CN106918807A - A kind of Targets Dots condensing method of radar return data - Google Patents
A kind of Targets Dots condensing method of radar return data 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
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
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Abstract
The invention belongs to Radar Signal Processing Technology field, a kind of Targets Dots condensing method of radar return data is disclosed, including：Obtain the raw radar data of radar multiple scan period；Carry out envelope detection and multiple-pulse non-inherent accumulation successively to raw radar data, obtain the echo data after pulse accumulation；CFAR detection is carried out to the echo data after pulse accumulation, and then carries out two-value quantification treatment and the two-value sliding window detection along azimuth dimension successively to the echo data after CFAR detection；Echo data after two-value sliding window is detected first is expanded the operation of post-etching to binary image data, so as to obtain all connected domains in binary image data as binary image data；The first connected domain and the second connected domain are filtered, the remaining connected domain comprising Targets Dots is obtained；Target information is obtained according to the remaining connected domain comprising Targets Dots, the cohesion to Targets Dots is realized；Target component estimated accuracy and target resolution capability can be improved.
Description
Technical field
A kind of Targets Dots the invention belongs to Radar Signal Processing Technology field, more particularly to radar return data are condensed
Method, pretreatment and target component for radar return data are extracted.
Background technology
With the development of Radar Technology, people require that radar has more functions and effect.Traditional radar
It is mainly used in measuring the essential informations such as distance, orientation, the pitching of target, modern radar requirement is in increasingly complex environment (interference
With clutter) under realize detection to target, plot extraction and target following.
Modern radar technology develops towards intelligent, miniaturization, information-based and precise treatment direction.People require that radar can
More accurate target information is obtained, and realizes more stable target following.Plot coherence technology is exactly by radar
Echo data carries out processing the process for realizing that target component is estimated with plot extraction, point mark of the radar data processing system to admission
Carry out the tracking display that flight path processing realizes target.The domestic research to radar data treatment technology is started late compared to foreign countries,
Radar system of the research of Plot coherence treatment technology mainly for MTD systems.The method that Plot coherence is mainly used at this stage
There are the Plot coherence based on sliding window method, the Plot coherence based on image procossing etc..
The problem that Plot coherence is primarily present at this stage be under complex environment how the accurate differentiation to Targets Dots, and
The method for how improving Plot coherence treatment under different radar systems.Plot coherence method based on sliding window method is more conventional
A kind of Plot coherence method, the problem being primarily present occurs the division of Targets Dots, mesh when being larger target end of a period threshold value
The division being marked in orientation is solved often through the method for reducing threshold value, and threshold value selection can not be too low, too low
Threshold value cause False Intersection Points mark excessive, an influence point mark quality.The classical method based on image procossing is to use image outline
The method that barycenter is asked in lookup realizes Plot coherence, it is impossible to improve point mark in the fragmentation problem in upper and orientation.
The content of the invention
For the shortcoming of above-mentioned prior art, it is an object of the invention to provide a kind of Targets Dots of radar return data
Condensing method, does not detect only with the two-value sliding window in sliding window method, while the Morphological Filtering Algorithm in employing mathematics is to connection
Domain carries out dilation erosion operation, and the Targets Dots of sliding window method appearance can be not only improved in side by choosing suitable structural element
Separating phenomenon on position, while can realize improving Targets Dots apart from upper separating phenomenon.
To reach above-mentioned purpose, the present invention is adopted the following technical scheme that and is achieved.
A kind of Targets Dots condensing method of radar return data, methods described comprises the following steps：
Step 1, obtains raw radar data of the radar by multiple scan periods of process of pulse-compression, described original time
Wave number according to be comprising the 2-D data apart from peacekeeping azimuth dimension, and the multiple scan period raw radar data along azimuth dimension
It is arranged in order；
Step 2, carries out envelope detection and non-inherent accumulation, after obtaining pulse accumulation successively to the raw radar data
Echo data；
Step 3, CFAR detection is carried out to the echo data after the pulse accumulation, obtains the echo after CFAR detection
Data, and then carry out two-value quantification treatment and the two-value cunning along azimuth dimension successively to the echo data after the CFAR detection
Window detection, obtains the echo data after the detection of two-value sliding window.
