CN110109112B - InSAR-based method for monitoring deformation of airport in sea reclamation area - Google Patents
InSAR-based method for monitoring deformation of airport in sea reclamation area Download PDFInfo
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Abstract
The invention provides a sea-filling area airport deformation monitoring method based on InSAR, which extracts discretely distributed candidate point targets; calculating the phase standard deviation of each candidate point target to obtain a stable point target; performing three-dimensional space-time unwrapping on the phase of the stable point target to obtain an unwrapped phase; obtaining a deformation phase containing a space interference component by using a least square method; separating an atmospheric phase and an orbit error phase according to the deformation phase containing the space interference component to obtain a deformation phase; and calculating the weight of the deformation phase and the time sequence deformation of the stable point target, thereby completing the monitoring of the deformation of the airport in the sea-fill area by using the time sequence InSAR technology. The method combines an amplitude dispersion threshold and a time coherence coefficient method, improves the number and density of candidate point targets in the sea-filling airport field area, improves the accuracy of deformation rate, and can also be used for high-precision inversion of the deformation field of the complex field area in the low-coherence region.
Description
Technical Field
The invention belongs to the technical field of surface deformation monitoring, and particularly relates to a sea reclamation area airport deformation monitoring method based on InSAR.
Background
Conventional surface deformation monitoring methods mainly include traditional geodetic measurements, such as setting a layering target, leveling, and GPS measurements. The monitoring means can only acquire deformation data on a small number of discrete observation points, cannot be used for revealing the spatial-temporal evolution rule of the surface deformation field, and compared with the traditional surface monitoring means, the time series InSAR technology can monitor the deformation in a large range, and the precision can reach millimeter level. The technology collects SAR image sets covering the same area, intensively studies ground point targets keeping high coherence in long-time sequence SAR images, and is successfully applied to surface deformation monitoring of urban areas with high coherence such as Shanghai, Tianjin, Beijing and the like and other experimental areas with scarce vegetation coverage at present.
However, from the perspective of InSAR analysis, land reclamation areas belong to low coherence regions, lack easily identifiable point targets, and are difficult to perform time series deformation analysis, and meanwhile, large-scale infrastructure structures such as airports are different from other urban buildings, airport runways are usually bare or lawn grass, and coherence of echo signals in the field is very low, so that these places lack easily identifiable target features besides the infrastructure of the airport itself. If an SAR system with medium space-time resolution is adopted, such as SAR images acquired by European space agency satellites ERS-1/2 and ENVISAT are taken as data sources, and deformation calculation is carried out by using a conventional time series InSAR processing technology, the extracted stable target points are sparse due to the limitation of the image resolution and the limitation of a conventional method, and at the moment, the deformation on the point target is difficult to reflect the real deformation field in the region.
The in-orbit operation of the high-resolution radar satellite, for example, a terraSAR-X satellite, has greatly improved orbit positioning accuracy, image resolution and the like compared with the conventional SAR system, has more obvious advantages in surface deformation monitoring, and enables the fine monitoring of large artificial ground features to be possible to a certain extent. However, the radar wavelength of the X band is short and is easily affected by the decoherence phenomenon, and meanwhile, the geological conditions of land reclamation areas are usually complex, and the complex geological conditions can cause variable deformation patterns of buildings thereon, thereby causing difficult interpretation of the InSAR deformation observation.
Therefore, how to combine the TerraSAR-X satellite images with high resolution and expand the application of the time series InSAR technology in low-coherence areas such as sea reclamation face new opportunities and challenges.
Disclosure of Invention
Aiming at the defects in the prior art, the method for monitoring the deformation of the airport in the sea-filling area based on InSAR can utilize a candidate point target extraction strategy of radar imaging and a time coherence coefficient method, improve the number and density of candidate point targets in the sea-filling airport area, realize the space-time analysis of deformation fields in typical areas of airports, such as airport runways, taxiways and the like, and improve the accuracy of deformation monitoring rate.
In order to achieve the above purpose, the invention adopts the technical scheme that:
the scheme provides a sea reclamation area airport deformation monitoring method based on InSAR, which comprises the following steps:
s1, extracting candidate point targets which are discretely distributed in the area where the airport in the sea-filling area is located according to a preset amplitude dispersion threshold;
s2, calculating the phase standard deviation of each candidate point target according to the candidate point targets in the discrete distribution to obtain a stable point target;
s3, performing three-dimensional space-time unwrapping on the phase of the stable point target to obtain an unwrapped phase;
s4, obtaining a deformation phase containing a space interference component by using a least square method according to the unwrapping phase;
s5, separating an atmospheric phase and an orbit error phase according to the deformation phase containing the space interference component to obtain a deformation phase;
and S6, calculating the weight of the deformation phase and the time sequence deformation of the stable point target according to the deformation phase by utilizing the relation between the surface deformation and the radar imaging, thereby completing the monitoring of the deformation of the airport in the sea-filling area by using the time sequence InSAR technology.
