CN107063259A - A kind of Data Association and electronic equipment - Google Patents
A kind of Data Association and electronic equipment Download PDFInfo
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- CN107063259A CN107063259A CN201710135102.8A CN201710135102A CN107063259A CN 107063259 A CN107063259 A CN 107063259A CN 201710135102 A CN201710135102 A CN 201710135102A CN 107063259 A CN107063259 A CN 107063259A
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- G—PHYSICS
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- 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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Abstract
The invention discloses a kind of Data Association and electronic equipment, including：The N group sensing datas that the M sensor collection being arranged on the flight equipment obtains the flight track for being used to characterize the flight equipment are obtained, M is the integer more than or equal to 2, and N is the integer more than zero；The N groups sensing data is divided into shared data and identity data, wherein, the shared data are the data that the M sensor can be gathered, and the identity data is for the data for the type for characterizing the M sensor；The shared data and the identity data are utilized respectively, the flight track is associated with the flight path in flight path storehouse, wherein, the flight path storehouse includes at least one flight track of at least one flight equipment., there is the technical problem under-utilized to identity information for solving track association of the prior art in the technical scheme provided by the present invention.
Description
Technical field
The present invention relates to electronic technology field, more particularly to a kind of Data Association and electronic equipment.
Background technology
With developing rapidly for computer, data fusion has been developed rapidly, and be widely used to target following,
The military and civilian such as Situation Assessment field.In recent years, scholars are in order to solve the problems, such as the multiple shot array of data correlation, it is proposed that
Tracking of one class based on stochastic finite collection, and obtained tracking the very big concern on boundary, but because it is difficult in engineering at present
Middle to realize, therefore, the track algorithm based on track association is still the emphasis studied at present.
The quality of Data Association effect is the precondition and guarantee of data fusion correctness.Main method has weighted statistical
Distance test method, the weighted statistical Distance test method of amendment, nearest neighbor algorithm, classical distribution method, Likelihood ration test method, maximum likelihood
Scheduling algorithm, and these above-mentioned algorithms are all based on radar data foundation, it is more single by radar gathered data type, therefore,
Above-mentioned algorithm mainly uses shared information to be associated, it is impossible to be associated using the identity information of multi-source information.
It can be seen that, there is the technical problem under-utilized to identity information in track association of the prior art.
The content of the invention
The embodiment of the present invention provides a kind of Data Association and electronic equipment, is closed for solving flight path of the prior art
Connection is realized the identity information for utilizing multi-source information and had information layered time in the presence of the technical problem under-utilized to identity information
Track association is realized, the technique effect for improving identity information utilization rate is reached.
The embodiment of the present invention provides a kind of Data Association, applied in electronic equipment, and the electronic equipment can be with
Flight equipment is communicated, including：
Obtain the M sensor collection being arranged on the flight equipment and obtain the flight for being used for characterizing the flight equipment
The N group sensing datas of flight path, M is the integer more than or equal to 2, and N is the integer more than zero；
The N groups sensing data is divided into shared data and identity data, wherein, the shared data are described M biography
The data that sensor can be gathered, the identity data is for the data for the type for characterizing the M sensor；
The shared data and the identity data are utilized respectively, the flight path in the flight track and flight path storehouse is carried out
Association, wherein, the flight path storehouse includes at least one flight track of at least one flight equipment.
Optionally, it is described that the N groups sensing data is divided into shared data and identity data, including：
The time tag of every group of sensing data in the N groups sensing data is obtained, N number of time tag is obtained altogether；
Whether based on N number of time tag, it is continuous sensing data to determine the N groups sensing data；
If the N groups sensing data is continuous sensing data, the N groups sensing data is divided into shared data and identity
Data.
Optionally, it is described to be utilized respectively the shared data and the identity data, by the flight track and flight path storehouse
In flight path be associated, including：
Based on the identity data, determine in the flight path storehouse with the presence or absence of the first history matched with the flight track
Flight path；
If being not present, based on the shared data, determine to whether there is and the flight track in the flight path storehouse
The the first history flight path matched somebody with somebody.
Optionally, it is described to be based on the identity data, determine to whether there is and the flight track in the flight path storehouse
The the first history flight path matched somebody with somebody, including：
Obtain corresponding with identity data very first time label, and the flight path in the flight path storehouse it is corresponding second when
Between label；
Determine the very first time label whether earlier than the time tag of time the latest in second time tag；
If it has not, being then based on the identity data, determine in the flight path storehouse with the presence or absence of being matched with the flight track
The first history flight path.
Optionally, if described be not present, based on the shared data, determine in the flight path storehouse whether there is with it is described
The first history flight path of flight track matching, including：
Obtain difference in height, gun parallax and the range difference between every flight path in the flight track and the flight path storehouse；
Based on the difference in height, the gun parallax and the range difference, determine that candidate's history is navigated from the flight path storehouse
Mark, wherein, the difference in height between candidate's history flight path and the flight track is less than height ripple door, candidate's history boat
Gun parallax between mark and the flight track is less than between orientation Bo Men, candidate's history flight path and the flight track
Range difference is less than range gate；
Determine in candidate's history flight path with the presence or absence of the first history flight path matched with the flight track.
Optionally, the difference in height obtained in the flight track and the flight path storehouse between every flight path, gun parallax
And range difference, including：
Determine the second history flight path at the time of the flight track is whether before the current time and flight path storehouse
Association；
If it is, determine between the flight track and the second history flight path associate it is whether effective；
If invalid, obtain difference in height in the flight track and the flight path storehouse between every flight path, gun parallax and away from
Deviation.
Optionally, it is described to determine in candidate's history flight path with the presence or absence of described first matched with the flight track
History flight path, including：
The flight track and every flight path are extrapolated to current time using least square method；
Calculate the vector difference between the flight track and every flight path, and modulus, obtain it is described at least one to
Measure the mould of difference；
Obtain the first overall error average of the flight track, and every flight path the second overall error average, obtain altogether
Obtain at least one second overall error average；
Based on the mould of at least one vector difference, the first overall error average, and at least one described second total mistake
Poor average, obtains the statistical correlation distance between the flight track and every flight path；
Based on the statistical correlation distance, determine in candidate's history flight path with the presence or absence of being matched with the flight track
The first history flight path.
Optionally, N number of time tag is based on described, whether determine the N groups sensing data is continuous sensing
After data, methods described also includes：
If the N groups sensing data is discrete sensing data, it is determined that whether include body in the N groups sensing data
Number evidence；
If comprising being determined based on the identity data in the flight path storehouse with the presence or absence of the matched with the flight track
One history flight path；
If not including, based on the N groups sensing data, determine to whether there is and the flight track in the flight path storehouse
The the first history flight path matched somebody with somebody.
Optionally, if described do not include, based on the N groups sensing data, determine to whether there is and institute in the flight path storehouse
The first history flight path of flight track matching is stated, including：
Determine whether the N groups sensing data has openness；
If with described openness, based on the N groups sensing data, determine to whether there is in the flight path storehouse with it is described winged
The first history flight path of row track matching.
Optionally, it is described whether to determine the N groups sensing data with openness, including：
When determining whether the time difference of the time tag of two adjacent groups sensing data in the N groups sensing data is less than default
Between it is poor；Or
Determine whether the difference of space angle in two adjacent groups sensing data in the N groups sensing data is less than pre-set space
Differential seat angle；Or
Determine whether the dimension of two adjacent groups sensing data in the N groups data is consistent, or the dimension after Coordinate Conversion
Whether degree is consistent.
Optionally, if being not present described, based on the shared data, determine to whether there is and institute in the flight path storehouse
After the first history flight path for stating flight track matching, methods described also includes：
Determine that the flight track conflicts with the presence or absence of association；Wherein, the association conflict is the flight equipment not
Upper different history flight path is associated with the period；
If there is association conflict, the association results to the flight track are adjusted, and obtain new association results.
Optionally, if described have association conflict, the association results to the flight track are adjusted, and obtain new pass
It is coupled fruit, including：
The 3rd associated at the time of the current flight path number of the first history flight path is determined between the current time
Whether the history flight path number of history flight path is identical；
If it is different, then obtaining the degree of incidence of the flight track and the 3rd history flight path；
If the degree of incidence is more than 1, the association flight path of the flight track is adjusted by the first history flight path
For the 3rd history flight path.
