CN114333432A - Assignment method based on airspace grid - Google Patents

Assignment method based on airspace grid Download PDF

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CN114333432A
CN114333432A CN202111642058.2A CN202111642058A CN114333432A CN 114333432 A CN114333432 A CN 114333432A CN 202111642058 A CN202111642058 A CN 202111642058A CN 114333432 A CN114333432 A CN 114333432A
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airspace
aircraft
matrix
probability
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CN114333432B (en
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朱永文
刘杨
蒲钒
王长春
唐治理
柴保华
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93209 Troops Of Chinese Pla
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Abstract

The invention provides an assignment method based on an airspace grid, belonging to the field of air traffic management; the method specifically comprises the following steps: firstly, carrying out grid recursive division on a target airspace; at t ═ taRespectively endowing parameters to the positions of each aircraft in each sub-grid at each moment aiming at each aircraft in a target airspace according to real-time flight dynamics, meteorological information and a flight plan to form a deterministic grid assignment matrix; meanwhile, according to errors of each aircraft in the flight process, a probability type grid assignment matrix is established, and the probability of the actual sub-grid where each aircraft is located is assigned; finally, calculating the complexity of a target airspace, the flight flow in the grid and the collision probability by utilizing the deterministic grid assignment matrix and the probability type grid assignment matrix of each aircraft respectively, and providing reference data for the air traffic control; the invention takes the airspace grid unit as a basic bottom layer framework of spatial motion modeling to realize the visualization, quantification and operation of the airspace traffic management systemAnd (4) precision is achieved.

Description

Assignment method based on airspace grid
Technical Field
The invention belongs to the field of air traffic management, and particularly relates to an assignment method based on an airspace grid.
Background
With the rapid development of national economy, air traffic moves from low density to high density times, air congestion, blockage, danger approaching, energy consumption uneconomic and the like become common problems facing all countries in the world at present, great challenges are brought to the existing air operation system, and the target levels of future safety, efficiency, capacity and environmental sustainability cannot be ensured due to the fact that the existing air management is operated based on airspace isolation division.
At present, a calculation rule for space domain assignment is still lacked, and an advanced data management and analysis model and a novel space domain use visualization method are realized.
Disclosure of Invention
In order to solve the technical problems, the invention provides an assignment method based on an airspace grid, which maintains and improves the efficiency and safety of airspace management.
The assignment method based on the airspace grid specifically comprises the following steps:
performing grid recursive division on a target airspace A to form uniformly distributed sub-grids of m rows and n columns, and regarding the sub-grids as an mxn-order matrix;
from the origin of grid coordinates, a Z-shaped sorting method is established according to the line numbers of the matrix from small to large and the column numbers of the same line numbers from small to large, and the sub-grids are subjected to numerical coding in sequence; obtaining a grid code number l which is 1, 2. Using discrete random variables X ═ X1,x2,...,xl,...,xm×nRepresents it.
Step two, when t is equal to taAiming at a single aircraft i of a target airspace A at any moment, parameters are respectively given to the position of the aircraft in each sub-grid according to real-time flight dynamics, meteorological information and a flight plan, and a deterministic grid assignment matrix is formed, wherein the deterministic grid assignment matrix is
Figure BDA0003444050140000011
Expressed as:
Figure BDA0003444050140000012
u＝1,2,...,m，v＝1,2,...,n；
Figure BDA0003444050140000013
is expressed in t ═ taThe sub-grid with the sequence number of u x v where the aircraft i is located is endowed with a parameter value at the moment;
according to real-time flight dynamics, meteorological information and a flight plan, assigning the submesh with the serial number of u multiplied by v where the aircraft i is actually located as
Figure BDA0003444050140000021
The rest positions are 0, so that a grid assignment matrix of the determined aircraft position information is obtained;
similarly, the t-t of each aircraft in the target airspace A is obtainedaAnd determining the grid assignment matrix corresponding to each time.
