CN117310706A - Discontinuous deformation monitoring method and system for foundation radar - Google Patents

Abstract

The invention provides a discontinuous deformation monitoring method and a discontinuous deformation monitoring system for a foundation radar, which provide relocation error compensation for a two-dimensional azimuth nonlinear model according to scene assumption and model error analysis, and can compensate phase errors caused by radar position deviation. The scheme is suitable for long-term slow deformation monitoring of the foundation radar, can improve the flexibility of radar layout, reduces the complexity of data processing, has higher error compensation precision, improves deformation measurement precision, and is applied to discontinuous monitoring of buildings, and the deformation measurement precision after compensation is superior to millimeter level.

Description

Discontinuous deformation monitoring method and system for foundation radar

Technical Field

The invention relates to the fields of computer data processing and radar data processing, is applied to radar positioning error compensation, and particularly relates to a discontinuous deformation monitoring method and system for a foundation radar.

Background

The foundation SAR has been successfully applied to high-precision deformation monitoring of natural disaster affected areas, dams, alpine glaciers, pier piers and the like by virtue of the advantages of short-time empty baselines, high resolution, short measurement period, convenient operation and the like, and the limitations of time incoherence, long spatial baselines, long revisit period and the like of the foundation SAR are broken through. The GBSAR realizes the distance high resolution by emitting electromagnetic waves with high frequency and large bandwidth in the distance direction, and the azimuth direction synthesizes a virtual large aperture antenna by utilizing the motion in a fixed orbit to realize the azimuth high resolution.

GBSAR can be divided into two monitoring modes depending on the manner in which the data is acquired: continuous monitoring (C-GBSAR) and intermittent monitoring (D-GBSAR). However, in the continuous monitoring model, GBSAR monitors for a long time that there is data redundancy, and the complexity of data processing is large; for a slow deformation monitoring scene, a large amount of manpower and material resources are consumed, and the monitoring efficiency is low. In the intermittent monitoring mode, the movement of the radar in the space position is monitored, and the space position is similar to the space baseline of the space-borne SAR.

The current wide application in intermittent monitoring is GB-SAR intermittent deformation monitoring, which generally mainly comprises the following steps: image registration, interferogram generation, permanent scatterer (Permanent Scatterers, PS) selection, phase unwrapping, repositioning error compensation, deformation resolution. The discontinuous measurement mode of the foundation synthetic aperture radar is suitable for monitoring landslide with slow deformation. However, the radar needs to be repeatedly installed and disassembled, which inevitably causes repositioning errors and seriously affects the accuracy of deformation measurement. In the multi-scene monitoring process, the radar can generate space position deviation, so that errors except deformation exist in the interference phase. Because the wavelength of the radar is short, the measurement accuracy reaches the sub-millimeter level, and the deviation of the millimeter level of the radar position can generate serious error phase for a monitored target. Thus, the repositioning error is very sensitive to the position offset, and if not accurately corrected, the reliability of the deformation inversion results is severely reduced.

In the spaceborne InSAR, the most widely used method for correcting the baseline error is to estimate the best fit plane by using a first-order polynomial function or a second-order model, however, the first-order model still has residual phase after error correction, and the error compensation scheme is directly based on the influence of error correction by a data analysis and error plane fitting method, and does not start from an error generation mechanism, so that error compensation is basically carried out.

Disclosure of Invention

In view of this, the embodiment of the invention provides a new repositioning error compensation scheme, which can compensate the phase error caused by the radar position deviation, and is suitable for the long-term slow deformation monitoring of the foundation radar, so that the flexibility of radar layout can be improved, the complexity of data processing can be reduced, and the deformation measurement precision can be improved.

Specifically, the invention provides the following technical scheme:

in one aspect, the invention provides a method for monitoring discontinuous deformation of a foundation radar, which comprises the following steps:

s1, calculating monitoring target deformation caused by the displacement of a radar space baseline along the directions of an x axis, a y axis and a z axis based on interference patterns obtained at different time points in intermittent deformation monitoring;

s2, based on the deformation of the monitoring target and the relation between the radar echo phase change and the radar distance change, an x-axis, y-axis and z-axis repositioning error model is established;

s3, calculating an interference phase model of a PS point in the monitoring scene based on the repositioning error model and combining a target pitch angle span; the interference phase model is as follows:

wherein,、/>and->Is the parameter to be estimated, +.>Is azimuth angle, +>、/>、/>Respectively representing phase changes caused by the displacement of the radar along the directions of the x axis, the y axis and the z axis;

and S4, estimating parameters in the interference phase model to obtain a repositioning error curved surface.

