CN104808679A - Flight path predication-based general aviation AIP file intelligent matching method - Google Patents
Flight path predication-based general aviation AIP file intelligent matching method Download PDFInfo
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Abstract
The invention discloses a flight path predication-based general aviation AIP file intelligent matching method. The method comprises steps: a mapping relationship between a flight data compilation file and geographic information is built, and an XML configuration file is generated; flight path information is recorded; a movement trend of an aircraft is predicted on the basis of a polynomial prediction method; points of interest (POI) are selected; the flight data compilation file is searched reversely; and the like. The flight path predication-based general aviation AIP file intelligent matching method has the following advantages that the mapping relationship between the flight data compilation file and the geographic information is built, and a brand-new easy-to-manage file hierarchy is formed; by adopting the flight path predication method, intelligent file matching is realized, and the problem that the traditional file is hard to search is solved; computation is simple, and reliability is strong; and a more convenient, intelligent and three-dimensional flight information service can be provided.
Description
Technical field
The invention belongs to blank pipe technical field of automation, particularly relate to a kind of General Aviation AIP based on Flight Trajectory Prediction (Aeronautial Information Publication, navigational information collects) file Intelligent Matching method.
Background technology
General Aviation refers to and uses civil aircraft to be engaged in Civil Aviation Activities beyond public air transport, multiple industries such as events in operation cover agriculture, woods, herd, fishing, industry, building, scientific research, traffic, amusement.The particular content of General Aviation embraces a wide spectrum of ideas, and has maneuverability, the feature such as rapidly and efficiently, in the last few years, along with the development of civil aviaton of China cause and the opening of low altitude airspace, the industry size expanding day of General Aviation, flight demand is gradually vigorous, therefore has very large market outlook.
Navigational intelligence service is the important component part in flight service.Navigational intelligence service is provided to be the basis of safe flight to unit accurately and timely.General Aviation operation has very strong dirigibility, and airborne equipment is relatively simple, therefore, requires very high in General Aviation to navigational intelligence service convenience, ease for use.Navigational intelligence service comprises provides chart, navigational information collect and inform the multinomial contents such as notice to navigator to pilot.Chart and navigational information assembling file refer in flight course the file such as regulations handbook, airport and en-route data needing to use, and quantity is large, and content is numerous and diverse.Traditional navigational information ways of distribution provides a large amount of papery version file to unit, uses very inconvenience, be therefore unsuitable for General Aviation.
At present, both at home and abroad there is a lot of manufacturer have developed to be used in EFB (the Electronic Flight Bag system on intelligent movable equipment, EFB), this EFB, by chart and navigational information assembling file electronization, improves the convenience of use.But also there is Railway Project, as these manufacturers mostly are planemaker, as Boeing, Air Passenger etc., have very strong monopoly, therefore, equipment price is high, and maintenance cost is huge simultaneously.Because the operating cost of General Aviation is lower, thus do not possess the condition being extensively equipped with EFB.In addition, EFB is not further processed navigational information file, still needs to browse the file that just can find and need in-flight by file from level to level.
In view of the foregoing, General Aviation is badly in need of a kind of intellectual search method of electronics navigational information assembling file, solves complicated ground ff problem in traditional approach and existing EFB, thus ensures the flight safety of General Aviation.
Summary of the invention
In order to solve the problem, one is the object of the present invention is to provide to be easy to management, achieve the Intelligent Matching of file, break away from the problem that traditional heap file searches difficulty, the General Aviation AIP file Intelligent Matching method based on Flight Trajectory Prediction that the navigational intelligence of intelligent three-dimensional can be provided to serve.
