CN109239702A - A kind of airport low latitude flying bird quantity statistics method based on dbjective state collection - Google Patents
A kind of airport low latitude flying bird quantity statistics method based on dbjective state collection Download PDFInfo
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- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/02—Systems using reflection of radio waves, e.g. primary radar systems; Analogous systems
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Abstract
The present invention provides a kind of airport low latitude flying bird quantity statistics method based on dbjective state collection, comprising: in each filtering cycle, bird radar return metric data, which is visited, according to multiple first continuous cycles carries out frame border merging acquisition flying bird target candidate collection, and concentrated using historical track information in above-mentioned flying bird target candidate and remove existing target, obtain the newborn target candidate collection of the filtering cycle；According to above-mentioned newborn target candidate collection and the already present track of previous moment, the metric data at current time is filtered to obtain current dbjective state collection；The dbjective state collection is carried out track connection and withered away to differentiate, exports the flying bird destination number in the currently monitored range.Method of the invention efficiently uses historical track information, is suitable for the fast-changing airport low latitude of flying bird destination number and visits bird scene, improves flying bird tag number estimate accuracy.
Description
Technical field
The present invention relates to low altitude airspace security monitoring technical field more particularly to radar image processing and target following, tools
Body is a kind of airport low latitude flying bird quantity statistics method based on dbjective state collection.
Background technique
" visit bird radar " has been widely used in the monitoring of airport low latitude bird feelings, can with round-the-clock automatic running and not by
The factors such as weather influence, and are to reduce the raw effective means of bird percussion.
Due to the features such as airport low latitude flying bird flight randomness is strong, radar return is weak, it is difficult to form stable track, together
When, flying bird target quantitatively changes comparatively fast, in addition noise jamming, possible in the measurement of certain targets of certain moment of observation
Missing, thereby increases and it is possible to be mixed into some false-alarm targets, cause traditional target tracking algorism to be difficult to accurately estimate destination number, cause
The decline of tracking performance.
Summary of the invention
In order to overcome the above problem, the invention proposes a kind of, and the airport low latitude flying bird quantity based on dbjective state collection is united
Flying bird dbjective state is expressed as with stochastic finite collection form, no longer Parallel Tracking single target in this method, together by meter method
When, current state set is updated using historical track information, false-alarm is effectively reduced, improves low latitude flying bird destination number
The accuracy of estimation.
A kind of airport low latitude flying bird quantity statistics method based on dbjective state collection, includes the following steps: step 1, every
One filtering cycle visits bird radar return metric data according to multiple first continuous cycles and carries out frame border merging acquisition flying bird mesh
Candidate Set is marked, and is concentrated using historical track information in above-mentioned flying bird target candidate and removes existing target, obtains filtering week
The newborn target candidate collection of phase；Step 2, gathered according to the track of above-mentioned newborn target candidate collection and previous moment, to working as
The metric data at preceding moment is filtered, and obtains current dbjective state collection；Step 3, gather in conjunction with the track of previous moment,
Track state information matrix and current dbjective state collection obtain track set, the track state information matrix at current time,
Realize track connection；Step 4, according to the track at current time set, track state information matrix, judge the mesh withered away
Mark, and the target is removed, obtain flying bird destination number in current period.
Further, in step 1, the form of the metric data is two-dimensional coordinate, and the multiple first continuous cycles are
Two first connection periods.
Further, in step 1, the frame border merges specifically: calculates any two amount between continuous two filtering cycles
The first frame border distance of measured value:
Calculate the second frame border distance of any three measuring values between continuous three filtering cycles:
Meet following frame border and merges condition
d1,ji∈[vmin,vmax]&&d1,pj∈[vmin,vmax]&&d2∈[0,amax]
Point to (r* (k,i),r* (k-1,j),r* (k-2,p)), then it is assumed that it is candidate newborn target, remembers r* (k,i)For candidate new life
The birth position of target, when flying bird target candidate collection is calculated in the measurement set at input k, k-1, k-2 moment, wherein T is
Radar scanning period, rk,iI-th of measuring value that the expression k moment generates, i=1,2 ..., Q, the moment share Q measuring value,
rk-1,jJ-th of measuring value that the expression k-1 moment generates, j=1,2 ..., N, the moment a total of N number of measuring value,rk-2,pIt indicates
P-th of measuring value that the k-2 moment generates, p=1,2 ..., L, the moment a total of L measuring value, vmax、vmin、amaxTable respectively
Show maximum flying bird, minimum flying speed and peak acceleration.
