CN115792905A - Quantitative evaluation method, system, equipment and medium for atmospheric delay phase correction precision - Google Patents
Quantitative evaluation method, system, equipment and medium for atmospheric delay phase correction precision Download PDFInfo
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Abstract
The invention belongs to the technical field of environmental monitoring, and discloses a quantitative evaluation method, a system, equipment and a medium for atmospheric delay phase correction accuracy. The method realizes quantitative evaluation of atmospheric delay phase correction, does not need the assumption that ground settlement or ground surface deformation in an evaluation area is zero, greatly ensures the accuracy of a quantitative evaluation result, and provides a basis for realizing optimal correction of the atmospheric delay phase.
Description
Technical Field
The invention belongs to the technical field of environmental monitoring, and relates to a quantitative evaluation method, a system, equipment and a medium for atmospheric delay phase correction precision.
Background
Surface subsidence, also known as ground subsidence or subsidence, is a localized downward movement (or engineering geology) that results in a reduction in the elevation of the crust surface due to consolidation and compression of the unconsolidated formation under the influence of natural or ergonomic activities. At present, the ground subsidence monitoring is usually performed by using the interferometric Synthetic Aperture Radar (InSAR) technology. When the InSAR technology is adopted to monitor ground subsidence, the changes of the water vapor content in the atmosphere during satellite revisit and the spatial changes of the water vapor content in the same radar image can cause the difference of radar signal propagation delay, so that larger additional phase changes, namely the atmospheric delay phase, are brought to the InSAR interference phase, and the atmospheric delay phase is a main error source in time sequence InSAR processing. Therefore, in order to realize high-precision sedimentation quantity inversion in the process of carrying out ground sedimentation monitoring based on the time series InSAR, how to accurately remove the atmospheric delay phase is one of the most critical problems.
At present, in time series InSAR processing, a plurality of correction methods for atmospheric delay phase have been proposed and can be divided into three categories. The first category is based on the assumption that the atmospheric delay phases are randomly distributed in the time dimension, and includes pair-wise analysis methods, stacking methods, and widely adopted spatio-temporal filtering methods. The second type is an empirical method based on the correlation between the atmospheric laminar flow and the terrain, which comprises a linear model method, an exponential mode method and a quadtree auxiliary combined model method; the third type is an atmospheric correction method based on external data, which comprises the steps of utilizing water vapor products of GPS station data, space radiometers MERIS, MODIS and the like and an atmospheric model product to estimate an atmospheric delay phase.
Based on the various atmospheric delay phase correction methods, when time series InSAR processing is specifically carried out, how to accurately evaluate the correction effect of the atmospheric delay phase correction method becomes an important basis for correctly selecting the atmospheric delay phase correction method. There are two methods for the quantitative evaluation of the atmospheric delay phase correction accuracy. The first is to calculate the spatial root mean square error or standard deviation of a single differential interferogram over different spatial scales or even over the global range, and the second is to calculate the root mean square error or standard deviation of all points along the time series over the global range of the interferogram. However, both of the above evaluation methods are based on the same assumption that there is no settlement point in the calculation region, and the differential phase values of all the points are theoretically zero. However, with the expansion and development of cities, various degrees and ranges of ground settlement are caused by human activities such as sea reclamation, subway tunnel construction, underground water exploitation and the like for years, most areas do not meet the assumptions, and the evaluation accuracy of the conventional evaluation method cannot be effectively guaranteed.
Disclosure of Invention
The present invention is directed to overcome the above-mentioned shortcomings of the prior art, and provides a method, system, device and medium for quantitatively evaluating the accuracy of atmospheric delay phase correction.
In order to achieve the purpose, the invention adopts the following technical scheme to realize the purpose:
in a first aspect of the present invention, a method for quantitatively evaluating accuracy of atmospheric delay phase correction is provided, which includes: acquiring a time series correction differential interference phase diagram subjected to atmospheric delay phase correction, and extracting time series differential phase values of all PS points in the time series correction differential interference phase diagram; calculating Spearman rank correlation coefficients of the time sequence differential phase value of each PS point and a time axis according to the time sequence differential phase value of each PS point; acquiring the annual average displacement of each PS point, acquiring settlement points in all the PS points according to the time sequence differential phase value of each PS point, the Spearman rank correlation coefficient of a time axis and the annual average displacement of each PS point, and removing the settlement points from all the PS points to obtain a plurality of target PS points; and obtaining a time series RMSE value of each target PS point according to the time series difference phase value of each target PS point, and obtaining a quantitative evaluation result of the atmospheric delay phase correction precision according to the time series RMSE value of each target PS point.
