CN104156977B - Point target movement velocity detection method based on multiple linear moveout scanning, extending and sampling - Google Patents
Point target movement velocity detection method based on multiple linear moveout scanning, extending and sampling Download PDFInfo
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Abstract
A point target movement velocity detection method based on multiple linear moveout scanning, extending and sampling comprises the following steps: (1) establishing a multiple linear moveout scanning detection device; (2) using each linear detector to detect point targets in an extending and sampling manner; (3) processing Nt groups of image data acquired by each linear detector to obtain sub-pixel images; (4) performing non-uniformity correction and sub-pixel match on two sub-pixel images processed by the two adjacent processed linear detectors, then performing difference computation to complete the background subtraction; (5) performing threshold filtering on difference images processed by the two adjacent processed linear detectors, extracting positive and negative point pairs in the difference images by adopting the neighborhood constraint criterion, so as to complete the target detection and extraction of moving points in once scanning process; (6) marking regions of paired positive and negative points extracted in the step (5) respectively, calculating movement velocity and movement directions of the targets according to the position relation of the marked regions of the positive and negative points; (7) averaging the movement velocity and the movement directions obtained in the step (6) to obtain the velocity and the direction of a detected target.
Description
Technical field
The invention belongs to target acquisition image processing field, is related to a kind of point that sampling is extended based on many alignment moveout scans
Target speed detection method.
Background technology
The research of small dim moving target Detection Techniques under complex background has important application in civilian, space flight and military affairs.By
The impact of remote and complex background in image-forming range, target lacks enough texture information and shape information in the picture into point-like,
And the target signal to noise ratio in image is very low, the difficulty of dim targets detection is this considerably increases.Optical imagery general at present
Detection system typically carries out detection imaging using single detector, to acquired image, using method, base based on filtering
In the method for small echo, based on morphologic method etc., single frames background suppression is carried out, suspected target is carried out on single-frame imagess and is carried
Take, the mode for being associated using multiframe afterwards carries out target trajectory fitting, so as to realize target detection.This Detecting System is often by multiple
The impact of miscellaneous background, it is impossible to Objective extraction is reliably carried out on single-frame imagess, while this Detecting System is in Objective extraction mistake
The movable information of target is not made full use of in journey, it is impossible to which the estimation of target speed is carried out by single pass, needed
By Multiple-Scan, using multiframe trajectory analysis, target speed analytical calculation could be realized, reduce the reality of target acquisition
Effect property, improves the complexity of detection data analyzing and processing.
The content of the invention
The present invention technology solve problem be：Overcome the deficiencies in the prior art, propose a kind of based on many alignment moveout scans
The point target movement velocity detection method of extension sampling, realizes the quick analytical calculation of friction speed scope target velocity, improves multiple
The ability of moving target detection under miscellaneous background environment.
The present invention technical solution be：A kind of point target movement velocity that sampling is extended based on many alignment moveout scans
Detection method, step is as follows：
(1) many alignment moveout scan detection devices are constructed, the device includes the detection of optical system, sweep mechanism and many alignments
Device；Described sweep mechanism includes pendulum mirror and its drive shaft；Described many detector array include NdIndividual detector array, often
Individual detector array is arranged in parallel, and the distance between two neighboring detector array is di, wherein i=1,2 ..., Nd-1；Optics
Scene in visual field is imaged in focal plane by system and sweep mechanism together, and drive shaft drives pendulum mirror rotation, the field in linear field
Scape imaging is with tandem many detector array on certain inswept focal plane of speed, angular scanning rateMultiple detector array are successively imaged to same position scene in visual field, two neighboring alignment imaging time
IntervalWherein dminFor the minimum spread length between two neighboring detector array, vminDetectable target
Minimum movement speed, f is optical system focal length, and GSD is the ground sampled distance of detector array；The NdSpan is Nd
≥2；
