CN108731686A - A kind of Navigation of Pilotless Aircraft control method and system based on big data analysis - Google Patents
A kind of Navigation of Pilotless Aircraft control method and system based on big data analysis Download PDFInfo
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- CN108731686A CN108731686A CN201810535950.2A CN201810535950A CN108731686A CN 108731686 A CN108731686 A CN 108731686A CN 201810535950 A CN201810535950 A CN 201810535950A CN 108731686 A CN108731686 A CN 108731686A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/20—Instruments for performing navigational calculations
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/10—Simultaneous control of position or course in three dimensions
- G05D1/101—Simultaneous control of position or course in three dimensions specially adapted for aircraft
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Abstract
The invention belongs to Navigation Control technical fields,More particularly to a kind of Navigation of Pilotless Aircraft control method based on big data analysis,The Navigation of Pilotless Aircraft control system based on big data analysis that present invention simultaneously provides a kind of,First data source and the second data source are merged into navigable attribute data respectively and form the first fused data source and the second fused data source,Automatically the controlling element of the identical atural object element in the first fused data source and the second fused data source is chosen respectively and is respectively formed the first controlling element set and the second controlling element set,It converts the first controlling element set and the second controlling element set to form same coordinate space by model,The present invention solves the prior art and exists since the key factor of Navigation Control is the accuracy and real-time of electronic map,But base surveying data and interest point information the fusion performance of existing navigation map are undesirable,The problem of so as to cause that cannot achieve the effect that precise guidance by existing electronic map,With precise guidance,Information science,It is abundant,Fusion accuracy is high,The advantageous effects of multi-source navigation data.
Description
Technical field
The invention belongs to Navigation Control technical field more particularly to a kind of Navigation of Pilotless Aircraft controls based on big data analysis
Method, the Navigation of Pilotless Aircraft control system based on big data analysis that present invention simultaneously provides a kind of.
Background technology
In the today's society that scientific technological advance speed is exceedingly fast, small drone starts to be used among numerous areas,
And certain achievement is achieved, small drone refers to being suitble to short distance short-range flights, can complete target inspection and calamity
One kind of the aircraft of evil monitoring, has very vast potential for future development, many skills covered as small drone
A kind of technology of opposite core in art, navigation and guidance are the emphasis of expert and scholar's research always, it may be said that only guaranteed to lead
Boat and guidance technology reasonable application, small drone can high quality complete task, the prior art exist due to navigation control
The key factor of system is the accuracy and real-time of electronic map, but the base surveying data and interest of existing navigation map
Point information fusion performance is undesirable, the problem of so as to cause that cannot achieve the effect that precise guidance by existing electronic map.
Invention content
The present invention provides a kind of Navigation of Pilotless Aircraft control method and system based on big data analysis, to solve above-mentioned background
The prior art is proposed in technology to exist since the key factor of Navigation Control is the accuracy and real-time of electronic map, but
Base surveying data and interest point information the fusion performance of existing navigation map are undesirable, so as to cause existing electronics is passed through
Map cannot achieve the effect that the problem of precise guidance.
Technical problem solved by the invention is realized using following technical scheme：A kind of nobody based on big data analysis
Machine navigation control method, including：
It chooses two different spaces and is respectively formed the first data source and the second data source, the first data source and second are counted
It merges navigable attribute data respectively according to source and forms the first fused data source and the second fused data source, choose first respectively automatically and melt
Close the controlling element of data source and the identical atural object element in the second fused data source and be respectively formed the first controlling element set and
Second controlling element set converts the first controlling element set and the second controlling element set to form same coordinate by model
Same coordinate space is formed transformation model parameter, according to transformation model parameter by same coordinate by space by least square method
Space converts to form the same coordinate system system by space geometry.
Further, the navigable attribute data include comprising course line title, grade, thematic information, the topology of width navigation
Information and traffic restricted information.
Further, if need to compare field length, type and the corresponding criteria for classification of fusion navigable attribute data differ
It causes, then establishes mutual mapping table, geometrical relationship matching is carried out to attribute field according to mapping table, it will after matched
Corresponding attribute data is updated.
