Earth surface deformation speed monitoring method and device, medium and equipment

Abstract

The invention discloses an earth surface deformation speed monitoring method and device, a medium and equipment, and relates to the technical field of earth surface deformation monitoring. The method comprises the steps that interferometric phase diagrams of a target area at N different moments are acquired, M reference points are arranged at the corresponding positions of the interferometric phase diagrams at the N different moments, and N and M are positive integers; based on an interferometric phase diagram sequence formed by the interferometric phase diagrams at N different moments, taking each reference point in the M reference points as a datum reference point, and obtaining M * (M-1) / 2 baseline velocities about the M reference points; and performing unconstrained joint adjustment processing on the M * (M-1) / 2 baseline velocities to obtain the deformation velocity of the target area. According to the scheme, the accuracy of monitoring the surface deformation speed is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of surface deformation monitoring, and in particular to a method, device, medium and equipment for monitoring surface deformation velocity. Background Art

[0002] The measurement of surface deformation velocity is one of the important technologies for understanding the current characteristics of the Earth and its past evolution. However, existing technologies still face some challenges, such as the coverage and availability of observation data, as well as the measurement of small deformations, especially the monitoring of weak deformations in cases such as slow slip of active faults. Since the early 1990s, the interferometric synthetic aperture radar (InSAR) technology has been successfully applied to ground deformation measurement. Due to its global range and all-weather advantages, InSAR has been widely used in the field of surface deformation velocity monitoring (such as coseismic and landslides). Generally speaking, under reasonable conditions, the deformation monitoring accuracy of a single interferometric phase image can reach the centimeter level, while when deformation monitoring is performed through the interferometric phase image time series, the accuracy can reach the millimeter level or sub-centimeter level. However, the errors caused by the reference point, especially the interferometric phase image unwrapping errors, are often ignored, and these errors may affect the accuracy of the deformation velocity. Therefore, how to reduce the influence of the reference point error on the calculation of the surface deformation velocity is an important topic of current research.

[0003] Traditional methods for calculating surface deformation velocity usually rely on a single reference point. This method is prone to large error accumulation and affects the accuracy of deformation velocity when there are influencing factors such as atmospheric and topographic errors and interferometric phase map unwrapping errors. Especially in complex deformation scenarios such as low coherence areas (such as lakes, rivers and densely vegetated areas) and slow slip faults or interseismic loading, the calculation accuracy and reliability of the single-reference deformation monitoring (SRM) method are not high. In many applications, high-resolution continuous velocity maps are not required unless they are used for visualization (for example, monitoring the deformation of discrete objects such as corner reflectors and small buildings). Especially when the coherence of the interferometric phase map is too low and most of the effective pixels are sparsely distributed. Even if a continuous velocity map is produced with sufficient coherence, the deformation results usually need to be downsampled to discrete samples due to the high spatial correlation of the measured data. This is particularly common in the modeling of coseismic, post-seismic, volcanic and other events.

[0004] In summary, the existing surface deformation velocity monitoring methods have the problem of low monitoring accuracy. Summary of the invention

[0005] Traditional surface deformation velocity calculation methods usually rely on a single reference point. This method is prone to large error accumulation and affects the accuracy of monitoring surface deformation velocity when there are influencing factors such as atmospheric and topographic errors and interferometric phase pattern unwrapping errors. Especially in complex deformation scenarios such as low coherence areas (such as lakes, rivers and densely vegetated areas) and slow slip faults or interseismic loading, the accuracy of single reference point deformation monitoring is often unsatisfactory. Based on this, it is necessary to provide a surface deformation velocity monitoring method, device, medium and equipment to address the problem of low monitoring accuracy of existing surface deformation velocity monitoring methods.

[0006] The present invention adopts the following technical solutions:

[0007] In a first aspect, the present invention provides a method for monitoring surface deformation velocity, the method comprising:

[0008] Obtaining interference phase images of the target area at N different times, setting M reference points at corresponding positions of the interference phase images at the N different times, where N and M are positive integers;

[0009] Based on the interference phase image sequence formed by the N interference phase images at different times, each reference point in the M reference points is used as a reference reference point to obtain M*(M-1) / 2 baseline velocities about the M reference points;

[0010] The M*(M-1) / 2 baseline velocities are subjected to unconstrained joint adjustment processing to obtain the deformation velocity of the target area.

