Unmanned aerial vehicle SAR image data correction method and system

Abstract

The invention discloses an unmanned aerial vehicle SAR image data correction method and system, and relates to the technical field of data correction, and the method comprises the steps: obtaining the original echo data of an unmanned aerial vehicle SAR sensor, and the pose parameters outputted by an IMU / GNSS system in real time; on the basis of a pre-stored DEM function, a terrain elevation gradient vector is calculated through a finite difference method in combination with the position coordinates; constructing a topographic constraint matrix according to a topographic elevation gradient vector, and calculating a motion error vector fused with topographic features in combination with the pose parameters; performing phase correction on the original echo data based on the motion error vector to obtain compensated echo data; and according to the terrain elevation gradient vector, calculating a local incident angle correction amount, and according to the local incident angle correction amount, performing radiometric calibration on the compensated echo data to obtain a backscattering coefficient of radiometric correction. According to the invention, terrain-adaptive image data correction is realized, and the quality of the image data is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data correction, in particular to a UAV SAR image data correction method and system. BACKGROUND

[0002] With the rapid development of UAV technology, UAV-borne synthetic aperture radar (SAR) image data is increasingly widely used in topographic mapping, environmental monitoring, disaster assessment and other fields. However, due to the influence of various factors on the UAV during flight, such as changes in the attitude of the aircraft, terrain undulations, etc., the acquired SAR image data has geometric distortion and radiation inconsistency, which seriously affects the quality and application effect of the image data.

[0003] Existing UAV SAR image data correction methods mainly focus on motion compensation and radiation correction. Motion compensation methods compensate for motion errors during UAV flight to reduce image geometric distortion, while radiation correction methods correct the radiation characteristics of the image to improve the radiation consistency of the image. However, these methods are often handled independently and do not fully consider the influence of terrain undulations on image data, resulting in unsatisfactory correction results. SUMMARY

[0004] In view of the problem that the motion compensation method and the radiation correction method in the prior art consider only a single factor and do not fully consider the influence of terrain undulations on image data, resulting in unsatisfactory correction results, the present application provides a UAV SAR image data correction method and system, which introduces a terrain constraint matrix to integrate terrain features into the motion error compensation and radiation calibration process, achieving terrain-adaptive image data correction and improving the geometric accuracy and radiation consistency of the image data. The specific technical solutions are as follows: In a first aspect, the present application provides a UAV SAR image data correction method, comprising: acquiring the original echo data of a UAV-borne SAR sensor and the real-time output of an IMU / GNSS system, including position coordinates and attitude angles; based on a pre-stored DEM function, the terrain elevation gradient vector is calculated by finite difference method combined with the position coordinates; a terrain constraint matrix is constructed according to the terrain elevation gradient vector, and a motion error vector integrating terrain features is calculated combined with the attitude parameters; the original echo data is phase-corrected based on the motion error vector to obtain compensated echo data; the local incidence angle correction amount is calculated according to the terrain elevation gradient vector, and the compensated echo data is radiation-calibrated according to the local incidence angle correction amount to obtain the radiation-corrected backscatter coefficient.

[0005] Preferably, the DEM function is specifically a DEM function generated based on external LiDAR point cloud .

[0006] Preferably, the constructing a terrain constraint matrix according to the terrain elevation gradient vector and calculating a motion error vector fusing terrain features in combination with the pose parameter comprises: calculating a motion error vector fusing terrain features according to the terrain constraint matrix, in combination with the pose parameter, an error conversion matrix and a preset adaptive terrain curvature weight factor ; the specific calculation is as follows: In the formula, is an error conversion matrix; is a preset adaptive terrain curvature weight factor; is a terrain constraint matrix; is a transposed matrix; respectively represent the position error of the unmanned aerial vehicle in the x, y and z directions; respectively represent the roll angle deviation and the pitch angle deviation of the unmanned aerial vehicle.

[0007] Preferably, the terrain constraint matrix is represented as: In the formula, is a terrain sensitivity coefficient.

[0008] Preferably, the method for correcting unmanned aerial vehicle SAR image data further comprises: constraining the distance relationship between the target point and the unmanned aerial vehicle and the Doppler zero frequency condition through a range Doppler equation according to the compensated echo data and the pose parameter; jointly DEM elevation constraint, iteratively calculating the coordinates of the target point, and in each iteration, calculating the local geometric residual between the coordinates of the target point and the coordinates of the corresponding DEM elevation point; when the local geometric residual exceeds a preset residual threshold, adjusting and updating the terrain curvature weight factor and calculating a motion error vector fusing terrain features.

