Optimal Scene Coordinate System Establishment Method for Fast Temporal Imaging of Medium- and High-Orbit SAR

Abstract

This invention provides an optimal scene coordinate system establishment method for rapid temporal imaging using medium- and high-orbit SAR, relating to the field of radar imaging technology. Specifically, this invention first proposes four methods for establishing the scene coordinate system under large squint mode. By analyzing the characteristics of spectral compression performance and spectral tilt distribution under different coordinate systems, a maximizing scene coordinate system suitable for large-scene imaging is derived. This coordinate system maximizes the mapping bandwidth of a single processing operation, thereby improving imaging efficiency. Furthermore, this invention provides a method for selecting the scene coordinate system under different imaging conditions. By determining whether the scene is regular and whether the scene area is smaller than a preset size, a suitable scene coordinate system is selected to meet the imaging requirements of medium- and high-orbit SAR under large squint mode and reduce the computation of redundant data.

Description

Technical Field

[0001] This invention relates to the field of radar imaging technology, and in particular to a method for establishing an optimal scene coordinate system for rapid time-domain imaging of medium- and high-orbit SAR. Background Technology

[0002] Medium- and high-orbit synthetic aperture radar (SAR) has become a research hotspot in the field of SAR imaging due to its ultra-wide observation swath and excellent continuous observation capability. It plays a crucial role in earthquake disaster early warning, flood disaster observation, biomass monitoring, maritime target detection, and agricultural and forestry surveys. However, the complex observation geometry and ultra-wide imaging swath of medium- and high-orbit SAR present significant challenges in focusing images in the large-slant-view mode. Furthermore, in the large-slant-view mode, the ground sidelobe directions of the point response function do not satisfy the orthogonality requirement. Therefore, it is necessary to determine a scene coordinate system suitable for medium- and high-orbit SAR in the large-slant-view mode.

[0003] Currently, the method for establishing the scene coordinate system is based on the front-side view imaging mode, with the premise that the azimuth and range sidelobes of the point response function on the ground plane are orthogonal. One coordinate axis of the scene coordinate system is aligned with the satellite beam direction. Utilizing the orthogonality of the coordinate system, the direction of the other axis of the scene coordinate system is obtained according to the right-hand rule.

[0004] However, existing scene coordinate systems are primarily suitable for front-side-view imaging modes, where the sidelobe directions of the point response function on the ground plane are orthogonal. But in the large-angle-view imaging mode of medium- and high-orbit SAR, the radar beam observes the target at a large angle. Due to geometric deformation and terrain effects, the sidelobe directions of the point response function on the ground plane are no longer orthogonal. Therefore, the scene coordinate system establishment method used in front-side-view imaging modes is no longer suitable and cannot meet the imaging requirements of medium- and high-orbit SAR in this mode. Furthermore, the mapping bandwidth for imaging processing under the scene coordinate system suitable for front-side-view imaging modes is limited, resulting in low imaging processing efficiency. Summary of the Invention

[0005] The purpose of this invention is to provide an optimal scene coordinate system establishment method for fast temporal imaging of medium- and high-orbit SAR, which solves the problems of not being able to meet the imaging requirements of medium- and high-orbit SAR in large oblique-view imaging mode and the low efficiency of imaging processing.

[0006] To address the aforementioned technical problems, the embodiments of the present invention provide the following technical solutions:

[0007] The first aspect of this invention provides a method for establishing an optimal scene coordinate system for rapid temporal imaging using medium- and high-orbit SAR, the method comprising:

[0008] In the azimuth sidelobe reference coordinate system, the range sidelobe reference coordinate system, and the range-azimuth two-dimensional reference coordinate system, the spectral compression result map and spectral tilt distribution of the corresponding multiple point targets are determined respectively;

[0009] Based on the spectral compression results and the spectral tilt distribution, the condition for maximizing the imaging scene is determined to be that the spectral compression results are aligned with the center and the top and bottom, and the spectral tilt distribution is consistent along the v-axis of the coordinate system and symmetrical along the u-axis of the coordinate system.

[0010] By determining the gradient direction and orthogonal direction of the spectral tilt angle under the condition of maximizing the imaging scene, a maximizing scene coordinate system is established based on the gradient direction and orthogonal direction of the spectral tilt angle.