[0011] Further, based on the interference phase image sequence formed by the interference phase images at the N different moments, each reference point in the M reference points is used as a reference reference point to obtain M*(M-1) / 2 baseline velocities about the M reference points, specifically including:

[0012] Based on the interference phase image sequence formed by the N interference phase images at different times, each reference point in the M reference points is used as a reference reference point to obtain M*(M-1) / 2 phase differences about the M reference points;

[0013] Based on the constant relationship between the phase difference and the baseline velocity, the M*(M-1) / 2 baseline velocities are obtained;

[0014] The calculation formula of the M*(M-1) / 2 phase differences is:

[0015]

[0016] in, is the acquisition time t of the i-th interference phase image iand the acquisition time t of the jth interference phase image j The phase difference between position p and position q, is the acquisition time t of the i-th interference phase image i and the acquisition time t of the jth interference phase image j The phase of position p relative to the reference point r, is the acquisition time t of the i-th interference phase image i and the acquisition time t of the jth interference phase image j The phase of position q relative to the reference point r, B ⊥ is the vertical baseline, λ is the wavelength of the signal, θ is the incident angle, v pr is the linear velocity, h pr is the digital elevation model error, is the unmodeled noise.

[0017] Furthermore, an unconstrained joint adjustment process is performed on the M*(M-1) / 2 baseline velocities, specifically including:

[0018] The M*(M-1) / 2 baseline velocities are adjusted respectively using an unconstrained joint adjustment method. The expression of the adjustment is:

[0019]

[0020] Where n is the number of reference points, L is the observation matrix, v1 is the velocity constraint, C is a constant, and v pq It refers to the deformation speed of position p relative to position q.

[0021] In a second aspect, the present invention provides a surface deformation velocity monitoring device, comprising:

[0022] A first acquisition module is used to acquire the interference phase images of the target area at N different moments, and to set M reference points at corresponding positions of the interference phase images at the N different moments;

[0023] A second acquisition module is used to obtain M*(M-1) / 2 baseline velocities about the M reference points by taking each of the M reference points as a reference reference point based on the interference phase image sequence formed by the N interference phase images at different times;

[0024] The processing module is used to perform unconstrained joint adjustment processing on the M*(M-1) / 2 baseline velocities to obtain the deformation velocity of the target area.

[0025] The present invention provides a computer-readable storage medium, wherein the storage medium stores a computer program, and when the computer program is executed by a processor, the method for monitoring the velocity of surface deformation is implemented.

[0026] The present invention provides a computer device, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the method for monitoring the velocity of surface deformation is implemented when the processor executes the program.

[0027] The at least one technical solution adopted by the present invention can achieve the following beneficial effects:

[0028] The present invention calculates the velocity of multiple reference points in the interference phase diagram of the target area obtained at multiple different times, calculates the deformation velocity using the velocity relationship between the multiple reference points, and performs joint adjustment processing on the baseline velocities of all reference points, thereby reducing the influence of the error of a single reference point on the deformation velocity calculation, and can improve the accuracy of monitoring the surface deformation velocity. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0030] Figure 1 A schematic diagram of a flow chart of a method for monitoring surface deformation velocity provided by the present invention;

[0031] Figure 2 A performance comparison diagram of the simulation results of the SRM method provided by the present invention and the multi-reference point baseline method under different circumstances;

[0032] Figure 3 The performance of the SRM method and the MRB method provided by the present invention in fault slip inversion;

[0033] Figure 4 The velocity comparison diagram of InSAR and GNSS system in the Haiyuan fault zone area provided by the present invention;

[0034] Figure 5 A schematic diagram of a surface deformation velocity monitoring device provided by the present invention;

[0035] Figure 6 A schematic diagram of a computer device for implementing a method for monitoring surface deformation velocity provided by the present invention. DETAILED DESCRIPTION

[0036] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the specific embodiments of the present invention and the corresponding drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0037] The server mentioned in the present invention can be a server set on a business platform, or a device such as a desktop computer, a laptop computer, etc. that can execute the solution of the present invention. For the convenience of description, the following description is only based on the server as the execution subject. The following is a detailed description of the technical solutions provided by various embodiments of the present invention in conjunction with the accompanying drawings.

