CN106940443A - Complicated city infrastructure PSInSAR deformation methods of estimation under the conditions of cloud-prone and raining - Google Patents
Complicated city infrastructure PSInSAR deformation methods of estimation under the conditions of cloud-prone and raining Download PDFInfo
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Abstract
The present invention relates to interfering synthetic aperture radar technical field, more particularly to a kind of PSInSAR methods of estimation suitable for complicated city infrastructure under the conditions of cloud-prone and raining, comprise the following steps：Data prediction is carried out to InSAR data；Build Delaunay triangulation network and adaptive refinement net；By surely building estimator estimation segmental arc relative parameter；Carry out Tikhonov regularization adjustment computings；Component partial StarNet；Identify that single PS points cover PS points with folded；By surely building single PS points in estimator resolving residual pixel, PS points are covered so that the detection of compressed sensing algorithm is folded；Output list PS points cover PS points height and deformation results with folded.The present invention is by mixing network forming realization list PS points and folded Combined Calculation for covering PS points in the case of without global removal air, introduce the degree of fitting that nonlinear temperature deformation model improves timing rhohase, the accurate estimation of PS points is realized by using robust estimator, PS points are covered using the complicated urban environment of super-resolution MD TomoSAR imaging extractions is folded.
Description
Technical field
It is applied to the present invention relates to interfering synthetic aperture radar technical field, more particularly to one kind under the conditions of cloud-prone and raining again
The PSInSAR methods of estimation of miscellaneous city infrastructure.
Background technology
Urban infrastructure (including highway, building, railway, bridge, dam, airport etc.) is the important composition of urban environment
Part, the structure safety problem of infrastructure is directly connected to the sustainable development of urban environment and social economy.
But in recent years, surface subsidence and basis as caused by groundwater mining, underground space development, Soft Soil Layer deposition etc.
Facility deformation problems are increasingly serious, cause the malformation and damage of infrastructure, or even the accident that causes casualties, and such as 2013
Year Shenzhen earth subsidence in March event causes 1 people dead, and Zhejiang in April, 2014 Fenghua building event of collapsing causes 1 dead 6 wound, in December, 2015
The Gypsum Mine event that collapses in Shandong causes many people to be buried, and sedimentation and deformation geological disaster have become a kind of new "urban disease".《State
Long-term scientific and technological development planning outline in family》In (2006~the year two thousand twenty), clearly will " monitoring of geological disaster, early warning and
Emergency disposal key technology " has been classified as major fields and preferential theme, issued by the State Council《The whole nation of-the year two thousand twenty in 2011 ground
Prevention and cure of settlement is planned》In also explicitly point out national Land Subsidence Survey is completed in the year two thousand twenty and national monitoring network is set up, make
Surface subsidence degradating trend is effectively controlled.
Because Ground Deformation disaster has coverage wide, incitant polyphyly, the features such as occurring disguised is traditional
Measurement means (such as measurement of the level, GPS are measured) based on single-point often can not be positioned accurately and early warning, in application of preventing and reducing natural disasters
In have significant limitation.
Comparatively speaking, interfering synthetic aperture radar (SAR Interferometry, InSAR) technology is supervised in a wide range of city
There is in terms of survey advantageous advantage, especially Permanent scatterers interference technique (Persistent Scatterer InSAR,
PSInSAR proposition and development), realize Centimeter Level to millimetre-sized Ground Deformation monitoring accuracy, and what latest development was got up
SAR chromatography imaging techniques (SAR Tomography, TomoSAR) fold the scattering object covered because it can be separated in SAR imagings, break through
Traditional PS InSAR can only monitor the limitation of single PS points, be more suitable for the deformation monitoring of infrastructure in complicated urban environment.
The development of PSInSAR technologies starts from Ferretti etc. and existed《Geoscience and Remote Sensing,IEEE
Transactions on》Two articles delivered, so-called PS points refer to the pixel point of phase stabilization in sequential image, its
Culture and bare rock in correspondence natural environment etc..Compared to traditional DInSAR technologies, PSInSAR is by extracting sequential phase
Dry target inhibits the influence of Temporal decoherence and atmosphere delay.