(2) each detector array carries out point target detection, i.e. detector array and adopts N using extension sample modetIt is individual
Detection array is constituted, and the corresponding instantaneous field of view of pixel is IFOV, and two neighboring detection array is arranged in parallel, in vertical scanning direction
Stagger successively 1/NtIndividual pixel, and arrange detection array in scanning direction, sample in a sampling length StIt is secondary；The sampling
Length is the corresponding instantaneous field of view of pixel；Described NtMore than or equal to 2；The StSpan is St≥2；
(3) N for respectively being gathered each detector arraytGroup view data is processed, and obtains subpixel image；
(4) two width sub-pixed mappings after processing two neighboring detector array respectively carry out Nonuniformity Correction, sub-pix
Difference Calculation is carried out after matching, background elimination is completed；
(5) difference image after processing two neighboring detector array in step (4) respectively carries out threshold filter, and adopts
It is right with neighborhood constraint criterion extraction positive and negative point therein, complete moving spot targets detection during single pass and extract；According to phase
The adjacent line row detector image-forming time difference and target speed form neighborhood constraint criterion
Wherein positive and negative region distance Di, target maximum movement velocity v of detectionmax；
(6) to the paired positive and negative marked region extracted respectively in step (5), closed according to the position of positive and negative marked region
System, calculates movement velocity v of targetiWith direction θi；
(7) movement velocity v that step (6) is obtainediWith direction θiAverage is asked for, speed and the side of detected target is obtained
To that is,
The N for being gathered each detector array in the step (3)tGroup view data is processed, and obtains sub- picture
The mode of first image, detailed process is as follows：
(3.1) N in each detector arraytIndividual detection array is imaged simultaneously, obtains NtGroup view data；Immediately afterwards
Proceed to step (3.2)；Simultaneously, each detector array is according to the setting sampling number corresponding sampling interval in step (2)
Imaging is scanned in scanning direction, imaging every time respectively obtains NtGroup view data, obtains proceeding to step after data immediately
(3.2)；
(3.2) respectively by the N of each detector arraytGroup view data carries out forming frame detection after alignment splicing
Image；
(3.3) complete in a scanning direction after default sampling number, the frame that each detector array correspondence is obtained is visited
Altimetric image carries out splicing and obtains corresponding subpixel image according to the time.
Before the two width subpixel images in the step (4) carry out sub-pix matching, visited with the alignment of first imaging
On the basis of surveying the corresponding subpixel image of device, by the corresponding subpixel image of the detector array of rear imaging in scanning direction forward
It is mobileOK, LpiSeveral rows are rounded, detector array array pixel dimension is a × a.
Filtering in the step (4) is by the way of threshold filter, and detailed process is as follows：
(4.1) each pixel in the difference image obtained after processing step (3) carries out enhancement process, i.e., pending picture
The pixel value of the neighborhood pixels of pixel value * α+four of the pixel value=pending pixel after unit's process, α takes 2～4, obtains after process
Image
(4.2) imageTake absolute value, be designated as image
(4.3) willAdjacent several image columns are divided into one group, are divided into NsubIndividual subimage；The columns L of subimagesub=
H/Nsub, H is imageTotal columns；Simultaneously to imageUsing with imageIdentical mode is grouped, imageWithSubimage correspond；
(4.4) fromThe first row of current subimage is designated as current line and starts, and sets a threshold value initial value T, and T takes first
The pixel value of individual pixel, or the value more slightly larger than the pixel of first pixel；
(4.5) by the L in current subimage current linesubThe pixel value of individual pixel is contrasted successively with threshold value initial value T-phase, such as
Fruit pixel value exceedes threshold value initial value T, then improve certain amplitude to T according to formula (a)：
T '=T+0.5k(Vj-T) (a)
T=T '
Wherein k is coefficient, is adjusted according to signal noise ratio (snr) of image, VjRepresent j-th pixel of current subimage current line
Pixel value；
The T obtained after last pixel of current line is processed, the final filtering of as current subimage current line r
Threshold value Tr；
(4.6) using final threshold value T obtained aboverIt is rightThe corresponding row of middle correspondence subimage carries out threshold filter, i.e.,
For in same a line image, the pixel that will be greater than filtering threshold is labeled as 1；If pixel value is negative, will be less than filtering threshold
The pixel of negative value is labeled as -1；Remaining pixel is labeled as 0；
(4.7) threshold value T for finally giving step (4.5)rRatio reduction is carried out in formula (b), as current subimage