Optionally, the calculating, according to the time-series differential phase value of each PS point, a Spearman rank correlation coefficient between the time-series differential phase value of each PS point and a time axis includes: arranging the differential phase values in the time sequence differential phase values of each PS point according to the magnitude sequence, and replacing the differential phase values with the arrangement order of the differential phase values to obtain the rank phase sequence of each PS point; acquiring a time sequence of the time sequence correction differential interference phase diagram, arranging all the time in the time sequence according to the magnitude sequence, and replacing all the time with the arrangement position of all the time to obtain a rank time sequence; the Spearman rank correlation coefficient of the time-series differential phase value of each PS point with the time axis is calculated by:
wherein r is si Spearman rank correlation coefficient of time-series differential phase value of ith PS point and time axis, R (Xi) is rank phase sequence of ith PS point, R (Y) is rank time sequence, cov (R (Xi), R (Y)) is covariance of R (Xi) and R (Y), sigma R(Xi) Is the standard deviation, σ, of R (Xi) R(Y) Is the standard deviation of R (Y).
Optionally, the obtaining the annual average displacement amount of each PS point and obtaining the settlement point in all PS points according to the Spearman rank correlation coefficient of the time-series differential phase value and the time axis of each PS point and the annual average displacement amount of each PS point includes: and taking the PS points with the average annual displacement quantity larger than a preset average annual displacement quantity threshold value and the Spearman rank correlation coefficient of the time sequence differential phase value and the time axis smaller than a preset correlation coefficient threshold value as settlement points.
Optionally, the annual average displacement threshold value ranges from 4 mm to 6mm, and the correlation coefficient threshold value ranges from-1 to-0.9.
Optionally, the annual average displacement threshold is 5mm, and the correlation coefficient threshold is-0.9.
Optionally, the obtaining a time series RMSE value of each target PS point according to the time series differential phase value of each target PS point includes: obtaining a differential phase value of each target PS point in each correction differential interference phase diagram according to the time sequence differential phase value of each target PS point; the time series RMSE values for each target PS point were obtained by the following formula:
wherein Q is the time series RMSE value, ph, of the ith target PS point i,j The converted differential phase value in the jth corrected differential interference phase map for the ith target PS point, N is the total number of corrected differential interference phase maps,
the differential phase value of the ith target point PS in the jth corrected differential interference phase diagram is shown, and lambda is the radar wavelength of the corrected differential interference phase diagram.
Optionally, the obtaining a quantitative evaluation result of the atmospheric delay phase correction accuracy according to the time series RMSE value of each target PS point includes: and calculating the mean value or the median value of the time series RMSE values of all the target PS points as the quantitative evaluation result of the atmospheric delay phase correction precision.
In a second aspect of the present invention, there is provided an atmospheric delay phase correction accuracy quantitative evaluation system, including: the acquisition module is used for acquiring a time series correction differential interference phase diagram subjected to atmospheric delay phase correction and extracting a time series differential phase value of each PS point in the time series correction differential interference phase diagram; the correlation analysis module is used for calculating Spearman rank correlation coefficients of the time sequence differential phase values of the PS points and a time axis according to the time sequence differential phase values of the PS points; the settlement point removing module is used for obtaining the annual average displacement of each PS point, obtaining settlement points in all the PS points according to the time sequence differential phase value of each PS point, the Spearman rank correlation coefficient of a time axis and the annual average displacement of each PS point, and removing the settlement points from all the PS points to obtain a plurality of target PS points; and the evaluation module is used for obtaining the time sequence RMSE value of each target PS point according to the time sequence difference phase value of each target PS point and obtaining the quantitative evaluation result of the atmospheric delay phase correction precision according to the time sequence RMSE value of each target PS point.
In a third aspect of the present invention, a computer device is provided, which includes a memory, a processor and a computer program stored in the memory and executable on the processor, and the processor implements the steps of the above quantitative evaluation method for atmospheric delay phase correction accuracy when executing the computer program.
In a fourth aspect of the present invention, a computer-readable storage medium is provided, which stores a computer program, and the computer program, when executed by a processor, implements the steps of the above-described atmospheric delay phase correction accuracy quantitative evaluation method.