Preferably, in S1, the monitoring target deformation amount caused by the offset along the x-axis direction is:

wherein,indicating the radar initial position +.>Indicating radar position offset post position->For the target position +.>Three-dimensional skew representing target and radar, +.>Represents the offset of the radar along the x-axis, < >>The pitch angle at the PS point is indicated.

Preferably, in S1, the monitoring target deformation amount caused by the offset along the y-axis direction is:

wherein,indicating the radar initial position +.>Indicating radar position offset post position->For the target position +.>Three-dimensional skew representing target and radar, +.>Represents the offset of the radar along the y-axis, < >>The pitch angle at the PS point is indicated.

Preferably, in S1, the monitoring target deformation amount caused by the offset along the z-axis direction is:

wherein,indicating the radar initial position +.>Indicating radar position offset post-positionPut (I) at>For the target position +.>Three-dimensional skew representing target and radar, +.>Representing the offset of the radar along the z-axis, < >>The pitch angle at the PS point is indicated.

Preferably, in the step S2, the relocation error model is:

wherein,represents the offset of the radar along the x-axis, < >>Represents the offset of the radar along the y-axis, < >>Represents the offset along the z-axis, +.>Pitch angle, denoted PS Point, +.>Representing the radar signal wavelength.

Preferably, in the step S3, for the interference phase after unwrapping the PS point in the monitored sceneIn matrix form, i.e.Matrix of interference phase modelThe form is converted into:

wherein,error of representation model +.>Representing interference phase in matrix form, azimuth angle of PS pointX represents a matrix of sine and cosine function values of azimuth angle, < ->Representing parameters to be estimated, they are represented as follows:

preferably, in the interferometric phase model building, a target pitch angleIn which value +.>Instead, namely:

wherein,the target pitch span is +.>，/>Represents the offset of the radar along the x-axis, < >>Represents the offset of the radar along the y-axis, < >>Representing the offset of the radar along the z-axis, < >>Representing the radar signal wavelength.

Preferably, in the step S3, for screening PS points, a dual threshold of coherence coefficient and amplitude information is used for screening;

and in the phase unwrapping stage after PS point screening, phase unwrapping is carried out along the azimuth direction.

Preferably, the estimated relocation error model parameters are solved by least squares:

wherein,representing estimated repositioning error model parameters;

then, the estimated relocation error phase is derived:

finally, using the unwrapped PS-point phaseSubtracting the estimated relocation error phase +.>The deformation amount can be calculated to obtain deformation phase +.>。

On the other hand, the invention also provides a discontinuous deformation monitoring system of the foundation radar, which comprises:

the monitoring target deformation amount calculation module is used for calculating the monitoring target deformation amount caused by the displacement of the radar space base line along the directions of the x axis, the y axis and the z axis based on the interference patterns obtained at different time points in the intermittent deformation monitoring;

the repositioning error model module is used for establishing an x-axis, y-axis and z-axis repositioning error model based on the deformation of the monitoring target and the relation between the radar echo phase change and the radar distance change of the monitoring target;

the interference phase model module is used for calculating an interference phase model of a PS point in a monitoring scene based on the repositioning error model and combined with a target pitch angle span; the interference phase model is as follows:

wherein,、/>and->Is the parameter to be estimated, +.>Is azimuth angle, +>、/>、/>Respectively representing phase changes caused by the displacement of the radar along the directions of the x axis, the y axis and the z axis;

and the parameter estimation module is used for estimating parameters in the interference phase model to obtain a repositioning error curved surface.

Preferably, the system further comprises:

the image registration module is used for carrying out image registration based on the amplitude phase coherence of different SLC images;

the interference pattern generation module is used for generating an interference pattern based on the registered image;

the PS point screening module adopts a dual threshold value of the coherence coefficient and the amplitude information to carry out PS point screening;

the phase unwrapping module is used for carrying out phase unwrapping on the interference pattern after PS point screening, and the image data after phase unwrapping is input into the monitoring target deformation amount calculating module;

and the deformation calculation module is used for calculating the deformation based on the repositioning error curved surface obtained by the parameter estimation module.

In a third aspect, the present invention also provides a device for monitoring discontinuous deformation of ground-based radar, the device comprising a processor and a memory, the processor being operable to invoke computer instructions stored in the memory to perform the method for monitoring discontinuous deformation of ground-based radar as described above.