The threshold value initial value of next line：
T=(1-0.5m)Tr (b)
Wherein m is proportionality coefficient；
Using current subimage next line as current line, start to perform from step (4.5), until all rows of current subimage
It is disposed；
(4.8) next subimage is selected as current subimage, repeat step (4.4)～(4.7), until completing to imageThe threshold filter of all rows of all subimages is processed, and is designated as image
(4.9) travel throughEvery string, if continuous more than 2 pixels are denoted as 1, it is constant to retain former mark, otherwise will
The pixel is labeled as 0；If continuous less than 2 pixels are marked as -1, retain former labelling, will otherwise visit pixel and be labeled as 0；
CompleteAfter all pixels traversal, image is designated as
Present invention advantage compared with prior art is：
1st, the comprehensive design for having carried out moving target Detecting System and data processing technique, takes full advantage of moving target
Motion feature, realizes moving target quick detection with detection using new Detecting System and corresponding data processing method：One
During secondary scanning imagery, using imaging difference of the moving target on two width scanograms, dividing for target speed is realized
Analysis is calculated, and compared to traditional scanning probe system, significantly improves the ability of mobile target in complex background detection, is quickly carried out
Target speed is detected；
2nd, carried out by the way of active scan imaging using sweep mechanism, it is possible to achieve on a large scale, the mesh in arbitrary motion direction
Mark detection；According to the change of detecting movements of objects speed, scanning speed can be adjusted, and with reference to the difference of many alignment arrangement pitches
It is different, the positive and negative point on adjacent two alignment difference image is made to meeting certain neighborhood constraints.
3rd, the motion feature of moving target is made full use of, according to moving target on two width subpixel image difference images
Positive and negative marked region differentiates extraction to carrying out moving target, can effectively suppress false-alarm, improves target acquisition accuracy, improves multiple
The ability of moving target detection under miscellaneous background；
4th, when two width subpixel images are matched, directly can be matched using conventional sub-pix matching process, but be matched
Efficiency and precision are relatively low；The present invention makes full use of detector array arrangement feature and the imaging mode for arranging, with first imaging
On the basis of the corresponding subpixel image of detector array, by the corresponding subpixel image of the detector array of rear imaging in scanning side
To forward movement LpOK, two width Rapid Image Registrations are carried out, are matched using sub-pix method for registering again on this basis,
Two width images match scopes are reduced, matching efficiency is improved, reduces matching error, improve matching precision.
Description of the drawings
Fig. 1,2 extend Sample acquisition device two ways schematic diagram for many alignment moveout scans of the invention；
Fig. 3 is the detector array two field picture splicing schematic diagram of the present invention；
Fig. 4 is the residual image column split schematic diagram of the present invention；
Fig. 5 is the object pixel extraction scope schematic diagram of the present invention；
Fig. 6 is the neighborhood constraint criterion schematic diagram of the present invention.
Specific embodiment
Below in conjunction with the accompanying drawings and example elaborates to the present invention.It is a kind of to extend sampling based on many alignment moveout scans
Point target movement velocity detection method, step is as follows：
(1) many alignment moveout scans are constructed and extends Sample acquisition device, the device includes optical system 1, the and of sweep mechanism 2
Many detector array 3；Described Scan Architecture includes pendulum mirror and its drive shaft；Described many detector array include NdIndividual line
Row detector, each detector array is arranged in parallel, and the distance between two neighboring detector array is di, wherein i=1,
2,…,Nd- 1, each detector array adopts NtIndividual detection array composition, the corresponding instantaneous field of view of pixel is IFOV, two neighboring
Detection array is arranged in parallel, staggers successively 1/N in vertical scanning directiontIndividual pixel, and arrange detection array scanning direction,
Sampling S in one sampling lengthtIt is secondary；The sampling length is the corresponding instantaneous field of view of pixel；Many alignment moveout scans are expanded
Exhibition Sample acquisition device sweep mechanism scanning speed beBetween wherein two neighboring detector array
Minimum spread length dmin, target minimum movement speed v of detectionmin, optical system focal length f, the ground surface sample of detector array
Apart from GSD；Described NtMore than or equal to 2；The StSpan is St≥2；The NdSpan is Nd≥2；Each alignment
The ground sampled distance of detector is identical；Below with NtIllustrate as a example by=2.