Further, in step 2, it is filtered using GM_PHD filter.
Further, in step 3, k-1 moment already present track set is denoted as Ek-1={ ek-1,s, s=1,2 ..., n,
ek-1,sS-th of existing track value that the expression k-1 moment generates；Gather corresponding state information matrix and be denoted as S in the track1×n, k
The dbjective state that moment obtains integrates as Xk={ xk,i, i=1,2 ..., m, xk,iIt indicates i-th of effective target of k moment, establishes just
Beginning mean vector set U={ μi(i=1,2 ..., n), wherein μi=ek-1,i, to each xk,j, calculate its with it is all
It is worth vector μiEuclidean distance, apart from the smallest μiCorresponding track ek-1,iAs xk,jAffiliated track, if some track
ek-1,iCurrently without measuring value, then a discreet value is given according to front cross frame data.
Further, in step 4, the moment track k set Ek={ ek,i(i=1,2 ..., t), wherein ek,iWhen indicating k
The value of i-th of track is carved, the track state matrix S at k moment is inputted1×t, wherein SiRecord i-th of track ek,iCurrent shape
State, ergodic state matrix, if Si>=3, then prove that i-th of track has been withered away, from EkMiddle deletion ek,i, from S1×tMiddle deletion Si。
The present invention has the advantages that
(1) the airport low latitude flying bird quantity statistics method based on dbjective state collection quickly becomes suitable for flying bird destination number
Bird scene is visited in the airport low latitude of change, improves flying bird tag number estimate accuracy；
(2) the airport low latitude flying bird quantity statistics method based on dbjective state collection can efficiently use historical track information, no
It will receive missing inspection and the influence of false-alarm.
Detailed description of the invention
Fig. 1 is the flow chart of the airport low latitude flying bird quantity statistics method of dbjective state collection of the invention；
Fig. 2 is adjustment location and target following situation schematic diagram before the present frame of the embodiment of the present invention filters；
Fig. 3 is adjustment location and target following situation schematic diagram after the present frame of the embodiment of the present invention filters；
Fig. 4 is tag number estimate result schematic diagram after the present frame of the embodiment of the present invention filters.
Specific embodiment
Below in conjunction with drawings and examples, the present invention is described in further detail.
The invention proposes a kind of airport low latitude flying bird quantity statistics method based on dbjective state collection, flow chart is such as
Shown in Fig. 1.Firstly, visiting bird radar return metric data in each filtering cycle according to multiple first continuous cycles and carrying out frame
Border, which merges, obtains flying bird target candidate collection, and concentrates removal existing in above-mentioned flying bird target candidate using historical track information
Target obtains the newborn target candidate collection of the filtering cycle；Then, according to above-mentioned newborn target candidate collection and it is previous when
Already present track is carved, the metric data at current time is filtered, obtains current dbjective state collection；Finally, to filtering
The dbjective state collection of device output carries out track connection and differentiation of withering away, and exports the flying bird destination number in the currently monitored range.
It is described as follows:
Step 1, newborn target candidate collection is calculated:
In order to detect the newborn flying bird target at k moment, it is assumed that the measurement set at k, k-1, k-2 moment is respectively Mk=
{rk,i}、Mk-1={ rk-1,j}、Mk-2={ rk-2,p, wherein rk,i(i=1,2 ..., Q), i-th of amount that the expression k moment generates
Measured value, the moment share Q measuring value, similarly, rk-1,j(j=1,2 ..., N) indicates j-th of the measuring value generated at the k-1 moment,
The moment a total of N number of measuring value, rk-2,p(p=1,2 ..., L) indicates p-th of the measuring value generated at the k-2 moment, and the moment is total
Share L measuring value.Under two-dimensional scene, measuring value r=(x, y) indicates the two-dimensional coordinate of some position.