Step three, establishing a probability type grid assignment matrix according to errors of a single aircraft i in the flight process, and assigning the probability of an actual sub-grid where the aircraft is located;
aircraft i passes through subgrid xu×vHas a probability of P (X ═ X)u×v)＝pu×vThen sub-grid xu×vMatrix is assigned in the grid
Figure BDA00034440501400000217
Is assigned a corresponding position of pu×v(ii) a The coding number x of the sub-gridu×vConverting the matrix into a matrix row number and a matrix column number;
the matrix has a row number of
Figure BDA0003444050140000022
The matrix column number is nu×v≡[u×v-1](modn)+1；
Wherein
Figure BDA0003444050140000023
Mod is a remainder function.
Similarly, for the target airspace A, t is taAssigning probability values to the actual sub grids of each aircraft at each moment; and obtaining the row and column numbers of the matrix corresponding to each row and column.
Respectively calculating the complexity, the flight flow in the grid and the collision probability of the target airspace A by utilizing the deterministic grid assignment matrix and the probability type grid assignment matrix of each aircraft, and providing reference data for the air pipes;
1) for a specified period T ═ T1,tN]The total number of the aircrafts entering the airspace A is called flight flow, and the calculation process is as follows:
first, for t ═ taAt any moment, the numerical values of all the aircraft in the airspace A at each position in the deterministic grid assignment matrix are accumulated and summed to obtain
Figure BDA0003444050140000024
And will be
Figure BDA0003444050140000025
Converting into binary form;
Figure BDA0003444050140000026
then, a binary string is calculated
Figure BDA0003444050140000027
Hamming weight of (i.e. t in airspace A)aTime of flight flow
Figure BDA0003444050140000028
The Hamming weight is the number of 1's in a binary string.
Similarly, binary character strings at each moment are respectively calculated
Figure BDA0003444050140000029
J is more than or equal to 1 and less than or equal to N; obtaining the corresponding flight flow at each moment;
traversing each moment and comparing the current moment tjIs recorded as
Figure BDA00034440501400000210
According to the relation between the current time and the adjacent time
Figure BDA00034440501400000211
Calculating Hamming distance between two adjacent moments
Figure BDA00034440501400000212
And updating the flight flow value at the next moment:
Figure BDA00034440501400000213
until j is N.
j is initialized to take 1; hamming distance
Figure BDA00034440501400000214
Is directed to binary strings
Figure BDA00034440501400000215
And
Figure BDA00034440501400000216
the elements of (a) are subjected to exclusive or operation and the statistical result is the number value of 1.
2) And aiming at the traffic complexity of each sub-grid, the calculation process is as follows:
first, for sub-grid xlAnd calculating each index of the traffic complexity:
traffic density N (x)l)：N(xl)＝Wk(xl)/(fs(xl)×H)；
Wherein Wk(xl) Representing a grid xlTraffic flow during the kth time period; h represents the flight airspace management altitude; f. ofs(xl) Representing a spatial grid xlThe spherical projection area of (a);
flight status cond (x)l): counting each grid unit in the k time periodThe number and time that the aircraft is climbing and descending;
③ airplane model mix influence v (x)l): i.e. cell grid xlThe complexity caused by the different aircraft speeds within.
Weather influence traffic index: WITI (x)l)＝Nk(xl)×Wk(xl)
Wherein N isk(xl) Indicating that the traffic flow passes through the grid x in the k-th time periodlThe number of times of national convection weather forecast reports; wk(xl) Representing a grid xlFlight flow during the kth time period;
then, the submesh x is calculated using the respective indiceslThe formula of the traffic complexity is as follows:
TC(xl)＝N(xl)×θ(xl)
where theta (x)l) Is a spatial grid xlThe complexity factor is obtained by compounding complexity index factors, and the calculation formula is as follows:
θ(xl)＝cond(xl)×v(xl)×WITI(xl)
3) and aiming at the collision probability in the airspace A, the calculation process is as follows:
first, for a target airspace A, a grid level r is used0The spatial grid unit of (2) is subjected to grid recursive division; grid level r0Selecting the size of the safety envelope of the root aircraft;
then, M airplanes Y ═ Y are calculated0,y1,...,yj,...,yM-1The probability of flying to different spatial grid cells;
number yjIs coded as xiProbability p of spatial grid cellijExpressed as follows:
pij＝P(X＝xi,Y＝yi)
further, calculating the fuzzy collision probability of each sub-grid according to the probability distribution of each airplane in the airspace grid unit; coded as xiSpatial grid cell of (1), fuzzy collision probability PiThe formula is:
Figure BDA0003444050140000031
all remaining fuzzy collision probabilities for each spatial grid cell ultimately make up the fuzzy collision probability set P' for that cell.