Compared with the prior art, the invention has the following beneficial effects:
the invention relates to a quantitative evaluation method for atmospheric delay phase correction accuracy, which comprises the steps of obtaining a time sequence differential phase value of each PS point in a time sequence correction differential interference phase diagram, then calculating a Spearman rank correlation coefficient of the time sequence differential phase value of each PS point and a time axis, carrying out settlement point masking based on the Spearman rank correlation coefficient and the annual average displacement of each PS point to obtain a plurality of target PS points, finally obtaining a time sequence RMSE value of each target PS point and obtaining a quantitative evaluation result for atmospheric delay phase correction accuracy based on the value. The quantitative evaluation method for the atmospheric delay phase correction precision realizes the quantitative evaluation result of the atmospheric delay phase correction precision, does not need the assumption that the ground subsidence or the ground surface deformation in the evaluation area is zero, can be widely applied to the area with the slow ground surface deformation, can not mistake the ground surface deformation as the residual error of the atmospheric correction due to the assumption of zero deformation, greatly ensures the accuracy of the quantitative evaluation result, and provides a basis for realizing the optimal correction of the atmospheric delay phase.
Drawings
FIG. 1 is a flowchart of a quantitative evaluation method for atmospheric delay phase calibration accuracy according to an embodiment of the present invention;
FIG. 2 is a flowchart of an atmospheric delay phase calibration method according to an embodiment of the present invention.
FIG. 3 is a diagram illustrating a result of quantitative evaluation of atmospheric delay phase correction accuracy according to an embodiment of the present invention.
Fig. 4 is a block diagram of a system for quantitatively evaluating the accuracy of atmospheric delay phase correction according to an embodiment of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Moreover, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
As introduced in the background, atmospheric delay phase is a major error source in time series InSAR processing, especially in cloudy and rainy areas throughout the year. Studies have shown that the delay caused by atmospheric moisture to one-way electromagnetic wave propagation varies from about 0 to 30 cm between polar and equatorial regions and from a few cm to 20 cm over the course of a year in mid-latitude regions, the effect of which has reached the order of magnitude of slow deformation such as ground subsidence. Therefore, in the process of monitoring ground settlement based on the time series InSAR, how to accurately remove the atmospheric delay phase is one of the most critical problems in order to realize high-precision inversion of the settlement amount.
Based on the above, the invention provides a quantitative evaluation method for atmospheric delay phase correction accuracy, which adopts a PS point time sequence differential phase value to perform time sequence rank correlation analysis and combines a annual deformation quantity to perform a settlement point mask, thereby calculating a time sequence root mean square error statistical index of the phase value as a quantitative evaluation index, so as to realize quantitative evaluation of atmospheric delay phase correction performance and realize preferred selection of different atmospheric delay phase correction methods.
The invention is described in further detail below with reference to the accompanying drawings:
referring to fig. 1, in an embodiment of the present invention, a method for quantitatively evaluating accuracy of atmospheric delay phase correction is provided, which specifically includes the following steps:
s1: acquiring a time series correction differential interference phase diagram subjected to atmospheric delay phase correction, and extracting time series differential phase values of all PS points in the time series correction differential interference phase diagram.
S2: and calculating the Spearman rank correlation coefficient of the time sequence differential phase value of each PS point and the time axis according to the time sequence differential phase value of each PS point.
S3: and acquiring the annual average displacement of each PS point, acquiring settlement points in all the PS points according to the time sequence differential phase value of each PS point, the Spearman rank correlation coefficient of a time axis and the annual average displacement of each PS point, and removing the settlement points from all the PS points to acquire a plurality of target PS points.
S4: and obtaining a time series RMSE value of each target PS point according to the time series difference phase value of each target PS point, and obtaining a quantitative evaluation result of the atmospheric delay phase correction precision according to the time series RMSE value of each target PS point.
Among them, PS (Persistent scatterer) is a variety of surface feature targets that are strong in backscattering of radar waves and are stable in time series. The PS points are pixel points of the ground object targets in the radar map. The Spearman rank correlation coefficient is a non-parametric measure of the statistical correlation between the levels of two variables and aims to evaluate the monotonic relationship between the two variables, even if the relationship is non-linear. Furthermore, the Spearman rank correlation coefficient is more robust to outliers than the Pearson correlation coefficient conventionally used. The RMSE value is a root mean square error value.