What Fig. 1 was given is that many alignment moveout scans extension Sample acquisition devices are scanned in front end；Spoke comprising target Yu background
Penetrate the incident illumination of the energy information Jing optical systems 1 Jing after pendulum mirror reflection and converge to focal plane, form the picture of scenery, drive shaft is driven
Movable pendulum mirror rotates according to default angular speed, makes the picture of scenery inswept each detector array successively.When the picture of scenery is with certain
Speed inswept one of detector array when, detector is sampled to the picture of scenery.What Fig. 2 was given is rear-end scanning
Many alignment moveout scans extend Sample acquisition device.Incident illumination Jing optical systems comprising target Yu the emittance information of background
1 converges to pendulum mirror, and Jing pendulum mirrors reflex to focal plane, form the picture of scenery.Drive shaft drives pendulum mirror according to default angular speed
Rotation, makes the picture of scenery inswept each detector array successively.When the picture of scenery is with certain inswept one of line of speed
During row detector, detector is sampled to the picture of scenery.
(2) scene in visual field is imaged in focal plane by optical system 1 and sweep mechanism 2 together, and drive shaft drives pendulum mirror
Rotation, the scene imaging in linear field is adjacent with tandem many detector array on certain inswept focal plane of speed
Two detector array are successively imaged to same position scene in visual field, imaging time interval
N i.e. in each detector arraytIndividual detection array is imaged simultaneously, obtains NtGroup view data；Obtain view data
After immediately enter step (3)；
Simultaneously, each detector array is still secondary according to the sampling in a sampling length is arranged in step (1)
Count, be scanned imaging in scanning direction, imaging every time respectively obtains NtGroup view data, is similarly obtained after view data immediately
Proceed to step (3)；For example, S can be sett>=2, then it is capable of achieving detector array more than 2 times over-samplings in a scanning direction；
(3) respectively by the N of each detector arraytGroup view data carries out forming a frame detection figure after alignment splicing
Picture, splicing is as shown in figure 3, by NtGroup pattern intersects splicing.Sub-pixed mapping frame detection image is obtained by splicing,
Realize stretching of the target in vertical scanning direction.
(4) after default sampling number, the frame detection image that each detector array correspondence is obtained is entered according to the time
Row splicing obtains several subpixel images；Default sampling number can use 200～300 rows, and increasing default sampling number can increase
Scanogram details, improves the precision that successive image is processed；Reducing default sampling number can improve the efficiency of data processing, because
This default sampling number can be adjusted according to practical situation.
(5) correcting mode is synthesized using many alignment moveout scan images, to two width formed by two neighboring detector array
Subpixel image carries out Nonuniformity Correction, specific as follows：
(5.1) two width subpixel images are carried out into intersection splicing by row, forms the new stitching image I of a widthp1；
(5.2) to stitching image Ip1Every string image carry out Nonuniformity Correction, arranged after the completion of all column processing
To the image I after nonuniformity correctionp2；
(5.3) order of splicing is intersected according to the row of two width images in step (5.1), from Ip2It is middle to extract corresponding row respectively
Image, rebuilds two width and completes to arrange the subpixel image to Nonuniformity Correction；
(5.4) row will be completed to be rotated by 90 ° respectively at same direction to two width subpixel images after nonuniformity correction, is repeated
Step (5.1)～(5.3), image I after being correctedp3；
(5.5) order of splicing is intersected according to the row of two width images in step (5.1), from Ip3It is middle to extract corresponding row respectively
Image, rebuilds two width and completes subpixel image of the row to nonuniformity correction；
(5.6) row will be completed to rotate by the opposite direction that step (5.4) rotates to two width subpixel images of nonuniformity correction
90 °, obtain completing two width subpixel images of row, column both direction nonuniformity correction；
(6) for image formed by two adjacent detector array, with the corresponding Asia of detector array of first imaging
On the basis of pixel image, the corresponding subpixel image of the detector array of rear imaging is moved forward in scanning directionLpiSeveral rows are rounded, detector array array pixel dimension is a × a；
(7) two width subpixel images after step (6) process are matched using sub-pix image registration algorithm, specifically
It is as follows：
(7.11) with the corresponding subpixel image of the detector array being first imaged as reference picture, the alignment detection being imaged afterwards
The corresponding subpixel image of device is image subject to registration.