Compared with the prior art, the technical scheme of the invention derives the geometrical relationship between the repositioning error and the radar baseline, the target pitch angle azimuth angle and other system parameters from the geometrical relationship of the radar three-dimensional baseline, and fundamentally reveals the mathematical principle and physical significance of the repositioning error phase. And then according to scene assumption and model error analysis, a conclusion that the pitch angle of the target has small influence on the repositioning error is obtained, and a repositioning error compensation method of the two-dimensional azimuth nonlinear model is provided. The method can compensate the repositioning error with high precision without additional Data Elevation Model (DEM) data. Compared with the traditional polynomial model, the method provided by the scheme has nonlinear error correction capability and higher error compensation precision. The method is applied to discontinuous monitoring of the building, the deformation measurement precision after compensation is better than millimeter level, and the practicability and superiority of the method are verified.

Drawings

In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 is a schematic diagram of three-dimensional coordinate relationship between a target and a radar in accordance with an embodiment of the present invention;

FIG. 2 is a schematic diagram of a baseline x-axis component of a intermittently monitored radar space in accordance with an embodiment of the present invention;

FIG. 3 is a schematic view of a discontinuous monitoring radar spatial baseline y-axis component according to an embodiment of the present invention;

FIG. 4 is a schematic diagram of a z-axis component of a baseline of intermittently monitored radar space in accordance with an embodiment of the present invention;

FIG. 5 is a graph comparing two types of terrain repositioning error compensation results according to an embodiment of the present invention; wherein: (a) (c) (e) is a flat ground compensation result; (b) (d) (f) is a linear ramp compensation result; (a) repositioning errors for the flat terrain model; (b) repositioning the error for the flat terrain model; (c) providing a nonlinear model compensation result; (d) providing a nonlinear model compensation result; (e) a second order polynomial model compensation result; (f) is a second order polynomial model compensation result;

FIG. 6 is a schematic diagram of experimental scenario and results according to an embodiment of the present invention; wherein: (a) a teaching building live-action diagram of a certain school district; (b) is a PS-point interferogram before compensation; (c) is a compensated PS-point interferogram;

FIG. 7 is a flow chart of a method according to an embodiment of the present invention;

FIG. 8 is a general link schematic of foundation radar interferometry;

fig. 9 is a schematic diagram of a relocation error compensation process.

Detailed Description

Embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be understood that the described embodiments are only some, but not all, of the embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

It will be appreciated by those of skill in the art that the following specific embodiments or implementations are provided as a series of preferred arrangements of the present invention for further explanation of the specific disclosure, and that the arrangements may be used in conjunction or association with each other, unless it is specifically contemplated that some or some of the specific embodiments or implementations may not be associated or used with other embodiments or implementations. Meanwhile, the following specific examples or embodiments are merely provided as an optimized arrangement, and are not to be construed as limiting the scope of the present invention.

In order to make up for the defects existing in the prior art, the scheme starts from a space baseline geometric model, and a two-dimensional azimuth nonlinear model repositioning error compensation method is provided according to scene assumption and model error analysis. Compared with the traditional polynomial model, the method has higher error compensation precision. The deformation measuring precision after compensation is better than millimeter level when the scheme is applied to discontinuous monitoring of buildings. The present invention is described in detail below with reference to fig. 7 and fig. 1 to 4.

1. Radar spatial baseline geometry analysis

As shown in FIG. 1, the present embodiment considers the three-dimensional coordinate relationship of the target and the radar, in whichIndicating the initial position of the radar,for the target position +.>Indicating lightningReaching the position after the position shift, +.>Representing the pitch angle of the target; />Indicating azimuth angle, ++>Three-dimensional skew representing target and radar, +.>Representation->And a tilt distance projected onto a horizontal plane. For each target of the monitored scene we consider the spatial baselines of the three directions of the radar.

(1) Spatial baseline model along x-axis direction

For the case where the radar offset direction is along the x-axis, as shown in fig. 2 (top view of fig. 1). With positive displacement of radar along x-axis, i.e. azimuth of x-axis. Since the distance of the target is in the order of kilometers, the radar offset can be controlled in the order of millimeters. So for the same object->Angle due to radar position offset +.>The change of (2) is small, it can be considered that the azimuth angle of the target is unchanged +>。/>The pitch angle at the PS point is indicated.

First, in order to obtain a deformation phase induced by a radar position shiftIt is necessary to solve the target deformation +.>. The target deformation expression obtained according to the cosine theorem is as follows:

（1）

according toIs approximated by the taylor expansion formula:

（2）

for formula (VI)And (3) unfolding to obtain:

（3）

therefore, in the present embodiment, the deformation expression caused by the spatial baseline is:

（4）

as can be obtained from equation (4), the amount of deformation introduced by the displacement of the radar in the x-axis direction is related to the azimuth angle, pitch angle, and pitch of the target. We can build a functional relationship between the radar spatial baseline and the target phase through a parameterized model.