Step 4, the echo data after the two-value sliding window is detected is converted into corresponding binary image data, and binary map
The range cell of the echo data after the length correspondence two-value sliding window detection of picture, the width correspondence two-value of bianry image
The umber of pulse of the echo data after sliding window detection, the operation of post-etching is first expanded to the binary image data, so that
All connected domains in the binary image data；
Step 5, in all connected domains, filters the first connected domain and the second connected domain, and first connected domain is
Only comprising a connected domain for isolated point mark, second connected domain is the point mark composition that threshold value is enlarged beyond in distance dimension
Connected domain, so as to obtain the remaining connected domain comprising Targets Dots；Obtained according to the remaining connected domain comprising Targets Dots
To target information, the cohesion to Targets Dots is realized.
The characteristics of technical solution of the present invention and further it is improved to：
(1) after the step 1, and before the step 2, methods described also includes：To the raw radar data
Cancellation is carried out, suppresses the clutter in raw radar data.
(2) step 2 is specially：
Envelope detection is carried out to the raw radar data, so as to obtain raw radar data in respective distances-orientation list
The amplitude information of unit；The range cell is sampled point of the raw radar data in distance dimension, and the localizer unit is
Sampled point of the raw radar data in azimuth dimension.
Sliding window accumulation is carried out on adjacent pulse to the echo data after envelope detection, the number of echoes after pulse accumulation is obtained
According to.
(3) step 3 is specially：
Sliding window detection is carried out along range cell to the echo data after the pulse accumulation, by all reference units in window
Average be multiplied by the threshold value that the value that threshold factor obtains is set to sliding window detection；By the amplitude of unit to be detected and the sliding window
The threshold value of detection is compared, if the amplitude of unit to be detected is more than the threshold value of sliding window detection, by list to be detected
The data of unit retain, and the data of the unit to be detected otherwise are set into 0；
And then the data of the unit to be detected of the threshold value by amplitude more than sliding window detection are set to 1, complete to perseverance
Echo data after false-alarm detection carries out the process of two-value quantification treatment；
When carrying out the detection of two-value sliding window along azimuth dimension to carrying out the echo data after two-value quantification treatment, using M/N criterions,
Wherein, M represents the detection threshold of two-value sliding window detection, the length of window used when N represents that two-value sliding window is detected.
(4) in step 4, the operation of post-etching is first expanded to the binary image data, so as to obtain the two-value
All connected domains in view data, specifically include：
Selecting structure element, the operation of post-etching is first expanded with the structural element chosen, so to binary image data
The lookup of connected domain is carried out to the binary image data for first expanding post-etching afterwards.
(5) in step 5, the remaining connected domain comprising Targets Dots obtains target information described in the basis, realizes to mesh
The cohesion of punctuate mark, specifically includes：
The centroid position of the remaining connected domain comprising Targets Dots is obtained, by the centroid position in original echo number
In corresponding range cell as target range information, by the centroid position in raw radar data corresponding orientation
Unit as target azimuth information；
The corresponding raw radar data of remaining connected domain comprising Targets Dots is obtained, according to described comprising impact point
Range-azimuth unit and corresponding envelope detection result where the corresponding raw radar data of remaining connected domain of mark, ask
Obtain range information, azimuth information and the amplitude information of target.
The present invention compared with prior art, with advantages below：
(1) processed because echo data is converted to bianry image by the present invention, can be realized using software and offline
Treatment；With based on image procossing and based on the sliding window method respective advantage of Plot coherence method, and in classical Plot coherence side
Further a mark is processed using shape filtering method on the basis of method, two kinds of deficiencies of classical way are compensate for, enters one
Step improves the separating phenomenon of Targets Dots, while having point mark quality higher；
(2) the Targets Dots condensing method that the present invention is provided uses bianry image connected domain lookup method, can be accurately true
Set the goal a mark distributed areas, there is resolution ratio higher to Targets Dots, after lookup using centroid method determine region barycenter or
Target component is estimated using echo amplitude method of weighting, it is more accurate than sliding window method that target component is estimated；
(3) filtering more effectively for differentiation for Targets Dots and False Intersection Points mark, combines be based on sliding window method target first
The differentiation of point mark and Plot coherence criterion and target distribution feature, can formulate such target-recognition criterion：On adjusting the distance
Extend that larger Targets Dots are filtered and the point mark that is isolated is filtered, it is secondly less to connected domain area to filter
(design parameter will according to circumstances be set, and not have unified standard), these object judgements filter criterion with point mark can be effective
Identification Targets Dots, while can flexible control point mark quantity；
(4) carrying out connected domain merging by image expansion etching operation can efficiently reduce the influence that Target Splitting is caused,
Further improve the effect based on sliding window method Plot coherence.