(7.12) gradient largest block is searched in reference picture；The definition of gradient largest block is：Calculate reference frame image
Gradient image, the corresponding pixel logic value of gradient that will be greater than image gradient maximum 4/5 is labeled as 1, is otherwise labeled as 0, shape
Into image be referred to as logical value image.Appropriately sized window is selected in logical value image slide, it is corresponding containing 1 most windows
Block is referred to as gradient largest block.Maximum in by comparing sliding window is determining the position of gradient largest block.Window size is built
It is vertical to adopt 50x50.
(7.13) it is, to picture, using based on the related image matching algorithm of gray scale, to enter to the gradient largest block in (7.12)
Row reference picture is matched with the sub-pix of image subject to registration.By reference picture is entered row interpolation obtain more intensive grid come
For target image search, the registration accuracy of sub-pixel is obtained.
(7.14) registration parameter calculated according to (7.13), carries out image conversion, after obtaining registration to image subject to registration
Image.
(8) Difference Calculation is carried out to two width images after step (7) process, completes the elimination of complex background self adaptation, obtained
Residual image
(9) image to obtaining after step (8) processIn each pixel carry out enhancement process, i.e., pending pixel
The pixel value of the neighborhood pixels of pixel value * α+four of the pixel value after process=pending pixel, α typically takes 2～4, after process
To image
(10) to imageIt is filtered, filtering herein can adopt several filtering modes conventional at present, for example
Iterative threshold segmentation algorithm, naturally it is also possible to which, using the Promethean threshold filter mode of the application, the method detailed process is as follows：
(10.1) imageTake absolute value, be designated as image
(10.2) willAdjacent several image columns (general 6-10 row) are divided into one group, are divided into NsubIndividual subimage, such as Fig. 4
It is shown.The columns L of subimagesub=H/Nsub, H is imageTotal columns；WillAccording to it is above-mentionedIt is identical
Mode is grouped, and is similarly obtained NsubIndividual subimage,WithIn subimage correspond；
(10.3) it is rightIn the first row (being designated as current line) of current subimage start, set a threshold value initial value T, T
The pixel value of first pixel, or the value more slightly larger than the pixel of first pixel can be taken；
(10.4) by the L in current subimage current linesubThe pixel value of individual pixel is contrasted successively with threshold value initial value T-phase, such as
Fruit pixel value exceedes threshold value initial value T, then T is improved into certain amplitude, as shown in formula (a)：
T '=T+0.5k(Vj-T) (a)
T=T '
Wherein k is usually taken to be 4, and k value can be adjusted according to signal noise ratio (snr) of image, and signal noise ratio (snr) of image is higher, can take k value
Little, signal noise ratio (snr) of image is relatively low, k value can be taken greatly, VjRepresent the pixel value of j-th pixel of current subimage current line；
After last pixel of current line is processed, the final filtering threshold T of current subimage current line r is obtainedr；
(10.5) using final threshold value T obtained aboverIt is rightThe corresponding row of middle correspondence subimage carries out threshold filter,
I.e. in same a line image, the pixel that will be greater than filtering threshold is labeled as 1；If pixel value is negative, will be less than filtering threshold
The pixel of value negative value is labeled as -1；Remaining pixel is labeled as 0；
(10.6) threshold value T for finally giving step (10.4)rReduce in a certain ratio, as current subimage next line
Threshold value initial value, now T computing formula such as formula (b)：
T=(1-0.5m)Tr (b)
Wherein m is usually taken to be 4, m values and can be adjusted according to signal noise ratio (snr) of image, and signal noise ratio (snr) of image is higher, can take m values
Greatly, signal noise ratio (snr) of image is relatively low, can take m values little.