[0009] Preferably, the calculation formula of the adjusting and updating terrain curvature weight factor is: In the formula, is the terrain curvature weight factor before adjustment and update; is the terrain curvature weight factor after adjustment and update; is a feedback gain coefficient; is a local geometric residual; is a preset residual threshold; is a terrain elevation gradient vector.

[0010] Preferably, the UAV SAR image data correction method further comprises: When the local geometric residual exceeds a preset residual threshold, the backscatter coefficient of the corresponding pixel is marked as an invalid value.

[0011] Preferably, the compensated echo data is represented as: In the formula, represents the original echo data; represents the compensated echo data; is an imaginary unit; represents a phase and distance conversion coefficient.

[0012] Preferably, the radiation-corrected backscatter coefficient is represented as: wherein, , is a local incidence angle correction amount, is a terrain elevation gradient vector; is a radar line-of-sight direction.

[0013] In a second aspect, the present application also provides a UAV SAR image data correction system, which applies the aforementioned UAV SAR image data correction method, and comprises: a data acquisition module, configured to acquire original echo data of a UAV-borne SAR sensor and real-time output of a pose parameter of an IMU / GNSS system, the pose parameter including a position coordinate and an attitude angle; a terrain optimization calculation module, configured to calculate a terrain elevation gradient vector by a finite difference method based on a pre-stored DEM function in combination with the position coordinate; a motion error calculation module, configured to construct a terrain constraint matrix according to the terrain elevation gradient vector and calculate a motion error vector fused with terrain features in combination with the pose parameter; a phase correction module, configured to perform phase correction on the original echo data based on the motion error vector to obtain compensated echo data; a radiation calibration module, configured to calculate a local incidence angle correction amount according to the terrain elevation gradient vector and perform radiation calibration on the compensated echo data according to the local incidence angle correction amount to obtain a radiation-corrected backscatter coefficient.

[0014] Compared with the prior art, the present application has the following beneficial effects: The unmanned aerial vehicle SAR image data correction method of the present application compensates for the motion error in the flight process of the unmanned aerial vehicle by combining the terrain constraint matrix and the pose parameter, improves the geometric accuracy of the image, calculates the local incidence angle correction amount using the terrain elevation gradient vector, performs radiation calibration on the compensated echo data, improves the radiation consistency of the image, and enhances the comparability and application value of the image. The present application can adapt to image data correction under different terrain conditions, significantly improves the geometric accuracy and radiation consistency of the image data through the terrain adaptive correction strategy, and at the same time, the correction method fusing the terrain features reduces the complexity of data processing, improves the efficiency of data processing, and is helpful to quickly obtain high-quality SAR image data. BRIEF DESCRIPTION OF DRAWINGS

[0015] In order to more clearly illustrate the specific embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the specific embodiments or the prior art description will be briefly introduced below. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, each element or part is not necessarily drawn according to the actual proportion.

[0016] Figure 1 A flow chart of a UAV SAR image data correction method of the present application.

[0017] Figure 2 A principle diagram of a UAV SAR image data correction system of the present application. DETAILED DESCRIPTION

[0018] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0019] It should be understood that when used in the present specification, the terms "comprise" and "include" indicate the existence of the described features, integers, steps, operations, elements, and / or components, but do not exclude one or more other features, integers, steps, operations, elements, components, and / or sets thereof.

[0020] It should also be understood that the terms used in the present specification are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in the present specification and the appended claims, unless otherwise clearly indicated by the context, the singular forms "a", "an" and "the" are intended to include the plural forms.

[0021] It should be further understood that the term "and / or" used in the description of the present application means any combination of one or more of the associated listed items and all possible combinations, and includes these combinations.

[0022] The following embodiments refer to Figure 1 and Figure 2 .

[0023] The embodiments of the present application provide a UAV SAR image data correction method, comprising: Step S1, acquiring original echo data of a UAV-borne SAR sensor , and a real-time output pose parameter of an IMU / GNSS system, the pose parameter comprising a position coordinate and an attitude angle; When a UAV-borne synthetic aperture radar (SAR) sensor flies over a mountainous area along a preset flight route, the SAR sensor continuously emits electromagnetic waves and receives ground echoes, collects original echo data, and records the original echo data as a time sequence in a complex number form The original echo data includes scattering information of targets such as mountains and vegetation, and phase interference caused by UAV jitter. At the same time, the IMU / GNSS combined system of the fuselage outputs a pose parameter at a high frequency.