Brief description of the drawings
In order to illustrate more clearly about the embodiment of the present invention or technical scheme of the prior art, below will be to embodiment or existing
The accompanying drawing to be used needed for having technology description is briefly described, it should be apparent that, drawings in the following description are only this
Some embodiments of invention, for those of ordinary skill in the art, can also obtain other attached according to these accompanying drawings
Figure.On the premise of not paying creative work, other accompanying drawings can also be obtained according to these accompanying drawings.
Fig. 1 is that a kind of flow of the Targets Dots condensing method of radar return data provided in an embodiment of the present invention is illustrated
Figure；
Fig. 2 is two-value sliding window detection process schematic diagram provided in an embodiment of the present invention；
Fig. 3 is expansion results schematic diagram of the different structure element provided in an embodiment of the present invention to same target；
Fig. 4 is Corrosion results schematic diagram of the different structure element provided in an embodiment of the present invention to same target；
Fig. 5 is pixel syntople schematic diagram provided in an embodiment of the present invention；
Fig. 6 is the connected relation schematic diagram of P, Q, S point provided in an embodiment of the present invention；
Fig. 7 is connected domain search procedure schematic diagram provided in an embodiment of the present invention；
Fig. 8 is raw radar data schematic diagram provided in an embodiment of the present invention；
Fig. 9 is the echo data schematic diagram after non-inherent accumulation provided in an embodiment of the present invention；
Figure 10 is the echo data schematic diagram after CFAR detection result provided in an embodiment of the present invention；
Figure 11 is two-value sliding window testing result schematic diagram provided in an embodiment of the present invention；
Figure 12 is bianry image dilation erosion result schematic diagram provided in an embodiment of the present invention；
Figure 13 is that Targets Dots provided in an embodiment of the present invention condense result schematic diagram.
Specific embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out clear, complete
Site preparation is described, it is clear that described embodiment is only a part of embodiment of the invention, rather than whole embodiments.It is based on
Embodiment in the present invention, it is every other that those of ordinary skill in the art are obtained under the premise of creative work is not made
Embodiment, belongs to the scope of protection of the invention.
The demand for development radar system of Radar Technology provides target component higher, after antenna beam is scanned to target
Echo data separating phenomenon can be produced after signal transacting and target detection, be divided into distance division and orientation division.For two
Plot coherence is exactly the extraction to target primary information (apart from orientation) for dimensional Radar.Extraction generally to target information is adopted
Binary Slide-window detector is used, the degree that Slide-window detector reduces false-alarm depends on detection threshold and length of window.Plot coherence one
Aspect requirement is filtered to False Intersection Points mark, on the other hand requires there is resolution capability higher.Target Splitting can be reduced to bring
Influence simultaneously improve target component quality be an important index for Plot coherence.It is provided in an embodiment of the present invention
Plot coherence method one side algorithm based on image procossing is realized in bianry image, not influenceed by other conditions, more holds
Easily realize；Another aspect image procossing is combined with based on sliding window method Plot coherence, increased the criterion to a mark, favorably
In raising Targets Dots quality.Plot coherence method based on image procossing provided in an embodiment of the present invention is based on sliding window method point
The thought and principle of mark cohesion are combined with image procossing related algorithm, and the result being improved on this basis.