[0011] Determine whether the angle between the u-axis of the coordinate system and the beam movement direction is less than a preset angle;

[0012] If the angle between the u-axis of the coordinate system and the beam movement direction is not less than the preset angle, then the beam scanning consistent coordinate system is selected for imaging;

[0013] If the angle between the u-axis of the coordinate system and the beam movement direction is less than the preset angle, then determine whether the size of the scene area is greater than the preset size;

[0014] If the size of the scene area is larger than the preset size, then the scene coordinate system is maximized for imaging.

[0015] If the size of the scene area is not larger than the preset size, then the azimuth sidelobe reference coordinate system is selected for imaging.

[0016] In some modified embodiments of the first aspect of the present invention, before determining the spectral compression result map and spectral tilt distribution of the corresponding multiple point targets in the azimuth sidelobe reference coordinate system, the range sidelobe reference coordinate system, and the range-azimuth two-dimensional reference coordinate system, the method further includes:

[0017] Set the basis vector of the u-axis of the azimuth sidelobe reference coordinate system to be consistent with the azimuth sidelobe direction of the point response function on the ground plane;

[0018] The direction orthogonal to the basis vector direction of the u-axis of the azimuth sidelobe reference coordinate system is determined as the basis vector of the v-axis of the azimuth sidelobe reference coordinate system, so as to establish the azimuth sidelobe reference coordinate system.

[0019] In some modified embodiments of the first aspect of the present invention, before determining the spectral compression result map and spectral tilt distribution of the corresponding multiple point targets in the azimuth sidelobe reference coordinate system, the range sidelobe reference coordinate system, and the range-azimuth two-dimensional reference coordinate system, the method further includes:

[0020] Set the basis vector of the v-axis of the sidelobe reference coordinate system to be consistent with the distance of the point response function on the ground plane in the direction of the sidelobe;

[0021] The direction orthogonal to the direction of the basis vector of the v-axis of the range sidelobe reference coordinate system is determined as the basis vector of the u-axis of the range sidelobe reference coordinate system, so as to establish the range sidelobe reference coordinate system.

[0022] In some modified embodiments of the first aspect of the present invention, before determining the spectral compression result map and spectral tilt distribution of the corresponding multiple point targets in the azimuth sidelobe reference coordinate system, the range sidelobe reference coordinate system, and the range-azimuth two-dimensional reference coordinate system, the method further includes:

[0023] Set the basis vector of the u-axis of the two-dimensional reference coordinate system of range and azimuth to be consistent with the azimuth sidelobe direction of the point response function on the ground plane;

[0024] The basis vector of the v-axis of the two-dimensional reference coordinate system of range and azimuth is set to be consistent with the distance sidelobe direction of the point response function on the ground plane to establish the two-dimensional reference coordinate system of range and azimuth.

[0025] In some modified embodiments of the first aspect of the present invention, before determining the spectral compression result map and spectral tilt distribution of the corresponding multiple point targets in the azimuth sidelobe reference coordinate system, the range sidelobe reference coordinate system, and the range-azimuth two-dimensional reference coordinate system, the method further includes:

[0026] Set the u-axis of the beam scanning coordinate system to be in the same direction as the beam footprint movement.

[0027] The v-axis direction of the beam scanning coherent coordinate system is set to the direction of the beam projection on the ground plane to establish the beam scanning coherent coordinate system.

[0028] In some modified embodiments of the first aspect of the present invention, the spectral compression result map and spectral tilt distribution of the corresponding multiple point targets are determined in the azimuth sidelobe reference coordinate system, the range sidelobe reference coordinate system, and the range-azimuth two-dimensional reference coordinate system, respectively, including:

[0029] Determine the reference coordinate system for the azimuth sidelobe, the reference coordinate system for the range sidelobe, and the two-dimensional reference coordinate system for both range and azimuth. See the spectral compression results in the same range direction but different azimuth directions.

[0030] Determine the azimuth sidelobe reference coordinate system, the range sidelobe reference coordinate system, and the range-azimuth two-dimensional reference coordinate system, and obtain spectral compression results in different azimuth and different range directions;

[0031] The spectral tilt distributions corresponding to the azimuth sidelobe reference coordinate system, the range sidelobe reference coordinate system, and the range-azimuth two-dimensional reference coordinate system were determined.