Using current subimage next line as current line, start to perform from step (10.4), until current subimage owns
Row is disposed；
(10.7) next subimage is selected as current subimage, repeat step (10.3)～(10.6), until completing right
ImageThe threshold filter of all rows of all subimages is processed, and is designated as image
(10.8) travel throughEvery string, if continuous more than 2 pixels are denoted as 1, it is constant to retain former mark, otherwise
The pixel is labeled as into 0；If continuous less than 2 pixels are marked as -1, retain former labelling, will otherwise visit pixel and be labeled as
0；CompleteAfter all pixels traversal, image is designated as
(11) extractIn paired positive and negative marked region, complete moving target detection during single pass and extract；Such as
Shown in Fig. 6, in pairs the neighborhood constraint criterion of positive negative region is that two positive and negative region distances are Di, it is general desirableTarget maximum movement velocity v for wherein detectingmax；
(12) to the paired positive and negative marked region extracted respectively in step (11), closed according to the position of positive and negative marked region
System, calculates movement velocity v of targetiWith direction θi, comprise the following steps that：
(12.1) for a pair positive and negative marked regions, two registering width subpixel images are corresponded to respectively, extract original image
Element value；Positive marked region correspondence is first imaged subpixel image, extracts the pixel of correspondence position on subpixel image, and including area
The eight neighborhood pixel of the continuous pixel in domain side, as shown in figure 5, as target initial data；Sub-pixed mapping is imaged after the correspondence of negative flag region
Image, extracts the pixel value of correspondence position on subpixel image, and including the eight neighborhood pixel value of the continuous pixel of regional edge, such as schemes
Shown in 5, as target initial data；
(12.2) for the target initial data that formerly imaging subpixel image is extracted in step (12.1), calculated using barycenter
Method, calculates the position coordinateses that target is formerly imaged on subpixel image, is designated asExtracted using rear imaging subpixel image
Target initial data, using centroid algorithm, calculate target in the rear position coordinateses on subpixel image, be designated as
(12.3) position coordinateses on subpixel image and rear imaging subpixel image are formerly imaged using target, calculate mesh
Mark movement velocity, computing formula is as follows：
According to the position coordinateses on priority imaging subpixel imageBy pointPoint toDirection as target direction of motion θi。
(13) movement velocity v that step (12) is obtainediWith direction θiAsk for average, obtain detected target speed and
Direction, i.e.,
Unspecified part of the present invention belongs to general knowledge as well known to those skilled in the art.
Claims (4)
1. it is a kind of that the point target movement velocity detection method sampled is extended based on many alignment moveout scans, it is characterised in that step is such as
Under：
(1) many alignment moveout scan detection devices are constructed, the device includes optical system, sweep mechanism and many detector array；
Described sweep mechanism includes pendulum mirror and its drive shaft；Described many detector array include NdIndividual detector array, each
Detector array is arranged in parallel, and the distance between two neighboring detector array is di, wherein i=1,2 ..., Nd-1；Optical system
Scene in visual field is imaged in focal plane by system and sweep mechanism together, and drive shaft drives pendulum mirror rotation, the scene in linear field
Imaging is with tandem many detector array on certain inswept focal plane of speed, angular scanning rateMultiple detector array are successively imaged to same position scene in visual field, two neighboring alignment imaging time
IntervalWherein dminFor the minimum spread length between two neighboring detector array, vminDetectable target
Minimum movement speed, f is optical system focal length, and GSD is the ground sampled distance of detector array；The NdSpan is Nd
≥2；
(2) each detector array carries out point target detection, i.e. detector array and adopts N using extension sample modetIndividual detection battle array
Row composition, the corresponding instantaneous field of view of pixel is IFOV, and two neighboring detection array is arranged in parallel, wrong successively in vertical scanning direction
Open 1/NtIndividual pixel, and arrange detection array in scanning direction, sample in a sampling length StIt is secondary；The sampling length is
The corresponding instantaneous field of view of pixel；Described NtMore than or equal to 2；The StSpan is St≥2；
(3) N for respectively being gathered each detector arraytGroup view data is processed, and obtains subpixel image；
(4) carry out Nonuniformity Correction, sub-pix to two width sub-pixed mappings after the process of two neighboring detector array respectively to match
After carry out Difference Calculation, complete background elimination；
(5) difference image after processing two neighboring detector array in step (4) respectively carries out threshold filter, and using adjacent
Region constraint criterion extraction positive and negative point therein is right, completes moving spot targets detection during single pass and extracts；According to adjacent lines
The row detector image-forming time difference and target speed form neighborhood constraint criterionIts
In positive and negative region distance Di, target maximum movement velocity v of detectionmax；
(6) to the paired positive and negative marked region extracted respectively in step (5), according to the position relationship of positive and negative marked region, meter
Calculate movement velocity v of targetiWith direction θi；
(7) movement velocity v that step (6) is obtainediWith direction θiAverage is asked for, speed and the direction of detected target is obtained, i.e.,
2. it is according to claim 1 it is a kind of based on many alignment moveout scans extend sampling point target movement velocity detection side
Method, it is characterised in that：The N for being gathered each detector array in the step (3)tGroup view data is processed, and is obtained
To the mode of subpixel image, detailed process is as follows：
(3.1) N in each detector arraytIndividual detection array is imaged simultaneously, obtains NtGroup view data；Each alignment detection
Device is scanned imaging according to the sampling number corresponding sampling interval is arranged in step (2) in scanning direction, every time imaging difference
Obtain NtGroup view data, obtains every time NtStep (3.2) is all proceeded to immediately after group view data；
(3.2) respectively by the N of each detector arraytGroup view data carries out forming a frame detection image after alignment splicing；
(3.3) complete in a scanning direction after default sampling number, the frame detection figure that each detector array correspondence is obtained
Corresponding subpixel image is obtained as carrying out splicing according to the time.