The embodiment of the present invention provides a kind of Targets Dots condensing method of radar return data, as shown in figure 1, methods described
Comprise the following steps：
Step 1, obtains raw radar data of the radar by multiple scan periods of process of pulse-compression, described original time
Wave number according to be comprising the 2-D data apart from peacekeeping azimuth dimension, and the multiple scan period raw radar data along azimuth dimension
It is arranged in order.
You need to add is that, after the step 1, and before the step 2, methods described also includes：To the original
Beginning echo data carries out cancellation, suppresses the clutter in raw radar data.
Step 2, envelope detection and multiple-pulse non-inherent accumulation are carried out to the raw radar data successively, obtain pulse product
Echo data after tired.
Pulse accumulation is divided into correlative accumulation and non-inherent accumulation.Correlative accumulation can preferably improve target signal to noise ratio, but by
It is higher in computational complexity, and Plot coherence evaluated error after correlative accumulation is larger, especially when target Doppler frequency
The effect condensed when appearing in multiple passages or when target is tangentially moved is bad, for two-coordinate radar, target
Major parameter is distance, orientation and velocity, and target component is extracted according to the data after signal target detection.Using non-phase
Ginseng accumulation computational complexity is low, and adaptability is very strong under many scenes, therefore technical solution of the present invention uses the non-coherent of multiple-pulse
Accumulation.
The step 2 is specially：
Envelope detection is carried out to the raw radar data, so as to obtain raw radar data in respective distances-orientation list
The amplitude information of unit；The range cell is sampled point of the raw radar data in distance dimension, and the localizer unit is
Sampled point of the raw radar data in azimuth dimension.
Sliding window accumulation is carried out on adjacent pulse to the echo data after envelope detection, the number of echoes after pulse accumulation is obtained
According to.
Step 3, CFAR detection is carried out to the echo data after the pulse accumulation, obtains the echo after CFAR detection
Data, and then carry out two-value quantification treatment and the two-value cunning along azimuth dimension successively to the echo data after the CFAR detection
Window detection, obtains the echo data after the detection of two-value sliding window, further reduces the influence that False Intersection Points mark brings.The two-value sliding window
Echo data after detection is 2-D data, wherein one-dimensional representation range cell, the umber of pulse of another one-dimensional representation azimuth dimension；
The CFAR detection is using CA-CFAR detection (CA-CFAR).
In the step 3, so the echo data after the CFAR detection is carried out successively two-value quantification treatment and
Detected along the two-value sliding window of azimuth dimension, obtain the echo data after the detection of two-value sliding window, specially：
First to by the echo data after the pulse accumulation that step 2 treatment is obtained examined using CA-CFAR
Survey is processed, and CA-CFAR detection is to carry out sliding window detection along range cell, by the average of all reference units in window
The threshold value that the value that threshold factor obtains is set to sliding window detection is multiplied by, the amplitude of unit to be detected and the sliding window are detected
Threshold value is compared, and retains crossing threshold data, threshold data is not crossed and is set to 0；The data that threshold value will then be crossed are set
It is 1, so as to complete to carry out the echo data after the pulse accumulation process of CFAR detection and two-value quantification treatment；
When carrying out the detection of two-value sliding window along azimuth dimension to carrying out the echo data after two-value quantification treatment, using M/N criterions,
Wherein, M represents the detection threshold of two-value sliding window detection, the length of window used when N represents that two-value sliding window is detected.
Resolution influence of the target starting thresholding of two-value sliding window detection on Targets Dots is little, so setting target end here
Thresholding is identical with initial thresholding, and empirically formula M=1.5*sqrt (N) is chosen the relation of M and N, but in order to subtract
Few Targets Dots division, the detection threshold of two-value sliding window detection answers appropriate reduction.
It should be noted that target end of a period threshold value refers to point mark in sliding window detection process to target when differentiating,
Two-value sliding window accumulating value is a change procedure, judges Targets Dots in orientation by choosing initial thresholding and end of a period thresholding
Starting point and end of a period point, so as to complete resolution of the Targets Dots in orientation.