Specifically, the time-series corrected differential interferometric phase map after atmospheric delay phase correction is obtained by preprocessing a time-series synthetic aperture radar image by a PS inssar algorithm and then respectively processing the preprocessed image by various preset atmospheric delay phase correction methods.
The method comprises the steps that a conventional processing mode which is currently produced can be adopted for preprocessing the PS InSAR algorithm, time base line and space base line analysis is carried out on the synthetic aperture radar image of the whole time sequence, a first-stage image which is the shortest with the space base line and the time base line of other images is selected as a main image, and then the other images and the main image are accurately registered by utilizing an orbit parameter base reference digital elevation model and the like; according to the pairing rule of the PS-InSAR algorithm, except the main image, other images in the sequence and the main image form an interference pair to obtain a differential interference phase diagram, and a reference digital elevation model assists in removing a terrain phase and a flat ground phase, so that a time sequence differential interference phase diagram for carrying out atmospheric delay phase correction is obtained on the basis. And then, taking the time series differential interference phase diagram as an object to be processed, and processing by respectively adopting various preset atmospheric delay phase correction methods to further obtain the time series correction differential interference phase diagram corrected by different atmospheric delay phase correction methods.
Referring to fig. 2, when the atmospheric delay phase correction method is used for processing, the atmospheric delay phase correction method may be used alone by using a space-time filtering method, or may be used in combination with the atmospheric delay phase correction method of the atmospheric model product.
Specifically, the specific process of performing the atmospheric delay phase correction by separately using the space-time filtering method includes: taking a time sequence differential interference phase diagram after phase unwrapping as input, firstly carrying out primary correction on atmospheric delay phase, then forming a Delaunay network based on a spatial relationship, carrying out phase difference on adjacent PS points, and then carrying out time-dimensional low-pass filtering and least square inversion on a main image to obtain atmospheric delay phase and orbit error estimation of the main image; and performing time-dimensional high-pass filtering and spatial low-pass filtering on the secondary image to obtain atmospheric delay phase and orbit error estimation of the secondary image and a space related part of the reference digital elevation model error. And finally, obtaining the time series correction differential interference phase diagram corrected by the atmospheric delay phase based on the atmospheric delay phase and orbit error estimation of the main image, the atmospheric delay phase and orbit error estimation of the secondary image and the space correlation part of the reference digital elevation model error.
When the atmospheric delay phase correction is carried out by combining a space-time filtering method and an atmospheric delay phase correction method of an atmospheric model product, a time sequence differential interference phase diagram after phase unwrapping and an estimated atmospheric delay phase of the atmospheric model product are jointly used as input on the basis of independently adopting the space-time filtering method.
It should be noted that, the specific processing details of the processing flow adopting the atmospheric delay phase correction method can refer to the conventional atmospheric delay phase correction processing flow, and the details are not described herein.
It should be noted that, the quantitative evaluation method for atmospheric retardation phase correction accuracy of the present invention is used to quantitatively evaluate the correction accuracy of the atmospheric retardation phase correction method, so that in practical applications, when comparing the quantitative evaluation results of atmospheric retardation phase correction accuracy of the atmospheric retardation phase correction methods for different atmospheric retardation phase correction methods, the other processes are kept the same except for the difference of the atmospheric retardation phase correction methods.
In summary, according to the atmospheric delay phase correction accuracy quantitative evaluation method, the time sequence differential phase value of each PS point in the time sequence correction differential interference phase map is obtained, then the Spearman rank correlation coefficient between the time sequence differential phase value of each PS point and the time axis is calculated, the settlement point masking is performed based on the Spearman rank correlation coefficient and the annual average displacement of each PS point to obtain a plurality of target PS points, and finally the time sequence RMSE value of each target PS point is obtained and the quantitative evaluation result of the atmospheric delay phase correction accuracy is obtained based on the value. The quantitative evaluation method for the atmospheric delay phase correction precision realizes the quantitative evaluation result of the atmospheric delay phase correction precision, does not need the assumption that the ground subsidence or the ground surface deformation in the evaluation area is zero, can be widely applied to the area with the slow ground surface deformation, can not mistake the ground surface deformation as the residual error of the atmospheric correction due to the assumption of zero deformation, greatly ensures the accuracy of the quantitative evaluation result, and provides a basis for realizing the optimal correction of the atmospheric delay phase.