In order to achieve the above object, the General Aviation AIP file Intelligent Matching method based on Flight Trajectory Prediction provided by the invention comprises the following step carried out in order:
Step (1) is set up the mapping relations of navigational information assembling file and geography information and is generated the S01 stage of XML configuration file: in initial navigational information assembling file, comprise course line, guidance station, Aerial Ports File catalogue arrange in alphabetical order, arrange these files successively, and the mapping relations between navigational information assembling file and geography information are described self-defined two XML configuration file;
The S02 stage of step (2) record flight path information: in flight course, current 5 the up-to-date track points information of aircraft real time record, comprise speed, longitude and latitude, deflection, and these data are stored in local database;
The S03 stage that step (3) is predicted based on the movement tendency of polynomial prediction method to aircraft: establish t
i(i=1,2,3 ..., n) moment target direction angle s (t
i) available one group of orthogonal polynomial function of time represents, then according to t
i(i=1,2,3 ..., n) the measured value x at moment target direction angle
iadopt least square method to coefficient a
jcarry out least-squares estimation to obtain
last according to coefficient
to (t
n+ dt) moment target direction angle predicts;
The S04 stage of step (4) screening POI point of interest: the target direction angle according to prediction defines a deflection nargin θ, geography information in traversal XML configuration file, utilize the mapping relations between geography information and navigational information assembling file, the point these with navigational information assembling file attribute is defined as POI point of interest, the declinate α between POI point of interest and the target direction angle of prediction is calculated afterwards according to the latitude and longitude coordinates of aircraft, and judge whether declinate α is less than deflection nargin θ, if declinate α is within deflection nargin θ, continue to calculate the distance between this POI point of interest and aircraft, be exactly the highest point of matching degree apart from minimum point,
The S05 stage of step (5) reverse find navigational information assembling file: obtain the mapping relations between navigational information assembling file and geography information by analyzing XML configuration file, namely according to the geography information reverse find of the POI point of interest of coupling to corresponding navigational information assembling file, thus the Intelligent Matching of navigational information assembling file can be realized.
In step (3), the described method predicted based on the movement tendency of polynomial prediction method to aircraft comprises the following step performed in order:
1) t is established
i(i=1,2,3 ..., n) moment target direction angle s (t
i) an available orthogonal polynomial function of time represents, wherein t
i=iT, T are the sampling interval of track:
2) according to t
i(i=1,2,3 ..., n) the measured value x at moment target direction angle
iadopt least square method to coefficient a
jcarry out least-squares estimation, can be solved by following formula:
A=(P
T·P)
-1P
TX (2)
In formula:
Therefore the optimal estimation of target direction angle s (t) is:
Formula (3) so just can be utilized (t
n+ dt) the target direction angle in moment predicts, that is:
In above-mentioned formula, n=5, n represent historical track sampled point, x
ibe in the S02 stage database export 5 prescriptions to angular data, the deflection of t is exactly
then the polynomial function at target direction angle is:
Recycle 5 up-to-date prescriptions to angular data, adopt formula (2) to determine coefficient a
ileast-squares estimation
this makes it possible to basis
to t
nthe movement locus in moment is predicted, that is:
In step (4), the method for described screening POI point of interest comprises the following step performed in order:
1) define a deflection nargin θ according to the target direction angle of prediction, deflection nargin θ between 0 °-180 °, according to the motor-driven parameter of navigation aircraft, generally must be taken as 60 ° by this deflection nargin θ;
2) analyzing XML configuration file, obtains navigational information assembling file and geography information, has the POI point of interest of navigational information assembling file attribute according to geographical information definition;
3) according to the latitude and longitude coordinates (x of aircraft
0, y
0), the latitude and longitude coordinates (x of POI point of interest
1, y
1), and the target direction angle φ of prediction calculates the declinate α between POI point of interest and the target direction angle of prediction, concrete formula is as follows:
4) judge whether declinate α is less than deflection nargin θ, if declinate is within deflection nargin θ, then calculating the distance between this POI point of interest and aircraft, then sort to these POI points of interest by distance, is exactly the highest point of matching degree apart from minimum point.
General Aviation AIP file Intelligent Matching method based on Flight Trajectory Prediction provided by the invention has the following advantages: the mapping relations 1. establishing navigational information assembling file and geography information, defines the brand-new file hierarchy being easy to manage.2. have employed the Forecasting Methodology of flight path, achieve the Intelligent Matching of file, solve the problem of traditional ff difficulty.3. computing is simple, and reliability is strong.4. more convenient, intelligent, three-dimensional navigational intelligence service can be provided.
Accompanying drawing explanation
Fig. 1 is the General Aviation AIP file Intelligent Matching method flow diagram based on Flight Trajectory Prediction provided by the invention.
Fig. 2 is based on the method flow diagram that the movement tendency of polynomial prediction method to aircraft is predicted in the present invention.
Fig. 3 is the method flow diagram screening POI point of interest in the present invention.
Fig. 4 is the schematic diagram according to the target direction angle definition deflection nargin θ of prediction in the present invention.
Embodiment
Below in conjunction with accompanying drawing and instantiation, the General Aviation AIP file Intelligent Matching method based on Flight Trajectory Prediction provided by the invention is described in detail.