Specifically, two-value sliding window detection process is as shown in Fig. 2 wherein, Fig. 2 (a) is the input letter after two-value quantification treatment
Number, Fig. 2 (b) is that two-value sliding window detects cumulative process, and Fig. 2 (c) is two-value sliding window testing result schematic diagram；M/N criterions refer to window
Mouth length N=5, detection threshold M=3, are considered as detecting target when two-value accumulation result is more than or equal to threshold value in window
1 is designated as, 0 is otherwise designated as.
You need to add is that, the raw radar data refers to the number after being processed through extra pulse compression after antenna scanning
According to the treatment to echo data includes clutter recognition, signal accumulation and CFAR detection.
For two-coordinate radar, target component refers to the distance and bearing information of target, here to echo data
Non-inherent accumulation is carried out, clutter recognition is realized using canceller.
But as the case may be, such as in order to not influence the target detection to tangential flight, can be to echo data only
Carry out simple signal accumulation and omit cancellation process, the present invention is to echo data treatment using sliding window accumulation, CFAR
Detection and the method for two-value sliding window detection.
Step 4, using the echo data after two-value sliding window detection as binary image data, to the bianry image number
According to the operation for first being expanded post-etching, so as to obtain all connected domains in the binary image data.
Specifically, carrying out dilation erosion operation using Morphological Filtering Algorithm to the binary image data, it is therefore an objective to realize
The merging of connected domain.
The expansion of image and etching operation, from the point of view of image processing point, binary Images Processing is exactly by a small knot
Constitutive element pointwise on big bianry image is moved and compared, and corresponding treatment is made according to result of the comparison.Structural elements
Element refers to the background image with certain size, the shape that structural element is not fixed, while design form becomes scaling method
Needs carry out the design of structural element according to input picture and required information.Usual structural element shape have square, rectangle,
It is circular and linear etc..Briefly, expansion is exactly that the background dot around object is merged into object, and object is outside by expansion
Extension, object so adjacent for two is possible to be coupled together, and the conjunction of connected domain is will appear as in bianry image
And.Opposite, the etching operation of image is exactly the boundary point for eliminating object, and less object is eliminated in addition.
(1) expansion process of image can be simply described as structural element and be traveled through on bianry image, with two-value
As a example by image black color dot, when structural element origin is identical with certain point pixel in bianry image, then structural element and bianry image
It is corresponding to be a little all changed into black color dots.Expansion results schematic diagram of the different structure element to same target is illustrated in figure 3, is schemed
3 (a) is structural element 1, and Fig. 3 (b) is structural element 2, and Fig. 3 (c) is former bianry image, and Fig. 3 (d) is using structural element 1 pair
The result that former bianry image is expanded, Fig. 3 (e) is the result expanded using 2 pairs of former bianry images of structural element, its
In, symbol "+" denotation coordination origin position in structural element.
(2) etching operation of image can be briefly described for structural element traveled through on bianry image when, with two-value
As a example by image black color dot, when structural element origin is identical with certain point pixel in bianry image, if rest of pixels in structural element
There is the pixel of and the above different from bianry image corresponding pixel points, then the point of the bianry image corresponding to origin is changed into white
Color dot.Corrosion results schematic diagram of the different structure element to same target is illustrated in figure 4, Fig. 4 (a) is structural element 1, Fig. 4
B () is structural element 2, Fig. 4 (c) is former bianry image, and Fig. 4 (d) is corroded using 1 pair of former bianry image of structural element
As a result, Fig. 4 (e) is the result corroded using 2 pairs of former bianry images of structural element.
The structural element that the embodiment of the present invention is used is line segment shape structural element, and central point is in line segment center, length
Using the 1/4 of coherent processing umber of pulse, post-etching is first expanded to bianry image, dilation erosion is respectively carried out once.Bianry image is swollen
The swollen merging for realizing connected domain, etching operation recovers to the bianry image after expansion, but recover after image with it is original
Bianry image is different.
Specifically, in step 4, obtaining being needed to after dilation erosion during all connected domains in the binary image data
Connected domain is searched.
It is adjacent with to connect be fundamental relation between pixel, in bianry image in addition to edge pixel, around each pixel
There are 8 abutment points, the position according to abutment points makes a distinction and there are 4 abutment points.As shown in figure 5, being 8 around Fig. 5 (a) black color dots
Adjacent schematic diagram, is 4 adjoining schematic diagrames around Fig. 5 (b) black color dots.