After the proposition of PSInSAR methods, substantial amounts of research work is put into the research of PSInSAR technologies to improve
The precision and density of PS measurement points.Wherein compare the classical small baseline algorithm (Small for there are the propositions such as Berardino
Baseline Subsets), it, as main image, is added redundancy interference to number, set by baseline from several SAR images
Put, reduce space dephasing and do and influence of the landform to phase.Coherent Targets method (the Coherent Target of the propositions such as Mora
Monitoring), based on coherence factor reconnaissance, and small base line interference strategy is combined, it is adaptable to PS in the case that image quantity is few
The extraction of point.Werner etc. proposes coherent point analytic approach (Interferometric Point Target Analysis), passes through
To the Spatial And Temporal Characteristics of interference pattern point target, the robustness of Time Series Analysis Method is improved.In order to improve PSInSAR in low phase
The monitoring capability in region is done, Hooper etc. proposes Stamford Permanent scatterers Non-Interference Algorithm (Stanford Method for
Persistent Scatterers Algorithm), the sequential deformation data that algorithm obtains target is twined using three-dimensional space-time solution,
Be particularly suitable for use in volcano, seismic monitoring.LAMBDA algorithms are incorporated into PSInSAR by KAMPES etc., and propose that STUN algorithms are used
In the detection of PS points, it realizes extension a little using two layers of network construction method, and introduces probability statistics model for precision
Evaluate.Devanth é ry etc. propose PSIG (PSI chain of the Geomatics) method, and resolving is twined using 2+1D solutions
Deformation, it is adaptable to city, non-city, the monitoring of vegetation region.In order to increase the space density of PS measurement points, 2 class PS points in addition
It is extracted, a class is half coherent point, another kind of is distributed diffusion body point.
Although PSInSAR technologies have been achieved for significant progress, the complicated city ring under the conditions of monitoring cloud-prone and raining
Still there is limitation in border.The atmosphere delay (Atmospheric Phase Screen, APS) caused by steam is InSAR
Topmost error source, spatio-temporal filtering estimation air has very big in cloud-prone and raining area, traditional PS InSAR handling processes
Uncertainty, has influence on PS point estimation precision and reliability.In addition, under SAR oblique distance imaging patterns, it is high in complicated urban environment
Density, skyscraper facility can cause the Die Yan areas of large area, and folded covers in pixel may include two or more
PS points, traditional PS InSAR technologies can only handle single PS points (single PS are translated into single PS points), it is impossible to separation is folded cover it is many
Individual PS points (overlaid multiple PS are translated into fold and cover PS points), therefore cause the loss of deformation detailed information.Latest developments
The SAR chromatography imaging techniques got up, which are that current solution is folded, covers problem most efficient method.
TomoSAR imaging techniques using many base-line datas vertical oblique distance to synthetic aperture in orientation, thus can be with
Third dimension elevation is realized to imaging, (such as Fig. 1 covers PS for known fold so as to separate the folded multiple obstacles covered in same pixel
Shown in point schematic diagram, folded cover of roof, wall and three, ground point is imaged onto a pixel).
TomoSAR development is initially elevation information for extracting target, including forest height and depth of building, thus
It is referred to as 3D SAR, in forest application aspect, can be used to estimate biomass by the inverting height of tree, can in terms of urban applications
To obtain three-dimensional model building.3D SAR assume phase model only and in height correlation, but practical application, most of many baselines
Data are all obtained by repeat track, therefore elevation information is not only included in phase, also comprising deformation data, in 3D SAR
Single height phase model can not express phase information completely.
In order to solve this problem, 3D SAR expand to Multi-dimension SAR tomography (Multi-Dimensional SAR
Tomography, MD-TomoSAR), current MD-TomoSAR is mainly including 4D SAR and 4D+SAR or 5D SAR, 4D SAR
The difference SAR tomographies (Differential SAR Tomography) of the propositions such as Lombardini, 4D SAR are by linear shape
Varying model is introduced into SAR chromatography models, and height and linear deformation speed can be estimated simultaneously.4D SAR technologies and PSInSAR's
Difference is that 4D SAR can both detect single PS points, and the folded multiple PS points covered can be detected again.
Infrastructure can also produce nonlinear expand with heat and contract with cold in addition to it may occur linear deformation with temperature change
Effect, especially as the raising of shortwave SAR satellites (such as X-band TerraSAR-X) sensitiveness, uses single linear deformation letter
Number can poor fitting phase parameter model.In order to improve the goodness of fit, 4D+ SAR introduce temperature variable, 4D+ on the basis of 4D SAR
SAR in height dimension, linear deformation speed by being tieed up, the upward tomography of three dimensions is tieed up in thermal expansion, can extract single PS points
With the folded height and deformation data for covering PS points, it is adaptable to the monitoring of high building, bridge etc..
TomoSAR imaging algorithms are referred to as harmonic analysis, mainly including Beamforming, Capon, MUSIC
(multiple signal classification)、TSVD(truncated singular value
Decomposition), CS (compressed sensing, compressed sensing) algorithm.Improve chromatography resolution ratio and profit is done on compacting side
It is always the key technology and study hotspot of tomography in recognizing closely located scattering object.The layer of Beamforming invertings
Analysis resolution ratio relatively low (Rayleigh resolution), side do higher.Capon and MUSIC algorithms can suppress side and do raising tomography point
Resolution, but need multiple look processing.Comparatively speaking, TSVD algorithms can be handled under haplopia, but without super-resolution ability.