Optionally, if described have association conflict, the association results to the flight track are adjusted, and obtain new pass
It is coupled fruit, including:
Determine the cycle of the M sensor gathered data, and the M sensor gathered data cycle and described the
Sampling interval between the one history flight path corresponding sampling period；
Determine whether the first history flight path is successfully associated in the cycle of the M sensor gathered data；
If being successfully associated, determine whether association mass-sequential of the first history flight path within the sampling interval is to pass
Increasing sequence；It is described association mass-sequential be in the association results of the first history flight path correct association results add up；
If increasing sequence, by the flight track and the first history track association.
On the other hand, the embodiment of the present invention also provides a kind of electronic equipment, can be communicated with flight equipment, including：
First acquisition unit, is used to characterize for obtaining M sensor being arranged on flight equipment collection and obtaining
The N group sensing datas of the flight track of the flight equipment, M is the integer more than or equal to 2, and N is the integer more than zero；
First division unit, for the N groups sensing data to be divided into shared data and identity data, wherein, it is described common
There are the data that data can gather for the M sensor, the identity data is the type for characterizing the M sensor
Data；
First associative cell, for being utilized respectively the shared data and the identity data, by the flight track with
Flight path in flight path storehouse is associated, wherein, the flight path storehouse includes at least one flight boat of at least one flight equipment
Mark.
Optionally, first division unit is used for：
The time tag of every group of sensing data in the N groups sensing data is obtained, N number of time tag is obtained altogether；
Whether based on N number of time tag, it is continuous sensing data to determine the N groups sensing data；
If the N groups sensing data is continuous sensing data, the N groups sensing data is divided into shared data and identity
Data.
Optionally, first associative cell is used for：
Based on the identity data, determine in the flight path storehouse with the presence or absence of the first history matched with the flight track
Flight path；
If being not present, based on the shared data, determine to whether there is and the flight track in the flight path storehouse
The the first history flight path matched somebody with somebody.
Optionally, first associative cell is used for：
Obtain corresponding with identity data very first time label, and the flight path in the flight path storehouse it is corresponding second when
Between label；
Determine the very first time label whether earlier than the time tag of time the latest in second time tag；
If it has not, being then based on the identity data, determine in the flight path storehouse with the presence or absence of being matched with the flight track
The first history flight path.
Optionally, first associative cell is used for：
Obtain difference in height, gun parallax and the range difference between every flight path in the flight track and the flight path storehouse；
Based on the difference in height, the gun parallax and the range difference, determine that candidate's history is navigated from the flight path storehouse
Mark, wherein, the difference in height between candidate's history flight path and the flight track is less than height ripple door, candidate's history boat
Gun parallax between mark and the flight track is less than between orientation Bo Men, candidate's history flight path and the flight track
Range difference is less than range gate；
Determine in candidate's history flight path with the presence or absence of the first history flight path matched with the flight track.
Optionally, first associative cell is used for：
Determine the second history flight path at the time of the flight track is whether before the current time and flight path storehouse
Association；
If it is, determine between the flight track and the second history flight path associate it is whether effective；
If invalid, obtain difference in height in the flight track and the flight path storehouse between every flight path, gun parallax and away from
Deviation.
Optionally, first associative cell is used for：
The flight track and every flight path are extrapolated to current time using least square method；
Calculate the vector difference between the flight track and every flight path, and modulus, obtain it is described at least one to
Measure the mould of difference；
Obtain the first overall error average of the flight track, and every flight path the second overall error average, obtain altogether
Obtain at least one second overall error average；
Based on the mould of at least one vector difference, the first overall error average, and at least one described second total mistake
Poor average, obtains the statistical correlation distance between the flight track and every flight path；
Based on the statistical correlation distance, determine in candidate's history flight path with the presence or absence of being matched with the flight track
The first history flight path.
Optionally, N number of time tag is based on described, whether determine the N groups sensing data is continuous sensing
After data, the electronic equipment also includes：
First determining unit, if being discrete sensing data for the N groups sensing data, it is determined that the N groups are passed
Feel in data and whether include identity data；
Second determining unit, if for comprising, based on the identity data determine in the flight path storehouse whether there is and institute
State the first history flight path of flight track matching；
3rd determining unit, if for not including, based on the N groups sensing data, determining whether deposited in the flight path storehouse
In the first history flight path matched with the flight track.
Optionally, the 3rd determining unit is used for：
Determine whether the N groups sensing data has openness；
If with described openness, based on the N groups sensing data, determine to whether there is in the flight path storehouse with it is described winged
The first history flight path of row track matching.
Optionally, the 3rd determining unit is used for：
When determining whether the time difference of the time tag of two adjacent groups sensing data in the N groups sensing data is less than default
Between it is poor；Or
Determine whether the difference of space angle in two adjacent groups sensing data in the N groups sensing data is less than pre-set space
Differential seat angle；Or
Determine whether the dimension of two adjacent groups sensing data in the N groups data is consistent, or the dimension after Coordinate Conversion
Whether degree is consistent.
Optionally, if being not present described, based on the shared data, determine to whether there is and institute in the flight path storehouse
After the first history flight path for stating flight track matching, the electronic equipment also includes：
4th determining unit, for determining that the flight track conflicts with the presence or absence of association；Wherein, it is described association conflict be
Flight equipment history flight path different in different time sections association；
First adjustment unit, if for there is association conflict, the association results to the flight track are adjusted, and are obtained
New association results.
Optionally, first adjustment unit, is used for：
The 3rd associated at the time of the current flight path number of the first history flight path is determined between the current time
Whether the history flight path number of history flight path is identical；
If it is different, then obtaining the degree of incidence of the flight track and the 3rd history flight path；
If the degree of incidence is more than 1, the association flight path of the flight track is adjusted by the first history flight path
For the 3rd history flight path.
Optionally, first adjustment unit is used for:
Determine the cycle of the M sensor gathered data, and the M sensor gathered data cycle and described the
Sampling interval between the one history flight path corresponding sampling period；
Determine whether the first history flight path is successfully associated in the cycle of the M sensor gathered data；
If being successfully associated, determine whether association mass-sequential of the first history flight path within the sampling interval is to pass
Increasing sequence；It is described association mass-sequential be in the association results of the first history flight path correct association results add up；
If increasing sequence, by the flight track and the first history track association.
Said one or multiple technical schemes in the embodiment of the present application, are at least imitated with following one or more technologies
Really：
First, due to the technical scheme in the embodiment of the present invention, M sensing on the flight equipment is arranged on using acquisition
Device collection obtains the N group sensing datas for the flight track for being used to characterize the flight equipment, and M is the integer more than or equal to 2, and N is
Integer more than zero；The N groups sensing data is divided into shared data and identity data, wherein, the shared data are the M
The data that individual sensor can be gathered, the identity data is for the data for the type for characterizing the M sensor；It is sharp respectively
With the shared data and the identity data, the flight track is associated with the flight path in flight path storehouse, wherein, it is described
Flight path storehouse includes the technical scheme of at least one flight track of at least one flight equipment.Sensing number first to getting
According to being classified, it is divided into shared data and identity data, is then utilized respectively shared data and identity data carries out track association,
Efficiently solve track association of the prior art and there is the technical problem under-utilized to identity information, and then reach using many
The identity information of source information and the shared information layered secondary technique effect realized track association, improve identity information utilization rate.
2nd, due to the technical scheme in the embodiment of the present invention, if using the N groups sensing data for discrete sensing number
According to, it is determined that whether include identity data in the N groups sensing data；If comprising determining the boat based on the identity data
With the presence or absence of the first history flight path matched with the flight track in mark storehouse；If not including, based on the N groups sensing data,
The technological means with the presence or absence of the first history flight path matched with the flight track in the flight path storehouse is determined, i.e., true
Sensing data is determined in the case of discontinuous sensing data, using identity data and shared data to discrete point mark
Reason, and then reach the technique effect for improving association accuracy.
3rd, due to the technical scheme in the embodiment of the present invention, conflicted using determining that the flight track whether there is to associate；
Wherein, the association conflict is flight equipment history flight path different in different time sections association；If there is association punching
Prominent, the association results to the flight track are adjusted, and obtain the technological means of new association results, that is, utilize shared data
Completed with identity data after track association, association is also predefined with the presence or absence of conflict, if there is conflict, needs to affiliated partner
It is adjusted, and then reaches the technique effect for improving association accuracy.
Brief description of the drawings
In order to illustrate more clearly of the embodiment of the present application or technical scheme of the prior art, embodiment will be described below
In required for the accompanying drawing that uses be briefly described, it should be apparent that, drawings in the following description are only some of the present invention
Embodiment.