(2) Spatial baseline model along y-axis direction

For the case that the radar offset direction is along the y-axis, as shown in fig. 3, the following is obtained according to the geometric relationship analysis:

（5）

formulas (4) and (5) have the same structure, except that: the radar spatial baselines are projected in different directions, with only differences in azimuth parameters.

(3) Spatial baseline model along z-axis direction

For the radar spatial baseline along the z-axis direction, as shown in fig. 4, the spatial geometry is obtained by:

（6）

according to equation (6), it is relatively simple to solve for the repositioning error in the vertical direction, only the pitch angle of the target is required.

So far, we start from GBSAR intermittent monitoring physical geometry mechanism, and establish spatial baseline error models in three directions. The combination (4) (5) (6) and the direct proportion relation between the object surface and the radar echo phase change caused by the change of the radar distance, namely:

wherein,representing radar signal wavelength, < >>Representing the first Shan Shi complex image phase, < >>Representing the second Shan Shi complex image phase. They do interference to get +.>，/>I.e. the unwrapped PS-dot phase. />Representing the distance of the first observation between the object surface and the radar, i.e. the distance before deformation, +.>Representing the distance between the object surface and the radar for a second observation, i.e. the distance after deformation. Thus, in one phase period, the deformation amount corresponds to the value of the interference phase one by one. Based on which the phase and deformation relationship can be obtained.

A model of the three-directional repositioning errors and radar spatial baselines can be obtained:

（7）

wherein,、/>、/>the phase changes caused by the displacement of the radar along the x-axis, y-axis and z-axis directions are shown respectively. For formula (7) contain->Is a general radar position offset +.>In the sub-millimeter to centimeter range, e.g. +.>While the distance between the radar and the observation target is in the order of kilometers, in this embodiment we make the following assumptions:

（8）

the interference pattern obtained by intermittently monitoring GBSAR at two time points comprises radar space baseline errors, namelyTheir modeling can be reduced to the following formula:

（9）

2. relocation error compensation

Based on the model (9), the relation between the repositioning error of the discontinuous monitoring radar and the target parameter can be established, and the deformation quantity can be calculated with high precision. However, generally GBSAR imaging only has two-dimensional information, namely, the azimuth angle of a measured target is [ ]) Slant distance (+)>) And interference phase (+)>) Lack of accurate target pitch angle (+)>) Or elevation information (+)>). Therefore, it is not enough to directly apply the model (9) for error correction. Three-dimensional imaging or combination of DEM data is required.

Considering that the actual monitoring scene is far-field monitoring, the method is characterized in that the target distance is far, the azimuth angle visual angle is large, and the pitch angle change of the target is relatively small. The main factor affecting the repositioning error is the azimuth angle. Here, assume a target pitch angleThe target pitch span is +.>. When the maximum value of the difference in pitch angles of the targets is small, it can be assumed that +.>Taking->Median->Instead of. We then get a simplified functional expression:

（10）

wherein the method comprises the steps of、/>And->Is the parameter of the model to be estimated.

For monitoring the interference phase of the unwrapped PS point in a sceneAzimuth angle ofPitch angle->. We get the matrix form expression of (10):

（11）

wherein,representing the error of the model, X representing the matrix of sine and cosine functions of the azimuth of the PS point, ++>Representing the parameters to be estimated, they are expressed as follows:

finally, the repositioning error curved surface can be estimated by applying an optimization algorithm such as a least square method, an iteration method and the like. Here we prefer the least squares solution, we are based onCalculating estimated repositioning error model parameters:

（12）

then the estimated relocation error phase is derived:

（13）

finally, using the unwrapped PS-point phaseSubtracting the estimated relocation error phase +.>The deformation amount can be calculated to obtain deformation phase +.>。

Therefore, for the conditions of far-field monitoring and small pitch angle span of the target, the repositioning error can be compensated through the azimuth angle model, additional information such as the elevation of the target is not needed, the complexity of data processing is reduced, and the accuracy requirement of deformation monitoring is met.

The relocation error compensation processing flow is summarized below in conjunction with the above-described embodiment, as shown in fig. 9. Firstly, two-dimensional phase unwrapping is carried out based on the interference phase of the PS point, a trigonometric function nonlinear model is established based on the phase unwrapping result, and the nonlinear model can be obtained based on the conventional unwrapping algorithm and the phase relation, and is not repeated. After the nonlinear model is built, the model can be subjected to parameter estimation by using a least square method and the like, so that model parameters are determined. Then, the repositioning error phase obtained by calculation is subtracted by adopting the repositioning error compensation method provided by the invention, and subsequent deformation calculation is carried out, so that deformation monitoring is realized. Subsequently, the explanation will be further developed in connection with another embodiment.