CS algorithms based on sparse expression are unique methods with super-resolution ability, and with advantage is done without side, it has broken perfume (or spice)
The requirement of agriculture sampling thheorem, can realize the reconstruction of chromatography under the conditions of limited bar baseline sampling, and CS algorithms have been applied to
In 3D SAR imagings.
TomoSAR technologies are had begun to for the folded detection for covering PS points in city, but wherein also have crucial Science and Technology
Problem is not yet solved.First, atmosphere delay can increase the fuzziness of tomography, thus in a wide range of chromatography is resolved, typically
Need to remove air by the spatio-temporal filtering in PSInSAR, but under the conditions of cloud-prone and raining, spatio-temporal filtering estimation air is not
Certainty increase, and this uncertainty can cause parameter estimating error or even directly result in wrong estimation.In addition, TomoSAR
In terms of technical research is focusing more on 3D SAR Height Estimations at present, MD-TomoSAR just began one's study in recent years, and it is extremely
Folded PS point recognition capabilities, especially the super-resolution imaging ability covered of complicated urban environment be not all also by system research.
The content of the invention
In order to solve the above technical problems, the present invention provides complicated city infrastructure under the conditions of a kind of cloud-prone and raining
PSInSAR deformation methods of estimation, realize that list PS points cover PS with folded by mixing network forming in the case of without global removal air
The Combined Calculation of point, introduces the degree of fitting that nonlinear temperature deformation model improves timing rhohase, real by using robust estimator
The accurate estimation of existing PS points, PS points are covered using the complicated urban environment of super-resolution MD-TomoSAR imaging extractions is folded.
The technical solution adopted by the present invention is：Complexity city infrastructure PSInSAR under the conditions of a kind of cloud-prone and raining is provided
Deformation method of estimation, comprises the following steps：
Sequential SAR images are pre-processed, differential interferometry technology image data is obtained；
Single PS points candidate point of Delaunay triangulation network is extracted from the differential interferometry technology image data, each single PS is connected
Point candidate point simultaneously carries out self adaptation network forming encryption, and encryption segmental arc connection gives single PS points in distance threshold to set up phase mode
Type；
Solution twines the phase model and twines phase to produce a solution, and resolves the solution and twine the final segmental arc relative parameter of phase, with
The solution is rejected to twine in phase because measurement noise point or solution twine the exceptional value of error generation；
Phase is twined to the solution and carries out adjustment, with the regularization adjustment knot for the single PS points for obtaining the largest connected net in research area
Really；
List PS points are chosen from the residual pixel of phase model and are folded and cover PS points, and single PS points of selection are covered into PS points with folded
The single PS points candidate point extracted in the closest step before of connection, constitutes local StarNet；
Identify that single PS points in local StarNet cover PS points with folded；
The final segmental arc relative parameter of single PS points identified is resolved, and detects identify folded and covers PS points, is carried out many
Tie up SAR interferometry tomography, determine the phase model pixel whether include the folded multiple PS points covered, it is folded cover number and
Corresponding parametric values.
In method of the present invention, after phase model step is set up, also include：
One non-linear deformation model is set up according to the temperature data in research area, the non-linear deformation model is introduced into the phase
Model；
Judge the degree of fitting of the phase model；
When the phase model is high degree of fitting, solution twines the phase model and twines phase to produce solution.
In method of the present invention, also include after multidimensional SAR interferometry tomography step is carried out：It is defeated
Go out grade list PS points and the folded height and deformation results for covering PS points.
In method of the present invention, the differential interferometry technology image data includes relative elevation, linear deformation speed
Degree and thermal expansion amplitude.
In method of the present invention, the quantity of the encryption segmental arc is adaptive according to Delaunay triangulation network segmental arc density
It should set.
The present invention realizes traditional PS InSAR and TomoSAR combination by ADAPTIVE MIXED network forming, without removing
The extension of PS points is realized in the case of global air；The degree of fitting that nonlinear temperature deformation model improves phase model is introduced, is carried
High deformation estimated accuracy；When local segmental arc relative quantity is calculated with global compensating computation parameter Estimation is improved using robust estimator
Robustness；The folded extraction for covering PS points is realized using the compressed sensing algorithm based on weighting L1 norms；Realized by mixing network forming
Single PS points and the folded robust iterative and Combined Calculation for covering PS points, it is adaptable to the shape of infrastructure in cloud-prone and raining complexity urban environment
Become monitoring.