As shown in Figure 1, the General Aviation AIP file Intelligent Matching method based on Flight Trajectory Prediction provided by the invention comprises the following step performed in order:
Step (1) is set up the mapping relations of navigational information assembling file and geography information and is generated the S01 stage of XML configuration file: in initial navigational information assembling file, comprise course line, guidance station, Aerial Ports File catalogue arrange in alphabetical order, arrange these files successively, and self-defined two XML (Extensible Markup Language, extend markup language) configuration file describes the mapping relations between navigational information assembling file and geography information;
The S02 stage of step (2) record flight path information: in flight course, current 5 the up-to-date track points information of aircraft real time record, comprise speed, longitude and latitude, deflection etc., and these data are stored in local database;
The S03 stage that step (3) is predicted based on the movement tendency of polynomial prediction method to aircraft: establish t
i(i=1,2,3 ..., n) moment target direction angle s (t
i) available one group of orthogonal polynomial function of time represents, then according to t
i(i=1,2,3 ..., n) the measured value x at moment target direction angle
iadopt least square method to coefficient a
jcarry out least-squares estimation to obtain
last basis
to (t
n+ dt) moment target direction angle predicts;
As shown in Figure 2, the described method predicted based on the movement tendency of polynomial prediction method to aircraft comprises the following step performed in order:
1) t is established
i(i=1,2,3 ..., n) moment target direction angle s (t
i) an available orthogonal polynomial function of time represents, wherein t
i=iT, T are the sampling interval of track:
2) according to t
i(i=1,2,3 ..., n) the measured value x at moment target direction angle
iadopt least square method to coefficient a
jcarry out least-squares estimation, can be solved by following formula:
A=(P
T·P)
-1P
TX (2)
In formula:
Therefore the optimal estimation of target direction angle s (t) is:
Formula (3) so just can be utilized (t
n+ dt) the target direction angle in moment predicts, that is:
In above-mentioned formula, n=5 (n represents historical track sampled point), x
ibe in the S02 stage database export 5 prescriptions to angular data, the deflection of t is exactly
then the polynomial function at target direction angle is:
Recycle 5 up-to-date prescriptions to angular data, adopt formula (2) to determine coefficient a
ileast-squares estimation
this makes it possible to basis
to t
nthe movement locus in moment is predicted, that is:
The S04 stage of step (4) screening POI point of interest: the target direction angle according to prediction defines a deflection nargin θ, geography information in traversal XML configuration file, utilize the mapping relations between geography information and navigational information assembling file, the point these with navigational information assembling file attribute is defined as POI point of interest, the declinate α between POI point of interest and the target direction angle of prediction is calculated afterwards according to aircraft latitude and longitude coordinates, and judge whether declinate α is less than deflection nargin θ, if declinate α is within deflection nargin θ, continue to calculate the distance between this POI point of interest and aircraft, be exactly the highest point of matching degree apart from minimum point,
As shown in Figure 3, the method for described screening POI point of interest comprises the following step performed in order:
1) as shown in Figure 4, target direction angle according to prediction defines a deflection nargin θ, this deflection nargin θ must between 0 °-180 °, and can not be excessive or too small, otherwise just lose the effect of screening POI point of interest, according to the motor-driven parameter of navigation aircraft, generally deflection nargin θ is taken as 60 °;
2) analyzing XML configuration file, obtains navigational information assembling file and geography information, has the POI point of interest of navigational information assembling file attribute according to geographical information definition;
3) according to the latitude and longitude coordinates (x of oneself aircraft
0, y
0), the latitude and longitude coordinates (x of POI point of interest
1, y
1), and the target direction angle φ of prediction calculates the declinate α between POI point of interest and the target direction angle of prediction, concrete formula is as follows:
4) judge whether declinate α is less than deflection nargin θ, if declinate is within deflection nargin θ, then calculating the distance between this POI point of interest and aircraft, then sort to these POI points of interest by distance, is exactly the highest point of matching degree apart from minimum point.
The S05 stage of step (5) reverse find navigational information assembling file: obtain the mapping relations between navigational information assembling file and geography information by analyzing XML configuration file, namely according to the geography information reverse find of the POI point of interest of coupling to corresponding navigational information assembling file, thus the Intelligent Matching of navigational information assembling file can be realized.