[0024] Through the real-time output six-degree-of-freedom parameter: the position coordinate includes three-dimensional coordinates in the UAV geodetic coordinate system ; the attitude angle includes a pitch angle, a roll angle and a yaw angle, denoted as .

[0025] Step S2, based on a pre-stored DEM function, a terrain elevation gradient vector is calculated by a finite difference method in combination with the position coordinate; The DEM function is specifically a DEM function generated based on external LiDAR point clouds . LiDAR is a laser radar technology that can accurately measure the three-dimensional coordinate information of the terrain surface. By processing and interpolating these discrete point cloud data, a continuous DEM function is generated, which provides high-precision terrain elevation information. Using the DEM function generated based on LiDAR point clouds, more accurate terrain elevation data helps to more accurately calculate the terrain elevation gradient vector, thereby enhancing the construction quality of the terrain constraint matrix and further improving the effect of motion error compensation and geometric correction.

[0026] The system calls the DEM function corresponding to the pre-stored mountainous area DEM data . For the ground area corresponding to the current position of the UAV, the terrain gradient is calculated by the finite difference method; the specific calculation is as follows: Wherein, the elevation is directly determined by the DEM function: By Provide absolute height information, for the constraint of the target point elevation, correction due to terrain caused by SAR geometric distortion.

[0027] DEM function partial derivative calculation using DEM function Calculate the first-order partial derivative: Where: , respectively represent the rate of change of the slope of the terrain x direction, y direction; DEM grid X direction resolution; DEM grid Y direction resolution.

[0028] Constructing terrain elevation gradient vector: Provide terrain rate information, for judging the steepness of the terrain, guiding the motion error compensation, radiation correction parameter adaptive adjustment.

[0029] Step S3, according to the terrain elevation gradient vector, construct the terrain constraint matrix, and combine the pose parameters to calculate the motion error vector of the fusion terrain characteristics; specifically including: According to the terrain constraint matrix, combined with the pose parameters, error conversion matrix and pre-set adaptive terrain curvature weight factor, calculate the motion error vector of the fusion terrain characteristics ; The specific calculation is as follows: In the formula, is the error conversion matrix; is the pre-set adaptive terrain curvature weight factor; is the terrain constraint matrix; is the transpose matrix; respectively represent the position error of the unmanned aerial vehicle in x, y and z direction; respectively are the roll angle deviation, pitch angle deviation of the unmanned aerial vehicle.

[0030] It should be noted that the yaw angle has been implicitly compensated by the zero Doppler condition Influence, yaw error is absorbed by the geometric correction step, which makes the calculation amount reduced in the case of almost unchanged calculation result of the motion error vector.

[0031] The motion error vector fused with the terrain features is calculated by the above method, and various influencing factors are fully considered, including terrain constraints, pose changes, and terrain curvature, so that the calculated motion error vector is more accurate. This helps to improve the accuracy of phase correction, better compensates for the motion error of the unmanned aerial vehicle under complex terrain conditions, further improves the geometric correction accuracy of SAR image data, and reduces the image distortion problem caused by inaccurate error compensation.

[0032] The terrain constraint matrix is represented as: In the formula, is a terrain sensitivity coefficient. , respectively represent the bending degree of the terrain in the x direction and the y direction.

[0033] The terrain sensitivity coefficient is used to adjust the influence of the terrain elevation gradient on the motion error compensation, and its value range is between [0.1, 0.5]. By reasonably setting the coefficient, for example, setting flat terrain =0.1, hilly terrain =0.3, and mountainous terrain =0.5, the effect of the terrain constraint matrix on the motion error compensation can be flexibly adjusted according to the complexity of the actual terrain and application requirements, thereby realizing adaptive correction for different terrain conditions. By introducing the terrain sensitivity coefficient, in areas with large terrain undulations or high terrain sensitivity requirements, the coefficient can be appropriately increased to enhance the influence of terrain constraints on motion error compensation and improve correction accuracy; in areas with relatively flat terrain or low terrain sensitivity requirements, the coefficient can be reduced to avoid overemphasizing terrain factors and introducing other unnecessary errors. The flexible adjustment method helps to achieve fine correction for various complex terrain conditions.