Further, described to choose the identical atural object element control in the first fused data source and the second fused data source respectively automatically
Element processed includes：
Start node and the termination in the first fused data source and the second corresponding controlling element in fused data source are chosen respectively
Node is simultaneously respectively formed first buffering area and second buffering area, judges that first buffering area and second buffering area are handed over the presence or absence of data
Collection, if there are data intersection, judges that controlling element is effective, if controlling element is effective, match control element.
Further, the match control element includes：
If the controlling element precision of first buffering area is higher than the controlling element of second buffering area, by the control of first buffering area
The controlling element of second buffering area, is otherwise corrected the control of first buffering area by the controlling element of element correction second buffering area processed
Element；
If the course line of controlling element indicates inconsistent, if controlling element, which is single, double line, is compatible with course line, two-wire is navigated
Line drawing center line is as single line course line.
Further, the model transformation includes affine transformation, similarity transformation, projective transformation.
Further, the space geometry, which converts, includes：
If the same coordinate space deformation after transformation is substantially uniform, a certain number of control points are acquired, by the control of acquisition
System point carries out same coordinate space using unified mathematical model to be transformed to the same coordinate system system；
If the same coordinate space deformation after transformation is uneven, a certain number of control points are acquired, by the control of acquisition
Point is divided into block of cells, and block of cells is converted using respective mathematical model.
Further, the same coordinate system is united and syncretizing effect is evaluated by square error, evaluated according to syncretizing effect
Fusion process cycle is assessed by interative computation.
Further, edge fit processing is carried out to the same coordinate system system after cycle is assessed and controlling element reunifies definition
It is merged with attribute.
Meanwhile the present invention also provides a kind of Navigation of Pilotless Aircraft control system based on big data analysis, including Navigation Control
Module, the navigation control module are used for based on a kind of realization of the Navigation of Pilotless Aircraft control method based on big data analysis.
Advantageous effects：
1, this patent is respectively formed the first data source and the second data source using two different spaces are chosen, by the first number
Navigable attribute data are merged respectively according to source and the second data source forms the first fused data source and the second fused data source, it is automatic to divide
The controlling element of the identical atural object element in the first fused data source and the second fused data source is not chosen and is respectively formed the first control
Elements combination processed and the second controlling element set, the first controlling element set and the second controlling element set are converted by model
Same coordinate space is formed, same coordinate space is formed into transformation model parameter by least square method, is joined according to transformation model
Number converts same coordinate space by space geometry to form the same coordinate system system, due to the navigation through electronic for vector form
Not homologous data are carried out model transformation by diagram data first, are transferred to the same coordinate space, during reference is photogrammetric
The thought of ripe Remote Sensing Image Correction chooses a series of differences automatically based on coordinate transformation models such as affine, similar, projections
Same place (identical atural object element) in data source, different coordinate systems calculates transformation model using least square method and joins
Then number carries out space geometry transformation to whole picture map datum, unified to the same coordinate system in uniting；Utilize square error
Syncretizing effect is evaluated, and operation is iterated until meeting the requirements to fusion process according to evaluation of estimate；Finally to map
Data carry out edge fit, and element reunifies definition and attribute fusion etc., reaches multi-source navigation data and merges newer purpose, due to
By the abundant fusion of base surveying data and control point information, the effect of existing electronic map precise guidance is realized.
2, this patent using the navigable attribute data include comprising course line title, grade, width navigation thematic information,
Topology information and traffic restricted information, if fusion navigable attribute data need to compare field length, type and corresponding classification
Standard is inconsistent, then establishes mutual mapping table, and geometrical relationship matching, warp are carried out to attribute field according to mapping table
Corresponding attribute data is updated after matching, since the attribute information of navigation data includes the thematic information of various navigation
(course line title, grade, width etc.), topology information and traffic restricted information etc., these are non-for planning, inquiry, guiding
Often important, the fusion situation of attribute data determines the success or failure of navigation data overall applicability from now on.Attribute data fusion needs
Data model merges and carries out object matching on the basis of spatial data fusion, is then carried out to legacy data using newest data
Fusion update, in fusion process, whether with corresponding criteria for classification consistent, if classification if needing to compare field length, type
Standard is inconsistent just to be needed to establish mutual mapping table, is then matched to attribute field, and pass through geometrical relationship
Corresponding attribute data is updated after matching, therefore, has the characteristics that fuse information science, abundant.