[0038] Figure 1 The present invention is a flow chart of a method for monitoring ground deformation velocity, which specifically includes the following steps:

[0039] S10: Obtain interference phase images of the target area at N different moments, and set M reference points at corresponding positions of the interference phase images at N different moments.

[0040] In this embodiment, the target area refers to the area where the surface deformation velocity monitoring is required, and can be selected according to the measurement requirements. N and M are positive integers.

[0041] Optionally, the selection of reference points should avoid the influence of atmospheric, topographical and other errors as much as possible, and give priority to areas with high coherence and less atmospheric disturbance.

[0042] S20: Based on the interference phase image sequence formed by the interference phase images at N different moments, each reference point in the M reference points is used as a reference reference point to obtain M*(M-1) / 2 baseline velocities about the M reference points.

[0043] In this embodiment, any one of the multiple reference points is used as the reference point, and the speed of the reference point is 0. Compared with a single-connected network in which a single reference point is only used to refer to a fixed reference point, multiple reference points are used to estimate the baseline speed between any two pixels (forming a fully connected network). In this case, there are more redundant observations.

[0044] S30: Perform unconstrained joint adjustment processing on the M*(M-1) / 2 baseline velocities to obtain the deformation velocity of the target area.

[0045] In this embodiment, the error caused by a single reference point is eliminated by performing a joint adjustment process on the baseline velocity corresponding to each reference point. In the case where a high-resolution continuous velocity map is not required (for example, for various geophysical modeling purposes), this method can improve the overall accuracy of the deformation velocity by calculating discrete velocity samples, thereby improving the overall accuracy of the modeling process.

[0046] refer to Figure 1 , which is a performance comparison of the simulation results of the SRM method and the Multi-Reference Baseline (MRB) method in different situations. The first column shows the geometric distribution of the reference points in different scenarios; the second column shows the simulation results when the unwrapping error level is 0.5 and the Gaussian noise level varies; the third column shows the simulation results when the Gaussian noise standard deviation is fixed at 1.0 mm and the unwrapping error level varies.

[0047] refer to Figure 2 , which shows the performance of SRM method and MRB method in fault slip inversion.

[0048] in, Figure 2 a1 and a2 in the figure show the different processing strategies of the two algorithms; Figure 2 b1, b2, and b3 in the figure show the real (simulated) velocity and the deformation velocity generated by the two algorithms, respectively; Figure 2 c1 and c2 in the figure compare the difference between the deformation rate obtained by the two algorithms and the real (simulated) speed; Figure 2 Figures d1, d2, d3 and d4 respectively show the fault slip distribution model, the slip distribution inversion results based on the true (simulated) velocity, the slip distribution inversion results based on the SRM method velocity, and the slip distribution inversion results based on the MRB method velocity.

[0049] As a verification of the scheme of this embodiment, this study selected the Haiyuan fault zone (a typical left-lateral strike-slip fault) on the northeastern edge of the Qinghai-Tibet Plateau, and verified the superiority of the MRB method under different conditions by comparing the velocity results of the MRB method with those of the traditional SRM method.

[0050] refer to Figure 3 , showing the comparison of InSAR and GNSS velocities in the Haiyuan fault zone area.

[0051] in, Figure 3 (a) and Figure 3 (b) shows the line-of-sight (LOS) velocity maps of the Haiyuan fault zone region obtained from the ascending and descending Sentinel-1A / B orbits. The cyan circles indicate the locations of the GNSS stations. Figure 3 (c) in the figure is the comparison between the speed obtained using the SRM algorithm and the GNSS speed. Figure 3 (d) shows the comparison of the velocity obtained using the MRB method with the GNSS velocity. The green dots represent individual data points, and the regression line (pink) shows the general trend of the InSAR velocity relative to the GNSS-derived velocity.