Claims (3)
1., based on a General Aviation AIP file Intelligent Matching method for Flight Trajectory Prediction, it is characterized in that: it comprises the following step performed in order:
Step (1) is set up the mapping relations of navigational information assembling file and geography information and is generated the S01 stage of XML configuration file: in initial navigational information assembling file, comprise course line, guidance station, Aerial Ports File catalogue arrange in alphabetical order, arrange these files successively, and the mapping relations between navigational information assembling file and geography information are described self-defined two XML configuration file;
The S02 stage of step (2) record flight path information: in flight course, current 5 the up-to-date track points information of aircraft real time record, comprise speed, longitude and latitude, deflection, and these data are stored in local database;
The S03 stage that step (3) is predicted based on the movement tendency of polynomial prediction method to aircraft: establish t
i(i=1,2,3 ..., n) moment target direction angle s (t
i) available one group of orthogonal polynomial function of time represents, then according to t
i(i=1,2,3 ..., n) the measured value x at moment target direction angle
iadopt least square method to coefficient a
jcarry out least-squares estimation to obtain
last according to coefficient
to (t
n+ dt) moment target direction angle predicts;
The S04 stage of step (4) screening POI point of interest: the target direction angle according to prediction defines a deflection nargin θ, geography information in traversal XML configuration file, utilize the mapping relations between geography information and navigational information assembling file, the point these with navigational information assembling file attribute is defined as POI point of interest, the declinate α between POI point of interest and the target direction angle of prediction is calculated afterwards according to the latitude and longitude coordinates of aircraft, and judge whether declinate α is less than deflection nargin θ, if declinate α is within deflection nargin θ, continue to calculate the distance between this POI point of interest and aircraft, be exactly the highest point of matching degree apart from minimum point,
The S05 stage of step (5) reverse find navigational information assembling file: obtain the mapping relations between navigational information assembling file and geography information by analyzing XML configuration file, namely according to the geography information reverse find of the POI point of interest of coupling to corresponding navigational information assembling file, thus the Intelligent Matching of navigational information assembling file can be realized.
2. the General Aviation AIP file Intelligent Matching method based on Flight Trajectory Prediction according to claim 1, it is characterized in that: in step (3), the described method predicted based on the movement tendency of polynomial prediction method to aircraft comprises the following step performed in order:
1) t is established
i(i=1,2,3 ..., n) moment target direction angle s (t
i) an available orthogonal polynomial function of time represents, wherein t
i=iT, T are the sampling interval of track:
2) according to t
i(i=1,2,3 ..., n) the measured value x at moment target direction angle
iadopt least square method to coefficient a
jcarry out least-squares estimation, can be solved by following formula:
A=(P
T·P)
-1P
TX (2)
In formula:
Therefore the optimal estimation of target direction angle s (t) is:
Formula (3) so just can be utilized (t
n+ dt) the target direction angle in moment predicts, that is:
In above-mentioned formula, n=5, n represent historical track sampled point, x
ibe in the S02 stage database export 5 prescriptions to angular data, the deflection of t is exactly
then the polynomial function at target direction angle is:
Recycle 5 up-to-date prescriptions to angular data, adopt formula (2) to determine coefficient a
ileast-squares estimation
this makes it possible to basis
to t
nthe movement locus in moment is predicted, that is:
3. the General Aviation AIP file Intelligent Matching method based on Flight Trajectory Prediction according to claim 1, it is characterized in that: in step (4), the method for described screening POI point of interest comprises the following step performed in order:
1) define a deflection nargin θ according to the target direction angle of prediction, deflection nargin θ between 0 °-180 °, according to the motor-driven parameter of navigation aircraft, generally must be taken as 60 ° by this deflection nargin θ;
2) analyzing XML configuration file, obtains navigational information assembling file and geography information, has the POI point of interest of navigational information assembling file attribute according to geographical information definition;
3) according to the latitude and longitude coordinates (x of aircraft
0, y
0), the latitude and longitude coordinates (x of POI point of interest
1, y
1), and the target direction angle φ of prediction calculates the declinate α between POI point of interest and the target direction angle of prediction, concrete formula is as follows:
4) judge whether declinate α is less than deflection nargin θ, if declinate is within deflection nargin θ, then calculating the distance between this POI point of interest and aircraft, then sort to these POI points of interest by distance, is exactly the highest point of matching degree apart from minimum point.
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CN110608737A (en) * | 2019-09-16 | 2019-12-24 | 中国民航大学 | Land-based radio navigation station selection method based on total system error estimation |
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CN112911497A (en) * | 2019-12-02 | 2021-06-04 | 南京航空航天大学 | Real-time prediction method and system for track of cooperative unmanned aerial vehicle |
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