Brief description of the drawings
Below in conjunction with drawings and Examples, the invention will be further described, in accompanying drawing：
Fig. 1 covers PS point schematic diagrames for known fold；
Fig. 2 is the embodiment of the present invention for infrastructure PSInSAR deformation estimation in complicated city under the conditions of cloud-prone and raining
The wire structural representation of system；
Fig. 3 is the Experimental Area schematic diagram of the embodiment of the present invention；
Fig. 4 is the data baseline profile schematic diagram of inventive embodiments；
Fig. 5 is the embodiment of the present invention for infrastructure PSInSAR deformation estimation in complicated city under the conditions of cloud-prone and raining
The flow chart of method；
Fig. 6 is single PS points candidate point schematic diagram of the embodiment of the present invention；
Fig. 7 A are the DTN schematic diagrames of the embodiment of the present invention；
Fig. 7 B are the largest connected net schematic diagram after segmental arc rejecting on the basis of the DTN of the embodiment of the present invention；
Fig. 7 C are adaptive refinement result schematic diagram on the basis of the DTN of the embodiment of the present invention；
Fig. 7 D are the largest connected net schematic diagram after segmental arc rejecting on the basis of the adaptive refinement net of the embodiment of the present invention；
Fig. 8 is the otherness schematic diagram before and after embodiment of the present invention implementation Tikhonov regularizations, wherein left column：
Result before Tikhonov regularizations, intermediate hurdles：Result after Tikhonov regularizations, right column：Disparity map before and after regularization, it is above-listed：It is high
Cheng Tu, middle row：Thermal expansion map of magnitudes, it is following：Linear deformation hodograph；
Fig. 9 is the schematic diagram that the embodiment of the present invention builds local StarNet, wherein left figure：Black segmental arc represents two grades of construction
Network, red point represents the single PS points detected in first order network, middle figure：Detected in blue segmental arc connection second level network
Single PS points, right figure：The double PS points detected in green segmental arc connection second level network；
Figure 10 A are that the embodiment of the present invention shows L1 norms to the folded extraction schematic diagram for covering PS points of pixel；
Figure 10 B are that the embodiment of the present invention shows weighting L1 norms to the folded extraction schematic diagram for covering PS points of pixel；
Figure 11 is two grades of network forming extension point schematic diagrames of embodiment of the present invention PS algorithms, wherein above-listed：One-level network forming detection
Single PS points, it is following：PS points after extension point cover PS points with folded, left column：Highly, intermediate hurdles：Linear deformation speed, right column：Heat is swollen
Swollen amplitude.
Embodiment
In order to make the purpose , technical scheme and advantage of the present invention be clearer, it is right below in conjunction with drawings and Examples
The present invention is further elaborated.It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, and
It is not used in the restriction present invention.
The embodiment of the present invention provides complicated city infrastructure PSInSAR deformation estimation side under the conditions of a kind of cloud-prone and raining
Method, comprises the following steps：
Sequential SAR images are pre-processed, differential interferometry technology image data is obtained；
Using amplitude deviation threshold method or coherence factor threshold method or intensity method from the differential interferometry technology image data
Single PS points candidate point of Delaunay triangulation network is extracted, each single PS point candidate points is connected and carries out self adaptation network forming encryption, encrypt
Segmental arc connection gives single PS points in distance threshold to set up phase model；
The phase model, which is twined, using Beamforming method solutions twines phase to produce a solution, and by surely building estimator using changing
The solution is resolved for weighted least-squares method and twines the final segmental arc relative parameter of phase, is twined with rejecting the solution in phase because observation is made an uproar
The point of articulation or solution twine the exceptional value of error generation；
Phase is twined to the solution with the regularization matrix of Tikhonov regularizations and carries out adjustment, to obtain the research area most Dalian
The regularization adjustment result of single PS points of logical net；
Chosen with intensity threshold method from the residual pixel of phase model list PS points and it is folded cover PS points, and by single PS of selection
Point and folded PS points of covering connect the single PS points candidate point extracted in closest step before, constitute local StarNet；
Identify that single PS points in local StarNet cover PS points with folded using phase analysis and tomography；
The final segmental arc relative parameter of the single PS points identified is resolved by surely building estimator, is detected with compressed sensing algorithm
Identify it is folded cover PS points, and carry out multidimensional SAR interferometry tomography using L1 norms are weighted, determine the phase model
Pixel whether include the folded multiple PS points covered, folded cover number and corresponding parametric values.
