CN116659429A - A method and system for calculating three-dimensional surface deformation with high precision and time series of multi-source data - Google Patents

Abstract

A method and system for calculating three-dimensional surface deformation with high precision and time series of multi-source data, comprising the following steps: step S100, preprocessing GNSS data; step S200, preprocessing InSAR data; step S300, establishing a regional three-dimensional deformation monitoring Motion equations and observation equations; step S400, filter fusion solution. When the present invention calculates the three-dimensional deformation of the ground surface based on multi-source deformation monitoring data, the state quantity at the previous moment and the observation quantity at the current time can be used to obtain the three-dimensional deformation field of the ground surface at the current data acquisition time, realizing dynamic three-dimensional deformation monitoring; When there is only a single InSAR line-of-sight observation data, the three-dimensional deformation information of the surface at that moment can also be obtained.

Description

A method and system for calculating three-dimensional surface deformation with high precision and time series of multi-source data

technical field

The invention relates to the technical field of three-dimensional dynamic monitoring and tracking of surface deformation, in particular to a multi-source data high-precision time-series three-dimensional deformation calculation method and system.

Background technique

With the development and progress of space geodetic technology, GNSS (Global Navigation Satellite System, GNSS) and synthetic aperture radar interferometry (InterferometricSynthetic Aperture Radar, InSAR), as two new earth observation The application of early warning and prevention is becoming more and more prominent.

In the existing technology, GNSS, InSAR multi-source data fusion research on 3D surface deformation mainly focuses on two points, the first is the reconstruction of the 3D deformation field after the disaster, and the second is the calculation of the 3D deformation rate field. The former is to directly fuse the InSAR and GNSS deformation observations obtained by multiple technologies to obtain the instantaneous three-dimensional deformation field; the latter is to obtain the three-dimensional deformation rate field after averaging the velocity of various deformation observations. In any of the above cases, when there is only a single InSAR line-of-sight data, the three-dimensional deformation information cannot be obtained, which greatly sacrifices the time resolution of the InSAR data; moreover, the relationship before and after the surface deformation cannot be obtained, and the dynamic process of the surface deformation cannot be reflected.

Contents of the invention

In order to overcome the problems existing in the prior art, the object of the present invention is to provide a method and system for calculating multi-source data high-precision time-series three-dimensional surface deformation, specifically, a GNSS-InSAR high-precision time-series three-dimensional surface deformation based on Kalman filtering. Deformation solution method.

The present invention can only obtain the instantaneous deformation at a certain moment or the average three-dimensional deformation in a certain period of time for the general multi-source data fusion model to solve the three-dimensional deformation of the surface, but cannot reflect the dynamic process of the surface deformation, sacrificing the time resolution of the observation value To solve this problem, a high-precision time-series three-dimensional surface deformation calculation method based on Kalman filter GNSS-InSAR is proposed. This method builds observation equations and motion equations for regional three-dimensional deformation monitoring, and time-series fusion of two different sensors, GPS and InSAR, at different times , Observation data obtained under different earth observation angles to obtain the three-dimensional surface deformation variable at each deformation information acquisition time.

The present invention is realized by following technical scheme:

The first aspect of the present invention relates to a multi-source data high-precision time-series surface three-dimensional deformation calculation method, including the following steps:

Step S100, preprocessing the GNSS data;

Step S200, preprocessing the InSAR data;

Step S300, establishing motion equations and observation equations for regional three-dimensional deformation monitoring;

Step S400, filter fusion solution.

Further, in step S100, the GNSS monitoring value is processed to obtain the GNSS point deformation monitoring result, and the deformation monitoring result is interpolated to obtain GNSS data meeting the spatial resolution.

Further, in step S200, the spatial correlation error processing is removed from the InSAR data to obtain the line-of-sight deformation time series, and the deformation monitoring result is down-sampled to make it consistent with the spatial resolution of the GNSS interpolation result.

Further, in step S300, the motion equation of the discrete Kalman filter is established based on the deformation and displacement values to be obtained, the instantaneous velocity, and the instantaneous acceleration rate of the monitoring point; the observation equation is established according to the relationship between the InSAR line-of-sight deformation and its projection in the three-dimensional direction of the ground surface .

Further, step S400 includes:

Step S410, determining the initial filtering value;

In step S420, according to the state equation and the observation equation, filter recursive estimation is performed under the criterion of minimum mean square error estimation.