3, this patent chooses the identical atural object in the first fused data source and the second fused data source respectively automatically using described
Element controlling element includes the starting section for choosing the first fused data source and the second corresponding controlling element in fused data source respectively
Point and terminal node are simultaneously respectively formed first buffering area and second buffering area, judge whether first buffering area and second buffering area deposit
In data intersection, if there are data intersection, judge that controlling element is effective, if controlling element is effective, match control element, institute
If it includes that the controlling element precision of first buffering area is higher than the controlling element of second buffering area to state match control element, by first
The controlling element of the controlling element correction second buffering area of buffering area, otherwise delays the controlling element of second buffering area correction first
Rush the controlling element in area；If the course line of controlling element indicates inconsistent, if controlling element, which is single, double line, is compatible with course line,
Center line is extracted into as single line course line in two-wire course line.Due to being directed to the specific feature of data in navigation electronic map, a boat is chosen
Line rises, stops node and respectively as buffering area, judges whether the data intersection that two buffering areas are included is sky, if not empty then
Illustrate that this two course lines are course lines of the same name, corresponding node is exactly same place.For pretreated two width with the arrow in region
Spirogram (by taking the layer of course line as an example), it is destination layer to select higher A2 layers of precision, and correction has error.The wherein radius size of buffering area
The matching precision being arranged after slightly being corrected with preceding primary two parts of data is related, and matching precision is high, and buffering area radius is with regard to small, otherwise phase
Instead, such as the single, double line of course line expression wants consistent with each other, otherwise, to handle in advance it, such as the existing single line in course line of the same name
Have the case where two-wire again, to two-wire extraction center line so that it is become single line, pass through above-mentioned fusion, hence it is evident that improve fusion accuracy and
Effect.
4, this patent includes affine transformation, similarity transformation, projective transformation using model transformation, due to utilizing a certain number
It learns model to go to simulate or approach, common model has affine transformation, similarity transformation and projective transformation.This transformation not only can be real
Conversion between existing different coordinate systems, and can eliminate or weaken deformation error regular in gatherer process；Simultaneously
Corresponding precision information is provided by compensating computation, prior information and control constraints are provided for the adjustment of figure, for multi-source navigation number
According to fusion lay the first stone.
5, this patent includes using space geometry transformation：If the same coordinate space deformation after transformation is substantially uniform,
A certain number of control points are then acquired, the control point of acquisition is converted same coordinate space using unified mathematical model
It unites for the same coordinate system；If the same coordinate space deformation after transformation is uneven, a certain number of control points are acquired, will be acquired
Control point be divided into block of cells, block of cells is converted using respective mathematical model, since integral transformation is that acquisition is certain
The control point of quantity converts whole picture map using unified mathematical model, this to become each on whole picture map datum of changing commanders
The deformation of point is regarded as roughly the same.It is uniform for deformation comparison, and when deforming less big map datum and using integral transformation, one
As disclosure satisfy that transduced precision requirement.Only carried out bulk processing by the method for integral transformation, it is also necessary to it is larger to deformation ratio and
The method that non-uniform map datum uses block transform is deformed, to reach higher precision.The method of block transform is will to control
System point is divided into some small blocks, is then converted using respective mathematical model to each region.The setting of block is smaller,
It is higher to correct precision, but arithmetic speed is slower.Therefore, experiments have shown that block is set as 10km × 10km, if preceding primary correction
Matching precision is high afterwards, and block can suitably increase, and can be 15km × 15km, therefore, improves arithmetic speed.
6, this patent is used to unite the same coordinate system and be evaluated syncretizing effect by square error, according to syncretizing effect
Evaluation assesses fusion process cycle by interative computation, unites to the same coordinate system after cycle is assessed and carries out edge fit processing
And controlling element reunifies definition and attribute fusion, due to carrying out space geometry transformation to whole picture map datum, by it
In the unified system to the same coordinate system；Syncretizing effect is evaluated using square error, and according to evaluation of estimate to fusion process into
Row iteration operation is until meeting the requirements；Edge fit finally is carried out to map datum, element reunifies definition and attribute fusion etc., reaches
Newer purpose is merged to multi-source navigation data.