[0032] In some modified embodiments of the first aspect of the present invention, the azimuth sidelobe reference coordinate system, the range sidelobe reference coordinate system, and the range-azimuth two-dimensional reference coordinate system are determined, and the spectral compression result diagrams in the same range direction but different azimuth directions are respectively included:

[0033] Select multiple point targets within the scene area that are at the same distance but in different directions;

[0034] Multiple point targets with the same range but different azimuth directions are imaged in the azimuth sidelobe reference coordinate system, the range sidelobe reference coordinate system, and the range-azimuth two-dimensional reference coordinate system, and the spectral compression result map corresponding to each scene coordinate system is determined.

[0035] In some modified embodiments of the first aspect of the present invention, the azimuth sidelobe reference coordinate system, the range sidelobe reference coordinate system, and the range-azimuth two-dimensional reference coordinate system are determined, and the spectral compression result diagrams in different azimuth directions and different range directions are respectively included:

[0036] Select multiple point targets within the scene area that are in different orientations and at different distances;

[0037] Multiple point targets with different azimuth and range directions are imaged in the azimuth sidelobe reference coordinate system, the range sidelobe reference coordinate system, and the range-azimuth two-dimensional reference coordinate system, and the spectral compression result map corresponding to each scene coordinate system is determined.

[0038] In some modified embodiments of the first aspect of the present invention, by determining the gradient direction and orthogonal direction based on the spectral tilt angle under the condition of maximizing the imaging scene, a coordinate system for maximizing the scene is established, including:

[0039] Based on the condition of maximizing the imaging scene, it is determined that the direction of the basis vector of the u-axis of the maximized scene coordinate system should be consistent with the gradient direction of the spectral tilt angle.

[0040] The direction orthogonal to the basis vector direction of the u-axis of the maximized scene coordinate system is determined as the basis vector direction of the v-axis of the maximized scene coordinate system, so as to establish the maximized scene coordinate system.

[0041] In some modified embodiments of the first aspect of the present invention, the basis vector of the u-axis of the azimuth sidelobe reference coordinate system is set to be consistent with the cross product direction of the satellite beam pointing and point response function in the ground tangent plane normal vector.

[0042] Compared to existing technologies, the optimal scene coordinate system establishment method for rapid time-domain imaging of medium- and high-orbit SAR provided by this invention determines the spectral compression result map and spectral tilt angle distribution of multiple point targets under the azimuth sidelobe reference coordinate system, the range sidelobe reference coordinate system, and the range-azimuth two-dimensional reference coordinate system, respectively. Based on each spectral compression result map and each spectral tilt angle distribution, the condition for maximizing the imaging scene is determined to be that the spectral compression result meets the requirements of center alignment and top-bottom alignment, and the spectral tilt angle distribution meets the conditions that the spectral tilt angle is consistent along the v-axis of the coordinate system and symmetrical along the u-axis of the coordinate system. Through the condition of maximizing the imaging scene, the spectrum is determined. The invention first proposes four methods for establishing a scene coordinate system in a large oblique view mode. By analyzing the spectral compression performance and spectral tilt distribution characteristics under different coordinate systems, a maximized scene coordinate system suitable for large scene imaging is derived. This coordinate system maximizes the mapping bandwidth of a single processing operation, thereby improving imaging efficiency. Furthermore, the invention provides methods for selecting the scene coordinate system under different imaging conditions. By determining whether the scene is regular and whether the scene area is smaller than the preset size, a suitable scene coordinate system is selected to meet the imaging requirements of medium- and high-orbit SAR under large oblique view and reduce the calculation of redundant data. Attached Figure Description

[0043] The above and other objects, features, and advantages of exemplary embodiments of the present invention will become readily apparent upon reading the following detailed description with reference to the accompanying drawings. In the drawings, several embodiments of the invention are illustrated by way of example and not limitation, with the same or corresponding reference numerals denoteing the same or corresponding parts, wherein:

[0044] Figure 1 The flowchart illustrates the process of establishing the optimal scene coordinate system for rapid temporal imaging using medium- and high-orbit SAR. Figure 1 ;

[0045] Figure 2 The flowchart illustrates the process of establishing the optimal scene coordinate system for rapid temporal imaging using medium- and high-orbit SAR. Figure 2 ;

[0046] Figure 3The diagram schematically illustrates the settings of four scene coordinate systems;

[0047] Figure 4 The diagram schematically illustrates the spectral compression of multiple point targets in the same range direction in the azimuth sidelobe reference coordinate system;

[0048] Figure 5 The diagram schematically illustrates the spectral compression of multiple point targets in the same range direction in the range sidelobe reference coordinate system;

[0049] Figure 6 The diagram schematically illustrates the spectral compression of multiple point targets in the same range direction in a two-dimensional reference coordinate system of range and azimuth.