If two points are adjacent according to 4 syntoples or 8 by a series of gray scale identical point sequences in bianry image
It is connected domain to connect will connect together the two points that so just claim of relation, so all that the set of points for connecting are put with the two just
Constitute connected domain, as shown in fig. 6, pixel value is 1 point P, Q, S, wherein P and Q are 8 to connect, S and Q are 4 to connect, S with
P is 8 connections.
It is that 1 pixel carries out connection domain lookup to pixel value so that 8 connect as an example, it is assumed that A is a company in bianry image
Logical domain, a point is known as P in A, then lookup for connected domain A iterative can be carried out by following：
X0=P
Work as Xk=Xk-1When, algorithmic statement, and A=Xk.Wherein, B represents structural element,Represent image expansion operation, Y
It is original bianry image.
Connection domain lookup schematic diagram is illustrated in figure 7, using 8 connected relations, structural element such as Fig. 7 (a), Fig. 7 (b) are company
The starting point P of logical domain lookup, black elements are the element for having extracted, and grey is still undrawn element, and Fig. 7 (c) is the company of lookup
The result of logical domain first time iteration, Fig. 7 (d) is the result for searching second iteration of connected domain, and Fig. 7 (e) is to connect domain lookup most
Whole result schematic diagram.According to the method for connection domain lookup, the connected domain after lookup needs to be marked, until all of pixel is
Untill 1 point has all been marked, this completes the lookup of connected domain.
Step 5, in all connected domains, filters the first connected domain and the second connected domain, and first connected domain is
Only comprising a connected domain for isolated point mark, second connected domain is the point mark composition that threshold value is enlarged beyond in distance dimension
Connected domain, so as to obtain the remaining connected domain comprising Targets Dots；Obtained according to the remaining connected domain comprising Targets Dots
To target information, the cohesion to Targets Dots is realized.
In step 5, the remaining connected domain comprising Targets Dots obtains target information described in the basis, realizes to impact point
The cohesion of mark, specifically includes：
The centroid position of the remaining connected domain comprising Targets Dots is obtained, by the centroid position in original echo number
In corresponding range cell as target range information, by the centroid position in raw radar data corresponding orientation
Unit as target azimuth information；
The corresponding raw radar data of remaining connected domain comprising Targets Dots is obtained, according to described comprising impact point
Range cell, localizer unit and corresponding envelope detection knot where the corresponding raw radar data of remaining connected domain of mark
Really, range information, azimuth information and the amplitude information of target are tried to achieve.
Specifically, in the embodiment of the present invention, when measured data target echo is weaker, in order to retain Targets Dots as far as possible,
So as to the point mark that uses filter criterion for：
(1) independent point mark is filtered, according to target echo characteristic distributions, usual target is in orientation or distance
On can extend, therefore can according to Targets Dots distance or orientation extend size extension filter some False Intersection Points marks；
(2) it is corresponding to echo data to be filtered apart from the more point mark of upper extension, the maximum of range cell according to
The estimation parameter of target and system determines；
(3) in the case where system is allowed, more point mark should as far as possible be retained, so criterion is differentiated and filtered to point mark wanting
Increased according to actual conditions or reduced.
Experiment content and result
Experiment 1, echo data is the echo data of certain air search radar admission, is illustrated in figure 8 certain interception to empty data
Part, data are spliced by the data in the same orientation and distance segment of interception in 9 scan periods of radar.
Target echo data display is as shown in figure 8, the echo data after sliding window accumulation is as shown in Figure 9.It is as shown in Figure 10
Result after CFAR treatment, is as shown in figure 11 the result after the detection of two-value sliding window, and Figure 11 (a) is that two-value sliding window detects M/N
In criterion, M=2, testing result during N=5, Figure 11 (b) is detected in M/N criterions for two-value sliding window, M=3, detection during N=5
As a result.It is as shown in figure 12 the result after bianry image dilation erosion, is as shown in figure 13 target provided in an embodiment of the present invention
The Plot coherence result of Plot coherence method.