Further, step S420 includes:

Step S421, one-step prediction of the deformation state value at the current moment: using the state quantity at the previous moment, with the help of the state transition matrix, one-step prediction of the state is obtained;

Step S422, one-step prediction of the variance of the deformation state value at the current moment: use the covariance of the state vector at the previous moment and the noise vector of the dynamic model to find the variance matrix of the one-step prediction error;

Step S423, find the filter gain matrix: use the observation vector and the observation matrix to find the filter gain matrix;

Step S424, obtaining the filter update state vector and the corresponding covariance matrix.

Using the InSAR or GNSS observations obtained at different times to perform filter calculations, obtain the three-dimensional deformation state vector estimation at each data acquisition time, and dynamically monitor the three-dimensional deformation of the monitoring area.

The present invention also relates to a multi-source data high-precision time-series surface three-dimensional deformation calculation system, including:

GNSS data preprocessing module, for preprocessing GNSS data;

InSAR data preprocessing module, used for preprocessing InSAR data;

Equation establishment module, which is used to establish motion equation and observation equation for regional three-dimensional deformation monitoring;

The filter fusion solution module is used for filter fusion solution.

The present invention also relates to an electronic device comprising:

at least one processor; and,

a memory communicatively coupled to the at least one processor; wherein,

The memory stores instructions executable by the at least one processor, the instructions are executed by the at least one processor to enable the at least one processor to perform the method.

The present invention also relates to a non-transitory computer-readable storage medium storing computer instructions for causing the computer to execute the method.

The technical solution of the present invention can realize the following beneficial technical effects:

The Kalman filter-based GNSS-InSAR high-precision time-series three-dimensional surface deformation calculation algorithm of the present invention can solve the three-dimensional deformation information at any data acquisition time, realize real-time dynamic estimation of the three-dimensional surface deformation in the monitoring area, and obtain high-precision time-series three-dimensional The deformation field and three-dimensional deformation rate field improve the temporal and spatial resolution of surface three-dimensional deformation monitoring.

Description of drawings

Fig. 1 is a schematic flow chart of the multi-source data high-precision time-series surface three-dimensional deformation solution method of the present invention;

Fig. 2 is a flow chart of the multi-source data high-precision time-series surface three-dimensional deformation calculation method of the present invention.

Detailed ways

In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in combination with specific embodiments and with reference to the accompanying drawings. It should be understood that these descriptions are exemplary only, and are not intended to limit the scope of the present invention. Also, in the following description, descriptions of well-known structures and techniques are omitted to avoid unnecessarily obscuring the concept of the present invention.

The present invention will be described in detail below in conjunction with the accompanying drawings and embodiments.

The first aspect of the present invention provides a multi-source data high-precision time-series surface three-dimensional deformation calculation method, which is a method that supports dynamic calculation of three-dimensional surface deformation. By establishing a multi-source data fusion calculation model based on Kalman filtering, By constructing the motion equation and observation equation for regional three-dimensional deformation monitoring, the InSAR and GNSS observation data obtained at different times are sequentially fused to obtain the three-dimensional deformation filtering solution of the monitoring point at any observation data acquisition time, and the time resolution of the monitoring results is improved.

Specifically, the following steps are included:

Step S100, GNSS data preprocessing.

The GNSS data is collected through continuous GNSS monitoring points. After processing the GNSS monitoring values for baseline calculation and network adjustment processing, the deformation monitoring results of GNSS points are obtained, and Kriging interpolation is performed on the deformation monitoring results to obtain spatially resolved Rate GNSS data.

Step S200, InSAR data preprocessing.

InSAR data is processed through master-slave image registration, time series coherence factor calculation, high coherence point selection, phase unwrapping method for unwrapping, band-pass filtering to remove atmospheric and orbital space-related errors, etc. to obtain line-of-sight deformation time series. The deformation monitoring results are down-sampled to make them consistent with the spatial resolution of GNSS interpolation results.

Step S300, establishing motion equations and observation equations for regional three-dimensional deformation monitoring.

Set the value of the deformation and displacement of the monitoring point to be obtained , whose instantaneous rate is /> , the instantaneous acceleration /> As a random disturbance, the motion equation of the discrete Kalman filter can be expressed as:

(1)

(2)

In the above formula, and /> yes /> and /> The displacement of the monitoring point at all times, /> and /> yes /> and /> The instantaneous rate of the monitoring point at all times, /> , /> yes /> The acceleration rate at any moment can be expressed in matrix form as:

(3)

in, is the state vector to be requested, /> is the state transition matrix, /> is the system dynamic noise vector.