[0050] Figure 7 The diagram schematically illustrates the spectral compression of multiple point targets in different azimuth and range directions in the azimuth sidelobe reference coordinate system.

[0051] Figure 8 The diagram schematically illustrates the spectral compression of multiple point targets in different azimuth and range directions in the range sidelobe reference coordinate system;

[0052] Figure 9 The diagram schematically illustrates the spectral compression of multiple point targets in different azimuth and range directions in a two-dimensional reference coordinate system of range and azimuth.

[0053] Figure 10 The spectrum tilt distribution is schematically shown in the azimuth sidelobe reference coordinate system, the range sidelobe reference coordinate system, and the range-azimuth two-dimensional reference coordinate system;

[0054] Figure 11 The diagram schematically illustrates the distribution of point targets in the scene coordinate system;

[0055] Figure 12 Three sub-block images at close, medium, and long distances are schematically shown;

[0056] Figure 13 The simulation results of point target P are shown schematically.

[0057] Figure 14 The simulation results of point target O are shown schematically.

[0058] Figure 15 The simulation results for the point target Q are shown schematically. Detailed Implementation

[0059] Exemplary embodiments of the invention will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the invention are shown in the drawings, it should be understood that the invention can be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the invention and to fully convey the scope of the invention to those skilled in the art.

[0060] It should be noted that, unless otherwise stated, the technical or scientific terms used in this invention should have the ordinary meaning as understood by one of ordinary skill in the art.

[0061] The existing method for establishing a scene coordinate system is based on the frontal side-view imaging mode, assuming that the azimuth and range sidelobes of the point response function on the ground plane are orthogonal. One axis of the scene coordinate system is aligned with the satellite beam direction, and the direction of the other axis is obtained using the right-hand rule, taking advantage of the orthogonality of the coordinate system. However, this invention considers that the scene coordinate system of the existing technology is mainly oriented towards frontal side-view imaging. In the large squint mode, the existing technology is no longer suitable, only applicable to simple geometric imaging, with a narrow range of applicability. In the case of large squint, the imaging processing swath width increases significantly, and the mapping bandwidth processed under the existing coordinate system is very limited, resulting in reduced processing efficiency. A method that can meet the imaging requirements of medium and high orbit SAR in the large squint imaging mode and has higher imaging processing efficiency is needed. This invention determines the spectral compression results and spectral tilt distributions of multiple point targets in the azimuth sidelobe reference coordinate system, the range sidelobe reference coordinate system, and the range-azimuth two-dimensional reference coordinate system, respectively. Based on each spectral compression result and each spectral tilt distribution, the condition for maximizing the imaging scene is determined as follows: the spectral compression result conforms to center alignment and top-bottom alignment, and the spectral tilt distribution conforms to the condition that the spectral tilt is consistent along the v-axis of the coordinate system and symmetrical along the u-axis of the coordinate system. Through the condition for maximizing the imaging scene, the gradient direction and orthogonal direction of the spectral tilt are determined, and based on the spectrum... The invention establishes a maximized scene coordinate system by considering the gradient direction and orthogonal direction of the tilt angle. It then determines whether the angle between the u-axis of the coordinate system and the beam movement direction is less than a preset angle. If the angle is not less than the preset angle, the beam scanning consistent coordinate system is selected for imaging. If the angle is less than the preset angle, the size of the scene region is determined to be greater than a preset size. If the size is greater than the preset size, the maximized scene coordinate system is selected for imaging. If the size is not greater than the preset size, the azimuth sidelobe reference coordinate system is selected for imaging. Thus, this invention first proposes four methods for establishing a scene coordinate system in a large squint mode. By analyzing the spectral compression performance and spectral tilt angle distribution characteristics under different coordinate systems, a maximized scene coordinate system suitable for large scene imaging is derived. This coordinate system maximizes the mapping bandwidth of a single processing, thereby improving imaging efficiency. Furthermore, this invention provides a method for selecting the scene coordinate system under different imaging conditions. By determining whether the scene is regular and whether the scene region is smaller than a preset size, a suitable scene coordinate system is selected to meet the imaging requirements of medium- and high-orbit SAR under large squint conditions and reduce the computation of redundant data.