[0034] Step S4, phase correction of the original echo data based on the motion error vector to obtain compensated echo data; The compensated echo data is represented as: In the formula, represents the original echo data; represents the compensated echo data; is an imaginary unit; represents a phase-to-distance conversion coefficient.

[0035] Based on the calculated motion error vector, the original echo data is phase-corrected to realize phase adjustment of the echo signal, eliminate phase deviation caused by the motion error of the unmanned aerial vehicle, and thus obtain compensated echo data, improving the geometric positioning accuracy of the data.

[0036] Step S5, according to the terrain elevation gradient vector, a local incidence angle correction amount is calculated, and the compensated echo data is radiometrically scaled according to the local incidence angle correction amount to obtain a radiation-corrected backscattering coefficient.

[0037] The radiation-corrected backscattering coefficient is expressed as: wherein, is a scaling constant; , is a local incidence angle correction amount, is a terrain elevation gradient vector; is a radar initial incidence angle; is a radar line-of-sight direction.

[0038] The incidence angle is the angle between the radar beam and the terrain surface, and the local incidence angle correction amount is used to compensate for the difference between the actual incidence angle and the assumed incidence angle caused by the terrain undulation. Through the radiometric scaling based on the local incidence angle correction amount, the radiation consistency of the SAR image data can be improved. The corrected backscattering coefficient accurately reflects the actual physical characteristics of the target region, and eliminates the problems such as image brightness difference caused by radiation error.

[0039] The UAV SAR image data correction method of the present application compensates for the motion error in the flight process of the UAV by combining the terrain constraint matrix and the pose parameters, improves the geometric accuracy of the image; uses the terrain elevation gradient vector to calculate the local incidence angle correction amount, and performs radiometric scaling on the compensated echo data, improves the radiation consistency of the image, and enhances the comparability and application value of the image. The present application can adapt to image data correction under different terrain conditions, and through the terrain-adaptive correction strategy, the geometric accuracy and radiation consistency of the image data are significantly improved; at the same time, the correction method fusing the terrain features reduces the complexity of data processing and improves the efficiency of data processing, which is helpful for quickly obtaining high-quality SAR image data.

[0040] Specifically, in one preferred embodiment, a UAV SAR image data correction method further comprises: According to the compensated echo data and the pose parameters, the distance relationship between the target point and the UAV and the Doppler zero frequency condition are constrained through the range-Doppler equation; combined with the DEM elevation constraint, the coordinates of the target point are iteratively calculated, and in each iteration, the local geometric residual between the coordinates of the target point and the coordinates of the corresponding elevation point of the DEM is calculated. From the motion compensation, a phase-corrected echo signal is obtained Through pulse compression and time delay measurement, the slant range is extracted ; meanwhile, the instantaneous velocity vector of UAV is calculated from the pose parameters, and let the velocity vector of UAV be .

[0041] The distance equation is a spherical surface with the position of UAV as the center and the distance as the radius, which describes the possible spatial distribution of the target; the zero Doppler plane is a plane with the velocity vector as the normal vector, which constrains the target to be located at the center of the radar beam. Let the coordinates of the target point be , and the equation group is established: The following is the solving process of the equation group: First step, linearize the distance equation: In the formula, let be the initial guess coordinates of the target point, ; be the initial guess distance.

[0042] Second step, linearize the distance equation and the zero Doppler equation: Third step, solve by least squares: In the formula, is the coefficient matrix; is the initial guess coordinates of the target point; is the observation vector; is the coordinate correction.

[0043] Through the above solving, the initial value coordinates of the target point DEM constraint iterative optimization iteration function: In the formula, is the coordinate of the nth iteration; is the terrain constraint weight.

[0044] Wherein, adapt to the terrain complexity: Through the following steps: Calculate the Jacobian matrix: Newton method update: Where, take the step size .

[0045] The coordinates are gradually corrected by iteratively solving J=0 until a convergence condition is met, and the convergence includes: (1) a position change threshold: ; (2) a residual threshold: .

[0046] The initial coordinates of the target point are solved by simultaneously solving two equations, so that the target point coordinates simultaneously satisfy the geometric positioning constraint and the terrain elevation constraint.

[0047] When the local geometric residual exceeds a preset residual threshold, the terrain curvature weight factor is adjusted and updated, and the motion error vector fusing the terrain feature is calculated.