[0052] pass Figure 2 , Figure 3 and Figure 4 The simulation test results show that under noisy conditions and complex disentanglement scenarios, the MRB method reduces the root mean square error (RMSE) by 45% ( Figure 2 In addition to improving the accuracy of deformation velocity, the MRB method also reduces the uncertainty of slip distribution estimation through redundant observations of multiple baselines, thereby enhancing its effectiveness in geophysical inversion (such as fault slip inversion) ( Figure 2 In the simulation, the MRB method improves the slip inversion accuracy by 21% compared with the SRM method, and effectively corrects the erroneous slip area introduced by the SRM method ( Figure 2 In the actual data application of the Haiyuan fault zone, the MRB method further verified its effectiveness, achieving a 21% RMSE reduction compared with GNSS and InSAR speeds ( Figure 3 ). These results indicate that the MRB method provides higher accuracy and more reliable surface deformation measurements in complex geological environments.

[0053] In applications that do not require high-resolution continuous velocity maps, such as active fault monitoring and inversion, the MRB method can optimize computational efficiency by using sparse samples. In addition, the robust performance of the MRB method in low-coherence regions and complex disentanglement scenarios makes it an important tool in tectonic studies and disaster risk assessment. Integrating the MRB method with other geodetic data (such as GNSS) further enhances surface deformation modeling and the understanding of Earth dynamic processes.

[0054] based on Figure 1 A surface deformation velocity monitoring method shown in the figure calculates the velocity of multiple reference points in the interferometric phase diagram of the target area obtained at multiple different times, and jointly averages the baseline velocities of all reference points, thereby reducing the influence of the error of a single reference point on the deformation velocity calculation, so that the final deformation velocity result can be more stable, and the monitoring accuracy of the surface deformation velocity is significantly improved. Especially in applications that require the calculation of discrete velocity samples (such as earthquake intervals, fault slip, etc.), this method can provide more accurate deformation velocity results while ensuring calculation efficiency, thereby improving the accuracy of monitoring the surface deformation velocity.

[0055] When applying the surface deformation velocity monitoring method provided by the present invention, it is not necessary to Figure 1 The steps are executed in the order shown. The specific execution order of the steps can be determined according to needs, and the present invention does not limit this.

[0056] Optionally, a method of obtaining M*(M-1) / 2 baseline velocities about M reference points includes but is not limited to:

[0057] 1) Using the interference pattern stacking method, based on the interference phase pattern sequence composed of N interference phase patterns at different times, each reference point in the M reference points is used as a reference reference point to obtain M*(M-1) / 2 baseline velocities about the M reference points.

[0058] 2) Small Baseline Synthetic Aperture Radar Interferometry (SBAS) method:

[0059] The SBAS method monitors surface deformation by selecting multiple small baselines in the SAR image sequence (i.e., image pairing at adjacent time points). This method can better cope with the heterogeneity and complexity of the surface and provide more comprehensive monitoring results.

[0060] 3) Differential Interferometric Synthetic Aperture Radar (DInSAR) technology:

[0061] DInSAR technology analyzes surface deformation by comparing SAR images of the same area at two time points. This technology is suitable for monitoring the velocity of surface deformation over a large area and can identify ground displacement within a certain period of time within an area (pixel).

[0062] 4) PS-InSAR technology:

[0063] PS-InSAR estimates the surface deformation field by interferometry of multiple Single Look Complex (SLC) images and Ground Control Points (GCP). This technology provides high sensitivity and stability, and is suitable for monitoring and analysis over a long period of time.

[0064] The solution shown in this embodiment adopts an interference phase image stacking method to calculate the baseline velocity of any reference point based on an interference phase image sequence composed of interference phase images at N different moments, and can accurately calculate the baseline velocity of each reference point in the interference phase image.

[0065] Optionally, based on an interference phase image sequence composed of N interference phase images at different times, when any one of the M reference points is used as the base reference point, M-1 baseline velocities based on a single reference point can be obtained, and the calculation formula is:

[0066]

[0067] in, is the acquisition time t of the i-th interference phase image i and the acquisition time t of the jth interference phase image j The phase of position p relative to the reference point r, B ⊥ is the vertical baseline, λ is the wavelength of the signal, θ is the incident angle, v pr is the estimated linear velocity, h pr is the estimated digital elevation model error, is the unmodeled noise.