Fig. 2 estimates for the PSInSAR deformation in the embodiment of the present invention for complicated city infrastructure under the conditions of cloud-prone and raining
The wire structural representation of meter systems.As shown in Fig. 2 the Central Processing Unit 102 in the PSInSAR deformation estimating systems passes through control
Each functional module is to realize complicated city ring under the conditions of cloud-prone and raining in the Skysense softwares of Hong Kong Chinese University processed exploitation
The PS points detection of border infrastructure, improves InSAR deformation monitorings precision and space dot density.The function mould of Skysense softwares
Block include engineering management module 104, SAR basic handlings module 106, InSAR processing modules 108, DInSAR processing modules 110,
MT-InSAR analysis modules 112, post-processing module 114 and visualization model 116, are realized from SLC images to InSAR products
(include deformation, PS (Persistent Scatterer, the Permanent scatterers) generations of DEM, DInSAR generation of InSAR generations
Building height and deformation data) integrated treatment.
CPU 102 makes SAR satellite sensors obtain Distance-sensing by controlling SAR basic tools module 106
All scattering object information of device same distance, it is assumed that have the interference pattern of N scape repeat track interference SAR video generations, center processing
The control InSAR of unit 102 processing modules 108 perform order, and are expressed as InSAR signal models：
Y=A γ+e (1)
Wherein y=[y1,…,yN]T((·)TRepresent transfer) be N × 1 vector, represent pass through amplitude calibration and phase
The SAR pixel complex signals of position calibration, A is a N × M (M represents parameter sampling number to be asked) matrix, can be expressed as：
A=[a1,...,aM]
Interferometric phase is represented, wherein mainly including following several parts：
Elevation phase is represented,Deformation phase is represented,Atmosphere delay phase is represented,Represent the decoherence factor
Caused phase.Correlation principle is wherein distributed according to airspace, atmosphere delay can be removed by being made the difference by neighbor point phase, and
Coherence factor very little of PS points itself, therefore elevation and deformation data are just mainly included in phase, just can be with by model parameterization
Calculate elevation and deformation data.
As shown in figure 3, the Experimental Area of the present embodiment is located at Kowloon area, coverage is about 5km × 6km,
Hong Kong is located at tropical and subtropical zone monsoon region, long-term cloud-prone and raining, and because land area is rare, infrastructure develops in intensive.
The present embodiment the use of data is 56 scape TerraSAR-X Stripmap data from March, 2011 in March, 2014, distance
It is 0.9m to the sampling interval, the orientation sampling interval is 2m, and polarization mode is VV, and the main image of selection is on June 6th, 2012,
Baseline profile is if Fig. 4 is shown in the data baseline profile schematic diagram of invention.
Fig. 5 is complicated city infrastructure PSInSAR deformation methods of estimation under the conditions of cloud-prone and raining in the embodiment of the present invention
Flow chart.As shown in figure 5, the control InSAR of CPU 102 processing modules 108 perform order, with to sequential SAR shadows
As carry out data prediction (mainly include data import, registration, interfere, go to level land and difference) operation (step S202) after,
Obtained result just elevation can be carried out using the CuPS functions in MT-InSAR analysis modules 112 and deformation is extracted.
CuPS methods extract research area by mixing network forming (Delaunay triangulation network, adaptive refinement net and StarNet)
Single PS points cover PS points with folded.One-level network forming is to connect and extract most stable of single PS points in research area.
List PS point candidate points, choosing are extracted first with amplitude deviation threshold method or coherence factor threshold method or intensity method
The extraction that taking which kind of method is used for list PS points depends on SAR images quantity, quality and research area's type of ground objects.Due to the present embodiment
Study area and be located at city, therefore selection amplitude deviation threshold method selects single PS points candidate point with threshold value 0.23, as a result such as Fig. 6 institutes
Show.
Then use and selected in Delaunay triangulation network (Delaunay Triangulation Network, DTN) connection figure 6
Candidate point, to avoid the appearance of isolated net in CuPS methods, can select to carry out self adaptation network forming encryption on the basis of DTN,
The point in the given distance threshold of segmental arc connection one is encrypted, the quantity for encrypting segmental arc sets (step according to DTN segmental arcs degree adaptive
S204), segmental arc redundancy had so both been improved and in turn ensure that resolving efficiency, Fig. 7 A to Fig. 7 D be a fritter area in interception research area
DTN and adaptive refinement segmental arc result that domain is obtained, if only rejecting invalid segmental arc on the basis of DTN, the most Dalian resolved
Logical net may not cover PS points rarefaction (such as vegetation region), as shown in Figure 7 B, but after segmental arc is encrypted, it is possible to increase PS
The segmental arc redundancy of point rarefaction, then reject and can ensure after invalid segmental arc global connective (as illustrated in fig. 7d).It is worth noting
Be, if to encrypt segmental arc, encryption quantity to be determined according to the characters of ground object of survey region.