Fig. 1 implements flow chart for a kind of Data Association provided in an embodiment of the present invention；
Fig. 2 has the tool that data carry out track association to be utilized in a kind of Data Association provided in an embodiment of the present invention
Body implementation process figure；
Fig. 3 is to the handling process of discontinuous sensing data in a kind of Data Association provided in an embodiment of the present invention
Figure；
Fig. 4 is the first implementation process figure provided in an embodiment of the present invention for associating Conflict solving；
Fig. 5 is second of implementation process figure provided in an embodiment of the present invention for associating Conflict solving；
Fig. 6 is the structural representation of a kind of electronic equipment provided in an embodiment of the present invention.
Embodiment
The embodiment of the present invention provides a kind of Data Association and electronic equipment, is closed for solving flight path of the prior art
Connection is realized the identity information for utilizing multi-source information and had information layered time in the presence of the technical problem under-utilized to identity information
Track association is realized, the technique effect for improving identity utilization rate is reached.
Technical scheme in the embodiment of the present invention is in order to solve the above technical problems, general thought is as follows：
Obtain the M sensor collection being arranged on the flight equipment and obtain the flight for being used for characterizing the flight equipment
The N group sensing datas of flight path, M is the integer more than or equal to 2, and N is the integer more than zero；
The N groups sensing data is divided into shared data and identity data, wherein, the shared data are described M biography
The data that sensor can be gathered, the identity data is for the data for the type for characterizing the M sensor；
The shared data and the identity data are utilized respectively, the flight path in the flight track and flight path storehouse is carried out
Association, wherein, the flight path storehouse includes at least one flight track of at least one flight equipment.
Above-mentioned technical proposal, the M sensor collection being arranged on using acquisition on the flight equipment, which is obtained, to be used to characterize
The N group sensing datas of the flight track of the flight equipment, M is the integer more than or equal to 2, and N is the integer more than zero；Will be described
N group sensing datas are divided into shared data and identity data, wherein, the shared data are what the M sensor can be gathered
Data, the identity data is for the data for the type for characterizing the M sensor；It is utilized respectively the shared data and institute
Identity data is stated, the flight track is associated with the flight path in flight path storehouse, wherein, the flight path storehouse includes at least one
The technical scheme of at least one flight track of individual flight equipment.The sensing data got is classified first, is divided into altogether
There are data and identity data, be then utilized respectively shared data and identity data carries out track association, efficiently solve existing skill
There is the technical problem under-utilized to identity information in the track association in art, and then reach the identity information using multi-source information
Track association is realized with shared information layered time, the technique effect of identity information utilization rate is improved.
In order to be better understood from above-mentioned technical proposal, below by accompanying drawing and specific embodiment to technical solution of the present invention
It is described in detail, it should be understood that the specific features in the embodiment of the present application and embodiment are to the detailed of technical solution of the present invention
Thin explanation, rather than the restriction to technical solution of the present invention, in the case where not conflicting, the embodiment of the present application and embodiment
In technical characteristic can be combined with each other.
First aspect
Fig. 1 is refer to, is a kind of Data Association provided in an embodiment of the present invention, it is described applied in electronic equipment
Electronic equipment can be communicated with flight equipment, including：
S101：Obtaining the M sensor collection being arranged on the flight equipment and obtaining is used to characterize the flight equipment
Flight track N group sensing datas, M is integer more than or equal to 2, and N is the integer more than zero；
S102：The N groups sensing data is divided into shared data and identity data, wherein, the shared data are the M
The data that individual sensor can be gathered, the identity data is for the data for the type for characterizing the M sensor；
S103：The shared data and the identity data are utilized respectively, by the boat in the flight track and flight path storehouse
Mark is associated, wherein, the flight path storehouse includes at least one flight track of at least one flight equipment.
In embodiments of the present invention, step S101 is first carried out：Obtain M sensor being arranged on the flight equipment
Collection obtains the N group sensing datas for the flight track for being used to characterize the flight equipment, and M is the integer more than or equal to 2, and N is big
In zero integer.
In embodiments of the present invention, electronic equipment can be independently of flight equipment or be integrated in flight equipment
In equipment, here, being not specifically limited.Flight equipment is specifically as follows aircraft, guided missile or is other tracking targets,
This, just no longer schematically illustrates one by one.
In embodiments of the present invention, different type, different operating system, different data rate can be provided with flight equipment
Multiple sensors, e.g., ADS-B, Data-Link, IRST, ESM etc., after flight equipment takes off, electronic equipment by obtain flight set
Foreign peoples's asynchronous data that standby upper various sensors are collected, such as：Position data, static data or identity data etc., or be it
Its sensing data, here, just no longer schematically illustrating one by one.During implementing, with
Represent in tiThe data that moment is collected by sensor.
After N group sensing datas are obtained, then step S102 is performed：By the N groups sensing data be divided into shared data and
Identity data, wherein, the shared data are the data that the M sensor can be gathered, and the identity data is for table
Levy the data of the type of the M sensor.
In embodiments of the present invention, process is implemented for step S102, specifically includes following steps：
The time tag of every group of sensing data in the N groups sensing data is obtained, N number of time tag is obtained altogether；
Whether based on N number of time tag, it is continuous sensing data to determine the N groups sensing data；
If the N groups sensing data is continuous sensing data, the N groups sensing data is divided into shared data and identity
Data.
In embodiments of the present invention, different conditions are in tracking target, such as：When stealthy state or visible state, pass through
It is probably continuous between the sensing data that sensor is collected, it is also possible to discrete, therefore, in embodiments of the present invention,
In order to improve the accuracy of association, different handling processes are respectively adopted to continuous data and non-continuous data, therefore, are obtaining
During N group sensing datas, first determine whether between N group sensing datas whether be continuous data.
During implementing, the corresponding time tag of N group sensing datas is obtained first, that is, gathers N group sensing datas
When the corresponding time, it is as shown in table 1 below.
Table 1
| Gathered data is numbered | Time tag |
| 1 | 2016.12.5.16:02 |
| 2 | 2016.12.5.16:03 |
| 3 | 2016.12.5.16:05 |
| … | … |
| N | 2016.12.5.17:01 |
After the corresponding time tag of N group sensing datas is obtained, the corresponding time tag of two adjacent groups sensing data is determined
Between time interval whether exceed prefixed time interval, if more than prefixed time interval, it is determined that N groups sensing data is discrete
Data.
In embodiments of the present invention, prefixed time interval is specifically as follows 1 hour, 2 hours, 3 hours, or is other pre-
If time interval, those of ordinary skill in the art can be configured according to actual needs, not make to have in embodiments of the present invention
Body is limited.
During implementing, prefixed time interval is exemplified by 1 hour, and the time tag of N group sensing datas is with table one
In data instance, time interval between first group of sensing data and second group of sensing data is 2 minutes, less than preset time
Interval, time interval between second group of sensing data and the 3rd group of sensing data is 2 minutes, less than prefixed time interval, this
Sample calculates the time interval between every two adjacent groups sensing data successively, if respectively less than prefixed time interval, it is determined that N groups are sensed
Data are continuous sensing data.
In embodiments of the present invention, when it is determined that N groups sensing data is continuous sensing data, then according to the spy of sensing data
Point, is divided into shared data and identity data by N group sensing datas, wherein, shared data are the number that each sensor can be gathered
According to such as：Information source numbering, flight path numbering, the longitude of track points, latitude, height, the speed of a ship or plane, course, apart from information such as orientation；Identity
Data particularly for characterize sensor identity data, such as：ADS-B sets up 24 bit address code, the data that flight path has
Lot number, the AIS that chain is set up flight path and had set up ship'call sign that flight path has etc., here, just no longer schematically illustrating one by one.
In embodiments of the present invention, after the N group sensing datas to receiving are classified, then it is utilized respectively after classification
Data carry out track association, that is, perform step S103：The shared data and the identity data are utilized respectively, is flown described
Row flight path is associated with the flight path in flight path storehouse, wherein, the flight path storehouse includes at least the one of at least one flight equipment
Individual flight track.
In embodiments of the present invention, process is implemented for step S103, specifically includes following steps：
First step：Based on the identity data, determine in the flight path storehouse with the presence or absence of being matched with the flight track
The first history flight path；
Second step：If being not present, based on the shared data, determine in the flight path storehouse whether there is with it is described fly
The first history flight path of row track matching.
In embodiments of the present invention, process is implemented for first step, specifically includes following steps：
Obtain corresponding with identity data very first time label, and the flight path in the flight path storehouse it is corresponding second when
Between label；
Determine the very first time label whether earlier than the time tag of time the latest in second time tag；
If it has not, being then based on the identity data, determine in the flight path storehouse with the presence or absence of being matched with the flight track
The first history flight path.