Design airspace grid cell xiTriple data G ofi(xi,Pi',Si)；SiIs a spatial grid cell xiIn satisfies the probability pijSet of all aircraft not equal to 0.
The mapping relationship is as follows:
Figure BDA0003444050140000032
and is
Figure BDA0003444050140000033
So that
Figure BDA0003444050140000034
Figure BDA0003444050140000035
And is
Figure BDA0003444050140000036
So that
Figure BDA0003444050140000037
Using set collision probability operator PAScreening the airspace grid units with collision risks, sequentially selecting the ternary group data of each unit, and when P is the number of the ternary group datai'≥PAIf the unit has collision risk, returning the corresponding triple data to be stored in an array set G, otherwise, neglecting the collision risk, and continuously judging the next airspace grid unit; until all units judgeObtaining a new set G after finishing;
the set G is the grid cells, collision probabilities and their corresponding aircraft numbers in all the airspaces a at which there is a risk of collision.
The invention has the advantages that:
1. a assignment method based on airspace grids provides a quick realization method for assignment application calculation of the airspace grids;
2. a assignment method based on airspace grids constructs a set of airspace assignment calculation rules based on a grid assignment matrix, gives specific description and properties of operators, and lays a theoretical foundation for the practical application of subsequent matrix assignment and corresponding airspace management;
3. an assignment method based on an airspace grid realizes the establishment of deterministic and probabilistic airspace grid assignment matrixes, realizes the calculation of airspace grid complexity, flight flow in grids and collision probability by utilizing the grid assignment matrixes, and provides technical support for the management of future airspaces.
Drawings
FIG. 1 is a flow chart of a spatial grid-based assignment method of the present invention;
FIG. 2 is a flow chart of the calculation of the flight flow within the grid according to the present invention;
FIG. 3 is a flow chart of the computation of the collision probability within a mesh in accordance with the present invention.
Detailed Description
The foregoing and other advantages of the invention will become more apparent from the following detailed description of the invention when taken in conjunction with the accompanying drawings.
The invention provides an assignment method based on an airspace grid, which develops a novel airspace numerical calculation method by establishing a grid matrix assignment method of an airspace and an algorithm based on a grid assignment matrix under a digital airspace system, respectively establishes a deterministic airspace grid assignment matrix and a probabilistic airspace grid assignment matrix according to grid assignment types, establishes a set of airspace grid assignment matrix calculation rule, and calculates flight flow, complexity and collision risk in the airspace grid units by taking the airspace grid units as a basic bottom framework of space motion modeling, thereby realizing visualization, quantification and accuracy of an airspace traffic management system.
The assignment method based on the spatial domain grid is shown in fig. 1, and specifically comprises the following steps:
performing grid recursive division on a target airspace A to form uniformly distributed sub-grids of m rows and n columns, and regarding the sub-grids as an mxn-order matrix;
from the origin of grid coordinates, a Z-shaped sorting method is established according to the line numbers of the matrix from small to large and the column numbers of the same line numbers from small to large, and the sub-grids are subjected to numerical coding in sequence; obtaining a grid code number l which is 1, 2. Using discrete random variables X ═ X1,x2,...,xl,...,xm×nRepresents it.