In addition, in yet another embodiment, the solution of the present invention may be implemented by means of a discontinuous deformation monitoring system for ground-based radar, which is characterized by repositioning error compensation, and the system specifically includes:

the monitoring target deformation amount calculation module is used for calculating the monitoring target deformation amount caused by the displacement of the radar space base line along the directions of the x axis, the y axis and the z axis based on the interference patterns obtained at different time points in the intermittent deformation monitoring;

the repositioning error model module is used for establishing an x-axis, y-axis and z-axis repositioning error model based on the deformation of the monitoring target and the relation between the radar echo phase change and the radar distance change of the monitoring target;

the interference phase model module is used for calculating an interference phase model of a PS point in a monitoring scene based on the repositioning error model and combined with a target pitch angle span; the interference phase model is as follows:

wherein,、/>and->Is the parameter to be estimated, +.>Is azimuth angle, +>、/>、/>Respectively representing phase changes caused by the displacement of the radar along the directions of the x axis, the y axis and the z axis;

and the parameter estimation module is used for estimating parameters in the interference phase model to obtain a repositioning error curved surface.

Preferably, the system further comprises:

the image registration module is used for carrying out image registration based on the amplitude phase coherence of different SLC images;

the interference pattern generation module is used for generating an interference pattern based on the registered image;

the PS point screening module adopts a dual threshold value of the coherence coefficient and the amplitude information to carry out PS point screening;

the phase unwrapping module is used for carrying out phase unwrapping on the interference pattern after PS point screening, and the image data after phase unwrapping is input into the monitoring target deformation amount calculating module;

and the deformation calculation module is used for calculating the deformation based on the repositioning error curved surface obtained by the parameter estimation module.

In system implementation, as shown in connection with fig. 8 and 9, the ground-based radar interferometry process generally includes the following key processing steps:

(1) Image registration

In intermittent monitoring, because the radar is offset, there is an offset of pixels in the resulting SLC image. If the interference process is performed directly, a mismatch noise error is introduced. Registration of the images is therefore required. From the intermittent monitoring mechanism, radar offset is typically on the order of millimeters-decimeters, while target distance is on the order of kilometers. Therefore, the pixel coordinate shift corresponding to the SLC image obtained by imaging is small, typically, a shift of several pixels. Therefore, the two SLC images can be directly subjected to coarse registration to meet the requirements. According to the amplitude phase coherence of two SLC images, the image registration can be completed by applying a correlation coefficient method, and the requirement of the coherence is met.

(2) Interferogram generation

The GB-SAR monitoring image is a Single-Look-Complex (SLC) image with values distributed in. For the time sequence +.>And carrying out differential interference processing on the SLC image of the radar at different time for each target point:

wherein the method comprises the steps ofIs->Interference phase of individual points->Is->Zhang Leida echo image,/->Is->Zhang Leida echo image,/->The symbol represents the conjugate->Representing the phase taking.

The interference phase obtained generally cannot directly calculate deformation by using a proportional relation formula between the object surface and the radar echo phase change caused by the radar distance change, and in practice, the interference phase contains various noise interference sources and can be subjected to deformation calculation only by removing noise. Differential interferogram NoThe interferometric phase of the individual target points can be modeled as:

wherein the method comprises the steps ofA Line-Of-Sight (Line-Sight) argument for the target point; />The atmospheric delay phase is introduced by the atmospheric refractive index change at different times; />The incoherent noise phase can be filtered by a low-pass phase filter;for blurring phase +.>Is an integer and represents ambiguity. In this scenario we assume that the atmospheric phase in the scene is negligible and only focus on repositioning error compensation.

(3) PS point selection

The quality of the interferogram directly influences the accuracy of the atmospheric phase estimation and deformation solution. Because the interference pattern contains unstable interference points such as water, vegetation and the like, different targets are affected by atmospheric disturbance and incoherent noise differently, and the atmospheric phase is difficult to directly estimate. The permanent scatterer interferometry technology can effectively extract a reference point for measuring scene stability, and improve the accuracy of deformation inversion by overcoming the influence of non-ideal factors such as time decoherence and the like.