Further, the step S2 includes the following steps:
s201, constructing a spatial filtering grid by using the candidate point targets in discrete distribution, and removing phase contributions related to the space;
s202, calculating a terrain residual phase and an error phase which are uncorrelated in the candidate point space by using the nearest neighbor difference value to obtain a terrain residual phase and a time coherence coefficient;
s203, according to the time coherence coefficient, obtaining a time coherence coefficient threshold of a candidate point target by using a statistical method, and selecting a coherent point target;
s204, judging whether the time coherence coefficient is smaller than the time coherence coefficient threshold value, if so, entering a step S206, otherwise, entering a step S205;
s205, calculating the signal-to-noise ratio of the coherent point target according to the uncorrelated error phases of the candidate point space, updating the grid phase weight in the spatial filtering grid through the signal-to-noise ratio, and returning to the step S201;
s206, calculating the phase standard deviation of each candidate point according to the judgment result;
and S207, judging whether the phase standard deviation of the candidate points is smaller than a preset minimum phase standard deviation threshold, if so, entering the step S3, otherwise, removing wrong candidate point targets, and finishing the extraction of the stable point targets.
Still further, in step S205, an expression of the grid phase weights in the spatial filtering grid is as follows:
where φ represents the grid phase weight, ADI, in the spatial filtering gridiRepresenting the amplitude dispersion, n representing the total number of candidate points,
denotes the initial weight, phiiThe phase value of the i-th candidate point is represented.
Still further, the calculation formula of the deformation phase containing the spatial interference component in step S4 is as follows:
wherein the content of the first and second substances,
representing the deformed phase containing the spatial interference component,
representing the remaining phase of the interference phase after removal of the terrain phase,
representing the sum of the atmospheric phase and the track error phase,
representing the noise phase.
Still further, step S5 is specifically:
according to the deformation phase containing the space interference component, the atmospheric phase and the orbit error phase are separated by adopting high-pass filtering on a time domain and low-pass filtering on a space domain, and the deformation phase is obtained.
Still further, the weight calculation formula of the deformation phase in step S6 is as follows:
P＝diag(σ1，σ2，...σN)
wherein P represents the weight of the deformation phase, diag (·) represents the diagonal matrix function, σkRepresenting the interference phase standard deviation of the kth interference image pair, N representing the number of interference image pairs,
the noise phase of the x-th stable point target on the k-th interference image pair is shown, and M shows the number of stable point targets.
Still further, the expression of the time-series deformation v of the candidate point target in step S6 is as follows:
v＝(T'PT)-1T'Pd
wherein, T' represents the transpose matrix of the time base line matrix of the candidate point target, P represents the weight matrix of the deformation phase, T represents the time base line matrix of the candidate point target, and d represents the deformation quantity of the candidate point target.
The invention has the beneficial effects that:
(1) the method monitors airports in sea-filling land-building areas by using a time sequence InSAR technology, improves a method for combining amplitude dispersion ADI and a time coherence coefficient to identify candidate point targets in a low coherence area, eliminates possible error point targets by setting a phase standard deviation threshold of candidate points, namely calculates the phase standard deviation of each candidate point, discards the candidate target point as an unstable point target if the minimum phase standard deviation of the candidate target point in any interference pair is greater than a threshold, calculates the weight of a deformation phase and the time sequence deformation of the candidate point target by using a radar imaging and time coherence coefficient method, and improves the number and density of the candidate point targets in the sea-filling machine area;
(2) the invention improves the quantity and density of point targets in a sea-filling machine field area by combining a point target extraction strategy based on an amplitude deviation ADI and a time coherence coefficient method, can realize the space-time analysis of deformation fields of typical areas of airports such as airport runways and taxiways, and the confidence coefficient of the result corresponding to the real deformation rate of the ground is 95 percent.
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FIG. 1 is a flow chart of the method of the present invention.
Detailed Description
The following description of the embodiments of the present invention is provided to facilitate the understanding of the present invention by those skilled in the art, but it should be understood that the present invention is not limited to the scope of the embodiments, and it will be apparent to those skilled in the art that various changes may be made without departing from the spirit and scope of the invention as defined and defined in the appended claims, and all matters produced by the invention using the inventive concept are protected.
