraint condition, then calculating target function F (x), exports net result.

The invention has the beneficial effects as follows:

The deficiency of theory and technology means is transferred for Present Domestic air-to-air missile guidance power, based on modified particle swarm optiziation and auction algorithm, propose a kind of distributed dynamic, real-time and global optimizing performance population auction all preferably hybrid algorithm, the Optimization Solution of extensive air-to-air missile guidance power hand-off problem can be applied to.

Accompanying drawing explanation

Fig. 1 is process flow diagram of the present invention;

Fig. 2 is guided missile of the present invention and our unmanned plane relative attitude figure.

Embodiment

Embodiment 1: as shown in Figure 1-2,

The aerial real-time collaborative method of guidance of unmanned plane based on embedded Control, comprises the steps:

A, set objectives function and constraint condition;

B, calculate our unmanned plane guidance right of priority and enemy's threat value;

C, initialization population;

D, calculating guidance power transfer price;

The best fitness value of E, calculating single particle;

F, renewal population;

The best fitness value of G, calculating integral particles;

H, judge whether precocity, then go to step I if not, if then go to step F;

I, whether meet end condition, then go to step F if not, if then terminate.

The concrete steps of described method are as follows:

Step1, set objectives function and constraint condition;

Adopt the auction algorithm based on greediness to calculate the function that sets objectives, the function that sets objectives is:

$F\left(x\right)=MAX\underset{j=1}{\overset{N}{\Σ}}\underset{i=1}{\overset{M}{\Σ}}{S}_{ij}\[1-{(1-p_{ij})}^{x_{ij}}\];$

Formulation constraint condition is:

(1) represent that we guides at most I piece of guided missile by the i-th frame unmanned plane, I is threshold value;

(2) represent that one piece of guided missile is guided by a frame unmanned plane at most;

(3) Δ (T, j)≤Δ _i, i=1,2,3...M, represent that the sensing range of unfriendly target T and jth piece guided missile must the radar range Δ of unmanned plane at this end _iin;

Wherein, N is the guided missile number needing cooperative guidance, and M is our unmanned plane number, S _ijfor our unmanned plane guidance right of priority, p _ijfor our the i-th frame unmanned plane is to the guidance ability of jth piece guided missile, x _ijfor our the i-th frame unmanned plane transfers the element weighed in decision matrix to the guidance of jth piece guided missile, represent whether the i-th frame unmanned plane participates in the guidance to jth piece guided missile, can only get 0 or 1,0 expression does not participate in, and 1 represents participation; Power decision matrix is transferred in guidance: $\left[\begin{array}{cccc}{x}_{11}& ...& ...& x_{1N}\\ \·& & & \·\\ \·& ...& ...& \·\\ \·& & & \·\\ x_{M1}& ...& ...& x_{MN}\end{array}\right];$ Get any frame in footmark i our M frame unmanned plane corresponding, footmark j correspondence N piece needs any one piece in the guided missile of cooperative guidance;

Step2, calculate our unmanned plane guidance right of priority and enemy's threat value;

Step2.1, first, we comprises the guidance right of priority to enemy plane and the guidance right of priority to guided missile at unmanned plane guidance right of priority:

Step2.1.1, the guidance right of priority of our unmanned plane to enemy plane are that our the i-th frame unmanned plane is to the guidance ability p of jth piece guided missile _ij;

Step2.1.2, the guidance right of priority of our unmanned plane to guided missile comprise angle advantage and distance advantage:

Angle advantage: wherein, θ _ijfor we the i-th frame unmanned plane speed V _iscore d is departed from direction _ijangle; σ _ijfor jth piece missile velocity V _jscore d is departed from direction _ijthe angle of extended line; for the effective working cone angle of jth piece missile's rearward-facing antenna, δ _ifor our the i-th frame unmanned plane radar maximum search cone angle; d _ijfor the score of our the i-th frame unmanned plane and jth piece guided missile;

Distance advantage: ${\mathrm{\ρ}}_{ij}=\left\{\begin{array}{cc}{e}^{\frac{-3d_{ij}}{r_i}}& d_{ij}\≤r_i\\ 0& d_{ij}>r_i\end{array}\right\};$ Wherein, r _ifor our the i-th frame unmanned plane radar is to the maximum guidance range of guided missile, e is exponential constant;

Comprehensive angle advantage, distance advantage can obtain the guidance right of priority of our unmanned plane to guided missile and be: wherein, e ₁, e ₂for weight coefficient and e ₁+ e ₂=1;