7, this patent is using including navigation control module, the navigation control module be used for based on one kind based on big data
The realization of the Navigation of Pilotless Aircraft control method of analysis, improves the practicability of navigation.
Description of the drawings
Fig. 1 is a kind of Navigation of Pilotless Aircraft control method flow chart based on big data analysis of the present invention；
Fig. 2 is a kind of Navigation of Pilotless Aircraft control method module map based on big data analysis of the present invention.
Specific implementation mode
The present invention is described further below in conjunction with attached drawing：
In figure：
S101- chooses two different spaces and is respectively formed the first data source and the second data source；
S102- by the first data source and the second data source merge respectively navigable attribute data formed the first fused data source and
Second fused data source；
The control that S103- chooses the identical atural object element in the first fused data source and the second fused data source respectively automatically is wanted
Element and be respectively formed the first controlling element set and the second controlling element set；
S104- converts the first controlling element set and the second controlling element set by model to form same coordinate sky
Between；
Same coordinate space is formed transformation model parameter by S105- by least square method；
S106- converts same coordinate space by space geometry according to transformation model parameter to form the same coordinate system system；
The first data sources of 1-, the second data sources of 2-, the first fused datas of 3- source, the second fused datas of 4- source, 5- first are controlled
Elements combination processed, the second controlling elements of 6- set, the same coordinate spaces of 7-, 8- the same coordinate systems system；
Embodiment：
The present embodiment：As shown in Figure 1, 2, a kind of Navigation of Pilotless Aircraft control method based on big data analysis, including：
It chooses two different spaces and is respectively formed the first data source 1 and the second data source 2S101, by the first data source 1
It merges navigable attribute data respectively with the second data source 2 and forms the first fused data source 3 and the second fused data source 4S102, from
It moves the controlling element for choosing 4 identical atural object element of the first fused data source 3 and the second fused data source respectively and is respectively formed
First controlling element set 5 and the second controlling element set 6S103, by the first controlling element set 5 and the second controlling element collection
It closes 6 to convert to form same coordinate space 7S104 by model, same coordinate space 7 is formed by least square method and becomes mold changing
Shape parameter S105 converts same coordinate space 7 to form the same coordinate system system by space geometry according to transformation model parameter
8S106。
Due to being respectively formed the first data source and the second data source using two different spaces of selection, by the first data source
Navigable attribute data are merged respectively with the second data source and form the first fused data source and the second fused data source, are selected respectively automatically
It takes the controlling element of the identical atural object element in the first fused data source and the second fused data source and is respectively formed the first control and want
Element set and the second controlling element set, the first controlling element set and the second controlling element set are converted by model and to be formed
Same coordinate space is formed transformation model parameter by same coordinate space by least square method, will according to transformation model parameter
Same coordinate space converts to form the same coordinate system system by space geometry, due to the map of navigation electronic number for vector form
According to, not homologous data are subjected to model transformation first, are transferred to the same coordinate space, it is ripe during reference is photogrammetric
Remote Sensing Image Correction thought, based on it is affine, similar, projection etc. coordinate transformation models, choose a series of different data automatically
Same place (identical atural object element) in source, different coordinate systems, calculates transformation model parameter, so using least square method
Space geometry transformation is carried out to whole picture map datum afterwards, is unified to the same coordinate system in uniting；Using square error to melting
It closes effect to be evaluated, and operation is iterated until meeting the requirements to fusion process according to evaluation of estimate；Finally to map datum
Edge fit is carried out, element reunifies definition and attribute fusion etc., reaches multi-source navigation data and merges newer purpose, due to by base
The abundant fusion of plinth surveying and mapping data and control point information realizes the effect of existing electronic map precise guidance.
The navigable attribute data include thematic information, topology information and the friendship navigated comprising course line title, grade, width
Logical restricted information.
If fusion navigable attribute data to need to compare field length, type and corresponding criteria for classification inconsistent, build
Vertical mutual mapping table carries out geometrical relationship matching according to mapping table to attribute field, will be corresponding after matched
Attribute data is updated.