The common PS selection method comprises the following steps: a coherence coefficient thresholding method, an amplitude dispersion thresholding method, an amplitude information method, a phase variance method, a phase noise thresholding method, and the like. We can choose, for example, a coherence factor thresholding and an amplitude thresholding to combine PS-point screening:

1) Coherence coefficient thresholding: theoretically, a high coherence coefficient can reflect a high signal-to-noise ratio of the interferogram, and the selection principle is to estimate the coherence coefficient according to the pixel values adjacent to the periphery of the target pixel, and the expression is as follows:

wherein the method comprises the steps ofRepresenting the coherence coefficient of the pixel, ">And->Master-slave single vision complex number image respectively constituting kth interference pair,>represents the conjugate of complex numbers, m and n are the sliding window sizes, which can be set to +.>Etc. At->In the case of several interference images, each pixel corresponds to +.>Personal coherence factor->. The pixel coherence coefficient can then be averaged, i.e

To measure the size of the coherence coefficient of the target point by setting a threshold valueExtracting to satisfy->And obtaining a PS point.

2) Amplitude information method: the larger the amplitude of the scattering point echo, the more strongly the radar is backscattered at that point, and the greater the likelihood that the target point is a hard, steady scatterer. So the amplitude based on the echo information is largeAnd the method is small, can be used for initially screening strong scattering points, and provides important references for the selection of PS points. By setting amplitude thresholdCan screen out the drugs greater than the threshold +.>As candidate points for PS points. The experimental result shows that the larger the amplitude threshold value is, the fewer the points with large phase errors are selected; as the amplitude value decreases, the point where the phase error is large increases gradually.

(4) Phase unwrapping

The interference pattern is obtained after the radar SLC image is subjected to differential interference processing, and the interference phase of the interference pattern may have a time space winding phenomenon. The phase unwrapping is an indispensable step for restoring the true phase of the PS point and carrying out high-precision deformation resolving. The phase unwrapping process includes two-dimensional spatial unwrapping and one-dimensional temporal unwrapping. In the spatial domain, two-bit unwrapping is typically based on methods of road strength integration, minimum norm, or network flow optimization. Whereas in the time domain kalman filtering or euler expansion may be used. Time unwrapping can unwrap the phase of the discontinuous areas correctly, but requires more timing interferometry, and the phase must meet the established model; spatial unwrapping can be done using fewer interferograms (e.g., single interferograms) and the process after phase unwrapping is more flexible.

How to restore the phase difference in the real deformation information and solve the value of the ambiguity is always a difficulty in the field of DINSAR. To date, there are various methods of phase unwrapping: path tracking, minimum norm, optimal estimation, etc. However, many methods are based on phase continuity assumptions, i.e., adjacent points have an interference phase gradient of less than half a wavelength.

For phase unwrapping in the field of GB-SAR deformation monitoring, (1) in the spatial dimension: because of the discrete irregular distribution of PS points, the unwrapping method is usually performed based on an irregular grid, such as a triangle-based minimum cost flow algorithm; (2) in the time dimension: since the ground-based SAR monitoring time base line is short, phase fluctuations can be assumed to be small, and the time dimension can be unwrapped based on phase continuity assumptions and integrated along the time sequence.

(5) Relocation error compensation

After phase unwrapping, error compensation can be performed using the method of repositioning error compensation as given in the above embodiments of the invention. And will not be described in detail herein.

(6) Deformation solution

After reasonable error compensation is carried out, a repositioning error curved surface is obtained, and then the subsequent concrete calculation of deformation can be carried out so as to obtain concrete data.

The following will further describe the present embodiment in conjunction with specific comparative test examples and actual scenario cases.

In this embodiment, the present scheme is further described with reference to a simulation comparative test. In actual intermittent monitoring, the radar typically moves only in a horizontal two-dimensional plane. In this embodiment we consider only the repositioning error in the radar level, not the radar level。

Considering that most of the scenes can be approximated as flat ground or linear slopes, here experiments of two different monitoring scenes were simulated: flat ground, linear ramp to verify the superiority of the proposed method. The parameters of the scene are shown in table 1. In the present embodiment, the radar offset direction and the radar offset size are set asMillimeter, mainly consider radar baseline in horizontal direction, and not consider radar altitude baseline. To evaluate the accuracy of the model, root mean square error (Root Mean Square Error, RMSE) and maximum absolute error (Maximum Absolute Error, MAE) indices were introduced, and the experimental results are shown in fig. 5 below.

TABLE 1 scene simulation parameters

TABLE 2 Compensation results Root Mean Square Error (RMSE) and Maximum Absolute Error (MAE) comparison

As can be seen from fig. 5 and table 2, the relocation error compensation result of the proposed solution is better than the second order polynomial model, and the root mean square error of the residual phase is smaller. However, for a two-dimensional model, as the pitch span of the monitored scene increases from 0 to 10 degrees, its root mean square error increases. Therefore, the proposed method is affected by the pitch angle, and when the pitch angle span is large, the relocation error compensation accuracy of the proposed method is lowered. It should be noted here that the advantage of the proposed model is that it does not require additional DEM data. This simplifies the complexity of the D-GBSAR data processing while meeting the sub-millimeter deformation monitoring requirements.