Define any two measuring value first frame border distance are as follows:
Define the second frame border distance of any three continuous measuring values are as follows:
Wherein T is radar scanning period, r1、r2、r3For any 3 measuring values.First known to the definition of frame border distance
The physical significance of frame border distance assumes that target does the speed of linear uniform motion, the second frame border between continuous two measuring values
The physical significance of distance assumes that target does the acceleration of uniformly accelrated rectilinear motion between continuous three measuring values.
Calculate the first frame border distance of any two measuring value between continuous two filtering cycles:
Calculate the second frame border distance of any three measuring values between continuous three filtering cycles:
Meet following frame border and merges condition
d1,ji∈[vmin,vmax]&&d1,pj∈[vmin,vmax]&&d2∈[0,amax]
Point to (r* (k,i),r* (k-1,j),r* (k-2,p)), then it is assumed that it is candidate newborn target, remembers r* (k,i)For candidate new life
The birth position of target.Wherein vmax、vmin、amaxMaximum flying bird, minimum flying speed and peak acceleration are respectively indicated, it is fixed
Justice is the merging threshold of the first, second frame border distance, can be obtained by statistics.
According to above method, the measurement set M at k, k-1, k-2 moment is inputtedk、Mk-1、Mk-2, flying bird target is calculated
Candidate Set
Define the fastidious distance between any two measuring value are as follows:
Wherein T is the radar scanning period, and r, e are two different measuring values.
Assuming that k-1 moment historical track collection is combined into Ek-1={ ek-1,s, wherein ek-1,sWhen (s=1,2 ..., n) indicates k-1
Carve s-th of the existing track value generated.
It calculatesAnd Ek-1The fastidious distance of any two measuring value:
Meet following fastidious merging condition:
Point r* (k,i)Newborn target candidate collection is formed, Bk={ r is denoted as** (k,i)(i=1,2 ..., X), the X expression k moment
X newborn target is detected, wherein
Step 2, dbjective state collection is established:
Include a large amount of clutters in the measurement set at k moment, it is filtered by existing GM_PHD filter, from clutter
Middle extraction effective target measures, and establishes dbjective state collection.But the filter specifications are born information as priori using newborn target,
Generally by artificially specifying.But in the case where near airports low latitude flying bird detects scene, newborn flying bird target birth information can not be obtained artificially
It takes, the algorithm in available step 1 obtains.
The newborn target candidate collection B that will be detected in step 1kWith k-1 moment already present track set Ek-1As filtering
The initial information of device, and input the measurement M at k momentk, execute filtering and obtain the filter result set X at k momentk={ xk,i, i=
1,2 ..., m, xk,iIndicate the effective target position at k moment.
Step 3, track connects；
Since the dbjective state collection established in step 2 is unordered state set, it is not directly available stable flying bird rail
Mark, therefore execution track connects.
Input k-1 moment already present track set Ek-1With the filter result set X of k moment filterkAnd k-1
The state information matrix S of moment track1×n(it is initialized as 0 at the k=0 moment, each moment is updated by equal iteration and tieed up later
Shield) execute following procedure:
Select Ek-1In all values as initial mean value vector U={ μi(i=1,2 ..., n) // μi=ek-1,i
K moment updated track set E can be obtainedk={ ek,i(i=1,2 ..., t), wherein ek,i=CiAnd rail
Mark state matrix S1×t。
Step 4, it withers away and judges:
The target of extinction will not generate measurement again, although certain targets tracked may also deposit in certain detection
In missing inspection, but since track collection merges the number for combining track state matrix to will record the continuous missing inspection of some target,
In statistical significance, if the number of the continuous missing inspection of some target is greater than 3 times, so that it may think that it has withered away.