Due to including comprising course line title, grade, thematic information, the topology of width navigation using the navigable attribute data
Information and traffic restricted information, if fusion navigable attribute data need to compare field length, type and corresponding criteria for classification
It is inconsistent, then mutual mapping table is established, geometrical relationship matching is carried out to attribute field according to mapping table, it is matched
Corresponding attribute data is updated afterwards, since the attribute information of navigation data includes the thematic information (course line of various navigation
Title, grade, width etc.), topology information and traffic restricted information etc., these are very heavy for planning, inquiry, guiding
It wants, the fusion situation of attribute data determines the success or failure of navigation data overall applicability from now on.Attribute data fusion is needed in data
Object matching is carried out on the basis of Model Fusion and spatial data fusion, and then legacy data is merged using newest data
Update, in fusion process, whether with corresponding criteria for classification consistent, if criteria for classification if needing to compare field length, type
It is inconsistent just to need to establish mutual mapping table, then attribute field is matched, and after being matched by geometrical relationship
Corresponding attribute data is updated, therefore, has the characteristics that fuse information science, abundant.
It is described automatic to choose the first fused data source 3 respectively and the 4 identical atural object element control of the second fused data source is wanted
Element includes：
Start node and the end of 4 corresponding controlling element of the first fused data source 3 and the second fused data source are chosen respectively
Only node and it is respectively formed first buffering area and second buffering area, judges that first buffering area and second buffering area whether there is data
If intersection judges that controlling element is effective there are data intersection, if controlling element is effective, match control element.
The match control element includes：
If the controlling element precision of first buffering area is higher than the controlling element of second buffering area, by the control of first buffering area
The controlling element of second buffering area, is otherwise corrected the control of first buffering area by the controlling element of element correction second buffering area processed
Element；
If the course line of controlling element indicates inconsistent, if controlling element, which is single, double line, is compatible with course line, two-wire is navigated
Line drawing center line is as single line course line.
Due to choosing the identical atural object element in the first fused data source and the second fused data source respectively automatically using described
Controlling element include choose respectively the first fused data source and the second corresponding controlling element in fused data source start node and
Terminal node is simultaneously respectively formed first buffering area and second buffering area, judges first buffering area and second buffering area with the presence or absence of number
According to intersection, if there are data intersection, judge that controlling element is effective, if controlling element is effective, match control element, described
If including that the controlling element precision of first buffering area is higher than the controlling element of second buffering area with controlling element, by the first buffering
The controlling element of the controlling element correction second buffering area in area, otherwise corrects first buffering area by the controlling element of second buffering area
Controlling element；It, will be double if controlling element, which is single, double line, is compatible with course line if the course line of controlling element indicates inconsistent
Center line is extracted as single line course line in line course line.Due to being directed to the specific feature of data in navigation electronic map, choose a course line rise,
Only node and respectively as buffering area judges whether the data intersection that two buffering areas are included is empty, is then illustrated if not empty
This two course lines are course lines of the same name, and corresponding node is exactly same place.For pretreated two width with the polar plot in region
(by taking the layer of course line as an example), it is destination layer to select higher A2 layers of precision, and correction has error.The wherein radius size setting of buffering area
Matching precision after slightly being corrected with preceding primary two parts of data is related, and matching precision is high, and buffering area radius is on the contrary on the contrary, example with regard to small
Single, double line as course line indicates wants consistent with each other, otherwise, to handle in advance it, and such as existing single line in course line of the same name has again
The case where two-wire, makes it become single line two-wire extraction center line, passes through above-mentioned fusion, hence it is evident that improve fusion accuracy and effect
Fruit.
The model transformation includes affine transformation, similarity transformation, projective transformation.
Due to including affine transformation, similarity transformation, projective transformation using model transformation, due to utilizing a certain mathematical modulo
Type goes to simulate or approach, and common model has affine transformation, similarity transformation and projective transformation.This transformation not only may be implemented not
With the conversion between coordinate system, and it can eliminate or weaken deformation error regular in gatherer process；Pass through simultaneously
Compensating computation provides corresponding precision information, and prior information and control constraints are provided for the adjustment of figure, is multi-source navigation data
Fusion lays the first stone.
The space geometry converts：
If the same coordinate space 7 after transformation deforms substantially uniform, a certain number of control points are acquired, by the control of acquisition
System point carries out same coordinate space 7 using unified mathematical model to be transformed to the same coordinate system system 8；
If the same coordinate space 7 after transformation deforms uneven, a certain number of control points are acquired, by the control of acquisition
Point is divided into block of cells, and block of cells is converted using respective mathematical model.