In this scenario, we conclude that the repositioning error phase is mainly affected by azimuth for the case where the target pitch span is small. According to pitch angle parameters and deformation measurement precision of a monitoring scene, a radar space base line meeting the conditions can be designed, additional DEM data are not needed, and the intermittent monitoring data processing efficiency is improved.

In the following, we verify the superiority of the two-dimensional azimuth model by the measured data of the actual scene case. The experimental scene is selected from the teaching building in the western district of a certain school district, the building monitoring distance is 100 meters to 300 meters, the atmospheric delay phase is small, and the repositioning error compensation effect is easy to analyze. The circular SAR wavelength was 12.4 millimeters, the range resolution was 0.3 m, and the azimuth resolution was 0.114 °. The azimuth angle of the target of the monitoring scene is distributed in the range of [50 DEG, 130 DEG ] ] and the pitch angle range of the target is about [0 DEG, 11 DEG ] ]. The pitch angle span of the radar target in the monitoring scene is smaller, and the repositioning error is mainly influenced by the azimuth angle. In the experimental example, the repositioning error correction is performed by adopting the method provided by the application, and additional DEM data are not needed.

The scheme adopts a coherence coefficient and amplitude information dual threshold value PS point screening method to select PS points of an image; threshold screening of a coherence coefficient method and an amplitude information method both belong to the prior art, and can be performed by adopting the existing schemes in the prior art, and are not repeated here. Before this, the images need to be registered. In order to emphasize the necessity of registration, the number of PS points extracted by the same method before and after registration is used as an index. Before registration, the PS points were chosen to be 20776 under the same threshold. After registration, the same sub-threshold PS points were selected as 29852. Because of the mismatch noise of the images, the coherence of the target is reduced before registration, so that the number of PS points selected based on a coherence coefficient method is small. After registration, the number of PS points of the selected area is increased, the number of sample points is more, and the accuracy of the subsequent error parameter estimation is improved.

Fig. 6 is a graph of the results of one of the intermittent monitoring. Wherein (a) in fig. 6 is a real view of a teaching building in a certain school district; fig. 6 (b) shows a PS point interferogram before compensation; fig. 6 (c) is a PS-point interferogram after compensation. Before compensation, the repositioning error exists in the form of interference fringes, and it is difficult to accurately calculate the deformation amount. In (b) in fig. 6, we find that the interference phase distribution is regularly wound along the azimuth direction, and therefore, we perform a phase unwrapping method along the azimuth direction. After two-bit unwrapping of the PS-point interference phase, the root mean square error of the residual phase is about 0.197 rad (0.194 mm) based on the proposed nonlinear model compensation. The deformation of the building target after compensation is 0, which accords with the actual scene situation, and the feasibility and practicality of the proposed model are verified.

In yet another embodiment, the present solution may be implemented by means of an apparatus, which may include corresponding modules performing each or several steps of the above-described embodiments. Thus, each step or several steps of the various embodiments described above may be performed by a respective module, and the electronic device may include one or more of these modules. A module may be one or more hardware modules specifically configured to perform the respective steps, or be implemented by a processor configured to perform the respective steps, or be stored within a computer-readable medium for implementation by a processor, or be implemented by some combination. The device may be implemented using a bus architecture.

Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and further implementations are included within the scope of the preferred embodiment of the present invention in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the embodiment of the present invention. The processor performs the various methods and processes described above. For example, method embodiments in the present solution may be implemented as a software program tangibly embodied on a machine-readable medium, such as a memory. In some embodiments, part or all of the software program may be loaded and/or installed via memory and/or a communication interface. One or more of the steps of the methods described above may be performed when a software program is loaded into memory and executed by a processor. Alternatively, in other embodiments, the processor may be configured to perform one of the methods described above in any other suitable manner (e.g., by means of firmware).

Logic and/or steps represented in the flowcharts or otherwise described herein may be embodied in any readable storage medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions.

The foregoing is merely illustrative of the present invention, and the present invention is not limited thereto, and any changes or substitutions easily contemplated by those skilled in the art within the scope of the present invention should be included in the present invention. Therefore, the protection scope of the invention is subject to the protection scope of the claims.