3. it is according to claim 1 it is a kind of based on many alignment moveout scans extend sampling point target movement velocity detection side
Method, it is characterised in that：Before the two width subpixel images in the step (4) carry out sub-pix matching, with first imaging
On the basis of the corresponding subpixel image of detector array, by the corresponding subpixel image of the detector array of rear imaging in scanning side
To forward movementOK, LpiSeveral rows are rounded, detector array array pixel dimension is a × a.
4. it is according to claim 1 it is a kind of based on many alignment moveout scans extend sampling point target movement velocity detection side
Method, it is characterised in that：Filtering in the step (5) is by the way of threshold filter, and detailed process is as follows：
(4.1) each pixel in the difference image obtained after processing step (4) carries out enhancement process, i.e., at pending pixel
The pixel value of the neighborhood pixels of pixel value * α+four of the pixel value after reason=pending pixel, α takes 2～4, image is obtained after process
(4.2) imageTake absolute value, be designated as image
(4.3) willAdjacent several image columns are divided into one group, are divided into NsubIndividual subimage；The columns L of subimagesub=H/
Nsub, H is imageTotal columns；Simultaneously to imageUsing with imageIdentical mode is grouped, image
WithSubimage correspond；
(4.4) fromThe first row of current subimage is designated as current line and starts, and sets a threshold value initial value T, and T takes first picture
The pixel value of element；
(4.5) by the L in current subimage current linesubThe pixel value of individual pixel is contrasted successively with threshold value initial value T-phase, if picture
Element value exceedes threshold value initial value T, then improve certain amplitude to T according to formula (a)：
T '=T+0.5k(Vj-T) (a)
T=T '
Wherein k is coefficient, is adjusted according to signal noise ratio (snr) of image, VjRepresent the pixel of j-th pixel of current subimage current line
Value；
The T obtained after last pixel of current line is processed, the final filtering threshold of as current subimage current line r
Tr；
(4.6) using final threshold value T obtained aboverIt is rightIt is middle correspondence subimage corresponding row carry out threshold filter, i.e., for
With in a line image, the pixel that will be greater than filtering threshold is labeled as 1；If pixel value is negative, will be less than filtering threshold negative value
Pixel be labeled as -1；Remaining pixel is labeled as 0；
(4.7) threshold value T for finally giving step (4.5)rRatio reduction is carried out in formula (b), as current subimage next line
Threshold value initial value：
T=(1-0.5m)Tr (b)
Wherein m is proportionality coefficient；
Using current subimage next line as current line, start to perform from step (4.5), until all rows of current subimage are processed
Finish；
(4.8) next subimage is selected as current subimage, repeat step (4.4)～(4.7), until completing to image
The threshold filter of all rows of all subimages is processed, and is designated as image
(4.9) travel throughEvery string, if continuous more than 2 pixels are denoted as 1, it is constant to retain former mark, otherwise by the picture
Element is labeled as 0；If continuous less than 2 pixels are marked as -1, retain former labelling, otherwise the pixel is labeled as into 0；CompleteAfter all pixels traversal, image is designated as
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| CN110567589A (en) * | 2019-09-11 | 2019-12-13 | 北京空间飞行器总体设计部 | Multi-spectral-segment multi-linear detector system for detecting and identifying moving target |
| CN112997096A (en) * | 2020-07-21 | 2021-06-18 | 深圳市速腾聚创科技有限公司 | Laser radar and autopilot device |
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