In a possible implementation manner, the calculating the Spearman rank correlation coefficient of the time-series differential phase value of each PS point and the time axis according to the time-series differential phase value of each PS point includes: arranging the differential phase values in the time sequence differential phase values of each PS point according to the magnitude sequence, and replacing the differential phase values with the arrangement order of the differential phase values to obtain the rank sequence of each PS point; acquiring a time sequence of the time sequence correction differential interference phase diagram, arranging all the time in the time sequence according to a magnitude sequence, and replacing all the time with the arrangement order of all the time to obtain a rank time sequence; the Spearman rank correlation coefficient of the time-series differential phase value of each PS point with the time axis is calculated by:
wherein r is si Spearman rank correlation coefficient of time-series differential phase value of ith PS point and time axis, R (Xi) is rank sequence of ith PS point, R (Y) is rank time sequence, cov (R (Xi), R (Y)) is covariance of R (Xi) and R (Y), sigma R(Xi) Is the standard deviation, σ, of R (Xi) R(Y) Is the standard deviation of R (Y).
In a possible embodiment, the obtaining the annual average displacement amount of each PS point, and obtaining the sinking point of all PS points according to the Spearman rank correlation coefficient of the time-series differential phase value of each PS point and the time axis and the annual average displacement amount of each PS point includes: and taking the PS points with the average annual displacement quantity larger than a preset average annual displacement quantity threshold value and the Spearman rank correlation coefficient of the time sequence differential phase value and the time axis smaller than a preset correlation coefficient threshold value as settlement points.
Specifically, whether each PS point has a tendency of sedimentation or not is judged based on the time sequence differential phase value of each PS point, the Spearman rank correlation coefficient of a time axis and the annual average displacement of each PS point, and accurate elimination of the sedimentation point is realized, so that the influence of the sedimentation point on evaluation of atmospheric delay phase correction is avoided.
Optionally, the annual average displacement threshold value ranges from 4 mm to 6mm, and the correlation coefficient threshold value ranges from-1 to-0.9. Specifically, the selection of the annual average displacement threshold and the correlation coefficient threshold may be set based on an actual application area, and is an adaptive value. In the embodiment, based on historical data and empirical summary, a preferred value is provided, that is, the annual average displacement threshold is 5mm, and the correlation coefficient threshold is-0.9.
In a possible implementation manner, the obtaining the time-series RMSE value of each target PS point according to the time-series differential phase value of each target PS point includes: obtaining a differential phase value of each target PS point in each correction differential interference phase diagram according to the time sequence differential phase value of each target PS point; the time series RMSE values for each target PS point were obtained by the following formula:
wherein Q is the time series RMSE value of the ith target PS point, ph i,j The converted differential phase values in the jth corrected differential interference phase map for the ith target point PS, N is the total number of corrected differential interference phase maps,
and λ is the radar wavelength of the corrected differential interference phase map for the differential phase value of the ith target point PS in the jth corrected differential interference phase map.
Specifically, the time-series RMSE value of each target PS point can be understood as a global RMSE value of each target PS point in all ranges of the differential interference phase map, so as to reflect the accuracy of the atmospheric delay phase correction.
Optionally, the obtaining a quantitative evaluation result of the atmospheric delay phase correction accuracy according to the time series RMSE value of each target PS point includes: and calculating the mean value or the median value of the time series RMSE values of all the target PS points as the quantitative evaluation result of the atmospheric delay phase correction precision.
Specifically, the quantitative evaluation result of the atmospheric delay phase correction precision is obtained by calculating the mean value or the median value of the time series RMSE values of all the target PS points, so that the time series RMSE values of a single target PS point with a large or wrong error are prevented from causing large influence on the quantitative evaluation result, and the stability of the quantitative evaluation result is ensured.
In one possible implementation mode, a certain area is taken as a case study area, and the quantitative evaluation method for the atmospheric delay phase correction accuracy is verified.
In the embodiment, sentinel-1TOPS mode single-view complex data is adopted, the 68 th-stage images from 2015 to 2018 and 3 rd are included, the acquisition date interval is mostly 12 days, and data parameters are shown in table 1.
TABLE 1 data parameter Table
Data acquired in 2017, 3, 12 and are used as main images, other data in a time sequence are used as auxiliary images, the time base line range is 12-600 days, the space base line is not more than 121.1 meters, and the reference digital elevation model adopts AW3D DEM 30-meter resolution data.