Claims (10)

1. A method for monitoring discontinuous deformation of a ground-based radar, the method comprising:

s1, calculating monitoring target deformation caused by the displacement of a radar space baseline along the directions of an x axis, a y axis and a z axis based on interference patterns obtained at different time points in intermittent deformation monitoring;

s2, based on the deformation of the monitoring target and the relation between the radar echo phase change and the radar distance change, an x-axis, y-axis and z-axis repositioning error model is established;

s3, calculating an interference phase model of a PS point in the monitoring scene based on the repositioning error model and combining a target pitch angle span; the interference phase model is as follows:

wherein,、/>and->Is the parameter to be estimated, +.>Is azimuth angle, +>、/>、/>Respectively representing phase changes caused by the displacement of the radar along the directions of the x axis, the y axis and the z axis;

and S4, estimating parameters in the interference phase model to obtain a repositioning error curved surface.

2. The method according to claim 1, wherein in S1, the monitoring target deformation amount caused by the offset along the x-axis direction is:

wherein,indicating the radar initial position +.>Indicating radar position offset post position->For the target position +.>Three-dimensional skew representing target and radar, +.>Represents the offset of the radar along the x-axis, < >>The pitch angle at the PS point is indicated.

3. The method according to claim 1, wherein in S1, the monitoring target deformation amount caused by the offset along the y-axis direction is:

wherein,indicating the radar initial position +.>Indicating radar position offset post position->For the target position +.>Three-dimensional skew representing target and radar, +.>Represents the offset of the radar along the y-axis, < >>The pitch angle at the PS point is indicated.

4. The method according to claim 1, wherein in S1, the monitoring target deformation amount caused by the offset along the z-axis direction is:

wherein,indicating the radar initial position +.>Indicating radar position offset post position->For the target position +.>Three-dimensional skew representing target and radar, +.>Representing the offset of the radar along the z-axis, < >>The pitch angle at the PS point is indicated.

5. The method according to claim 1, wherein in S2, the relocation error model is:

wherein,represents the offset of the radar along the x-axis, < >>Represents the offset of the radar along the y-axis, < >>Representing the offset of the radar along the z-axis, < >>Pitch angle, denoted PS Point, +.>Representing the radar signal wavelength.

6. The method according to claim 1, wherein in S3, when the interference phase for PS points in the monitored scene is in matrix form, the interference phase isThe matrix form of the interferometric phase model is then converted into:

wherein,error of representation model +.>Represents the interference phase in matrix form, azimuth angle of PS point +.>，

。

7. The method according to claim 1, wherein in the interferometric phase model build, a target pitch angleIn which value +.>Instead, namely:

wherein,the target pitch span is +.>，/>Represents the offset of the radar along the x-axis, < >>Represents the offset of the radar along the y-axis, < >>Representing the offset of the radar along the z-axis, < >>Representing the radar signal wavelength.

8. The method according to claim 1, wherein in S3, for screening PS points, a dual threshold of coherence coefficient and amplitude information is used for screening;

and in the phase unwrapping stage after PS point screening, phase unwrapping is carried out along the azimuth direction.

9. A ground-based radar intermittent deformation monitoring system, the system comprising:

the monitoring target deformation amount calculation module is used for calculating the monitoring target deformation amount caused by the displacement of the radar space base line along the directions of the x axis, the y axis and the z axis based on the interference patterns obtained at different time points in the intermittent deformation monitoring;

the repositioning error model module is used for establishing an x-axis, y-axis and z-axis repositioning error model based on the deformation of the monitoring target and the relation between the radar echo phase change and the radar distance change of the monitoring target;

the interference phase model module is used for calculating an interference phase model of a PS point in a monitoring scene based on the repositioning error model and combined with a target pitch angle span; the interference phase model is as follows:

wherein,、/>and->Is the parameter to be estimated, +.>Is azimuth angle, +>、/>、/>Respectively representing phase changes caused by the displacement of the radar along the directions of the x axis, the y axis and the z axis;

and the parameter estimation module is used for estimating parameters in the interference phase model to obtain a repositioning error curved surface.

10. The system of claim 9, wherein the system further comprises:

the image registration module is used for carrying out image registration based on the amplitude phase coherence of different SLC images;

the interference pattern generation module is used for generating an interference pattern based on the registered image;

the PS point screening module adopts a dual threshold value of the coherence coefficient and the amplitude information to carry out PS point screening;

the phase unwrapping module is used for carrying out phase unwrapping on the interference pattern after PS point screening, and the image data after phase unwrapping is input into the monitoring target deformation amount calculating module;

and the deformation calculation module is used for calculating the deformation based on the repositioning error curved surface obtained by the parameter estimation module.