Due to including using space geometry transformation：If the same coordinate space deformation after transformation is substantially uniform, adopt
Collect a certain number of control points, same coordinate space be transformed to together by the control point of acquisition using unified mathematical model
One coordinate system；If the same coordinate space deformation after transformation is uneven, a certain number of control points are acquired, by the control of acquisition
System point is divided into block of cells, and block of cells is converted using respective mathematical model, since integral transformation is acquisition certain amount
Control point, whole picture map is converted using unified mathematical model, this change is changed commanders each point on whole picture map datum
Deformation is regarded as roughly the same.It is uniform for deformation comparison, and when deforming less big map datum and using integral transformation, general energy
Enough meet transduced precision requirement.Bulk processing has only been carried out by the method for integral transformation, it is also necessary to and deformation larger to deformation ratio
The method that non-uniform map datum uses block transform, to reach higher precision.The method of block transform is by control point
It is divided into some small blocks, then each region is converted using respective mathematical model.The setting of block is smaller, corrects
Precision is higher, but arithmetic speed is slower.Therefore, experiments have shown that block is set as 10km × 10km, if after preceding primary correction
With precision height, block can suitably increase, and can be 15km × 15km, therefore, improve arithmetic speed.
The same coordinate system system 8 evaluates syncretizing effect by square error, is passed through repeatedly according to syncretizing effect evaluation
Fusion process cycle is assessed for operation.
Definition and attribute are reunified to the 8 progress edge fit processing of the same coordinate system system and controlling element after cycle is assessed
Fusion.
Due to being evaluated syncretizing effect by square error using uniting the same coordinate system, evaluated according to syncretizing effect
By interative computation to fusion process cycle assess, cycle assess after to the same coordinate system unite carry out edge fit processing and
Controlling element reunifies definition and attribute fusion, due to carrying out space geometry transformation to whole picture map datum, is unified
In uniting to the same coordinate system；Syncretizing effect is evaluated using square error, and is changed to fusion process according to evaluation of estimate
For operation until meeting the requirements；Edge fit finally is carried out to map datum, element reunifies definition and attribute fusion etc., reaches more
Source navigation data merges newer purpose.
Meanwhile the present invention also provides a kind of Navigation of Pilotless Aircraft control system based on big data analysis, including Navigation Control
Module, the navigation control module are used for a kind of unmanned plane based on big data analysis based on 1~claim 9 of claim
The realization of navigation control method.
Due to using including navigation control module, the navigation control module be used for based on one kind based on big data analysis
Navigation of Pilotless Aircraft control method realization, improve the practicability of navigation.
Operation principle：
This patent is respectively formed the first data source and the second data source by choosing two different spaces, by the first data
Source and the second data source merge navigable attribute data and form the first fused data source and the second fused data source, automatic difference respectively
It chooses the controlling element of the identical atural object element in the first fused data source and the second fused data source and is respectively formed the first control
First controlling element set and the second controlling element set are converted shape by elements combination and the second controlling element set by model
At same coordinate space, same coordinate space is formed into transformation model parameter by least square method, according to transformation model parameter
Same coordinate space is converted to form the same coordinate system system by space geometry, due to the map of navigation electronic for vector form
Not homologous data are carried out model transformation by data first, are transferred to the same coordinate space, use for reference it is photogrammetric at
The thought of ripe Remote Sensing Image Correction chooses a series of different numbers automatically based on coordinate transformation models such as affine, similar, projections
According to the same place (identical atural object element) in source, different coordinate systems, transformation model parameter is calculated using least square method,
Then space geometry transformation is carried out to whole picture map datum, is unified to the same coordinate system in uniting；Utilize square error pair
Syncretizing effect is evaluated, and is iterated operation until meeting the requirements to fusion process according to evaluation of estimate；Finally to map number
According to edge fit is carried out, element reunifies definition and attribute fusion etc., reaches multi-source navigation data and merges newer purpose, the present invention
It solves the prior art to exist since the key factor of Navigation Control is the accuracy and real-time of electronic map, but existing
Navigation map base surveying data and interest point information fusion performance it is undesirable, so as to cause by existing electronic map not
The problem of capable of achieving the effect that precise guidance, has precise guidance, information science, abundant, fusion accuracy height, multi-source navigation data
Advantageous effects.