Examples
The method monitors the airport of the land reclamation area by using the time sequence InSAR technology, improves the method of combining ADI and time coherence coefficient to identify the point target of the low coherence area, eliminates the possible error point target by setting the phase standard deviation threshold of the candidate points, namely calculates the phase standard deviation of each candidate point, if the minimum phase standard deviation of the point in any interference pair is more than the threshold, the point is taken as an unstable point target to be discarded, and the method is concretely realized as follows:
as shown in fig. 1, the invention discloses a sea-filling area airport deformation monitoring method based on InSAR, which is implemented as follows:
s1, extracting candidate point targets which are discretely distributed in the area where the airport in the sea-filling area is located according to a preset amplitude dispersion threshold;
s2, calculating the phase standard deviation of each candidate point target according to the candidate point targets in the discrete distribution to obtain a stable point target, and the method comprises the following steps:
s201, constructing a spatial filtering grid according to the discretely distributed candidate point targets, and removing spatially related phase contributions, in the specific embodiment, performing grid meshing on the candidate point targets, namely constructing the spatial filtering grid by using the discretely distributed candidate points to remove the spatially related phase contributions, wherein phase values of the grid are obtained by calculating weighted average of the phase of the point targets, and the reciprocal of ADI is defined as an initial weight;
s202, calculating a terrain residual phase and an error phase which are uncorrelated with a candidate point space by using the nearest difference value to obtain a terrain residual phase and a time coherence coefficient, wherein in the specific embodiment, as the terrain residual phase is a function of a DEM error, an optimal terrain residual phase can be searched by setting a search step length in a DEM error tolerance range, so that the time coherence coefficient reaches the maximum, and the time coherence coefficient and the terrain residual phase at the moment are recorded;
s203, according to the time coherence coefficient, obtaining a time coherence coefficient threshold of a candidate point target by using a statistical method, and selecting a coherent point target;
s204, judging whether the time coherence coefficient is smaller than the time coherence coefficient threshold value, if so, entering a step S206, otherwise, entering a step S205;
s205, calculating the signal-to-noise ratio of the coherent point target according to the uncorrelated error phases of the candidate points, updating the grid phase weight in the spatial filtering grid through the signal-to-noise ratio, returning to the step S201, and stopping iteration until the change of the value is smaller than a specified tolerance, wherein the expression of the grid phase weight in the spatial filtering grid is as follows
Where φ represents the grid phase weight, ADI, in the spatial filtering gridiRepresenting the amplitude dispersion, n representing the total number of candidate points,
denotes the initial weight, phiiA phase value representing the ith candidate point;
s206, calculating the phase standard deviation of each candidate point according to the judgment result;
s207, judging whether the phase standard deviation of the candidate points is smaller than a preset minimum phase standard deviation threshold value, if so, entering a step S3, otherwise, removing wrong candidate point targets, and finishing the extraction of stable candidate point targets;
in the embodiment, through the iterative solution, a point target with an error is removed, a stable point target for subsequent deformation inversion is identified, after the point target is extracted, an absolute unwrapping phase is recovered by performing three-dimensional space-time unwrapping on the phase of the point target, and then, a least square method is used for solving the phase variation in a time dimension to obtain a deformation phase including interference of other space-related components; and then according to the space-time characteristics of the interference components, separating an atmospheric phase and an orbit error phase by adopting high-pass filtering on a time domain and low-pass filtering on a space domain, and finally obtaining a deformation phase. Calculating to obtain the upward deformation of the radar sight by using the geometric relation between the surface deformation and the radar imaging so as to obtain the deformation value on the time sequence, and the following steps:
s3, performing three-dimensional space-time unwrapping on the phase of the stable point target to obtain an unwrapped phase;
s4, obtaining a deformation phase containing a space interference component by using a least square method according to the unwrapping phase, wherein a calculation formula of the deformation phase containing the space interference component is as follows:
wherein the content of the first and second substances,
representing the deformed phase containing the spatial interference component,
representing the remaining phase of the interference phase after removal of the terrain phase,
is the sum of the atmospheric phase and the track error phase,
representing the noise phase;
s5, separating the atmospheric phase and the orbit error phase according to the deformation phase containing the space interference component to obtain the deformation phase, which specifically comprises the following steps:
according to the deformation phase containing the space interference component, separating an atmospheric phase and an orbit error phase by adopting high-pass filtering on a time domain and low-pass filtering on a space domain to obtain the deformation phase;
s6, calculating the weight of the deformation phase and the time sequence deformation of the stable point target according to the deformation phase by utilizing the relation between the surface deformation and the radar imaging, thereby completing the monitoring of the deformation of the airport in the sea-filling area by using the time sequence InSAR technology, wherein,
the weight calculation formula of the deformation phase is as follows:
P＝diag(σ1，σ2，…σN)
wherein P represents the weight of the deformation phase, and diag (. circle.) representsDiagonal matrix function, σkRepresenting the interference phase standard deviation of the kth interference image pair, N representing the number of interference image pairs,representing the noise phase of the xth stable point target on the kth interference image pair, wherein M represents the number of the stable point targets;
the expression of the time series deformation v of the candidate point target is as follows:
v＝(T'PT)-1T'Pd
wherein, T' represents the transpose matrix of the time base line matrix of the candidate point target, P represents the weight matrix of the deformation phase, T represents the time base line matrix of the candidate point target, and d represents the deformation quantity of the candidate point target.