Input k moment track set Ek={ ek,i(i=1,2 ..., t), input the track state matrix S at k moment1×t,
Execute following algorithm:
Current track set E can be obtainedk={ ek,i(i=1,2 ..., m) (m≤t).By detecting track state
Matrix can detected extinction track within 3 periods.If containing false-alarm, since the measurement of false-alarm will not continue more
Newly, it can be detected quickly by extinction detection algorithm, reach the target for reducing false-alarm.The destination number for finally obtaining the k moment is
m。
Below with reference to Fig. 2-4, illustrate how to carry out airport low latitude flying bird quantity statistics using method of the invention.
Step 1, newborn target candidate collection is calculated:
Assuming that flying bird target information is as shown in the table in detection range:
| Target designation | 1 | 2 | 3 | 4 |
| Be born position X | -67.1709 | 795.0736 | -674.6922 | -620.0959 |
| Be born position Y | -7.4683 | 446.4412 | -470.3579 | -839.2658 |
| It is born the moment | 1 | 1 | 38 | 38 |
| It withers away the moment | 37 | 60 | 80 | 80 |
Target designation is corresponding with target designation in Fig. 2.Present scanning cycle k=40.Known k=38, k=39, k=40
Measurement have 38,39,40 respectively and the filter result collection of k=39 that previous scan period treatment obtains is combined into
{ (- 410.9456, -600.5789), (832.1801,647.2697) }, the last two o'clock of 1, No. 2 track in corresponding diagram 2, can
See there are two target, the set record position of target, corresponding track state matrix S=[2,0].Choose vmin=0, vmax
=50, amax=20.The newborn target candidate collection at k=40 moment can be obtained by the method in step 1 are as follows: (-
670.1934, -489.4508), (- 611.3860, -813.9683) }, just A, B two o'clock in corresponding diagram 2, it is seen that 40
Moment successfully has been detected No. 3 and No. 4 targets.
Step 2, dbjective state collection is established:
Using the newborn target candidate information detected in step 1 and 39 moment already present trace information as filter
Initial information, and input 40 moment measurement, execute filtering.Obtain the filter result set at k=40 moment are as follows:
{ (827.0614,653.6661), (- 670.1934, -489.4508), (- 611.3860, -813.9683) }, just correspond to
C, A, B point in Fig. 3.
Step 3, track connects:
It is corresponding by 39 moment filter result set { (- 410.9456, -600.5789), (832.1801,647.2697) }
Track state matrix S=[2,0] and the filter result set at 40 moment (827.0614,653.6661), (-
670.1934, -489.4508), (- 611.3860, -813.9683) } it inputs in above-mentioned track join algorithm, it can be obtained 40
Moment filter result (- 415.5473, -608.1287), (827.0614,653.6661), (- 670.1934, -
489.4508), (- 611.3860, -813.9683) }, just D, C, A, B point in corresponding diagram 3 and corresponding track state
Matrix S=[3,0,0,0].
Step 4, it withers away and judges:
It executes after above-mentioned extinction judges algorithm, it is known that No. 1 target has been withered away, obtains the filtering rail at 40 moment
Trace set is { (827.0614,653.6661), (- 670.1934, -489.4508), (- 611.3860, -813.9683) }, right
The track state matrix answered is S=[0,0,0].So determining that the destination number at 40 moment is 3, as shown in the E point in Fig. 4.
Since Bird Flight track is usually regular, such as straight line or camber line, therefore can use historical track letter
Breath effectively excludes false-alarm and predicts missing inspection target, improves the accuracy of quantity survey.
The foregoing is merely presently preferred embodiments of the present invention, is not intended to limit the invention, it is all in spirit of the invention and
Within principle, any modification, equivalent replacement, improvement and so on be should all be included in the protection scope of the present invention.
Claims (6)
1. a kind of airport low latitude flying bird quantity statistics method based on dbjective state collection comprising following steps:
Step 1, in each filtering cycle, bird radar return metric data is visited according to multiple first continuous cycles and carries out the conjunction of frame border
And flying bird target candidate collection is obtained, and concentrate using historical track information in above-mentioned flying bird target candidate and remove existing target,
Obtain the newborn target candidate collection of the filtering cycle；
Step 2, gathered according to the track of above-mentioned newborn target candidate collection and previous moment, to the metric data at current time
It is filtered, obtains current dbjective state collection；
Step 3, it in conjunction with track set, track state information matrix and the current dbjective state collection of previous moment, obtains current
The track set at moment, track state information matrix realize track connection；
Step 4, according to the track at current time set, track state information matrix, judge the target withered away, and removing should
Target obtains flying bird destination number in current period.