Specifically, according to the InSAR line-of-sight deformation Establish the observation equation in relation to its projection on the three-dimensional direction of the earth's surface:

(4)

In the formula, The projection vectors of line-of-sight deformation obtained from InSAR data of different orbits in the east-west, north-south and vertical directions of the surface. When the monitoring point has GNSS observation data, the observation equation can be established:

(5)

In the formula, It is the ground deformation observation value obtained by GNSS or the surface deformation observation value obtained by the interpolation of discrete GNSS observation points. The above observation equations of various observation quantities can be expressed in the following form:

(6)

In the formula, Indicates the observation values obtained by various monitoring techniques at time k, /> is the state vector to be sought at time k, /> Design a matrix for the observation equations of various observations at time k, /> is the observation noise vector of the monitoring point at time k, and its variance matrix /> .

Step S400, filter fusion solution.

Step S410, determining the initial filtering value;

Pick The three-dimensional surface deformation and variance of the moment are zero, using /> InSAR deformation observation value and GNSS deformation observation value least squares solution at any time to obtain the initial three-dimensional displacement value/> and the corresponding variance matrix /> , the initial three-dimensional deformation rate is taken as /> average deformation rate/> , and the corresponding variance matrix is /> . Observation noise variance matrix /> , the variance of the InSAR observations is determined by the conventional moving window estimation method, and the variance of the GNSS observations is determined by the ordinary Kriging interpolation variance calculation.

Step S420, according to the state equation and the observation equation, perform filter recursive estimation under the criterion of minimum mean square error estimation;

Step S421, one-step prediction of the deformation state value at this moment: using the state quantity at the previous moment , with the state transition matrix /> , get state one-step prediction/> ;

(66)

Step S422, predicting the variance of the deformation state value at this moment in one step: using the covariance of the state vector at the previous moment and the dynamic model noise vector /> , find one-step forecast error variance matrix /> ;

(77)

Step S423, find the filter gain matrix: use the observation vector and the observation matrix /> Find the filter gain matrix ;

(88)

Step S424, filter and update the state vector and the corresponding covariance matrix /> ;

(99)

(100)

After the initial value of the above filtering is determined, according to the initial state estimation and the corresponding covariance matrix, according to the formula (66) to formula (100), the InSAR or GNSS observations obtained at different times can be used for filtering calculation, and the obtained The three-dimensional deformation state vector estimation at each data acquisition moment realizes the three-dimensional deformation dynamic monitoring of the monitoring area.

The present invention starts from the function model and the random model in the three-dimensional deformation calculation model of the earth's surface, and establishes a dynamic three-dimensional deformation calculation model of the earth's surface based on Kalman Filtering (Kalman Filtering). The monitoring observation model and motion model, through the time-series fusion of GNSS and InSAR deformation monitoring data obtained by multiple technologies, realize real-time dynamic estimation of the three-dimensional deformation of the surface in the monitoring area, obtain high-precision time-series three-dimensional deformation field, and improve the reliability of the three-dimensional surface deformation monitoring results. Time resolution.

The present invention also relates to a multi-source data high-precision time-series surface three-dimensional deformation calculation system, including:

GNSS data preprocessing module, for preprocessing GNSS data;

InSAR data preprocessing module, used for preprocessing InSAR data;

Equation establishment module, which is used to establish motion equation and observation equation for regional three-dimensional deformation monitoring;

The filter fusion solution module is used for filter fusion solution.

The present invention also relates to an electronic device comprising:

at least one processor; and,

a memory communicatively coupled to the at least one processor; wherein,

The memory stores instructions executable by the at least one processor, the instructions are executed by the at least one processor to enable the at least one processor to perform the method.

The present invention also relates to a non-transitory computer-readable storage medium storing computer instructions for causing the computer to execute the method.

In summary, the present invention provides a multi-source data high-precision time-series surface three-dimensional deformation calculation method, including the following steps: step S100, preprocessing the GNSS data; step S200, preprocessing the InSAR data; step S300 , establishing a motion equation and an observation equation for regional three-dimensional deformation monitoring; step S400, filter fusion solution. When the present invention calculates the three-dimensional deformation of the ground surface based on multi-source deformation monitoring data, the state quantity at the previous moment and the observation quantity at the current time can be used to obtain the three-dimensional deformation field of the ground surface at the current data acquisition time, realizing dynamic three-dimensional deformation monitoring; When there is only a single InSAR line-of-sight observation data, the three-dimensional deformation information of the surface at that moment can also be obtained.