[0048] The calculation formula for adjusting and updating the terrain curvature weight factor is: In the formula, is the terrain curvature weight factor before adjustment and update; is the terrain curvature weight factor after adjustment and update; is a feedback gain coefficient; is a local geometric residual; is a preset residual threshold; is a terrain elevation gradient vector.

[0049] In the embodiment, the compensated echo data and the pose parameters are used to constrain the distance relationship between the target point and the UAV and the Doppler zero frequency condition through the range-Doppler equation. The range-Doppler equation can establish the geometric relationship and kinematic relationship between the target point and the UAV. At the same time, the DEM elevation constraint is combined, and an iterative calculation method is used to determine the coordinates of the target point. In each iteration process, the local geometric residual between the coordinates of the target point and the coordinates of the corresponding elevation point of the DEM is calculated, which reflects the difference between the currently calculated target point coordinates and the actual terrain elevation. When the local geometric residual exceeds the preset residual threshold, it indicates that the current terrain curvature weight factor may not accurately reflect the influence of the actual terrain on the motion error, and the terrain curvature weight factor needs to be adjusted and updated, and the motion error vector fusing the terrain feature is recalculated to optimize the correction result.

[0050] In the above optimization scheme, a closed-loop feedback adjustment mechanism is constructed, the terrain curvature weight factor is adjusted in real time by monitoring the local geometric residual, the motion error compensation and geometric correction process can be dynamically optimized, the error accumulation and divergence caused by terrain changes or other factors can be corrected in time, the accuracy of geometric correction is further improved, and the positioning accuracy of the corrected SAR image data in the geographic coordinate system is ensured to match the actual terrain.

[0051] Specifically, in a preferred embodiment, the UAV SAR image data correction method further comprises: When the local geometric residual exceeds the preset residual threshold, the backscattering coefficient of the corresponding pixel is marked as an invalid value.

[0052] It should be noted that when the local geometric residual exceeds the preset residual threshold, in addition to adjusting the terrain curvature weight factor, the backscattering coefficient of the corresponding pixel is also marked as an invalid value. This is because in the case of a large local geometric residual, the geometric correction result at the pixel may not be accurate, which will affect the result of radiometric calibration. By marking the backscattering coefficient that may have a problem as an invalid value, the invalid value is removed or corrected, effectively avoiding the pollution of the radiation calibration error caused by the large local geometric residual to the entire SAR image data, and improving the accuracy of the radiation calibration result. Through the marking and processing of the invalid value, the backscattering coefficient obtained after the radiation correction can more truly reflect the physical characteristics of the target region.

[0053] In a second aspect, the present application also provides a UAV SAR image data correction system applying the above-mentioned UAV SAR image data correction method, comprising: a data acquisition module for acquiring original echo data of a UAV-borne SAR sensor and real-time output of a pose parameter of an IMU / GNSS system, the pose parameter including a position coordinate and an attitude angle; a terrain optimization calculation module for calculating a terrain elevation gradient vector based on a pre-stored DEM function and combining the position coordinate through a finite difference method; a motion error calculation module for constructing a terrain constraint matrix according to the terrain elevation gradient vector, and calculating a motion error vector fused with terrain features in combination with the pose parameter; a phase correction module for performing phase correction on the original echo data based on the motion error vector to obtain compensated echo data; a radiometric calibration module for calculating a local incidence angle correction amount according to the terrain elevation gradient vector, and performing radiometric calibration on the compensated echo data according to the local incidence angle correction amount to obtain a radiation-corrected backscattering coefficient.

[0054] The functions of the units in this embodiment are explained as in the xxxxx method, and the technical effects are the same, which will not be repeated here.

[0055] Those skilled in the art can appreciate that the units of the examples described in combination with the embodiments disclosed herein can be realized in electronic hardware, computer software or a combination of both. In order to clearly illustrate the interchangeability of hardware and software, the components of the examples have been described in general terms in the above description. Whether the functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. The skilled person can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0056] In the embodiments provided by the present application, it should be understood that the division of units is only a logical functional division, and there can be another division manner in actual implementation, for example, multiple units can be combined into one unit, one unit can be split into multiple units, or some features can be ignored, etc.

[0057] In addition, each functional unit in each embodiment of the present application can be integrated in one processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0058] When the integrated unit is realized in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application essentially or the part that contributes to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a number of instructions for causing a computer device (which can be a personal computer, a server or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: a U disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a mobile hard disk, a magnetic disk or an optical disk, and various media that can store program codes.