[0068] In addition, in one or more embodiments of the present invention, based on the interference phase image sequence composed of N interference phase images at different times, each reference point in the M reference points is used as a reference reference point to obtain M*(M-1) / 2 baseline velocities about the M reference points, specifically including:

[0069] Based on an interference phase image sequence composed of N interference phase images at different moments, each reference point in the M reference points is used as a benchmark reference point to obtain M*(M-1) / 2 phase differences about the M reference points.

[0070] Based on the constant relationship between the phase difference and the baseline velocity, M*(M-1) / 2 baseline velocities are obtained.

[0071] Among them, the calculation formula of M*(M-1) / 2 phase differences is:

[0072]

[0073] in, is the acquisition time t of the i-th interference phase image i and the acquisition time t of the jth interference phase image j The phase difference between position p and position q, is the acquisition time t of the i-th interference phase image i and the acquisition time t of the jth interference phase image j The phase of position p relative to the reference point r, is the acquisition time t of the i-th interference phase image i and the acquisition time t of the jth interference phase image j The phase of position q relative to the reference point r, B⊥ is the vertical baseline, λ is the wavelength of the signal, θ is the incident angle, v pr is the linear velocity, h pr is the digital elevation model error, is the unmodeled noise.

[0074] Specifically, the expression for the constant relationship between the phase difference and the baseline velocity is:

[0075]

[0076] in, is the phase difference, V is the baseline velocity, T is the time interval, and λ is the radar wavelength.

[0077] In this embodiment, for n target pixels that need to be estimated in an interference phase image time series, there are a total of n*(n-1) / 2 baseline velocities.

[0078] This embodiment uses multiple reference points in the interference phase diagram as reference points to calculate the baseline velocity of each reference point. Compared with a single-connected network in which a single reference point is only used as a reference to a fixed reference point, this embodiment can estimate the baseline velocity between any two reference points through multiple reference points (forming a fully connected network).

[0079] In addition, in one or more embodiments of the present invention, an unconstrained joint adjustment process is performed on M*(M-1) / 2 baseline velocities, specifically including:

[0080] The unconstrained joint adjustment method is used to adjust the M*(M-1) / 2 baseline velocities respectively. The expression of the adjustment is:

[0081]

[0082] Where n is the number of reference points, L is the observation matrix, v1 is the velocity constraint, C is a constant, and v pq It refers to the deformation speed of position p relative to position q.

[0083] In this embodiment, the observation matrix L contains the baseline velocity estimates between n reference points (Formula (2)), and a velocity constraint (e.g., v1=0) is added. When there are no known reference points, the constraint can be set to an arbitrary value C, and only the baseline velocity (i.e., differential velocity) is estimated. The baseline velocity can be applied to inverse problems such as fault slip inversion as easily as the absolute velocity.

[0084] When there are known reference points (such as GNSS stations), the absolute velocity can be estimated. If only one reference point is introduced, the estimation is unconstrained and the introduced reference point will not affect the relative velocity between the two points. If multiple reference points are introduced, the estimation is constrained and the relative velocity between the two points will be constrained by the introduced reference points.

[0085] This embodiment combines redundant observations to perform unconstrained joint adjustment processing on M*(M-1) / 2 baseline velocities, and obtains deformation velocities corresponding to multiple reference points, that is, the deformation velocity of the target area, thereby achieving a more robust estimation of the surface deformation velocity and improving the accuracy and reliability of the estimation of the surface deformation velocity.

[0086] The above is a method for monitoring the speed of ground deformation provided by one or more embodiments of the present invention. Based on the same idea, the present invention also provides a corresponding device for monitoring the speed of ground deformation, such as Figure 5 As shown, including:

[0087] The first acquisition module is used to acquire the interference phase images of the target area at N different moments, and to set M reference points at corresponding positions of the interference phase images at the N different moments.

[0088] The second acquisition module is used to obtain M*(M-1) / 2 baseline velocities about the M reference points based on an interference phase image sequence composed of interference phase images at N different moments, taking each reference point of the M reference points as a reference reference point.