Step two, when t is equal to taAiming at a single aircraft i of a target airspace A at any moment, parameters are respectively given to the position of the aircraft in each sub-grid according to real-time flight dynamics, meteorological information and a flight plan, and a deterministic grid assignment matrix is formed, wherein the deterministic grid assignment matrix is
Figure BDA0003444050140000041
Firstly, aiming at a divided grid of an airspace A, a parameter function g (x) is endowed to each sub-grid, and a grid assignment function mainly determines specific contents according to the requirements of air traffic management or battlefield airspace control;
then, the number i of the aircraft in the airspace A is t ═ taThe grid of time is assigned a matrix of
Figure BDA0003444050140000042
The grid valuation function of each sub-grid is respectively
Figure BDA0003444050140000043
1,2, n, wherein:
Figure BDA0003444050140000051
Figure BDA0003444050140000052
is expressed in t ═ taThe sub-grid with the sequence number of u x v where the aircraft i is located is endowed with a parameter value at the moment;
according to real-time flight dynamics, meteorological information and a flight plan, assigning the submesh with the serial number of u multiplied by v where the aircraft i is actually located as
Figure BDA0003444050140000053
The rest positions are 0, so that a grid assignment matrix of the determined aircraft position information is obtained;
similarly, the t-t of each aircraft in the target airspace A is obtainedaAnd determining the grid assignment matrix corresponding to each time.
Any positive integer can be split into 2 sums of different powers, the grid assignment matrix is split, and the actual position information of each aircraft in the airspace can be obtained;
step three, establishing a probability type grid assignment matrix according to errors of a single aircraft i in the flight process, and assigning the probability of an actual sub-grid where the aircraft is located;
aircraft i passes through subgrid xu×vHas a probability of P (X ═ X)u×v)＝pu×vThen sub-grid xu×vMatrix is assigned in the grid
Figure BDA0003444050140000054
Is assigned a corresponding position of pu×v(ii) a The coding number x of the sub-gridu×vConversion to matrix row and column numbers, i.e. matrix (n)u×v,mu×v) Location assignment pu×v；
The matrix has a row number of
Figure BDA0003444050140000055
The matrix column number is nu×v≡[u×v-1](mod n)+1；
Wherein
Figure BDA0003444050140000056
Mod is a remainder function.
Similarly, for the target airspace A, t is taAssigning probability values to the actual sub grids of each aircraft at each moment; and obtaining the row and column numbers of the matrix corresponding to each row and column.
Respectively calculating the complexity, the flight flow in the grid and the collision probability of the target airspace A by utilizing the deterministic grid assignment matrix and the probability type grid assignment matrix of each aircraft, and providing reference data for the air pipes;
1) for a specified period T ═ T1,tN]The total number of the aircrafts entering the airspace A is called flight flow, and the calculation process is as follows:
as shown in fig. 2, first, for t ═ taAt the moment, the numerical values of all the positions in the deterministic grid assignment matrix of all the aircrafts in the airspace A are accumulated and summed, namely the sum of all the elements in the matrix is calculated to obtain
Figure BDA0003444050140000057
And will be
Figure BDA0003444050140000058
Converting into binary form, namely, a character string only containing numbers 0 and 1;
Figure BDA0003444050140000059
then, a binary string is calculated
Figure BDA00034440501400000510
Hamming weight of (i.e. t in airspace A)aTime of flight flow
Figure BDA00034440501400000511
The Hamming weight is the number of non-zero symbols in a binary string, and in the most common data bit strings, is typically the number of 1's.
In the same way, divide intoSeparately computing binary strings at each time
Figure BDA00034440501400000512
J is more than or equal to 1 and less than or equal to N; obtaining the corresponding flight flow at each moment;
traversing each moment and comparing the current moment tjIs recorded as
Figure BDA00034440501400000513
According to the relation between the current time and the adjacent time
Figure BDA00034440501400000514
Calculating Hamming distance between two adjacent moments
Figure BDA00034440501400000515
And updating the flight flow value at the next moment:
Figure BDA0003444050140000061
until j is N.
j is initialized to take 1; hamming distance
Figure BDA0003444050140000062
Refers to binary strings of equal size for aggregate capacity
Figure BDA0003444050140000063
And
Figure BDA0003444050140000064
and carrying out exclusive OR operation on the elements in the two sets, and counting the number of the result as 1.