[0062] The main idea of ​​this invention is to first propose four methods for establishing the scene coordinate system under large oblique view mode. By analyzing the characteristics of spectral compression performance and spectral tilt distribution under different coordinate systems, a maximizing scene coordinate system suitable for large scene imaging is derived. This coordinate system maximizes the mapping bandwidth of a single processing, thereby improving imaging efficiency. Furthermore, this invention provides a method for selecting the scene coordinate system under different imaging conditions. By determining whether the scene is regular and whether the scene area is smaller than a preset size, a suitable scene coordinate system is selected to meet the imaging requirements of medium- and high-orbit SAR under large oblique view, reducing the computation of redundant data.

[0063] The methods described in the embodiments of the present invention will be explained in detail below.

[0064] Figure 1 A flowchart illustrating an optimal scene coordinate system establishment method for rapid temporal imaging using medium-to-high orbit SAR in an embodiment of the present invention is shown schematically. See [link to flowchart illustration]. Figure 1 As shown, the method may include:

[0065] S101. Under the azimuth sidelobe reference coordinate system, the range sidelobe reference coordinate system, and the range-azimuth two-dimensional reference coordinate system, determine the spectral compression result map and spectral tilt distribution of the corresponding multiple point targets respectively.

[0066] S102. Based on the spectral compression results and the spectral tilt distribution, the condition for maximizing the imaging scene is determined to be that the spectral compression results are aligned with the center and the top and bottom, and the spectral tilt distribution is consistent along the v-axis of the coordinate system and symmetrical along the u-axis of the coordinate system.

[0067] Specifically, based on the spectral compression result diagrams and spectral tilt angle distributions determined in step S101, the condition for maximizing the imaging scene is that the spectral compression result conforms to the center alignment and top-bottom alignment, and the spectral tilt angle distribution conforms to the condition that the spectral tilt angles are distributed consistently along the v-axis of the coordinate system and symmetrically along the u-axis of the coordinate system.

[0068] Scene maximization refers to maximizing the scene in a single processing step. The conditions for maximizing the imaging scene in a single processing step are: the direction of the radar beam footprint movement is consistent with the u-axis of the scene coordinate system, and the scene area is relatively regular.

[0069] S103. Based on the conditions for maximizing the imaging scene, determine the gradient direction and orthogonal direction of the spectral tilt angle, and establish a maximized scene coordinate system according to the gradient direction and orthogonal direction of the spectral tilt angle.

[0070] Specifically, the spectral compression result determined by step S102 is a result that meets the requirements of center alignment and top and bottom alignment, and the spectral tilt angle distribution meets the condition of maximizing the imaging scene by ensuring that the spectral tilt angle is consistent along the v-axis of the coordinate system and symmetrical along the u-axis of the coordinate system. The gradient direction and orthogonal direction of the spectral tilt angle are determined, and a maximizing scene coordinate system is established based on the gradient direction and orthogonal direction of the spectral tilt angle.

[0071] Maximizing the scene coordinate system is the process that maximizes the scene coordinates in a single operation.

[0072] S104. Determine whether the angle between the u-axis of the coordinate system and the beam movement direction is less than the preset angle.

[0073] The preset angle can be 30°, or it can be any other value. There is no limitation on the preset angle here.

[0074] S105. If the angle between the u-axis of the coordinate system and the beam movement direction is not less than the preset angle, then select the beam scanning consistent coordinate system for imaging.

[0075] Specifically, it is determined whether the angle between the u-axis of the coordinate system and the beam movement direction is less than the preset angle. If not, the beam scanning consistent coordinate system is selected for imaging.

[0076] S106. If the angle between the u-axis of the coordinate system and the beam movement direction is less than the preset angle, then determine whether the size of the scene area is greater than the preset size.

[0077] Determine whether the angle between the coordinate system's u-axis and the beam movement direction is less than a preset angle. If so, determine whether the size of the scene area is greater than a preset size.