In embodiments of the present invention, flight path storehouse also turns into history flight path storehouse, i.e., under Same Scene, all targetpaths
Set, wherein every flight path is made up of flight path number, shared data and identity data, under the conditions of all targetpaths are continuous,
Flight path storehouse has that flight path number is unique, flight path information is run with scene and updated and flight path is made up of the association results in newest multiple cycles
The characteristics of.
During implementing, the flight path in the corresponding time tag of identity data, flight path storehouse is obtained first with flight path
Number for 1,2 flight path exemplified by, corresponding time tag is respectively：2016.12.5.15:50、2016.12.5.15:53, at this moment,
Latest time label is 2016.12.5.15 in the corresponding time tag of two flight paths:53, it is then determined that identity information is corresponding
Whether time tag is earlier than latest time label 2016.12.5.15:53, if：The corresponding time tag of identity data is
2016.12.5.15:35, then earlier than latest time label, then ignore the identity data, i.e., flight path pass is not made to the identity data
Connection.
If the corresponding time tag of identity data is later than latest time label, by the flight path in identity data and flight path storehouse
Corresponding identity data is matched, specifically, the identity data collected by sensor is 24 bit address code, and in flight path
Presence in storehouse has the flight path of 24 bit address code, it is determined that there is the first history boat matched with flight track in flight path storehouse
Mark, determines deposit position of the flight track in flight path storehouse, so as to which subsequent treatment result is updated on this position in succession.
In embodiments of the present invention, process is implemented for second step, specifically includes following steps：
Obtain difference in height, gun parallax and the range difference between every flight path in the flight track and the flight path storehouse；
Based on the difference in height, the gun parallax and the range difference, determine that candidate's history is navigated from the flight path storehouse
Mark, wherein, the difference in height between candidate's history flight path and the flight track is less than height ripple door, candidate's history boat
Gun parallax between mark and the flight track is less than between orientation Bo Men, candidate's history flight path and the flight track
Range difference is less than range gate；
Determine in candidate's history flight path with the presence or absence of the first history flight path matched with the flight track.
In embodiments of the present invention, for step：It is described to obtain the flight track and every flight path in the flight path storehouse
Between difference in height, gun parallax and range difference implement process, including：
Determine the second history flight path at the time of the flight track is whether before the current time and flight path storehouse
Association；
If it is, determine between the flight track and the second history flight path associate it is whether effective；
If invalid, obtain difference in height in the flight track and the flight path storehouse between every flight path, gun parallax and away from
Deviation.
In embodiments of the present invention, it is first determined at the time of flight track is before current time, such as：Current time is
2016.12.5.15:50, it is determined that the corresponding tracking target of flight track is in current time 2016.12.5.15:Before 50 whether
It is associated with a flight path in flight path storehouse, such as：Target is tracked in current time 2016.12.5.15:Zeng Yuyu flight paths before 50
The second history flight path in storehouse is associated.Flight path number is associated for 2 flight path.
During implementing, the second history flight path is so that flight path number is 2 flight path as an example, if flight track and flight path number
Associated for 2 flight path, then further determine that whether flight track and flight path number are effective for associating between 3 flight path.
In embodiments of the present invention, by judging whether flight track disconnected batch of phenomenon occurs come determination flight track and the second history
Whether the association between flight path is effective, specifically, such as：The sensing data gathered by sensor is received between 10s to 20s,
And between 20s to 30s, or even to being all not received by the sensing data that is gathered by sensor between 50 seconds, it is determined that flight
There is disconnected batch of phenomenon in flight path, indicate that in this case tracking target occur in that it is larger palpitate from nervousness, that is, needing will be to flight track
Association is re-started, if there is not disconnected batch of phenomenon, it is determined that the association flight path of flight track is the second history flight path.
In embodiments of the present invention, however, it is determined that associating between flight track and the second history flight path is invalid, obtain described
Difference in height, gun parallax and the range difference between every flight path in flight track and the flight path storehouse.
In embodiments of the present invention, N groups sensing data is exemplified by 2 groups, the sensing data collected, with including height, side
Position and distance, such as：In t1The data that moment collects are expressed as t1(3000 meters, 45 degree, 200 meters)；In t2The number that moment collects
According to being expressed as t2History flight path in (4000 meters, 45 degree, 300 meters), flight path storehouse is with 2, the corresponding sensing of every history flight path
Data are exemplified by 2 groups, specifically, the history flight path that flight path number is 1 is in t1Moment corresponding flight path point data (3500 meters, 40 degree,
180 meters)；In t2Moment corresponding flight path point data (3800 meters, 45 degree, 220 meters)；Flight path number is 2 history flight path t1Moment pair
The flight path point data (5100 meters, 45 degree, 300 meters) answered；In t2Moment corresponding flight path point data (3400 meters, 45 degree, 180
Rice), at this moment, then flight track and history flight path are calculated in t1Moment and t2Moment corresponding difference in height, gun parallax, range difference.
In embodiments of the present invention, obtain corresponding with flight path in the flight path storehouse difference in height of flight track, gun parallax and away from
After deviation, then candidate's history flight path is determined based on difference in height, gun parallax and range difference, it is described in detail below：
During implementing, preset height difference is with 2000 meters, pre-configured orientation difference with 15 degree, pre-determined distance difference with 50 meters
Exemplified by.Flight track and flight path number for 1 history flight path in t1Moment and t2Moment corresponding difference in height is 500 meters, 800 meters,
Poor less than preset height, gun parallax is 5 degree, 0 degree, and respectively less than pre-configured orientation is poor, and range difference is 20 meters, 20 meters, is respectively less than preset
Range difference, in this case, it is determined that the history flight path that flight path number is 1 is candidate's history flight path.
Flight track and flight path number for 2 history flight path in t1Moment and t2Moment corresponding difference in height is 2100,400, side
Potential difference is 0 degree, 0 degree, and range difference is 100 meters, 20 meters, wherein, due in t1It is poor that moment corresponding difference in height is more than preset height
2000 meters, in this case, it is determined that the history flight path that flight path number is 2 is non-candidate history flight path.
In embodiments of the present invention, it is determined that after candidate's history flight path, then performing step：Determine candidate's history boat
With the presence or absence of the first history flight path matched with the flight track in mark.
In embodiments of the present invention, Fig. 2 is refer to, the process that implements for above-mentioned steps specifically includes following step
Suddenly：
S201：The flight track and every flight path are extrapolated to current time using least square method；
S202：Calculate the vector difference between the flight track and every flight path, and modulus, obtain described at least one
The mould of individual vector difference；
S203：Obtain the first overall error average of the flight track, and every flight path the second overall error average,
At least one second overall error average is obtained altogether；
S204：Based on the mould of at least one vector difference, the first overall error average, and it is described at least one second
Overall error average, obtains the statistical correlation distance between the flight track and every flight path；
S205：Based on the statistical correlation distance, determine to whether there is in candidate's history flight path and navigated with the flight
The first history flight path of mark matching.
During implementing, the history flight path and flight track in flight path storehouse are extrapolated to using least square method and worked as
The preceding time, in embodiments of the present invention, so that the flight path number in flight path storehouse is 1 flight path as an example, flight track and boat is calculated first
Mark number is the difference vector between 1 flight path, i.e. calculates flight track and flight path number and gathers number at the correspondingly moment for 1 flight path
Vector difference between, and then calculate the mould DeltaR of difference vector.
Further, the overall error average of flight track and flight path number for 1 flight path is calculated, specifically, flight track is total
The site error of error mean TotalMeasError=flight tracks+velocity error * extrapolation times；Flight path number is 1 flight path
Overall error average TotalTrackError=flight paths number for 1 flight path the site error+velocity error * extrapolation time, its
In, the extrapolation time is the time between the corresponding time tag of flight track time tag corresponding with the flight path that flight path number is 1
Difference.
It is determined that after the overall error average of flight track and flight path number for 1 flight path, then calculating flight track and flight path
Number for 1 flight path between statistical correlation distance, specifically, CorrDis=DeltaR-TotalMeasError-
TotalTrackError。
Further, according to the relation between statistical correlation distance and default correlation distance, determine be in history candidate's flight path
It is no to there is the first history flight path matched with flight track.
During implementing, it is CorrGate*sigma to preset correlation distance, and CorrGate is setting value, such as：280
Rice, sigma=max { MeasRSS, TrackRSS }, MeasRSS is the error mean of flight track, and TrackRSS is flight path number
For the error mean of 1 flight path.