[0089] The processing module is used to perform unconstrained joint adjustment processing on M*(M-1) / 2 baseline velocities to obtain the deformation velocity of the target area.

[0090] For the specific definition of a surface deformation velocity monitoring device, please refer to the definition of a surface deformation velocity monitoring method mentioned above, which will not be repeated here. Each module in the surface deformation velocity monitoring device can be implemented in whole or in part by software, hardware and a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute the operations corresponding to each of the above modules.

[0091] The present invention also provides a computer-readable storage medium, which stores a computer program, which can be used to execute the Figure 1 A method for monitoring surface deformation velocity is provided.

[0092] The present invention also provides Figure 6 The structural diagram of the computer device shown in FIG. Figure 6As shown, at the hardware level, the computer device includes a processor, an internal bus, a network interface, a memory, and a non-volatile memory, and may also include other hardware required for the business. The processor reads the corresponding computer program from the non-volatile memory into the memory and then runs it to implement the Figure 1 A method for monitoring surface deformation velocity is provided.

[0093] Those skilled in the art can understand that all or part of the processes in the embodiment method can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided by the present invention can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory or optical memory, etc. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0094] The technical features of the above embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of the present invention.

Claims

1. A method for monitoring ground surface deformation velocity, characterized in that: include: Obtaining interference phase images of the target area at N different times, and setting M reference points at corresponding positions of the interference phase images at the N different times; Based on the interference phase image sequence formed by the N interference phase images at different times, each reference point in the M reference points is used as a reference reference point to obtain M*(M-1) / 2 baseline velocities about the M reference points; The M*(M-1) / 2 baseline velocities are subjected to unconstrained joint adjustment processing to obtain the deformation velocity of the target area.

2. A method for monitoring ground surface deformation velocity according to claim 1, characterized in that: Based on the interference phase image sequence formed by the N interference phase images at different times, each reference point in the M reference points is used as a reference reference point to obtain M*(M-1) / 2 baseline velocities about the M reference points, specifically including: Based on the interference phase image sequence formed by the N interference phase images at different times, each reference point in the M reference points is used as a reference reference point to obtain M*(M-1) / 2 phase differences about the M reference points; Based on the constant relationship between the phase difference and the baseline velocity, the M*(M-1) / 2 baseline velocities are obtained; The calculation formula of the M*(M-1) / 2 phase differences is: in, is the acquisition time t of the i-th interference phase image i and the acquisition time t of the jth interference phase image j The phase difference between position p and position q, is the acquisition time t of the i-th interference phase image i and the acquisition time t of the jth interference phase image j The phase of position p relative to the reference point r, is the acquisition time t of the i-th interference phase image i and the acquisition time t of the jth interference phase image j The phase of position q relative to the reference point r, B ⊥ is the vertical baseline, λ is the wavelength of the signal, θ is the incident angle, v pr is the linear velocity, h pr is the digital elevation model error, is the unmodeled noise.

3. A method for monitoring ground surface deformation velocity according to claim 1, characterized in that: The M*(M-1) / 2 baseline velocities are subjected to unconstrained joint adjustment processing, specifically including: The M*(M-1) / 2 baseline velocities are adjusted respectively using an unconstrained joint adjustment method. The expression of the adjustment is: Where n is the number of reference points, L is the observation matrix, v1 is the velocity constraint, C is a constant, and v pq It refers to the deformation speed of position p relative to position q.

4. A surface deformation velocity monitoring device, characterized in that: include: A first acquisition module is used to acquire the interference phase images of the target area at N different moments, and to set M reference points at corresponding positions of the interference phase images at the N different moments; A second acquisition module is used to obtain M*(M-1) / 2 baseline velocities about the M reference points by taking each of the M reference points as a reference reference point based on the interference phase image sequence formed by the N interference phase images at different times; The processing module is used to perform unconstrained joint adjustment processing on the M*(M-1) / 2 baseline velocities to obtain the deformation velocity of the target area.

5. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by a processor, a method for monitoring ground surface deformation velocity as claimed in any one of claims 1 to 4 is implemented.

6. A computer device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor. When the processor executes the program, a method for monitoring the velocity of surface deformation as claimed in any one of claims 1 to 3 is implemented.

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