The method utilizes the time sequence InSAR technology to monitor the airport in the sea-filling and land-building area, and utilizes the combination of the amplitude deviation threshold and the time coherence coefficient method, thereby improving the quantity and the density of candidate point targets in the sea-filling airport area, realizing the space-time analysis of deformation fields in typical areas of airports, such as airport runways, taxiways and the like, and improving the deformation accuracy.
Claims (6)
1. An InSAR-based method for monitoring airport deformation in sea-filling areas is characterized by comprising the following steps:
s1, extracting candidate point targets which are discretely distributed in the area where the airport in the sea-filling area is located according to a preset amplitude dispersion threshold;
s2, calculating the phase standard deviation of each candidate point target according to the candidate point targets in the discrete distribution to obtain a stable point target, wherein the step S2 comprises the following steps:
s201, constructing a spatial filtering grid by using the candidate point targets in discrete distribution, and removing phase contributions related to the space;
s202, calculating a terrain residual phase and an error phase which are uncorrelated in the candidate point space by using the nearest neighbor difference value to obtain a terrain residual phase and a time coherence coefficient;
s203, according to the time coherence coefficient, obtaining a time coherence coefficient threshold of a candidate point target by using a statistical method, and selecting a coherent point target;
s204, judging whether the time coherence coefficient is smaller than the time coherence coefficient threshold value, if so, entering a step S206, otherwise, entering a step S205;
s205, calculating the signal-to-noise ratio of the coherent point target according to the uncorrelated error phases of the candidate point space, updating the grid phase weight in the spatial filtering grid through the signal-to-noise ratio, and returning to the step S201;
s206, calculating the phase standard deviation of each candidate point according to the judgment result;
s207, judging whether the phase standard deviation of the candidate points is smaller than a preset minimum phase standard deviation threshold value, if so, entering a step S3, otherwise, removing wrong candidate point targets, and finishing the extraction of the stable point targets;
s3, performing three-dimensional space-time unwrapping on the phase of the stable point target to obtain an unwrapped phase;
s4, obtaining a deformation phase containing a space interference component by using a least square method according to the unwrapping phase;
s5, separating an atmospheric phase and an orbit error phase according to the deformation phase containing the space interference component to obtain a deformation phase;
and S6, calculating the weight of the deformation phase and the time sequence deformation of the stable point target according to the deformation phase by utilizing the relation between the surface deformation and the radar imaging, thereby completing the monitoring of the deformation of the airport in the sea-filling area by using the time sequence InSAR technology.
2. The method for monitoring deformation of an airport in a sea reclamation area based on InSAR as claimed in claim 1, wherein the expression of the grid phase weight in the spatial filter grid in the step S205 is as follows:
where φ represents the grid phase weight, ADI, in the spatial filtering gridiRepresenting the amplitude dispersion, n representing the total number of candidate points,
denotes the initial weight, phiiThe phase value of the i-th candidate point is represented.
3. The InSAR-based sea-filling area airport deformation monitoring method according to claim 1, wherein the calculation formula of deformation phase containing spatial interference component in the step S4 is as follows:
wherein the content of the first and second substances,
representing the deformed phase containing the spatial interference component,
representing the remaining phase of the interference phase after removal of the terrain phase,
representing the sum of the atmospheric phase and the track error phase,
representing the noise phase.
4. The InSAR-based sea-filling area airport deformation monitoring method according to claim 1, wherein the step S5 specifically comprises:
according to the deformation phase containing the space interference component, the atmospheric phase and the orbit error phase are separated by adopting high-pass filtering on a time domain and low-pass filtering on a space domain, and the deformation phase is obtained.
5. The InSAR-based sea-filling area airport deformation monitoring method according to claim 1, wherein the weight calculation formula of deformation phase in the step S6 is as follows:
P＝diag(σ1，σ2，…σN)
wherein P represents the weight of the deformation phase, diag (·) represents the diagonal matrix function, σkRepresenting the interference phase standard deviation of the kth interference image pair, N representing the number of interference image pairs,
the noise phase of the x-th stable point target on the k-th interference image pair is shown, and M shows the number of stable point targets.
6. The InSAR-based sea-filling area airport deformation monitoring method according to claim 1, wherein the expression of the time series deformation v of the candidate point target in the step S6 is as follows:
v＝(T'PT)-1T'Pd
wherein, T' represents the transpose matrix of the time base line matrix of the candidate point target, P represents the weight matrix of the deformation phase, T represents the time base line matrix of the candidate point target, and d represents the deformation quantity of the candidate point target.
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| CN113866765B (en) * | 2021-09-24 | 2022-12-13 | 中国科学院精密测量科学与技术创新研究院 | PS-InSAR measurement method based on multi-component time coherent model |
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