Wherein, the error mean and flight path number of flight track are as follows for the specific calculating process of the error mean of 1 flight path：
Assuming that flight path covariance matrixFor 6*6 matrix, refer specifically to distance, away from
From the covariance matrix of the relation composition between rate of change, orientation, rate of azimuth change, pitching and pitch rate, wherein, flight path
The initial value of element is all 1 in covariance matrix, can be constantly updated with the addition of new track points, then renewal process is specific such as
It is lower described.
The first step, calculates flight path covariance matrix, is designated as the Sigma factors, the note tracking range error Sigma factors, orientation
The error Sigma factors and the pitch error Sigma factors are respectively SigmaRng, SigmaAz and SigmaEl, and corresponding calculating is public
Formula is respectively as shown in following formula (1)-formula (3)：
Wherein,
RngRand：Distance is uncertain, and unit is rice；AzRand：Orientation is uncertain, and unit is degree；SElRand：Bow
Uncertainty is faced upward, unit is degree；RngSysNoise：System of distance noise, unit is rice；AzSysNoise：Azimuth system is made an uproar
Sound, unit is degree；ElMultiPth：Pitching multi-path coefficients, dimensionless；MlPth：The sum of multi-path coefficients, dimensionless；
ElBeamwidth：The pitching width of sensor beam, unit is degree；DiffChannleSlop：The high difference slope of sensor, nothing
Dimension, general value is 1.2；k1,k2,k3Respectively range resolution ratio square, azimuth resolution quadratic sum pitching resolution ratio are put down
Side.Above parameter is the performance parameter of sensor or can calculated according to the performance parameter of sensor.
Shown in parameter in flight track covariance is calculated as follows：
The value of other elements is all that zero, CovVel is the coefficient that covariance updates, and its general value is between 1~2.
Wherein,
SumRng1=SumRng1+SigmaRng SumRng2=SumRng2+SigmaRng*t
SumRng3=SumRng3+SigmaRng*t*t SumAz1=SumAz1+SigmaAz；
SumAz2=SumAz2+SigmaAz*t SumAz3=SumAz3+SigmaAz*t*t；
SumEl1=SumEl1+SigmaEl SumEl2=SumEl2+SigmaEl*t；
SumEl3=SumEl3+SigmaEl*t*3
DenomAz=SumAz1*SumAz3-SumAzi2*SumAz2
DenomElev=SumEl1*SumEl3-SumEl2*SumEl2；
DenomRng=SumRng1*SumRng3-SumRng2*SumRng2
In above formula, SumRng1, SumAz1, SumEl1 initial value are that 1, t is the boat that flight track is 1 with flight path number
The time difference of mark, calculated more than, just obtained flight path covariance matrix.Meanwhile, by SumRng1, SumRng2,
SumRng3, SumAz1, SumAz2, SumAz3, SumEl1, SumEl2, SumEl3 are updated into the corresponding data item of flight path.
Second step, calculates the course error average (RSS) of flight track.Course error average RSS calculation formula is such as
Shown in lower：
Wherein,
TrackError1=cov00+cov11+cov22
TrackError2 and TrackError3 are respectively second and the 3rd characteristic value of covariance matrix.
For flight path number for 1 flight path error mean RSS calculating process with flight track course error average,
This, just repeats no more.After error mean RSS of the course error and flight path number of flight track for 1 flight path is calculated, then
The Sigma factors can be determined.
In embodiments of the present invention, in the case where N groups sensing data is continuous data, and by identity data and have
After data are associated, in the absence of the first history flight path associated with flight track, then new flight path is added in flight path storehouse,
With the flight path storehouse after being updated.
Further, in embodiments of the present invention, N number of time tag is based on described, determines the N groups sensing data
After whether being continuous sensing data, Fig. 3 is refer to, methods described also includes：
S301：If the N groups sensing data be discrete sensing data, it is determined that in the N groups sensing data whether
Include identity data；
S302：If comprising, based on the identity data determine in the flight path storehouse whether there is and the flight track
The the first history flight path matched somebody with somebody；
S303：If not including, based on the N groups sensing data, determine to whether there is and the flight in the flight path storehouse
The first history flight path of track matching.
During implementing, first determine whether to whether there is identity data in N group sensing datas, if including identity number
According to then using identity data, flight track being matched with the flight path in flight path storehouse in flight path storehouse, specifically, such as：By passing
The identity data that sensor is collected is 24 bit address code, and the presence in flight path storehouse has the flight path of 24 bit address code, then really
Determine the presence of the first history flight path matched with flight track in flight path storehouse.
If not comprising identity data, determining to whether there is and the flight in the flight path storehouse using N group sensing datas
First history flight path of track matching, in embodiments of the present invention, process is implemented for the step, specifically included as follows
Step：
Determine whether the N groups sensing data has openness；
If with described openness, based on the N groups sensing data, determine to whether there is in the flight path storehouse with it is described winged
The first history flight path of row track matching.
In embodiments of the present invention, for step：It is described to determine the N groups sensing data whether with openness specific
Implementation process, specifically includes following steps：
When determining whether the time difference of the time tag of two adjacent groups sensing data in the N groups sensing data is less than default
Between it is poor；Or
Determine whether the difference of space angle in two adjacent groups sensing data in the N groups sensing data is less than pre-set space
Differential seat angle；Or
Determine whether the dimension of two adjacent groups sensing data in the N groups data is consistent, or the dimension after Coordinate Conversion
Whether degree is consistent.
During implementing, the judgement of N group Deta sparseness can from time, space, information dimension any dimension
The combination of degree or multiple dimensions is judged, below then respectively in terms of time, space, information dimension three to openness
Judgement is illustrated.Assuming that Table
Show the data of adjacent moment.
Firstth, time angle.Assuming that a given time threshold epsilonTimeIf the information is met | ti-ti+1| ＜ εTime, i=
1...N-1, i.e., the time difference between two groups of sensing datas of arbitrary neighborhood is poor less than preset time, then it is assumed that two adjacent groups sense number
According to Info (ti) and Info (ti+1) in time angle it is sparse.
In embodiments of the present invention, it is either 3s or for other preset time that preset time difference, which is specifically as follows 1s, 2s,
Difference, those of ordinary skill in the art can be configured according to actual conditions, be not especially limited in embodiments of the present invention.
Secondth, space angle.In embodiments of the present invention, space angle mainly includes：Orientation, height, angle of pitch etc. are believed
Breath, it is assumed that give one group of capacity-threshold εSpace={ ε1, ε2..., εn, and Info (ti) and Info (ti+1) in information without missing,
Then for the angle in space angle, such as：Any one in orientation, height or the angle of pitch has
Then Info (ti) and Info (ti+1) in space k angles it is sparse；If forHaveSet up, then Info (ti) and Info (ti+1) in space angle it is sparse.
3rd, information dimension angle.Assuming that adjacent moment information dimension it is inconsistent or after Coordinate Conversion it is inconsistent, i.e.,
Show Info (ti) or Info (ti+1) in information have missing, then it is sparse to give tacit consent to the adjacent data.
Wherein, the inconsistent coordinate system for referring to sensing data of information dimension is different, such as：May be load by radar plot
Distance, orientation and pitching under machine coordinate system, and ADS-B point mark is then longitude, latitude and the height under terrestrial coordinate system, this
Can mutually it be changed between both coordinate systems, if both are after conversion, information dimension is still inconsistent, such as：Assuming that
tiTime information includes the information such as longitude, latitude, height, speed, course, and in ti+1Moment only has height, the speed of a ship or plane and boat
To it is sparse in information dimension angle then to show the sensing data.
In embodiments of the present invention, when N group sensing datas have openness, then to N groups sensing data carry out cluster and
The processing of classification, clustering method is specifically as follows partitioning, stratification, density algorithm, graph theory clustering method or is other algorithm,
Here, just no longer schematically illustrating one by one；Sorting technique is specifically as follows decision tree, Bayes, artificial neural network or is other
Sorting technique, those of ordinary skill in the art can be selected according to actual needs, not make specific in embodiments of the present invention
Limit.
In embodiments of the present invention, after being handled by cluster and classification N group sensing datas, it is determined that collection
Whether the quantity of N group sensing datas exceeds predetermined number, when beyond predetermined number, then by N group data, that is, has data,
Such as：Position data is related, and flight track is associated.
By above-mentioned technical proposal provided in an embodiment of the present invention, when N groups sensing data is non-continuous data, pin is proposed
To the handling process of non-continuous data, and then reach the technique effect for improving association accuracy.