As seen from Figure 8, there is stronger clutter around target to be distributed, the data of single interception are difficult to judge impact point
The position of mark, therefore the position of target can be substantially seen by spliced data, can be by the estimation to target location
Plot coherence effect is verified.
As seen from Figure 9, target is by after non-inherent accumulation, the improvement situation for weak signal target is not obvious, but
Still there is certain benefit, mainly have certain smoothing effect to radially distributed meteorological clutter, to followed by permanent empty
Alert detection is favourable.
As seen from Figure 10, Targets Dots and False Intersection Points mark are influenceed by signal transacting and CFAR detection in left point mark
Than larger, contrasted with raw radar data after CFAR detection, be can see together by the substantially judgement to target location
The point mark separating phenomenon of one target is more obvious, and the place marked in figure is the point mark of Target Splitting.
As seen from Figure 11, two-value sliding window detection can be effectively improved the influence that Target Splitting brings, while false-alarm is reduced,
But when using M/N criterions, threshold value crosses point mark of the conference loss compared with weak signal target, and sliding window occurs that Targets Dots divide when detecting
Phenomenon, is generally solved by reducing the method for threshold value, and the too low False Intersection Points mark of threshold value can increase, on a mark quality influence compared with
Greatly.So threshold value needs compromise to consider.As seen from Figure 12, by being detected to sliding window after bianry image to carry out expansion rotten
Erosion operation latter aspect ensure that on the other hand target resolution capability is also fairly effective to the improvement of Target Splitting.
As seen from Figure 13, the method after improvement is successfully realized Plot coherence, and Targets Dots cohesion is achieved preferably
Effect.
To sum up, from experimental result, the inventive method can effectively realize Plot coherence, while reducing Target Splitting
Influence to Plot coherence.
Technical scheme provided in an embodiment of the present invention compares the Plot coherence of sliding window method, the Plot coherence based on image procossing
Technology substantially increases target component precision and target resolution capability, and the related algorithm such as present invention is used in image two
Value image expansion caustic solution can further improve the problem that Target Splitting is there may be in sliding window method Plot coherence.Sliding window method
Benefit be the influence that can effectively overcome Target Splitting and false-alarm to bring, but the selection of sliding window method threshold value is to Plot coherence shadow
Sound is larger, and this point can be improved by shape filtering in image procossing.So with reference to the excellent of sliding window method and image procossing
Point, transforms to a mark image area and is processed, using connected domain lookup algorithm and image expansion corrosion treatment, on the one hand uses
Two-value sliding window is detected and target echo data are processed and is put mark judgement, on the other hand can overcome using image processing method
Point mark division, so as to obtain the target state estimator parameter of better quality.The method that this patent is carried is combined at sliding window method and image
Reason method, it is using the treatment of Slide-window detector and CFAR detection to echo data, second that improved method is mainly reflected in one
It is the influence for improving Targets Dots division using shape filtering method in image procossing.Improved Plot coherence method is solidifying to a mark
The research of poly- technology has important reference value and Research Significance, and measured data demonstrates the validity of institute's extracting method.
The above, specific embodiment only of the invention, but protection scope of the present invention is not limited thereto, and it is any
Those familiar with the art the invention discloses technical scope in, change or replacement can be readily occurred in, should all contain
Cover within protection scope of the present invention.Therefore, protection scope of the present invention should be based on the protection scope of the described claims.