In the present embodiment, GACOS (Generic Atmospheric Correction Online Service), ERA-I (ERA-inter, a global atmosphere re-analysis data), ERA5 (a comprehensive global atmosphere re-analysis data), filter (space-time filtering), GACOS & Filter (GACOS Atmospheric product combined with space-time filtering), ERA-I & Filter (ERA-I Atmospheric re-analysis data combined with space-time filtering), and ERA5& Filter (ERA 5 Atmospheric re-analysis data combined with space-time filtering) are respectively used to perform Atmospheric delay phase Correction on the time series differential interference diagram, and then the Correction of various Atmospheric delay phase Correction methods is quantitatively evaluated by using the quantitative evaluation method for Atmospheric delay phase Correction accuracy of the present invention, see fig. 3, which shows 10% to 90% quantiles of the time series RMSE values of the target PS points, and thus, the Atmospheric noise of the original time series differential interference diagram is the maximum, the Atmospheric noise of the time series differential interference diagram is quantitatively evaluated by using a space-time Correction Online calibration Online network model, and the residual noise is corrected within 10mm of the ERA5 and the highest residual noise is corrected by using the Filter model.
The following are embodiments of the apparatus of the present invention that may be used to perform embodiments of the method of the present invention. For details not disclosed in the device embodiments, reference is made to the method embodiments of the invention.
Referring to fig. 4, in a further embodiment of the present invention, an atmospheric delay phase correction accuracy quantitative evaluation system is provided, which can be used for implementing the above atmospheric delay phase correction accuracy quantitative evaluation method.
The acquisition module is used for acquiring a time series correction differential interference phase diagram subjected to atmospheric delay phase correction and extracting a time series differential phase value of each PS point in the time series correction differential interference phase diagram; the correlation analysis module is used for calculating Spearman rank correlation coefficients of the time sequence differential phase values of the PS points and a time axis according to the time sequence differential phase values of the PS points; the settlement point removing module is used for obtaining the annual average displacement of each PS point, obtaining settlement points in all the PS points according to the time sequence differential phase value of each PS point, the Spearman rank correlation coefficient of a time axis and the annual average displacement of each PS point, and removing the settlement points from all the PS points to obtain a plurality of target PS points; the evaluation module is used for obtaining the time sequence RMSE value of each target PS point according to the time sequence difference phase value of each target PS point, and obtaining the quantitative evaluation result of the atmospheric delay phase correction precision according to the time sequence RMSE value of each target PS point.
In a possible embodiment, the calculating, according to the time-series differential phase value of each PS point, a Spearman rank correlation coefficient of the time-series differential phase value of each PS point with respect to a time axis includes: arranging the differential phase values in the time sequence differential phase values of each PS point according to the magnitude sequence, and replacing the differential phase values with the arrangement order of the differential phase values to obtain the rank sequence of each PS point; acquiring a time sequence of the time sequence correction differential interference phase diagram, arranging all the time in the time sequence according to the magnitude sequence, and replacing all the time with the arrangement position of all the time to obtain a rank time sequence; the Spearman rank correlation coefficient of the time-series differential phase value of each PS point with the time axis is calculated by:
wherein r is si Spearman rank correlation coefficient of time-series differential phase value of ith PS point and time axis, R (Xi) is rank sequence of ith PS point, R (Y) is rank time sequence, cov (R (Xi), R (Y)) is covariance of R (Xi) and R (Y), sigma R(Xi) Is the standard deviation, σ, of R (Xi) R(Y) Is the standard deviation of R (Y).
In a possible embodiment, the obtaining the annual average displacement amount of each PS point, and obtaining the sinking point in all PS points according to the Spearman rank correlation coefficient of the time-series differential phase value of each PS point and the time axis and the annual average displacement amount of each PS point includes: and taking the PS points with the average annual displacement quantity larger than a preset average annual displacement quantity threshold value and the Spearman rank correlation coefficient of the time sequence differential phase value and the time axis smaller than a preset correlation coefficient threshold value as settlement points.
In a possible embodiment, the annual average displacement threshold value ranges from 4 mm to 6mm, and the correlation coefficient threshold value ranges from-1 to-0.9.
Preferably, the annual average displacement threshold is 5mm, and the correlation coefficient threshold is-0.9.