During track association, because of situations such as having the uncertain of data, target distribution, it may occur however that association punching
It is prominent, therefore, in embodiments of the present invention, in order to avoid the presence of association conflict, further, in embodiments of the present invention, in institute
It is not present, based on the shared data, determines in the flight path storehouse with the presence or absence of the institute matched with the flight track if stating
State after the first history flight path, methods described also includes：
Determine that the flight track conflicts with the presence or absence of association；Wherein, the association conflict is the flight equipment not
Upper different history flight path is associated with the period；
If there is association conflict, the association results to the flight track are adjusted, and obtain new association results.
In embodiments of the present invention, it is necessary to determine whether whether tracking target deposits after being associated to flight track
In conflict, that is, judge flight equipment history flight path different in different time sections association, such as：Target is tracked in first data
The flight path that flight path number is 1 in the upper flight path storehouse of collection period association, the flight path in flight path storehouse in second data collection cycle association
Number be 2 flight path, at this moment, it is determined that flight track exist association conflict.
When flight track has association conflict, then the association results of flight track are adjusted, of the invention real
Apply in example, for step：If there is association conflict, the association results to the flight track are adjusted, and obtain new association
As a result implement process, including but not limited to following two implementations, separately below to both implementations carry out
It is described in detail.
The first implementation, refer to Fig. 4, comprise the following steps：
S401：Associated at the time of the current flight path number of the first history flight path is determined between the current time
Whether the history flight path number of the 3rd history flight path is identical；
S402：If it is different, then obtaining the degree of incidence of the flight track and the 3rd history flight path；
S403：If the degree of incidence is more than 1, by the association flight path of the flight track by the first history flight path
It is adjusted to the 3rd history flight path.
During implementing, the flight path n of the first history flight path is obtained firstk, at the time of between current time
The flight path m of the 3rd history flight path associated with flight track, then judges nkIt is whether identical with m, when differing, obtain and fly
The degree of incidence of row flight path and the 3rd history flight path.
If degree of incidence is more than 1, the association flight path of flight track is adjusted to the 3rd history flight path.
If degree of incidence is equal to 1, judge whether the first history flight path and the 3rd history flight path have identity data
Specifically, such as：If the first history flight path has identity data, identity data is not present in the 3rd history flight path, it is determined that flight boat
The association flight path of mark is the first history flight path；If identity data is not present in the first history flight path, there is identity in the 3rd history flight path
Data, then be adjusted to the 3rd history flight path by the association flight path of flight track；If identity data is not present in the first history flight path, the
Identity data is also not present in three history flight paths, then wouldn't export association results.
Second of implementation, refer to Fig. 5, comprise the following steps：
S501：Determine the cycle of the M sensor gathered data, and the M sensor gathered data cycle with
Sampling interval between the first history flight path corresponding sampling period；
S502：Determine whether the first history flight path is successfully associated in the cycle of the M sensor gathered data；
S503：If being successfully associated, determine that association mass-sequential of the first history flight path within the sampling interval is
No is increasing sequence；It is described association mass-sequential be in the association results of the first history flight path correct association results tire out
Plus；
S504：If increasing sequence, by the flight track and the first history track association.
During implementing, the cycle of sensor gathered data is determined, such as 10s, 20s are either 30s or are it
Its data collection cycle, those of ordinary skill in the art can be configured according to actual needs, in embodiments of the present invention not
Make specific limit.And sensor gathered data cycle and the cycle of flight path in flight path storehouse, such as：11s, 22s are 32s, this
When, period distances between the two are 1s, 2s or are 3s.
In embodiments of the present invention, it is first determined the first history flight path associated with flight track is in sensor gathered data
Periodic content whether be successfully associated, if being successfully associated, continue to determine association matter of the first history flight path in period distances
Sequence is measured, such as：It is successfully associated in period 1 interval, is successfully associated, is associated within the period 3 in second round interval
Success, is successfully associated in each period distances, then shows association mass-sequential incrementally to associate mass-sequential, specifically,
For the first history flight path, it has been successfully associated 5 times, then association quality may be 0.95；If the 6th time is also associated to
Work(, then association quality may be 0.98；But if there occurs association conflict for the 6th time, then association quality may be 0.85,
Therefore, can release whether there occurs association conflict from the variation tendency of association quality.
In embodiments of the present invention, when it is to be incremented by mass-sequential to associate mass-sequential, it is determined that the association of flight track
Flight path is the first history flight path.
Second aspect
Based on the same inventive concept of first aspect, Fig. 6 is refer to, the embodiment of the present invention also provides a kind of electronic equipment,
The electronic equipment can be communicated with flight equipment, including：
First acquisition unit 601, is used for table for obtaining M sensor being arranged on flight equipment collection and obtaining
The N group sensing datas of the flight track of the flight equipment are levied, M is the integer more than or equal to 2, and N is the integer more than zero；
First division unit 602, for the N groups sensing data to be divided into shared data and identity data, wherein, it is described
Shared data are the data that the M sensor can be gathered, and the identity data is the class for characterizing the M sensor
The data of type；
First associative cell 603, for being utilized respectively the shared data and the identity data, by the flight track
It is associated with the flight path in flight path storehouse, wherein, the flight path storehouse includes at least one flight of at least one flight equipment
Flight path.
Optionally, first division unit 602 is used for：
The time tag of every group of sensing data in the N groups sensing data is obtained, N number of time tag is obtained altogether；
Whether based on N number of time tag, it is continuous sensing data to determine the N groups sensing data；
If the N groups sensing data is continuous sensing data, the N groups sensing data is divided into shared data and identity
Data.
Optionally, first associative cell 603 is used for：
Based on the identity data, determine in the flight path storehouse with the presence or absence of the first history matched with the flight track
Flight path；
If being not present, based on the shared data, determine to whether there is and the flight track in the flight path storehouse
The the first history flight path matched somebody with somebody.
Optionally, first associative cell 603 is used for：
Obtain corresponding with identity data very first time label, and the flight path in the flight path storehouse it is corresponding second when
Between label；
Determine the very first time label whether earlier than the time tag of time the latest in second time tag；
If it has not, being then based on the identity data, determine in the flight path storehouse with the presence or absence of being matched with the flight track
The first history flight path.
Optionally, first associative cell 603 is used for：
Obtain difference in height, gun parallax and the range difference between every flight path in the flight track and the flight path storehouse；
Based on the difference in height, the gun parallax and the range difference, determine that candidate's history is navigated from the flight path storehouse
Mark, wherein, the difference in height between candidate's history flight path and the flight track is less than height ripple door, candidate's history boat
Gun parallax between mark and the flight track is less than between orientation Bo Men, candidate's history flight path and the flight track
Range difference is less than range gate；
Determine in candidate's history flight path with the presence or absence of the first history flight path matched with the flight track.
Optionally, first associative cell 603 is used for：
Determine the second history flight path at the time of the flight track is whether before the current time and flight path storehouse
Association；
If it is, determine between the flight track and the second history flight path associate it is whether effective；
If invalid, obtain difference in height in the flight track and the flight path storehouse between every flight path, gun parallax and away from
Deviation.
Optionally, first associative cell 603 is used for：
The flight track and every flight path are extrapolated to current time using least square method；
Calculate the vector difference between the flight track and every flight path, and modulus, obtain it is described at least one to
Measure the mould of difference；
Obtain the first overall error average of the flight track, and every flight path the second overall error average, obtain altogether
Obtain at least one second overall error average；
Based on the mould of at least one vector difference, the first overall error average, and at least one described second total mistake
Poor average, obtains the statistical correlation distance between the flight track and every flight path；
Based on the statistical correlation distance, determine in candidate's history flight path with the presence or absence of being matched with the flight track
The first history flight path.
Optionally, N number of time tag is based on described, whether determine the N groups sensing data is continuous sensing
After data, the electronic equipment also includes：
First determining unit, if being discrete sensing data for the N groups sensing data, it is determined that the N groups are passed
Feel in data and whether include identity data；
Second determining unit, if for comprising, based on the identity data determine in the flight path storehouse whether there is and institute
State the first history flight path of flight track matching；
3rd determining unit, if for not including, based on the N groups sensing data, determining whether deposited in the flight path storehouse
In the first history flight path matched with the flight track.
Optionally, the 3rd determining unit is used for：
Determine whether the N groups sensing data has openness；
If with described openness, based on the N groups sensing data, determine to whether there is in the flight path storehouse with it is described winged
The first history flight path of row track matching.