2. a kind of airport low latitude flying bird quantity statistics method based on dbjective state collection according to claim 1, in step 1
In, the form of the metric data is two-dimensional coordinate, and the multiple first continuous cycles are two first connection periods.
3. a kind of airport low latitude flying bird quantity statistics method based on dbjective state collection according to claim 2, in step 1
In, the frame border merges specifically: calculates the first frame border distance of any two measuring value between continuous two filtering cycles:
Calculate the second frame border distance of any three measuring values between continuous three filtering cycles:
Meet following frame border and merges condition
d1,ji∈[vmin,vmax]&&d1,pj∈[vmin,vmax]&&d2∈[0,amax]
Point to (r* (k,i),r* (k-1,j),r* (k-2,p)), then it is assumed that it is candidate newborn target, remembers r* (k,i)For the newborn target of the candidate
Birth position, input k, k-1, k-2 moment measurement set flying bird target candidate collection is calculated, wherein T be radar scanning
Period, rk,iI-th of measuring value that the expression k moment generates, i=1,2 ..., Q, the moment share Q measuring value, rk-1,jIndicate k-
J-th of measuring value that 1 moment generated, j=1,2 ..., N, the moment a total of N number of measuring value, rk-2,pIndicate that the k-2 moment generates
P-th of measuring value, p=1,2 ..., L, the moment a total of L measuring value, vmax、vmin、amaxRespectively indicate flying bird it is maximum,
Minimum flying speed and peak acceleration.
4. a kind of airport low latitude flying bird quantity statistics method based on dbjective state collection according to claim 1, in step 2
In, it is filtered using GM_PHD filter.
5. a kind of airport low latitude flying bird quantity statistics method based on dbjective state collection according to claim 3, in step 3
In, the k-1 moment, already present track set was denoted as Ek-1={ ek-1,s, s=1,2 ..., n, ek-1,sIndicate what the k-1 moment generated
S-th of existing track value；Gather corresponding state information matrix and be denoted as S in the track1×n, the dbjective state that the k moment obtains integrates as Xk
={ xk,i, i=1,2 ..., m, xk,iIt indicates i-th of effective target of k moment, establishes initial mean value vector set U={ μi(i=
1,2 ..., n), wherein μi=ek-1,i, to each xk,j, calculate itself and all mean vector μiEuclidean distance, distance is minimum
μiCorresponding track ek-1,iAs xk,jAffiliated track, if some track ek-1,iCurrently without measuring value, then according to preceding two
Frame data give a discreet value.
6. a kind of airport low latitude flying bird quantity statistics method based on dbjective state collection according to claim 1, in step 4
In, the moment track k set Ek={ ek,i(i=1,2 ..., t), wherein ek,iThe value of i-th of track of k moment is indicated, when inputting k
The track state matrix S at quarter1×t, wherein SiRecord i-th of track ek,iCurrent state, ergodic state matrix, if Si>=3,
Then prove that i-th of track has been withered away, from EkMiddle deletion ek,i, from S1×tMiddle deletion Si。
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| CN110188832B (en) * | 2019-05-08 | 2020-12-08 | 中国民航科学技术研究院 | Airport bird-remaining activity rhythm statistical analysis method based on bird-detecting radar |
| CN111812635A (en) * | 2020-06-10 | 2020-10-23 | 广东电网有限责任公司 | Bird flight trajectory prediction method based on weight calculation by jitter elimination filtering method |
| CN111812635B (en) * | 2020-06-10 | 2023-08-01 | 广东电网有限责任公司 | Bird flight trajectory prediction method based on anti-shake filtering method weighting |
| CN115880646A (en) * | 2023-02-20 | 2023-03-31 | 中国民航大学 | Method for identifying in-out-of-position state of airplane |
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