Draw, we guides right of priority by unmanned plane wherein, u ₁, u ₂for weight coefficient and u ₁+ u ₂=1;

Step2.2, enemy's threat value comprise threat and kill probability; Wherein, A is the threat of enemy plane to our unmanned plane, and g is the kill probability of enemy plane guided missile;

Step3, initialization population:

By element x arbitrary in decision matrix _ijbe mapped to arbitrary particle x in population _ijbe PP at the positional representation of E dimension space _ij=(pp _ij1, pp _ij2... pp _ijE), the desired positions of arbitrary particle xij process is PP, i.e. the best fitness value of single particle, and the desired positions of integral particles process is PP _best, i.e. the best fitness value of integral particles; Wherein, pp _ij1, pp _ij2... pp _ijErepresent arbitrary particle x _ijthe component of position in E dimension coordinate system in E coordinate axis;

Step4, calculating guidance power transfer price:

Adopt the auction algorithm based on greediness to calculate guidance power and transfer price, calculating guidance power that our the i-th frame unmanned plane participates in jth piece guided missile, to transfer price be J _ij=a ₁* V _ij-a ₂* K _ij; Wherein, a ₁, a ₂for weight coefficient, for adjusting the ratio of interests and cost, and a ₁+ a ₂=1; The benefit that the guidance power that our the i-th frame unmanned plane participates in jth piece guided missile is transferred is e is exponential constant; The cost that the guidance power that our the i-th frame unmanned plane participates in jth piece guided missile is transferred is K _ij=A*g;

The best fitness value of Step5, calculating single particle:

First, the fitness function defining particle is

Secondly, price J is transferred by guidance power _ijinput as fitness function calculates the best fitness value PP of single particle;

Step6, renewal population;

After by Step3 initialization being carried out to population, define every generation particle and upgrade the speed of oneself and the formula of position is:

Speed: pv _ijk=cpv _ijk+ d ₁r ₁pp _ijk+ d ₂r ₂pp _ijk; Wherein, c is inertia weight, value between [0.1,0.9], d ₁, d ₂for Studying factors, r ₁, r ₂for coefficient value is between [0,1], footmark k represents each component in E dimension coordinate system in each coordinate axis, k=1,2,3...E, pv _ijkrepresent arbitrary particle x _ijthe component of speed in E dimension coordinate system in E coordinate axis;

(2) position: pp _ijk=pp _ijk+ tpv _ijkrepresent the position pp of previous generation particle _ijkwith previous generation particle in refresh time t with speed pv _ijkthe position sum changed is as the position pp of particle of future generation _ijk;

The best fitness value of Step7, calculating integral particles:

The fitness function of definition particle is price J is transferred by guidance power _ijinput as fitness function calculates the best fitness value PP of integral particles _best;

Step8, judge whether precocity:

When having a particle x _ijbest fitness value PP be greater than the best fitness value PP of integral particles _best, then become precocious, then forward Step6 to and continue to upgrade population; Otherwise represent and do not occur precocity, so enter Step9;

Step9, judge whether to meet end condition:

By step Step8, draw in population and do not occur precocity, then obtain and particle x _ijthe particle position PP corresponding to best fitness value PP _ij, according to PP _ijobtain element x in corresponding decision matrix _ijvalue as transfer program, then whether meet according to step Step1 constraint IF condition:

If do not meet constraint condition, then forward Step6 to and continue to upgrade population;

If meet constraint condition, then calculating target function F (x), exports net result.

Embodiment 2: as shown in Figure 1-2,

The aerial real-time collaborative method of guidance of unmanned plane based on embedded Control, comprises the steps:

A, set objectives function and constraint condition;

B, calculate our unmanned plane guidance right of priority and enemy's threat value;

C, initialization population;

D, calculating guidance power transfer price;

The best fitness value of E, calculating single particle;

F, renewal population;

The best fitness value of G, calculating integral particles;

H, judge whether precocity, then go to step I if not, if then go to step F;

I, whether meet end condition, then go to step F if not, if then terminate.

Embodiment 3: as shown in Figure 1-2,

The aerial real-time collaborative method of guidance of unmanned plane based on embedded Control, comprises the steps:

A, set objectives function and constraint condition;

B, calculate our unmanned plane guidance right of priority and enemy's threat value;

C, initialization population;

D, calculating guidance power transfer price;

The best fitness value of E, calculating single particle;

F, renewal population;

The best fitness value of G, calculating integral particles;

H, judge whether precocity, then go to step I if not, if then go to step F;

I, whether meet end condition, then go to step F if not, if then terminate.