Optionally, the 3rd determining unit is used for：
When determining whether the time difference of the time tag of two adjacent groups sensing data in the N groups sensing data is less than default
Between it is poor；Or
Determine whether the difference of space angle in two adjacent groups sensing data in the N groups sensing data is less than pre-set space
Differential seat angle；Or
Determine whether the dimension of two adjacent groups sensing data in the N groups data is consistent, or the dimension after Coordinate Conversion
Whether degree is consistent.
Optionally, if being not present described, based on the shared data, determine to whether there is and institute in the flight path storehouse
After the first history flight path for stating flight track matching, the electronic equipment also includes：
4th determining unit, for determining that the flight track conflicts with the presence or absence of association；Wherein, it is described association conflict be
Flight equipment history flight path different in different time sections association；
First adjustment unit, if for there is association conflict, the association results to the flight track are adjusted, and are obtained
New association results.
Optionally, first adjustment unit, is used for：
The 3rd associated at the time of the current flight path number of the first history flight path is determined between the current time
Whether the history flight path number of history flight path is identical；
If it is different, then obtaining the degree of incidence of the flight track and the 3rd history flight path；
If the degree of incidence is more than 1, the association flight path of the flight track is adjusted by the first history flight path
For the 3rd history flight path.
Optionally, first adjustment unit is used for:
Determine the cycle of the M sensor gathered data, and the M sensor gathered data cycle and described the
Sampling interval between the one history flight path corresponding sampling period；
Determine whether the first history flight path is successfully associated in the cycle of the M sensor gathered data；
If being successfully associated, determine whether association mass-sequential of the first history flight path within the sampling interval is to pass
Increasing sequence；It is described association mass-sequential be in the association results of the first history flight path correct association results add up；
If increasing sequence, by the flight track and the first history track association.
Said one or multiple technical schemes in the embodiment of the present application, are at least imitated with following one or more technologies
Really：
First, due to the technical scheme in the embodiment of the present invention, M sensing on the flight equipment is arranged on using acquisition
Device collection obtains the N group sensing datas for the flight track for being used to characterize the flight equipment, and M is the integer more than or equal to 2, and N is
Integer more than zero；The N groups sensing data is divided into shared data and identity data, wherein, the shared data are the M
The data that individual sensor can be gathered, the identity data is for the data for the type for characterizing the M sensor；It is sharp respectively
With the shared data and the identity data, the flight track is associated with the flight path in flight path storehouse, wherein, it is described
Flight path storehouse includes the technical scheme of at least one flight track of at least one flight equipment.Sensing number first to getting
According to being classified, it is divided into shared data and identity data, is then utilized respectively shared data and identity data carries out track association,
Efficiently solve track association of the prior art and there is the technical problem under-utilized to identity information, and then reach using many
The identity information of source information and the shared information layered secondary technique effect realized track association, improve identity information utilization rate.
2nd, due to the technical scheme in the embodiment of the present invention, if using the N groups sensing data for discrete sensing number
According to, it is determined that whether include identity data in the N groups sensing data；If comprising determining the boat based on the identity data
With the presence or absence of the first history flight path matched with the flight track in mark storehouse；If not including, based on the N groups sensing data,
The technological means with the presence or absence of the first history flight path matched with the flight track in the flight path storehouse is determined, i.e., true
Sensing data is determined in the case of discontinuous sensing data, using identity data and shared data to discrete point mark
Reason, and then reach the technique effect for improving association accuracy.
3rd, due to the technical scheme in the embodiment of the present invention, conflicted using determining that the flight track whether there is to associate；
Wherein, the association conflict is flight equipment history flight path different in different time sections association；If there is association punching
Prominent, the association results to the flight track are adjusted, and obtain the technological means of new association results, that is, utilize shared data
Completed with identity data after track association, association is also predefined with the presence or absence of conflict, if there is conflict, needs to affiliated partner
It is adjusted, and then reaches the technique effect for improving association accuracy.
Described above, above example is only described in detail to the technical scheme to the application, but implements above
The explanation of example is only intended to the method and its core concept for helping to understand the present invention, should not be construed as limiting the invention.This
Those skilled in the art the invention discloses technical scope in, the change or replacement that can be readily occurred in should all be covered
Within protection scope of the present invention.
Claims (26)
1. a kind of Data Association, applied in electronic equipment, the electronic equipment can be communicated with flight equipment, its
It is characterised by, including：
Obtain the M sensor collection being arranged on the flight equipment and obtain the flight track for being used for characterizing the flight equipment
N group sensing datas, M is integer more than or equal to 2, and N is the integer more than zero；
The N groups sensing data is divided into shared data and identity data, wherein, the shared data are the M sensor
The data that can gather, the identity data is for the data for the type for characterizing the M sensor；
The shared data and the identity data are utilized respectively, the flight track is closed with the flight path in flight path storehouse
Connection, wherein, the flight path storehouse includes at least one flight track of at least one flight equipment.
2. the method as described in claim 1, it is characterised in that described that the N groups sensing data is divided into shared data and body
Number evidence, including：
The time tag of every group of sensing data in the N groups sensing data is obtained, N number of time tag is obtained altogether；
Whether based on N number of time tag, it is continuous sensing data to determine the N groups sensing data；
If the N groups sensing data is continuous sensing data, the N groups sensing data is divided into shared data and identity number
According to.
3. method as claimed in claim 2, it is characterised in that described to be utilized respectively the shared data and the identity number
According to, the flight track is associated with the flight path in flight path storehouse, including：
Based on the identity data, determine in the flight path storehouse with the presence or absence of the first history boat matched with the flight track
Mark；
If being not present, based on the shared data, determine to whether there is what is matched with the flight track in the flight path storehouse
The first history flight path.
4. method as claimed in claim 3, it is characterised in that described to be based on the identity data, is determined in the flight path storehouse
With the presence or absence of the first history flight path matched with the flight track, including：
Obtain very first time label corresponding with the identity data, and the corresponding second time mark of flight path in the flight path storehouse
Label；
Determine the very first time label whether earlier than the time tag of time the latest in second time tag；
If it has not, being then based on the identity data, determine in the flight path storehouse with the presence or absence of the matched with the flight track
One history flight path.
5. method as claimed in claim 3, it is characterised in that if described be not present, based on the shared data, determines institute
State with the presence or absence of the first history flight path matched with the flight track in flight path storehouse, including：
Obtain difference in height, gun parallax and the range difference between every flight path in the flight track and the flight path storehouse；
Based on the difference in height, the gun parallax and the range difference, candidate's history flight path is determined from the flight path storehouse, its
In, difference in height between candidate's history flight path and the flight track be less than height ripple door, candidate's history flight path with
Gun parallax between the flight track is less than the distance between orientation Bo Men, candidate's history flight path and described flight track
Difference is less than range gate；
Determine in candidate's history flight path with the presence or absence of the first history flight path matched with the flight track.
6. method as claimed in claim 5, it is characterised in that every in the acquisition flight track and the flight path storehouse
Difference in height, gun parallax and range difference between flight path, including：
Determine the second history track association at the time of the flight track is whether before the current time and flight path storehouse；
If it is, determine between the flight track and the second history flight path associate it is whether effective；
If invalid, difference in height, gun parallax and range difference between every flight path in the flight track and the flight path storehouse are obtained.
7. method as claimed in claim 5, it is characterised in that whether there is and institute in determination candidate's history flight path
The first history flight path of flight track matching is stated, including：
The flight track and every flight path are extrapolated to current time using least square method；
The vector difference between the flight track and every flight path, and modulus are calculated, at least one described vector difference is obtained
Mould；
Obtain the first overall error average of the flight track, and every flight path the second overall error average, obtain altogether extremely
A few second overall error average；
Based on the mould of at least one vector difference, the first overall error average, and at least one described second overall error are equal
Value, obtains the statistical correlation distance between the flight track and every flight path；
Based on the statistical correlation distance, determine in candidate's history flight path with the presence or absence of the institute matched with the flight track
State the first history flight path.
8. method as claimed in claim 2, it is characterised in that be based on N number of time tag described, determine the N groups
After whether sensing data is continuous sensing data, methods described also includes：
If the N groups sensing data is discrete sensing data, it is determined that whether include identity number in the N groups sensing data
According to；
If comprising determining in the flight path storehouse first to go through with the presence or absence of what is matched with the flight track based on the identity data
History flight path；
If not including, based on the N groups sensing data, determine to whether there is what is matched with the flight track in the flight path storehouse
The first history flight path.