In a possible implementation manner, the obtaining the time-series RMSE value of each target PS point according to the time-series differential phase value of each target PS point includes: obtaining a differential phase value of each target PS point in each correction differential interference phase diagram according to the time sequence differential phase value of each target PS point; the time series RMSE values for each target PS point were obtained by the following formula:
wherein Q is the time series RMSE value of the ith target PS point, ph i,j The converted differential phase values in the jth corrected differential interference phase map for the ith target point PS, N is the total number of corrected differential interference phase maps,
and λ is the radar wavelength of the corrected differential interference phase map for the differential phase value of the ith target point PS in the jth corrected differential interference phase map.
In one possible implementation, the obtaining a result of quantitative evaluation of the accuracy of the atmospheric delay phase correction according to the time-series RMSE values of each target PS point includes: and calculating the mean value or the median value of the time series RMSE values of all the target PS points as the quantitative evaluation result of the atmospheric delay phase correction precision.
All relevant contents of each step involved in the foregoing embodiments of the method for quantitatively evaluating atmospheric delay phase correction accuracy may be introduced to the functional description of the functional module corresponding to the system for quantitatively evaluating atmospheric delay phase correction accuracy in the embodiments of the present invention, and are not described herein again. The division of the modules in the embodiments of the present invention is schematic, and is only a logical function division, and in actual implementation, there may be another division manner, and in addition, each functional module in each embodiment of the present invention may be integrated in one processor, or may exist alone physically, or two or more modules are integrated in one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode.
In yet another embodiment of the present invention, a computer device is provided that includes a processor and a memory for storing a computer program comprising program instructions, the processor for executing the program instructions stored by the computer storage medium. The Processor may be a Central Processing Unit (CPU), or may be other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable gate array (FPGA) or other Programmable logic device, discrete gate or transistor logic device, discrete hardware component, etc., which is a computing core and a control core of the terminal, and is specifically adapted to load and execute one or more instructions in a computer storage medium to implement a corresponding method flow or a corresponding function; the processor provided by the embodiment of the invention can be used for the operation of the quantitative evaluation method of the atmospheric delay phase correction precision.
In yet another embodiment of the present invention, the present invention further provides a storage medium, specifically a computer-readable storage medium (Memory), which is a Memory device in a computer device and is used for storing programs and data. It is understood that the computer readable storage medium herein can include both built-in storage medium in the computer device and, of course, extended storage medium supported by the computer device. The computer-readable storage medium provides a storage space storing an operating system of the terminal. Also, the memory space stores one or more instructions, which may be one or more computer programs (including program code), adapted to be loaded and executed by the processor. It should be noted that the computer readable storage medium may be a high-speed RAM memory, or a non-volatile memory (non-volatile memory), such as at least one disk memory. One or more instructions stored in a computer-readable storage medium may be loaded and executed by a processor to implement the corresponding steps of the quantitative evaluation method for atmospheric delay phase correction accuracy in the above embodiments.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting the same, and although the present invention is described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications and equivalents may be made to the embodiments of the invention without departing from the spirit and scope of the invention, which is to be covered by the claims.
Claims (10)
1. A quantitative evaluation method for atmospheric delay phase correction accuracy is characterized by comprising the following steps:
acquiring a time series correction differential interference phase diagram subjected to atmospheric delay phase correction, and extracting time series differential phase values of all PS points in the time series correction differential interference phase diagram;
calculating Spearman rank correlation coefficients of the time sequence differential phase values of the PS points and a time axis according to the time sequence differential phase values of the PS points;
acquiring the annual average displacement of each PS point, acquiring settlement points in all the PS points according to the time sequence differential phase value of each PS point, the Spearman rank correlation coefficient of a time axis and the annual average displacement of each PS point, and removing the settlement points from all the PS points to acquire a plurality of target PS points;
and obtaining a time series RMSE value of each target PS point according to the time series difference phase value of each target PS point, and obtaining a quantitative evaluation result of the atmospheric delay phase correction precision according to the time series RMSE value of each target PS point.