Specific experiment is as follows:

Assuming that we has 6 frame unmanned planes, r ₁, r ₂, r ₃, r ₄, r ₅, r ₆, wherein r ₄just guide M ₁, M ₂attack enemy plane b ₁, b ₂, now r ₄withdrawn by enemy plane locking needs, therefore abandon guidance power, require that other wing planes carry out guidance power and transfer.In algorithm, each parameter is provided by expertise, and each flight parameter is provided by table 1, and transfer program is provided by table 2.

Table 1. flight parameter

Numbering	Horizontal ordinate	Ordinate	Direction	Speed	Scope	Distance by radar
							r1	-140	-48	17.22	360	200	220
r2	-140	-120	35.43	385	200	220
							r3	-120	-140	47.74	400	200	220
r4	-140	0	0	440	200	220
							r5	-260	-255	49.17	400	200	220
r6	0	-160	100	400	200	220
							b1	10	0	0	420	220	240
b2	-120	-20	0	400	220	240
							M1	-120	0	0	1200
M2	-80	0	0	1200

As shown in Table 1, M=6, N=2, i=1,2,3,4,5,6, j=1,2.

The decision matrix that power is transferred in guidance is: $\left(\begin{array}{cc}{x}_{11}& x_{12}\\ x_{21}& x_{22}\\ x_{31}& x_{32}\\ x_{41}& x_{42}\\ x_{51}& x_{52}\\ x_{61}& x_{62}\end{array}\right);$

Step1, set objectives function and constraint condition;

Adopt the auction algorithm based on greediness to calculate the function that sets objectives, the function that sets objectives is:

$F\left(x\right)=MAX\underset{j=1}{\overset{2}{\Σ}}\underset{i=1}{\overset{6}{\Σ}}{S}_{ij}\[1-{(1-p_{ij})}^{x_{ij}}\];$

Formulation constraint condition is:

(1) represent that we guides at most I piece of guided missile by the i-th frame unmanned plane, I is threshold value;

(2) represent that one piece of guided missile is guided by a frame unmanned plane at most;

(3) Δ (T, j)≤Δ _i, i=1,2,3,4,5,6, represent that the sensing range of unfriendly target T and jth piece guided missile must the radar range Δ of unmanned plane at this end _iin;

Step2, calculate our unmanned plane guidance right of priority and enemy's threat value;

Step2.1, first, we comprises the guidance right of priority to enemy plane and the guidance right of priority to guided missile at unmanned plane guidance right of priority:

Step2.1.1, the guidance right of priority of our unmanned plane to enemy plane are that our the i-th frame unmanned plane is to the guidance ability p of jth piece guided missile _ij;

Wherein, we is to the guidance right of priority of enemy plane, for without loss of generality, gets the guidance ability of our 6 frame unmanned planes to 2 pieces of guided missiles and is 0.5, i.e. p _ij=0.5.

Step2.1.2, the guidance right of priority of our unmanned plane to guided missile comprise angle advantage and distance advantage:

Wherein, the guidance right of priority of our unmanned plane to guided missile comprises angle and distance advantage.For without loss of generality, the effective working cone angle of aft antenna of the radar maximum search cone angle and 2 pieces of guided missiles of getting our 6 frame unmanned planes is current accepted value.

Angle advantage:

$\begin{array}{c}{\mathrm{\α}}_{11}=0.37,{\mathrm{\α}}_{12}=0.35,{\mathrm{\α}}_{21}=0.21,{\mathrm{\α}}_{22}=0.18,{\mathrm{\α}}_{31}=0.76,{\mathrm{\α}}_{32}=0.61,{\mathrm{\α}}_{41}=0.28,{\mathrm{\α}}_{42}=0.44,\\ {\mathrm{\α}}_{51}=0.08,{\mathrm{\α}}_{52}=0.21,{\mathrm{\α}}_{61}=0.70,{\mathrm{\α}}_{62}=0.82\end{array}$ Distance advantage:

$\begin{array}{c}{\mathrm{\ρ}}_{11}=0.22,{\mathrm{\ρ}}_{12}=0.14,{\mathrm{\ρ}}_{21}=0.41,{\mathrm{\ρ}}_{22}=0.24,{\mathrm{\ρ}}_{31}=0.48,{\mathrm{\ρ}}_{32}=0.11,{\mathrm{\ρ}}_{41}=0.13,{\mathrm{\ρ}}_{42}=0.24,\\ {\mathrm{\ρ}}_{52}=0.15,{\mathrm{\ρ}}_{52}=0.93,{\mathrm{\ρ}}_{61}=0.40,{\mathrm{\ρ}}_{62}=0.56\end{array}$ Comprehensive angle, distance advantage can be tried to achieve the guidance right of priority of our unmanned plane to guided missile and is:

$\begin{array}{c}{q}_{11}=0.29,q_{12}=0.22,q_{21}=0.29,q_{22}=0.21,q_{31}=0.60,q_{32}=0.26,q_{41}=0.19,q_{42}=0.32,\\ q_{51}=0.11,q_{52}=0.29,q_{61}=0.62,q_{62}=0.68\end{array}$ For without loss of generality, get e ₁=e ₂=0.5.

In sum, can show that we guides right of priority and is thus:

$\begin{array}{c}{S}_{11}=0.38,S_{12}=0.33,S_{21}=0.38,S_{22}=0.32,S_{31}=0.55,S_{32}=0.36,S_{41}=0.31,S_{42}=0.40,\\ S_{51}=0.23,S_{52}=0.38,S_{61}=0.47,S_{62}=0.58\end{array}$ For without loss of generality, get u ₁=u ₂=0.5.

Step2.2, enemy's threat value comprise threat and kill probability.

Wherein, make 1 for enemy plane is to the threat of our unmanned plane, i.e. A=1,0.5 is the kill probability of enemy plane guided missile, i.e. g=0.5.

Step3, initialization population:

For without loss of generality, get E=3, namely in three dimensions, in population, speed and the position component on three axles of arbitrary particle is three random numbers.

Step4, calculating guidance power transfer price:

The benefit that the guidance power that our the i-th frame unmanned plane participates in jth piece guided missile is transferred is:

$\begin{array}{c}{V}_{11}=0.73,V_{12}=0.70,V_{21}=0.73,V_{22}=0.69,V_{31}=0.87,V_{32}=0.72,V_{41}=0.68,V_{42}=0.75,\\ V_{51}=0.63,V_{52}=0.73,V_{61}=0.80,V_{62}=0.89\end{array}$ The cost that the guidance power that our the i-th frame unmanned plane participates in jth piece guided missile is transferred is:

K ₁₁＝K ₁₂＝K ₂₁＝K ₂₂＝K ₃₁＝K ₃₂＝K ₄₁＝K ₄₂＝K ₅₁＝K ₅₂＝K ₆₁＝K ₆₂＝0.5

The guidance power transfer price that our the i-th frame unmanned plane participates in jth piece guided missile is:

For without loss of generality, get a ₁=a ₂=0.5, then

$\begin{array}{c}{J}_{11}=0.12,J_{12}=0.10,J_{21}=0.12,J_{22}=0.10,J_{31}=0.19,J_{32}=0.11,J_{41}=0.10,J_{42}=0.13\\ J_{51}=0.07,J_{52}=0.13,J_{61}=0.15,J_{62}=0.20\end{array}$ From N=2, only have 2 pieces of guided missiles needing cooperative guidance, then our unmanned plane of maximum two framves participates in cooperative guidance.Therefore table 2 is the unmanned plane numbering of participation 2 pieces of guided missile cooperative guidance.I.e. x ₃₁=x ₆₂=1, in decision matrix, other elements are 0.

Table 2. guides power transfer program

Guided missile is numbered	Unmanned plane is numbered	Price
			M 1	r 3	0.18595
M 2	r 6	0.195

The best fitness value of Step5, calculating single particle:

First, the fitness function defining particle is

Secondly, price J is transferred by guidance power _ijinput as fitness function calculates the best fitness value PP of single particle;

Step6, renewal population;

After by Step3 initialization being carried out to population, define every generation particle and upgrade the speed of oneself and the formula of position is:

Speed: pv _ijk=cpv _ijk+ d ₁r ₁pp _ijk+ d ₂r ₂pp _ijk; Wherein, because E=3, therefore k=1,2,3; For without loss of generality, c=0.5 might as well be established, d ₁=d ₂=0.5, r ₁=r ₂=0.5.