9. method as claimed in claim 8, it is characterised in that if described do not include, based on the N groups sensing data, it is determined that
With the presence or absence of the first history flight path matched with the flight track in the flight path storehouse, including：
Determine whether the N groups sensing data has openness；
If with described openness, based on the N groups sensing data, determining to whether there is in the flight path storehouse and being navigated with the flight
The first history flight path of mark matching.
10. method as claimed in claim 9, it is characterised in that it is sparse whether the determination N groups sensing data has
Property, including：
Determine whether the time difference of the time tag of two adjacent groups sensing data in the N groups sensing data is less than preset time
Difference；Or
Determine whether the difference of space angle in two adjacent groups sensing data in the N groups sensing data is less than pre-set space angle
Difference；Or
Determine whether the dimension of two adjacent groups sensing data in the N groups data is consistent, or the dimension after Coordinate Conversion is
It is no consistent.
11. method as claimed in claim 3, it is characterised in that if being not present described, based on the shared data, really
It whether there is in the fixed flight path storehouse after the first history flight path matched with the flight track, methods described is also wrapped
Include：
Determine that the flight track conflicts with the presence or absence of association；Wherein, the association conflict is the flight equipment when different
Between the upper different history flight paths of section association；
If there is association conflict, the association results to the flight track are adjusted, and obtain new association results.
12. method as claimed in claim 11, it is characterised in that if described have association conflict, to the flight track
Association results are adjusted, and obtain new association results, including：
The 3rd history associated at the time of the current flight path number of the first history flight path is determined between the current time
Whether the history flight path number of flight path is identical；
If it is different, then obtaining the degree of incidence of the flight track and the 3rd history flight path；
If the degree of incidence is more than 1, the association flight path of the flight track is adjusted to institute by the first history flight path
State the 3rd history flight path.
13. method as claimed in claim 11, it is characterised in that if described have association conflict, to the flight track
Association results are adjusted, and obtain new association results, including:
Determine that the cycle of the M sensor gathered data, and the cycle of the M sensor gathered data are gone through with described first
Sampling interval between the history flight path corresponding sampling period；
Determine whether the first history flight path is successfully associated in the cycle of the M sensor gathered data；
If being successfully associated, determine whether association mass-sequential of the first history flight path within the sampling interval is progressive sequence
Row；It is described association mass-sequential be in the association results of the first history flight path correct association results add up；
If increasing sequence, by the flight track and the first history track association.
14. a kind of electronic equipment, the electronic equipment can be communicated with flight equipment, including：
First acquisition unit, obtains described for characterizing for obtaining M sensor being arranged on flight equipment collection
The N group sensing datas of the flight track of flight equipment, M is the integer more than or equal to 2, and N is the integer more than zero；
First division unit, for the N groups sensing data to be divided into shared data and identity data, wherein, the shared number
According to the data that can be gathered for the M sensor, the identity data is for the number for the type for characterizing the M sensor
According to；
First associative cell, for being utilized respectively the shared data and the identity data, by the flight track and flight path
Flight path in storehouse is associated, wherein, the flight path storehouse includes at least one flight track of at least one flight equipment.
15. electronic equipment as claimed in claim 14, it is characterised in that first division unit is used for：
The time tag of every group of sensing data in the N groups sensing data is obtained, N number of time tag is obtained altogether；
Whether based on N number of time tag, it is continuous sensing data to determine the N groups sensing data；
If the N groups sensing data is continuous sensing data, the N groups sensing data is divided into shared data and identity number
According to.
16. electronic equipment as claimed in claim 15, it is characterised in that first associative cell is used for：
Based on the identity data, determine in the flight path storehouse with the presence or absence of the first history boat matched with the flight track
Mark；
If being not present, based on the shared data, determine to whether there is what is matched with the flight track in the flight path storehouse
The first history flight path.
17. electronic equipment as claimed in claim 16, it is characterised in that first associative cell is used for：
Obtain very first time label corresponding with the identity data, and the corresponding second time mark of flight path in the flight path storehouse
Label；
Determine the very first time label whether earlier than the time tag of time the latest in second time tag；
If it has not, being then based on the identity data, determine in the flight path storehouse with the presence or absence of the matched with the flight track
One history flight path.
18. electronic equipment as claimed in claim 17, it is characterised in that first associative cell is used for：
Obtain difference in height, gun parallax and the range difference between every flight path in the flight track and the flight path storehouse；
Based on the difference in height, the gun parallax and the range difference, candidate's history flight path is determined from the flight path storehouse, its
In, difference in height between candidate's history flight path and the flight track be less than height ripple door, candidate's history flight path with
Gun parallax between the flight track is less than the distance between orientation Bo Men, candidate's history flight path and described flight track
Difference is less than range gate；
Determine in candidate's history flight path with the presence or absence of the first history flight path matched with the flight track.
19. electronic equipment as claimed in claim 18, it is characterised in that first associative cell is used for：
Determine the second history track association at the time of the flight track is whether before the current time and flight path storehouse；
If it is, determine between the flight track and the second history flight path associate it is whether effective；
If invalid, difference in height, gun parallax and range difference between every flight path in the flight track and the flight path storehouse are obtained.
20. electronic equipment as claimed in claim 19, it is characterised in that first associative cell is used for：
The flight track and every flight path are extrapolated to current time using least square method；
The vector difference between the flight track and every flight path, and modulus are calculated, at least one described vector difference is obtained
Mould；
Obtain the first overall error average of the flight track, and every flight path the second overall error average, obtain altogether extremely
A few second overall error average；
Based on the mould of at least one vector difference, the first overall error average, and at least one described second overall error are equal
Value, obtains the statistical correlation distance between the flight track and every flight path；
Based on the statistical correlation distance, determine in candidate's history flight path with the presence or absence of the institute matched with the flight track
State the first history flight path.
21. electronic equipment as claimed in claim 15, it is characterised in that be based on N number of time tag described, determine institute
State after whether N groups sensing data be continuous sensing data, the electronic equipment also includes：
First determining unit, if being discrete sensing data for the N groups sensing data, it is determined that the N groups sense number
Whether identity data is included in；
Second determining unit, if for comprising, based on the identity data determine in the flight path storehouse whether there is with it is described fly
First history flight path of row track matching；
3rd determining unit, if for not including, based on the N groups sensing data, determine in the flight path storehouse whether there is with
The first history flight path of the flight track matching.
22. electronic equipment as claimed in claim 21, it is characterised in that the 3rd determining unit is used for：
Determine whether the N groups sensing data has openness；
If with described openness, based on the N groups sensing data, determining to whether there is in the flight path storehouse and being navigated with the flight
The first history flight path of mark matching.
23. electronic equipment as claimed in claim 22, it is characterised in that the 3rd determining unit is used for：
Determine whether the time difference of the time tag of two adjacent groups sensing data in the N groups sensing data is less than preset time
Difference；Or
Determine whether the difference of space angle in two adjacent groups sensing data in the N groups sensing data is less than pre-set space angle
Difference；Or
Determine whether the dimension of two adjacent groups sensing data in the N groups data is consistent, or the dimension after Coordinate Conversion is
It is no consistent.
24. electronic equipment as claimed in claim 15, it is characterised in that if being not present described, based on the shared number
According to determining in the flight path storehouse with the presence or absence of after the first history flight path for being matched with the flight track, the electronics
Equipment also includes：
4th determining unit, for determining that the flight track conflicts with the presence or absence of association；Wherein, the association conflict is described
Flight equipment history flight path different in different time sections association；
First adjustment unit, if for there is association conflict, the association results to the flight track are adjusted, and are obtained newly
Association results.
25. electronic equipment as claimed in claim 24, it is characterised in that first adjustment unit, is used for：
The 3rd history associated at the time of the current flight path number of the first history flight path is determined between the current time
Whether the history flight path number of flight path is identical；
If it is different, then obtaining the degree of incidence of the flight track and the 3rd history flight path；
If the degree of incidence is more than 1, the association flight path of the flight track is adjusted to institute by the first history flight path
State the 3rd history flight path.
26. electronic equipment as claimed in claim 24, it is characterised in that first adjustment unit is used for:
Determine that the cycle of the M sensor gathered data, and the cycle of the M sensor gathered data are gone through with described first
Sampling interval between the history flight path corresponding sampling period；
Determine whether the first history flight path is successfully associated in the cycle of the M sensor gathered data；
If being successfully associated, determine whether association mass-sequential of the first history flight path within the sampling interval is progressive sequence
Row；It is described association mass-sequential be in the association results of the first history flight path correct association results add up；
If increasing sequence, by the flight track and the first history track association.
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