Claims (6)
1. a kind of Targets Dots condensing method of radar return data, it is characterised in that methods described comprises the following steps：
Step 1, obtains raw radar data of the radar by multiple scan periods of process of pulse-compression, the original echo number
According to for comprising the 2-D data apart from peacekeeping azimuth dimension, and the multiple scan period raw radar data along azimuth dimension successively
Arrangement；
Step 2, envelope detection and non-inherent accumulation are carried out to the raw radar data successively, obtain the echo after pulse accumulation
Data；
Step 3, CFAR detection is carried out to the echo data after the pulse accumulation, obtains the number of echoes after CFAR detection
According to, and then carry out two-value quantification treatment and the two-value sliding window along azimuth dimension successively to the echo data after the CFAR detection
Detection, obtains the echo data after the detection of two-value sliding window, and the echo data after the two-value sliding window detection is 2-D data, wherein
One-dimensional representation range cell, the umber of pulse of another one-dimensional representation azimuth dimension；
Step 4, the echo data after the two-value sliding window is detected is converted into corresponding binary image data, and bianry image number
According to the length correspondence two-value sliding window detect after echo data range cell, the width correspondence of binary image data is described
The umber of pulse of the echo data after the detection of two-value sliding window, the operation of post-etching is first expanded to the binary image data, from
And obtain all connected domains in the binary image data；
Step 5, in all connected domains, filters the first connected domain and the second connected domain, and first connected domain is a bag
Containing a connected domain for isolated point mark, second connected domain is the company of the point mark composition that threshold value is enlarged beyond in distance dimension
Logical domain, so as to obtain the remaining connected domain comprising Targets Dots；Mesh is obtained according to the remaining connected domain comprising Targets Dots
Mark information, realizes the cohesion to Targets Dots.
2. the Targets Dots condensing method of a kind of radar return data according to claim 1, it is characterised in that described
After step 1, and before the step 2, methods described also includes：Cancellation is carried out to the raw radar data, is suppressed
Clutter in raw radar data.
3. a kind of Targets Dots condensing method of radar return data according to claim 1, it is characterised in that the step
Rapid 2 are specially：
Envelope detection is carried out to the raw radar data, so as to obtain raw radar data in respective distances-localizer unit
Amplitude information；Range cell is sampled point of the raw radar data in distance dimension, and localizer unit is the original echo
Sampled point of the data in azimuth dimension；
Sliding window accumulation is carried out on adjacent pulse to the echo data after envelope detection, the echo data after pulse accumulation is obtained.
4. a kind of Targets Dots condensing method of radar return data according to claim 1, it is characterised in that the step
Rapid 3 are specially：
Sliding window detection is carried out along range cell to the echo data after the pulse accumulation, by all reference units in window each
The average of amplitude is multiplied by the threshold value that the value that threshold factor obtains is set to sliding window detection；By the amplitude of unit to be detected with it is described
The threshold value of sliding window detection is compared, if the amplitude of unit to be detected is more than the threshold value of sliding window detection, will be to be checked
The data for surveying unit retain, and the data of the unit to be detected otherwise are set into 0；The threshold factor is set in advance
Value；
And then will be greater than the data of the unit to be detected of the threshold value of sliding window detection and be set to 1, complete to CFAR detection
Echo data afterwards carries out the process of two-value quantification treatment；
When carrying out the detection of two-value sliding window using M/N criterions along azimuth dimension to carrying out the echo data after two-value quantification treatment, M tables
Show the detection threshold of two-value sliding window detection, the length of window used when N represents that two-value sliding window is detected.
5. a kind of Targets Dots condensing method of radar return data according to claim 1, it is characterised in that step 4
In, the operation of post-etching is first expanded to the binary image data, it is all in the binary image data so as to obtain
Connected domain, specifically includes：
Selecting structure element, the operation of post-etching is first expanded with the structural element chosen to binary image data, obtains elder generation
The binary image data of post-etching is expanded, the lookup of connected domain is then carried out to the binary image data for first expanding post-etching, from
And obtain all connected domains in the binary image data.
6. a kind of Targets Dots condensing method of radar return data according to claim 1, it is characterised in that step 5
In, target information is obtained according to the remaining connected domain comprising Targets Dots, realize the cohesion to Targets Dots, specific bag
Include：
The centroid position of the remaining connected domain comprising Targets Dots is obtained, by the centroid position in raw radar data
Corresponding range cell as target range information, by the centroid position in raw radar data corresponding localizer unit
As the azimuth information of target；
The corresponding raw radar data of remaining connected domain comprising Targets Dots is obtained, according to described comprising Targets Dots
Range-azimuth unit and corresponding envelope detection result where the corresponding raw radar data of remaining connected domain, try to achieve mesh
Target range information, azimuth information and amplitude information.
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