(2) position: pp _ijk=pp _ijk+ tpv _ijkrepresent the position pp of previous generation particle _ijkwith previous generation particle in refresh time t with speed pv _ijkthe position sum changed is as the position pp of particle of future generation _ijk; Wherein, because E=3, therefore k=1,2,3

The best fitness value of Step7, calculating integral particles:

The fitness function of definition particle is price J is transferred by guidance power _ijinput as fitness function calculates the best fitness value PP of integral particles _best;

Step8, judge whether precocity:

Step9, judge whether to meet end condition:

From the above, be without loss of generality in the present embodiment, all parameters all choose the convenient conventional fixed value calculated, and get E=3 in population, namely, in three dimensions, in population, speed and the position component on three axles of arbitrary particle is three random numbers simultaneously.Therefore all meet PP≤PP _best, namely there will not be precocious phenomenon, and certainly meet constraint condition.

Then:

The decision matrix that power is transferred in guidance is: $\left(\begin{array}{cc}0& 0\\ 0& 0\\ 1& 0\\ 0& 0\\ 0& 0\\ 0& 1\end{array}\right);$

Objective function: F (x)=MAX{0.29,0.275}=0.29.

From table 2, guidance transfer power decision matrix, objective function can be found out, this algorithm consider guidance power transfer time interests and cost, have selected r ₃and r ₆as the cooperative guidance of guided missile, guidance advantage and self loss have been taken into account simultaneously, in addition each frame unmanned plane can determine whether joining in cooperative guidance and goes by the environment residing for self, when certain frame unmanned plane does not participate in the transfer of guidance power, the traffic between the calculated amount of algorithm and body can be effectively reduced.

By reference to the accompanying drawings the specific embodiment of the present invention is explained in detail above, but the present invention is not limited to above-mentioned embodiment, in the ken that those of ordinary skill in the art possess, can also make a variety of changes under the prerequisite not departing from present inventive concept.

Claims (2)

1., based on the aerial real-time collaborative method of guidance of unmanned plane of embedded Control, it is characterized in that: comprise the steps:

A, set objectives function and constraint condition;

B, calculate our unmanned plane guidance right of priority and enemy's threat value;

C, initialization population;

D, calculating guidance power transfer price;

The best fitness value of E, calculating single particle;

F, renewal population;

The best fitness value of G, calculating integral particles;

H, judge whether precocity, then go to step I if not, if then go to step F;

I, whether meet end condition, then go to step F if not, if then terminate.

2. the aerial real-time collaborative method of guidance of the unmanned plane based on embedded Control according to claim 1, is characterized in that: the concrete steps of described method are as follows:

Step1, set objectives function and constraint condition;

Adopt the auction algorithm based on greediness to calculate the function that sets objectives, the function that sets objectives is:

$F\left(x\right)=MAX\underset{j=1}{\overset{N}{\Σ}}\underset{i=1}{\overset{M}{\Σ}}{S}_{ij}\[1-{(1-p_{ij})}^{x_{ij}}\];$

Formulation constraint condition is:

(1) represent that we guides at most I piece of guided missile by the i-th frame unmanned plane, I is threshold value;

(2) represent that one piece of guided missile is guided by a frame unmanned plane at most;

(3) Δ (T, j)≤Δ _i, i=1,2,3...M, represent that the sensing range of unfriendly target T and jth piece guided missile must the radar range Δ of unmanned plane at this end _iin;

Wherein, N is the guided missile number needing cooperative guidance, and M is our unmanned plane number, S _ijfor our unmanned plane guidance right of priority, p _ijfor our the i-th frame unmanned plane is to the guidance ability of jth piece guided missile, x _ijfor our the i-th frame unmanned plane transfers the element weighed in decision matrix to the guidance of jth piece guided missile, represent whether the i-th frame unmanned plane participates in the guidance to jth piece guided missile, can only get 0 or 1,0 expression does not participate in, and 1 represents participation; Power decision matrix is transferred in guidance: $\left[\begin{array}{cccc}{x}_{11}& \mathrm{...}& \mathrm{...}& x_{1N}\\ .& & & .\\ .& \mathrm{...}& \mathrm{...}& .\\ .& & & .\\ x_{M1}& \mathrm{...}& \mathrm{...}& x_{MN}\end{array}\right];$ Get any frame in footmark i our M frame unmanned plane corresponding, footmark j correspondence N piece needs any one piece in the guided missile of cooperative guidance;

Step2, calculate our unmanned plane guidance right of priority and enemy's threat value;

Step2.1, first, we comprises the guidance right of priority to enemy plane and the guidance right of priority to guided missile at unmanned plane guidance right of priority:

Step2.1.1, the guidance right of priority of our unmanned plane to enemy plane are that our the i-th frame unmanned plane is to the guidance ability p of jth piece guided missile _ij;

Step2.1.2, the guidance right of priority of our unmanned plane to guided missile comprise angle advantage and distance advantage:

Angle advantage: wherein, θ _ijfor we the i-th frame unmanned plane speed V _iscore d is departed from direction _ijangle; σ _ijfor jth piece missile velocity V _jscore d is departed from direction _ijthe angle of extended line; for the effective working cone angle of jth piece missile's rearward-facing antenna, δ _ifor our the i-th frame unmanned plane radar maximum search cone angle; d _ijfor the score of our the i-th frame unmanned plane and jth piece guided missile;

Distance advantage: ${\mathrm{\ρ}}_{ij}=\left\{\begin{array}{cc}{e}^{\frac{-3d_{ij}}{r_i}}& d_{ij}\≤r_i\\ 0& d_{ij}>r_i\end{array}\right\};$ Wherein, r _ifor our the i-th frame unmanned plane radar is to the maximum guidance range of guided missile, e is exponential constant;

Comprehensive angle advantage, distance advantage can obtain the guidance right of priority of our unmanned plane to guided missile and be: wherein, e ₁, e ₂for weight coefficient and e ₁+ e ₂=1;

Draw, we guides right of priority by unmanned plane wherein, u ₁, u ₂for weight coefficient and u ₁+ u ₂=1;

Step2.2, enemy's threat value comprise threat and kill probability; Wherein, A is the threat of enemy plane to our unmanned plane, and g is the kill probability of enemy plane guided missile;

Step3, initialization population:

By element x arbitrary in decision matrix _ijbe mapped to arbitrary particle x in population _ijbe PP at the positional representation of E dimension space _ij=(pp _ij1, pp _ij2... pp _ijE), arbitrary particle x _ijthe desired positions of process is PP, i.e. the best fitness value of single particle, and the desired positions of integral particles process is PP _best, i.e. the best fitness value of integral particles; Wherein, pp _ij1, pp _ij2... pp _ijErepresent arbitrary particle x _ijthe component of position in E dimension coordinate system in E coordinate axis;

Step4, calculating guidance power transfer price:

Adopt the auction algorithm based on greediness to calculate guidance power and transfer price, calculating guidance power that our the i-th frame unmanned plane participates in jth piece guided missile, to transfer price be J _ij=a ₁* V _ij-a ₂* K _ij; Wherein, a ₁, a ₂for weight coefficient, for adjusting the ratio of interests and cost, and a ₁+ a ₂=1; The benefit that the guidance power that our the i-th frame unmanned plane participates in jth piece guided missile is transferred is e is exponential constant; The cost that the guidance power that our the i-th frame unmanned plane participates in jth piece guided missile is transferred is K _ij=A*g;

The best fitness value of Step5, calculating single particle:

First, the fitness function defining particle is

Secondly, price J is transferred by guidance power _ijinput as fitness function calculates the best fitness value PP of single particle;

Step6, renewal population;

After by Step3 initialization being carried out to population, define every generation particle and upgrade the speed of oneself and the formula of position is:

Speed: pv _ijk=cpv _ijk+ d ₁r ₁pp _ijk+ d ₂r ₂pp _ijk; Wherein, c is inertia weight, value between [0.1,0.9], d ₁, d ₂for Studying factors, r ₁, r ₂for coefficient value is between [0,1], footmark k represents each component in E dimension coordinate system in each coordinate axis, k=1,2,3...E, pv _ijkrepresent arbitrary particle x _ijthe component of speed in E dimension coordinate system in E coordinate axis;

(2) position: pp _ijk=pp _ijk+ tpv _ijkrepresent the position pp of previous generation particle _ijkwith previous generation particle in refresh time t with speed pv _ijkthe position sum changed is as the position pp of particle of future generation _ijk;

The best fitness value of Step7, calculating integral particles:

The fitness function of definition particle is price J is transferred by guidance power _ijinput as fitness function calculates the best fitness value PP of integral particles _best;

Step8, judge whether precocity:

When having a particle x _ijbest fitness value PP be greater than the best fitness value PP of integral particles _best, then become precocious, then forward Step6 to and continue to upgrade population; Otherwise represent and do not occur precocity, so enter Step9;

Step9, judge whether to meet end condition:

By step Step8, draw in population and do not occur precocity, then obtain and particle x _ijthe particle position PP corresponding to best fitness value PP _ij, according to PP _ijobtain element x in corresponding decision matrix _ijvalue as transfer program, then whether meet according to step Step1 constraint IF condition:

If do not meet constraint condition, then forward Step6 to and continue to upgrade population;

If meet constraint condition, then calculating target function F (x), exports net result.