2) And aiming at the traffic complexity of each sub-grid, the calculation process is as follows:
first, for sub-grid xlAnd calculating each index of the traffic complexity:
traffic density N (x)l)：N(xl)＝Wk(xl)/(fs(xl)×H)；
Wherein Wk(xl) Representation gridxlTraffic flow during the kth time period; h represents the flight airspace management altitude; f. ofs(xl) Representing a spatial grid xlThe spherical projection area of (a);
flight status cond (x)l): counting the number of times and time that the aircraft climbs and descends in the kth time period of each grid unit;
③ airplane model mix influence v (x)l): to illustrate the complexity caused by the differences in aircraft speed within a grid of cells, an interplay of speed is introduced to this index. When two aircrafts appear in the same grid and the difference of the navigational speeds is more than 40km/h, the two aircrafts have influence on the speed;
weather influence traffic index: representing the number of airplane frames affected by weather, and standardizing the potential influence of dangerous weather on the airway sector and the terminal area, wherein the calculation formula is as follows:
WITI(xl)＝Nk(xl)×Wk(xl)
wherein N isk(xl) Indicating that the traffic flow passes through the grid x in the k-th time periodlThe number of times of national convection weather forecast reports; wk(xl) Representing a grid xlFlight flow during the kth time period;
then, the submesh x is calculated using the respective indiceslThe formula of the traffic complexity is as follows:
TC(xl)＝N(xl)×θ(xl)
where theta (x)l) Is a spatial grid xlThe complexity factor is obtained by compounding complexity index factors, and the calculation formula is as follows:
θ(xl)＝cond(xl)×v(xl)×WITI(xl)
3) as shown in fig. 3, the calculation process for the collision probability in the airspace a is as follows:
first, for a target airspace A, a grid level r is used0The spatial grid unit of (2) is subjected to grid recursive division; grid level r0Aircraft with a selection root numberSelecting the size of the safety envelope;
then, the real-time aircraft information is read according to the manufacturing performance parameters of the aircraft, the aircraft speed, the aircraft wake, the human factors, the navigation performance and the like, and M airplanes Y are calculated as { Y ═ Y0,y1,...,yj,...,yM-1The probability of flying to different spatial grid cells;
number yjIs coded as xiProbability p of spatial grid cellijExpressed as follows:
pij＝P(X＝xi,Y＝yi)
further, calculating the fuzzy collision probability of each sub-grid according to the probability distribution of each airplane in the airspace grid unit; coded as xiSpatial grid cell of (1), fuzzy collision probability PiThe formula is:
Figure BDA0003444050140000071
all remaining fuzzy collision probabilities for each spatial grid cell ultimately make up the fuzzy collision probability set P' for that cell.
Design airspace grid cell xiTriple data G ofi(xi,Pi',Si) Organizing various data of air traffic operation; siIs a spatial grid cell xiIn satisfies the probability pijSet of all aircraft not equal to 0.
The mapping relationship is as follows:
Figure BDA0003444050140000072
and is
Figure BDA0003444050140000073
So that
Figure BDA0003444050140000074
Figure BDA0003444050140000075
And is
Figure BDA0003444050140000076
So that
Figure BDA0003444050140000077
Using set collision probability operator PAScreening the airspace grid units with collision risks, sequentially selecting the ternary group data of each unit, and when P is the number of the ternary group datai'≥PAIf the unit has collision risk, returning the corresponding triple data to be stored in an array set G, otherwise, neglecting the collision risk, and continuously judging the next airspace grid unit; obtaining a new set G until all units are judged;
the set G is the grid cells, collision probabilities and their corresponding aircraft numbers in all the airspaces a at which there is a risk of collision.
Firstly, constructing a set of airspace assignment calculation rules based on a grid assignment matrix, wherein the airspace assignment calculation rules comprise addition, subtraction, multiplication, division, integral, differential, derivative and the like, and specific description and properties of operators are respectively given, so that a theoretical basis is laid for the practical application of subsequent matrix assignment and corresponding airspace management;
matrix operators and descriptions
Figure BDA0003444050140000078
Figure BDA0003444050140000081
Figure BDA0003444050140000091
Then, on the basis of the subdivision and coding of the airspace grid unit, establishing a deterministic airspace grid assignment matrix according to the grid assignment type, and assigning according to real-time flight dynamics, meteorological information, a flight plan and the like; meanwhile, because the aircraft is influenced by uncertain factors in the flight process and various errors exist, a probability type airspace grid assignment matrix is established, and the probability type grid assignment method is to assign values according to corresponding probabilities;
secondly, splitting the matrix according to the obtained assignment matrix, and performing reverse-pushing to obtain the airspace information corresponding to the grid assignment matrix, so as to realize the accurate management of the airspace; finally, according to the airspace grid assignment method and the defined algorithm thereof, calculating the complexity of the airspace grid, the flight flow in the grid and the collision probability to develop traffic management control and realize more refined high-density traffic operation; the practical application of the novel airspace numerical calculation method can effectively improve the airspace management efficiency.