, it is necessary to resolve the segmental arc relative parameter in primary network station after one-level network forming, selection deformation model (step is first had to
Rapid S206), it is general in traditional PS method to use linear deformation model, but urban infrastructure deformation is not often single line
Property deformation, wherein it is most typical be exactly temperature seasonal variety caused by Architectural Equipment expand with heat and contract with cold effect, effect of expanding with heat and contract with cold
It is especially apparent in the infrastructure deformation such as high building, bridge, overpass.Therefore the single line of tradition when monitoring such infrastructure
Property deformation model phase model matching degree can be caused low, so as to cause deformation estimation deviation occur, influence interpretation.
In order to improve the degree of fitting to phase model, the CuPS methods of the present embodiment are used from grinding that Hong Kong Observatory is obtained
Study carefully the temperature data in region to participate in resolving as non-linear deformation model：Therefore phase model can be expressed as in formula (3)：
With
Wherein ξi=2bi/λr0(biVertical parallax is represented, λ represents wavelength, r0Represent oblique distance), s represents vertical radar sight
To the height value with course (chromatograph to), the vertical height of target can be obtained by ssin (θ) (θ represents incidence angle) conversions
Degree；ηi=2ti/λ(tiRepresent time reference line), v represents linear deformation speed；(TiRepresent temperature baselines), k is represented
Thermal expansion amplitude.
The PS point physical quantitys so resolved are in addition to elevation and linear deformation speed, also thermal expansion amplitude, and it represents temperature
Deformation amplitude caused by degree change.It is noted that, nonlinear temperature deformation model is optional model in Skysense,
Be not affected by thermal expansion and contraction or be affected by it is very small in the case of, need to only use the linear model can (step S208).
Determining needs after deformation model to resolve the relative physical parameter in first order network in segmental arc, including relatively high
Journey, linear deformation speed and thermal expansion amplitude.In segmental arc resolving, an end points selected first is as a reference point, another end
Point is as unknown point, and atmosphere delay phase can be removed by subtracting reference point phase using unknown point phase, and elevation is then carried out again
Resolved with deformation.
Traditional PS InSAR resolves segmental arc relative quantity using period map method, and it has 2 points of deficiencies, and one is the setting of parameter step length
Cause to solve not in continuous solution spatially, two be image wait power set can not suppress the influence of observation noise point.To solve
Above mentioned problem, the CuPS methods of the present embodiment twine timing rhohase, Beamforming invertings first with Beamforming method solutions
Normalization chromatography scattering value can be expressed as：
Wherein | | | |2Represent 2 norms.
When the normalization tried to achieve chromatographs scattering value maximum(this experiment is set as during more than a given threshold
0.8) this segmental arc, is retained, now corresponding s, v, k are preliminary required parameter, then take back formula (4) and twine phase to solution,
Otherwise the segmental arc is then rejected.Phase information (y amplitude normalizations) is only used relative to period map method, Beamforming methods are
Phase information make use of to make use of amplitude information again as weight, therefore parameter calculation precision is higher.Parameter is resolved due to preliminary
With step error, after acquisition sequential solution twines phase, CuPS methods are resolved finally using robust estimator-M estimators again
Segmental arc relative parameter, M estimators are a kind of iteration weighted least-squares methods, can with automatic detection and reject solution twine in phase by
Observation noise point or solution twine the exceptional value of error generation, so as to obtain globally optimal solution (step S210).The following institute of its process
Show：
1) it is unit square formation to set iterations l=0, weight matrix W：
W(l=0)=IM (6)
2) physical parameter is calculated using weighted least-square solution：
WhereinRepresent to twine phase using the solution that preliminary resolving parameter is obtained：
Δ φ=DJ
J=[s,v,k]T (8)
It is noted that, as l=0, calculation result is least squares approximation results.
3) residual phase r is calculated(l)=[r1 (l),…,rN (l)]TWith renewal weight matrix
CM-estimator1.345 can be generally set to.
4) convergence is terminated.Otherwise l=l+1, goes to the 2nd step.
By M estimators resolve segmental arc with respect to after physical parameter, it is necessary to pass through the integrated segmental arc relative quantity of network adjustment.