Using technical scheme of the present invention or those skilled in the art under the inspiration of technical solution of the present invention, design
Go out similar technical solution, and reach above-mentioned technique effect, is to fall into protection scope of the present invention.
Claims (10)
1. a kind of Navigation of Pilotless Aircraft control method based on big data analysis, which is characterized in that including：
It chooses two different spaces and is respectively formed the first data source and the second data source, by the first data source and the second data source
Fusion navigable attribute data form the first fused data source and the second fused data source respectively, choose the first fusion number respectively automatically
According to the identical atural object element in source and the second fused data source controlling element and be respectively formed the first controlling element set and second
First controlling element set and the second controlling element set are converted to form same coordinate sky by controlling element set by model
Between, same coordinate space is formed into transformation model parameter by least square method, it is according to transformation model parameter that same coordinate is empty
Between converted by space geometry to be formed the same coordinate system system.
2. a kind of Navigation of Pilotless Aircraft control method based on big data analysis according to claim 1, which is characterized in that institute
It includes comprising course line title, grade, the thematic information of width navigation, topology information and traffic limitation letter to state navigable attribute data
Breath.
3. a kind of Navigation of Pilotless Aircraft control method based on big data analysis according to claim 1, which is characterized in that if
Fusion navigable attribute data need to compare that field length, type and corresponding criteria for classification are inconsistent, then establish mutual reflects
Penetrate relation table, according to mapping table to attribute field carry out geometrical relationship matching, it is matched after by corresponding attribute data into
Row update.
4. a kind of Navigation of Pilotless Aircraft control method based on big data analysis according to claim 1, which is characterized in that institute
It states and automatic choose the identical atural object element controlling element in the first fused data source and the second fused data source respectively and include：
The start node and terminal node in the first fused data source and the second corresponding controlling element in fused data source are chosen respectively
And it is respectively formed first buffering area and second buffering area, judge that first buffering area and second buffering area whether there is data intersection,
If there are data intersection, judge that controlling element is effective, if controlling element is effective, match control element.
5. a kind of Navigation of Pilotless Aircraft control method based on big data analysis according to claim 4, which is characterized in that institute
Stating match control element includes：
If the controlling element precision of first buffering area is higher than the controlling element of second buffering area, the control of first buffering area is wanted
The controlling element of element correction second buffering area, otherwise control that the controlling element of second buffering area is corrected to first buffering area are wanted
Element；
If the course line of controlling element indicates inconsistent, if controlling element, which is single, double line, is compatible with course line, two-wire course line is carried
Take center line as single line course line.
6. a kind of Navigation of Pilotless Aircraft control method based on big data analysis according to claim 1, which is characterized in that institute
It includes affine transformation, similarity transformation, projective transformation to state model transformation.
7. a kind of Navigation of Pilotless Aircraft control method based on big data analysis according to claim 1, which is characterized in that institute
Stating space geometry transformation includes：
If the same coordinate space deformation after transformation is substantially uniform, a certain number of control points are acquired, by the control point of acquisition
Same coordinate space be transformed to the same coordinate system system using unified mathematical model；
If the same coordinate space deformation after transformation is uneven, a certain number of control points are acquired, by the control point of acquisition point
At block of cells, block of cells is converted using respective mathematical model.
8. a kind of Navigation of Pilotless Aircraft control method based on big data analysis according to claim 1, which is characterized in that will
The same coordinate system system evaluates syncretizing effect by square error, according to syncretizing effect evaluation by interative computation to fusion
Process cycle is assessed.
9. a kind of Navigation of Pilotless Aircraft control method based on big data analysis according to claim 8, which is characterized in that
Edge fit processing is carried out to the same coordinate system system after cycle assessment and controlling element reunifies definition and attribute merges.
10. a kind of Navigation of Pilotless Aircraft control system based on big data analysis, which is characterized in that including navigation control module, institute
Navigation control module is stated for a kind of Navigation of Pilotless Aircraft control based on big data analysis based on 1~claim 9 of claim
The realization of method processed.
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