The specific implementation method can be used for realizing the quantification of the spatial grid calculation and effectively improving the efficiency of spatial management.

Claims (7)

1. An assignment method based on an airspace grid is characterized by comprising the following specific steps:
firstly, carrying out grid recursive division on a target airspace A to form m rows and n columns of uniformly distributed sub-grids which are regarded as m multiplied by n-order matrixes;
then, when t is equal to taAiming at a single aircraft i of a target airspace A at any moment, parameters are respectively given to the position of the aircraft in each sub-grid according to real-time flight dynamics, meteorological information and a flight plan, and a deterministic grid assignment matrix is formed, wherein the deterministic grid assignment matrix is
Figure FDA0003444050130000011
Similarly, the t-t of each aircraft in the target airspace A is obtainedaDetermining a grid assignment matrix corresponding to each time;
then, according to errors of each aircraft in the flight process, a probability type grid assignment matrix is established, and the probability of the actual sub-grid where each aircraft is located is assigned;
and finally, calculating the complexity, the in-grid flight flow and the collision probability of the target airspace A respectively by utilizing the deterministic grid assignment matrix and the probability type grid assignment matrix of each aircraft, and providing reference data for the air traffic control.
2. The spatial domain grid-based assignment method of claim 1, wherein said grid recursive partitioning of the target spatial domain a comprises:
from the origin of grid coordinates, a Z-shaped sorting method is established according to the line numbers of the matrix from small to large and the column numbers of the same line numbers from small to large, and the sub-grids are subjected to numerical coding in sequence; obtaining a grid code number l which is 1, 2. Using discrete random variables X ═ X1,x2,...,xl,...,xm×nRepresents it.
3. The spatial domain grid-based assignment method of claim 1, wherein said assigning is performed at t ═ taThe definite type grid assignment matrix of a single aircraft i of the time target airspace A is
Figure FDA0003444050130000012
Expressed as:
Figure FDA0003444050130000013
u＝1,2,...,m，v＝1,2,...,n；
Figure FDA0003444050130000014
is expressed in t ═ taThe sub-grid with the sequence number of u x v where the aircraft i is located is endowed with a parameter value at the moment;
according to real-time flight dynamics, meteorological information and a flight plan, assigning the submesh with the serial number of u multiplied by v where the aircraft i is actually located as
Figure FDA0003444050130000015
And the rest positions are 0, so that the determined grid assignment matrix of the aircraft position information is obtained.
4. The spatial domain grid-based assignment method of claim 1, wherein the probability-based grid assignment matrix is obtained by:
first, the aircraft i passes through the subgrid xu×vHas a probability of P (X ═ X)u×v)＝pu×vThen sub-grid xu×vMatrix is assigned in the grid
Figure FDA0003444050130000016
Is assigned a corresponding position of pu×v(ii) a The coding number x of the sub-gridu×vConverting the matrix into a matrix row number and a matrix column number;
the matrix has a row number of
Figure FDA0003444050130000017
The matrix column number is nu×v≡[u×v-1](modn)+1；
Wherein
Figure FDA0003444050130000018
Mod is a ceiling function, mod is a remainder function;
similarly, for the target airspace A, t is taAssigning probability values to the actual sub grids of each aircraft at each moment; and obtaining the row and column numbers of the matrix corresponding to each row and column.