It should be understood that the above specific embodiments of the present invention are only used to illustrate or explain the principle of the present invention, and not to limit the present invention. Therefore, any modification, equivalent replacement, improvement, etc. made without departing from the spirit and scope of the present invention shall fall within the protection scope of the present invention. Furthermore, it is intended that the appended claims of the present invention embrace all changes and modifications that come within the scope and metesques of the appended claims, or equivalents of such scope and metes and bounds.

Claims (6)

1. A multi-source data high-precision time sequence earth surface three-dimensional deformation resolving method is characterized by comprising the following steps:

step S100, preprocessing GNSS data: processing the GNSS monitoring value to obtain a GNSS point deformation monitoring result, and interpolating the deformation monitoring result to obtain GNSS data conforming to the spatial resolution;

step S200, preprocessing the InSAR data: removing spatial correlation errors from InSAR data to obtain a line-of-sight deformation time sequence, and performing downsampling on deformation monitoring results to enable the deformation monitoring results to be consistent with the spatial resolution of GNSS interpolation results;

step S300, a motion equation and an observation equation for monitoring the three-dimensional deformation of the region are established: establishing a discrete Kalman filtering equation of motion based on the deformation displacement value to be solved by the monitoring point, the instantaneous speed and the instantaneous acceleration rate; establishing an observation equation according to the relation between InSAR-LOS line-of-sight deformation, GNSS three-dimensional deformation and projection of the earth surface E, N, U in the three-dimensional direction;

and step S400, filtering fusion solution.

2. The method for resolving high-precision time-series earth surface three-dimensional deformation of multi-source data according to claim 1, wherein step S400 comprises:

step S410, determining a filtering initial value;

step S420, performing filter recurrence estimation under the criterion of minimum mean square error estimation according to the state equation and the observation equation.

3. The method of high-precision time-series earth surface three-dimensional deformation resolution of multi-source data according to claim 1, wherein step S420 comprises:

step S421, predicting the deformation state value at the current moment in one step: obtaining a state one-step prediction by using the state quantity of the previous moment and by means of a state transition matrix;

step S422, predicting the deformation state value variance at the current moment in one step: solving a one-step prediction error variance matrix by using the state vector covariance of the last moment and the dynamic model noise vector;

step S423, calculating a filtering gain matrix: solving a filtering gain matrix by using the observation vector and the observation matrix;

step S424, obtaining a filtering update state vector and a corresponding covariance matrix;

filtering and resolving are carried out by using InSAR or GNSS observation values acquired at different moments, three-dimensional deformation state vector estimation values at each data acquisition moment are obtained, and three-dimensional deformation of a monitoring area is dynamically monitored.

4. A multi-source data high-precision time sequence earth surface three-dimensional deformation resolving system is characterized by comprising:

the GNSS data preprocessing module is used for preprocessing GNSS data: processing the GNSS monitoring value to obtain a GNSS point deformation monitoring result, and interpolating the deformation monitoring result to obtain GNSS data conforming to the spatial resolution;

the InSAR data preprocessing module is used for preprocessing the InSAR data: removing spatial correlation errors from InSAR data to obtain a line-of-sight deformation time sequence, and performing downsampling on deformation monitoring results to enable the deformation monitoring results to be consistent with the spatial resolution of GNSS interpolation results;

the equation building module is used for building a motion equation and an observation equation for monitoring the three-dimensional deformation of the region: establishing a discrete Kalman filtering equation of motion based on the deformation displacement value to be solved by the monitoring point, the instantaneous speed and the instantaneous acceleration rate; establishing an observation equation according to the relation between InSAR-LOS line-of-sight deformation, GNSS three-dimensional deformation and projection of the earth surface E, N, U in the three-dimensional direction;

and the filtering fusion resolving module is used for filtering fusion resolving.

5. An electronic device, the electronic device comprising:

at least one processor; the method comprises the steps of,

a memory communicatively coupled to the at least one processor; wherein,,

the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of the preceding claims 1 to 3.

6. A non-transitory computer readable storage medium storing computer instructions for causing the computer to perform the method of any one of the preceding claims 1 to 3.