Before adjustment, the global largest connected net of search is first had to, is not global connect because first order network eliminates ropy segmental arc
It is logical, adjustment mistake can be caused due to adjustment matrix rank defect if adjustment of direct observations.It is resolved by first order network relative quantity
Afterwards, the largest connected net of the survey region of search includes P=422559 bars segmental arc and Q=152866 list PS point, then utilizes and adds
Power least-squares algorithm carrys out adjustment：
X=(GTWG)(-1)GTWH (10)
Wherein X=[x1,…,xQ]TRepresent the parameter after segmental arc relative quantity adjustment；G is adjustment matrix, is one sparse
Matrix, including -1,0,1 three numerical value；W is weighting matrix, and weight is usually using segmental arc time-domain coherence coefficientH represents solution
The segmental arc relative quantity calculated：
When adjustment matrix G conditional numbers are very big, formula (10) Weighted L. S. adjustment can take on morbit forms sex chromosome mosaicism, appearance
Global error.In order to solve this problem, the present invention carries out adjustment using Tikhonov regularizations, by introducing a regularization square
Battle array, can reduce adjustment matrix G conditional number, so as to improve adjustment robustness, Tikhonov regularizations are represented by：
X=(GTWG+σI)(-1)GTWH (12)
Wherein s is regularization parameter, is Weighted L. S. adjustment when s is 0, and when s changes are big, local error becomes
Greatly, global error diminishes, and s optimal value can be tried to achieve (step S212) by L-curve method.By calculating, survey region first
Level network adjustment Matrix condition number is calculated as in 3259, the present embodiment respectively by with 0.000001,0.00005,0.000001
It is integrated to height, linear deformation speed and thermal expansion amplitude progress adjustment for regularization parameter, and the ratio of the result without regularization
Compared with (as shown in Figure 8), according to priori, research area no sedimentation and lifting on a large scale, but the result before regularization,
Linear deformation speed has obvious a wide range of lifting (the oval wire frame favored area of such as Fig. 8 lower-lefts figure), and it is adjustment unstability
Caused global error, and after regularization, linear deformation speed global error diminishes, it was demonstrated that the validity of regularization,
And the difference before and after height and thermal expansion amplitude regularization is little.
In CuPS one-level network forming, by adaptive refinement segmental arc, nonlinear temperature deformation model is introduced and using steady
Strong estimator improves the inversion accuracy and stability of parameter.In order to extend PS points, CuPS algorithms resolve parameter in one-level network forming
On the basis of carry out two grades of network formings, traditional PS point extended method need in primary network station by spatio-temporal filtering estimate air, so
The overall situation is resolved again afterwards.Air estimates that this process has very big uncertainty, particularly with cloud-prone and raining area, the space of air
Heterogeneity is improved, and can increase the uncertainty of air estimation, and two grades of network formings can solve this problem.
Second level network, can be to extract remaining single PS points and complicated urban environment using first order network as reference net
In it is folded cover PS points, due to not having amplitude and a phase stability comprising the folded pixel for covering PS points, thus in two grades of network formings with
Intensity threshold method chooses candidate point from residual pixel, and the candidate point so selected includes single PS points (as schemed institute among Fig. 9
Show) and it is folded cover PS points (as shown in Fig. 9 right figure), then they are connected and identified in closest networks by the first order respectively
Single PS points, a pocket in local StarNet, interception research area is built using it as reference point and carries out two grades of network formings, as a result as schemed
Shown in 9 left figure (step S214).
After building two grades of nets, then single PS points therein are identified by phase analysis and tomography and folded PS points are covered
(step S216).Wherein the resolving of list PS points is consistent with the calculation method of segmental arc in first order network, the point such as Fig. 5 institutes calculated
Show (step S218).
When detection is folded covers PS points, in order to improve chromatography resolution ratio and reduction chromatography singular value, present invention uses weighting
L1 norms are compressed perception (CS) super-resolution imaging.CS super-resolution imaging is always that the key of TomoSAR researchs is asked
Topic, CS algorithms are realized by L0 norm constraints, and L0 norms are NP-hard undecidable decision problems, need to make in actual applications
L0 Norm Solutions are approached with L1 norms, but because L1 norms punish regular, the appearance of exceptional value, interference are had in sparse chromatography
The identification of true scattering object and parameter Estimation.Weighting L1 norms are used for MD- with rejecting abnormalities value, the present invention in order to detect
In TomoSAR imagings, the punishment rule for setting up more equality is weighted by iteration, therefore can effectively reduce Multi-dimension SAR chromatography
In exceptional value, weighting L1 norm algorithms it is as follows：
1) it is unit square formation to set iterations l=0, weight matrix W：
W(l=0)=IM
2) utilize and weight L1 minimum resolving parameters：
Wherein | | | |L11- norms are represented, argmin () is used for selecting minimum 1- Norm Solutions, and n represents noise level.
3) chromatography of inverting is utilizedUpdate weight matrix：
Wherein WiWeight matrix W diagonal element is represented, ρ is a weight factor, for avoiding weight infinitely great, it sets
Putting will determine according to the chromatography scattering value of inverting.