5. The assignment method based on the airspace grid according to claim 1, wherein the flight flow is: at time interval T ═ T1,tN]The total number of aircraft entering the airspace A; the calculation process is as follows:
first, for t ═ taAt any moment, the numerical values of all the aircraft in the airspace A at each position in the deterministic grid assignment matrix are accumulated and summed to obtain
Figure FDA0003444050130000021
And will be
Figure FDA0003444050130000022
Converting into binary form;
Figure FDA0003444050130000023
then, a binary string is calculated
Figure FDA0003444050130000024
Hamming weight of (i.e. t in airspace A)aTime of flight flow
Figure FDA0003444050130000025
The Hamming weight is the number of 1's in the binary string;
similarly, binary character strings at each moment are respectively calculated
Figure FDA0003444050130000026
Obtaining the corresponding flight flow at each moment;
traversing each moment and comparing the current moment tjIs recorded as
Figure FDA0003444050130000027
According to the relation between the current time and the adjacent time
Figure FDA0003444050130000028
Calculating Hamming distance between two adjacent moments
Figure FDA0003444050130000029
And updating the flight flow value at the next moment:
Figure FDA00034440501300000210
until j is N;
j initializationTaking 1; hamming distance
Figure FDA00034440501300000211
Is directed to binary strings
Figure FDA00034440501300000212
And
Figure FDA00034440501300000213
the elements of (a) are subjected to exclusive or operation and the statistical result is the number value of 1.
6. The spatial domain grid-based assignment method of claim 1, wherein the traffic complexity of each sub-grid is calculated as follows:
first, for sub-grid xlAnd calculating each index of the traffic complexity:
traffic density N (x)l)：N(xl)＝Wk(xl)/(fs(xl)×H)；
Wherein Wk(xl) Representing a grid xlTraffic flow during the kth time period; h represents the flight airspace management altitude; f. ofs(xl) Representing a spatial grid xlThe spherical projection area of (a);
flight status cond (x)l): counting the number of times and time that the aircraft climbs and descends in the kth time period of each grid unit;
③ airplane model mix influence v (x)l): i.e. cell grid xlComplexity due to different aircraft speeds within;
weather influence traffic index: WITI (x)l)＝Nk(xl)×Wk(xl)
Wherein N isk(xl) Indicating that the traffic flow passes through the grid x in the k-th time periodlThe number of times of national convection weather forecast reports; wk(xl) Representing a grid xlFlight flow during the kth time period;
then, the submesh x is calculated using the respective indiceslThe formula of the traffic complexity is as follows:
TC(xl)＝N(xl)×θ(xl)
where theta (x)l) Is a spatial grid xlThe complexity factor is obtained by compounding complexity index factors, and the calculation formula is as follows:
θ(xl)＝cond(xl)×v(xl)×WITI(xl)。
7. the spatial domain grid-based assignment method according to claim 1, wherein the collision probability in the spatial domain a is calculated as follows:
first, for a target airspace A, a grid level r is used0The spatial grid unit of (2) is subjected to grid recursive division; grid level r0Selecting the size of the safety envelope of the root aircraft;
then, M airplanes Y ═ Y are calculated0,y1,...,yj,...,yM-1The probability of flying to different spatial grid cells;
number yjIs coded as xiProbability p of spatial grid cellijExpressed as follows:
pij＝P(X＝xi,Y＝yi)
further, calculating the fuzzy collision probability of each sub-grid according to the probability distribution of each airplane in the airspace grid unit;
coded as xiSpatial grid cell of (1), fuzzy collision probability PiThe formula is:
Figure FDA0003444050130000031
the fuzzy collision probability of all the other spatial grid units finally form a fuzzy collision probability set P' of the unit;
designing spatial gridUnit xiTriple data G ofi(xi,Pi',Si)；SiIs a spatial grid cell xiIn satisfies the probability pijSet of all airplanes not equal to 0;
the mapping relationship is as follows:
Figure FDA0003444050130000032
and is
Figure FDA0003444050130000033
So that f1 -1(Pi')＝xi；
Figure FDA0003444050130000034
And is
Figure FDA0003444050130000035
So that f2 -1(Si)＝xi；
Using set collision probability operator PAScreening the airspace grid units with collision risks, sequentially selecting the ternary group data of each unit, and when P is the number of the ternary group datai'≥PAIf the unit has collision risk, returning the corresponding triple data to be stored in an array set G, otherwise, neglecting the collision risk, and continuously judging the next airspace grid unit; obtaining a new set G until all units are judged;
the set G is the grid cells, collision probabilities and their corresponding aircraft numbers in all the airspaces a at which there is a risk of collision.
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