2. The method for quantitatively evaluating the accuracy of atmospheric delay phase correction according to claim 1, wherein the calculating the Spearman rank correlation coefficient of the time-series differential phase value of each PS point with respect to the time axis according to the time-series differential phase value of each PS point comprises:
arranging the differential phase values in the time sequence differential phase values of the PS points according to the magnitude sequence, and replacing the differential phase values with the arrangement order of the differential phase values to obtain the rank phase sequence of the PS points;
acquiring a time sequence of the time sequence correction differential interference phase diagram, arranging all the time in the time sequence according to a magnitude sequence, and replacing all the time with the arrangement order of all the time to obtain a rank time sequence;
the Spearman rank correlation coefficient of the time-series differential phase value of each PS point with the time axis is calculated by:
wherein r is si Spearman rank correlation coefficient of time-series differential phase values of the i-th PS point with time axis, R (Xi) is rank phase sequence of the i-th PS point, R (Y) is rank time sequence, cov (R (Xi), R (Y)) is covariance of R (Xi) and R (Y), sigma R(Xi) Is the standard deviation, σ, of R (Xi) R(Y) Is the standard deviation of R (Y).
3. The method according to claim 1, wherein the obtaining of the annual average displacement of each PS point and the obtaining of the sink point of all PS points according to the Spearman rank correlation coefficient of the time-series differential phase value of each PS point with the time axis and the annual average displacement of each PS point comprises:
and taking the PS points with the average annual displacement quantity larger than a preset average annual displacement quantity threshold value and the Spearman rank correlation coefficient of the time sequence differential phase value and the time axis smaller than a preset correlation coefficient threshold value as settlement points.
4. The quantitative evaluation method for the atmospheric delay phase correction accuracy according to claim 1, wherein the annual average displacement threshold value ranges from 4 mm to 6mm, and the correlation coefficient threshold value ranges from-1 to-0.9.
5. The quantitative evaluation method for the accuracy of atmospheric delay phase correction according to claim 4, wherein the annual average displacement threshold value is 5mm, and the correlation coefficient threshold value is-0.9.
6. The method for quantitatively evaluating the accuracy of atmospheric delay phase correction according to claim 1, wherein the obtaining the time-series RMSE values of each target PS point from the time-series differential phase values of each target PS point comprises:
obtaining a differential phase value of each target PS point in each correction differential interference phase diagram according to the time sequence differential phase value of each target PS point;
the time series RMSE values for each target PS point were obtained by the following formula:
wherein Q is the time series RMSE value of the ith target PS point, ph i,j The converted differential phase values in the jth corrected differential interference phase map for the ith target point PS, N is the total number of corrected differential interference phase maps,
in the jth corrected differential interference phase map for the ith target PS pointλ is the radar wavelength of the corrected differential interference phase pattern.
7. The quantitative evaluation method for the atmospheric delay phase correction accuracy according to claim 1, wherein the obtaining of the quantitative evaluation result for the atmospheric delay phase correction accuracy according to the time series RMSE values of each target PS point comprises:
and calculating the mean value or the median value of the time series RMSE values of all the target PS points as the quantitative evaluation result of the atmospheric delay phase correction precision.
8. An atmospheric delay phase correction accuracy quantitative evaluation system, comprising:
the acquisition module is used for acquiring a time series correction differential interference phase diagram subjected to atmospheric delay phase correction and extracting a time series differential phase value of each PS point in the time series correction differential interference phase diagram;
the correlation analysis module is used for calculating Spearman rank correlation coefficients of the time sequence differential phase value of each PS point and a time axis according to the time sequence differential phase value of each PS point;
the settlement point removing module is used for obtaining the annual average displacement of each PS point, obtaining settlement points in all the PS points according to the time sequence differential phase value of each PS point, the Spearman rank correlation coefficient of a time axis and the annual average displacement of each PS point, and removing the settlement points from all the PS points to obtain a plurality of target PS points;
and the evaluation module is used for obtaining the time sequence RMSE value of each target PS point according to the time sequence difference phase value of each target PS point and obtaining the quantitative evaluation result of the atmospheric delay phase correction precision according to the time sequence RMSE value of each target PS point.
9. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor when executing the computer program implements the steps of the quantitative evaluation method of atmospheric delay phase correction accuracy of any one of claims 1to 7.
10. A computer-readable storage medium storing a computer program, wherein the computer program is executed by a processor to implement the steps of the quantitative estimation method for atmospheric delay phase correction accuracy according to any one of claims 1to 7.
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| CN202211543076.XA CN115792905A (en) | 2022-12-02 | 2022-12-02 | Quantitative evaluation method, system, equipment and medium for atmospheric delay phase correction precision |
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| CN109782282B (en) * | 2019-03-13 | 2023-04-18 | 武汉大学 | Time series InSAR analysis method integrating troposphere atmospheric delay correction |
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