4) convergence i.e. terminate, or l to setting maximum；Otherwise step 2 is changed to.
Show that L1 norms and weighting L1 norms are folded to a pixel from Figure 10 A and Figure 10 B and cover PS points (in Fig. 9 right figure
Red arrow point) extraction, it can be seen that except real PS points also have the appearance of exceptional value in L1 norm results, and pass through plus
Weigh operation exception value to reject, only remain real PS points (one on the wall, one on roof).
CS algorithms are only used for the folded spy for covering PS points in the network of the second level in order to improve in operation efficiency, flow of the present invention
Survey, list PS points are detected by maximum time-domain coherence coefficient threshold method (being set to 0.75) first, multiple folded presence for covering PS points can be led
Maximum sequential coherence factor is caused to diminish, therefore when time domain coherence factor thinks to be probably to fold to cover PS points less than 0.75 more than 0.5,
Recycling weighting L1 norms carry out Multi-dimension SAR tomography, determine the folded multiple PS points covered whether are included in pixel, fold and cover number
And corresponding parametric values, what Fig. 9 right figure display was extracted folded covers double PS points distributions (step S220).
After two grades of network forming extension points of CuPS algorithms, the distribution of the PS spaces of points is as shown in figure 11, single PS of one-level network forming detection
Point number is 152866, and single PS points number of extension is 759498, and double PS points numbers are 42238, it is seen that PS dot density phases
It is significantly improved (step S222) for one-level network forming result.
To sum up, it is used for complicated city infrastructure PSInSAR shapes under the conditions of cloud-prone and raining provided in an embodiment of the present invention
Become method of estimation, by mixing network forming realization list PS points and folded joint solution for covering PS points in the case of without global removal air
Calculate, introduce the degree of fitting that nonlinear temperature deformation model improves timing rhohase, the essence of PS points is realized by using robust estimator
Really estimation, PS points are covered using the complicated urban environment of super-resolution MD-TomoSAR imaging extractions is folded.
Embodiments of the invention are described above in association with accompanying drawing, but the invention is not limited in above-mentioned specific
Embodiment, above-mentioned embodiment is only schematical, rather than restricted, one of ordinary skill in the art
Under the enlightenment of the present invention, in the case of present inventive concept and scope of the claimed protection is not departed from, it can also make a lot
Form, these are belonged within the protection of the present invention.
Claims (5)
1. complicated city infrastructure PSInSAR deformation methods of estimation under the conditions of a kind of cloud-prone and raining, it is characterised in that including with
Lower step：
Sequential SAR images are pre-processed, differential interferometry technology image data is obtained；
Single PS points candidate point of Delaunay triangulation network is extracted from the differential interferometry technology image data, each single PS points is connected and waits
Reconnaissance simultaneously carries out self adaptation network forming encryption, and encryption segmental arc connection gives single PS points in distance threshold to set up phase model；
Solution twines the phase model and twines phase to produce a solution, and resolves the solution and twine the final segmental arc relative parameter of phase, to reject
The solution is twined in phase because measurement noise point or solution twine the exceptional value of error generation；
Phase is twined to the solution and carries out adjustment, with the regularization adjustment result for the single PS points for obtaining the largest connected net in research area；
List PS points are chosen from the residual pixel of phase model and are folded and cover PS points, and single PS points of selection and folded PS points of covering are connected
Single PS points candidate point that is closest, extracting before in step, constitutes local StarNet；
Identify that single PS points in local StarNet cover PS points with folded；
The final segmental arc relative parameter of single PS points identified is resolved, and detects identify folded and covers PS points, multidimensional thunder is carried out
Up to interferometry tomography, determine whether the pixel of the phase model includes the folded multiple PS points covered, fold and cover number and corresponding
Parameter value.
2. the method as described in claim 1, it is characterised in that after phase model step is set up, also include：
One non-linear deformation model is set up according to the temperature data in research area, the non-linear deformation model is introduced into the phase mode
Type；
Judge the degree of fitting of the phase model；
When the phase model is high degree of fitting, solution twines the phase model and twines phase to produce solution.
3. the method as described in claim 1, it is characterised in that after multidimensional SAR interferometry tomography step is carried out
Also include：Export grade list PS points and the folded height and deformation results for covering PS points.
4. the method as described in claim 1, it is characterised in that the differential interferometry technology image data include relative elevation,
Linear deformation speed and thermal expansion amplitude.
5. the method as described in claim 1, it is characterised in that the quantity of the encryption segmental arc is according to Delaunay triangulation network arc
Section degree adaptive setting.
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