[0059] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the above embodiments, those skilled in the art should understand that: it can still modify the technical solutions recorded in the above embodiments, or make equivalent replacement for part or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application, and they should be covered in the scope of the description of the present application.

Claims

1. A method for correcting unmanned aerial vehicle (UAV) SAR image data, characterized in that, The method comprises: acquiring raw echo data of an unmanned aerial SAR sensor and real-time output of a pose parameter of an IMU / GNSS system, the pose parameter comprising a position coordinate and an attitude angle; calculating a terrain elevation gradient vector based on a pre-stored DEM function and in combination with the position coordinate by a finite difference method; constructing a terrain constraint matrix according to the terrain elevation gradient vector and calculating a motion error vector fused with terrain features in combination with the pose parameter; performing phase correction on the raw echo data based on the motion error vector to obtain compensated echo data; calculating a local incidence angle correction amount according to the terrain elevation gradient vector and performing radiometric calibration on the compensated echo data according to the local incidence angle correction amount to obtain a radiation-corrected backscatter coefficient.

2. The method of claim 1, wherein, The DEM function is specifically a DEM function generated based on external LiDAR point clouds .

3. The method of claim 1, wherein, The method of constructing the terrain constraint matrix according to the terrain elevation gradient vector and calculating the motion error vector fused with terrain features in combination with the pose parameter comprises: According to the terrain constraint matrix, a motion error vector fused with terrain features is calculated in combination with the pose parameters, an error conversion matrix, and a preset adaptive terrain curvature weight factor ; the specific calculation is as follows: In the formula, is an error conversion matrix; is a preset adaptive terrain curvature weight factor; is a terrain constraint matrix; is a transpose matrix; respectively represent the position errors of the unmanned aerial vehicle in the x, y and z directions; respectively represent the roll angle deviation and the pitch angle deviation of the unmanned aerial vehicle.

4. The method of claim 3, wherein, The terrain constraint matrix is expressed as: In the formula, is the terrain sensitivity coefficient.

5. The method of claim 3, wherein, The method further comprises: restricting a distance relationship between a target point and the unmanned aerial vehicle and a Doppler zero frequency condition by a range-Doppler equation according to the compensated echo data and the pose parameter; iteratively calculating a coordinate of the target point in combination with DEM elevation constraint, and in each iteration, calculating a local geometric residual error between the coordinate of the target point and a coordinate of a corresponding elevation point of the DEM; when the local geometric residual error exceeds a preset residual error threshold, adjusting and updating a terrain curvature weight factor and calculating the motion error vector fused with terrain features.

6. The method of claim 5, wherein, The calculation formula of the terrain curvature weight factor is: wherein, is an adjusted terrain curvature weight factor before update; is an adjusted terrain curvature weight factor after update; is a feedback gain coefficient; is a local geometric residual; is a preset residual threshold; is a terrain elevation gradient vector.

7. The method of claim 5, wherein, The method further comprises: when the local geometric residual error exceeds the preset residual error threshold, marking a backscatter coefficient of a corresponding pixel as an invalid value.

8. The method of claim 3, wherein, The compensated echo data is expressed as: In the formula, represents the original echo data; represents the compensated echo data; is an imaginary unit; represents a conversion coefficient of phase and distance.

9. The method of claim 1, wherein, The radiation-corrected backscatter coefficient is represented as: wherein, , is a local incidence angle correction, is a terrain elevation gradient vector; is a radar line of sight direction. 10.A system for UAV SAR image data correction, characterized in that, The method comprises: a data acquisition module configured to acquire raw echo data of an unmanned aerial SAR sensor and real-time output of a pose parameter of an IMU / GNSS system, the pose parameter comprising a position coordinate and an attitude angle; a terrain optimization calculation module configured to calculate a terrain elevation gradient vector based on a pre-stored DEM function and in combination with the position coordinate by a finite difference method; a motion error calculation module configured to construct a terrain constraint matrix according to the terrain elevation gradient vector and calculate a motion error vector fused with terrain features in combination with the pose parameter; a phase correction module configured to perform phase correction on the raw echo data based on the motion error vector to obtain compensated echo data; a radiometric calibration module configured to calculate a local incidence angle correction amount according to the terrain elevation gradient vector and perform radiometric calibration on the compensated echo data according to the local incidence angle correction amount to obtain a radiation-corrected backscatter coefficient.

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