[0078] The preset size is 200km×200km. Specifically, it is determined whether the size of the scene area is greater than 200km×200km. If the size of the scene area is greater than 200km×200km, then step S107 is executed; if the size of the scene area is not greater than 200km×200km, then step S108 is executed.

[0079] S107. If the size of the scene area is larger than the preset size, then maximize the scene coordinate system for imaging.

[0080] Determine if the size of the scene area is larger than the preset size. If so, maximize the scene coordinate system for imaging.

[0081] S108. If the size of the scene area is not larger than the preset size, then select the azimuth sidelobe reference coordinate system for imaging.

[0082] The system determines whether the size of the scene region is larger than a preset size. If not, it selects the azimuth sidelobe reference coordinate system for imaging. In other words, if the size of the scene region is less than or equal to the preset size, the azimuth sidelobe reference coordinate system is selected for imaging.

[0083] Based on the above Figure 1 As can be seen from the implementation method, the embodiments of the present invention determine the spectral compression result map and spectral tilt angle distribution of multiple point targets in the azimuth sidelobe reference coordinate system, the range sidelobe reference coordinate system, and the range-azimuth two-dimensional reference coordinate system, respectively. Based on each spectral compression result map and each spectral tilt angle distribution, the condition for maximizing the imaging scene is determined to be that the spectral compression result meets the requirements of center alignment and top-bottom alignment, and the spectral tilt angle distribution meets the conditions that the spectral tilt angle is consistent along the v-axis of the coordinate system and symmetrical along the u-axis of the coordinate system. Through the condition for maximizing the imaging scene, the gradient direction and orthogonal direction of the spectral tilt angle are determined. Based on the gradient direction and orthogonal direction of the spectral tilt angle, a maximized scene coordinate system is established. It is then determined whether the angle between the u-axis of the coordinate system and the beam movement direction is less than a preset angle. If the angle is not less than the preset angle, the beam scanning consistency coordinate system is selected for imaging. If the angle is less than the preset angle, it is determined whether the size of the scene area is greater than a preset size. If the size is greater than the preset size, the maximized scene coordinate system is selected for imaging. If the size is not greater than the preset size, the azimuth sidelobe reference coordinate system is selected for imaging. Thus, this invention first proposes four methods for establishing a scene coordinate system in a large oblique-view mode. By analyzing the characteristics of spectral compression performance and spectral tilt angle distribution under different coordinate systems, a maximized scene coordinate system suitable for large-scene imaging is derived. This coordinate system maximizes the mapping bandwidth of a single processing, thereby improving imaging efficiency. Furthermore, this invention provides methods for selecting the scene coordinate system under different imaging conditions. By determining whether the scene is regular and whether the scene area is smaller than the preset size, a suitable scene coordinate system is selected to meet the imaging requirements of medium- and high-orbit SAR under large oblique view and reduce the calculation of redundant data.

[0084] As a refinement and extension of the above embodiments, it can be achieved through... Figure 2 The specific operations for establishing the optimal scene coordinate system for rapid temporal imaging of medium- and high-orbit SAR are illustrated. Figure 2 The flowchart of the optimal scene coordinate system establishment method for fast temporal imaging of medium- and high-orbit SAR in this embodiment of the invention. Figure 2 See Figure 2 As shown in the figure, the optimal scene coordinate system establishment method for fast temporal imaging of medium- and high-orbit SAR provided by the embodiments of the present invention may include:

[0085] S201. Set the basis vector of the u-axis of the azimuth sidelobe reference coordinate system to be consistent with the azimuth sidelobe direction of the point response function on the ground plane, and determine the direction orthogonal to the basis vector direction of the u-axis of the azimuth sidelobe reference coordinate system as the basis vector of the v-axis of the azimuth sidelobe reference coordinate system, so as to establish the azimuth sidelobe reference coordinate system.

[0086] The azimuth sidelobe reference coordinate system includes two coordinate axes, the u-axis and the v-axis, with the basis vectors corresponding to the two axes being respectively... and

[0087] Specifically, the u-axis of the azimuth sidelobe reference coordinate system is set to align with the azimuth sidelobe direction of the point response function on the ground plane. Based on the imaging geometry of the azimuth sidelobe direction of the point response function on the ground plane, the basis vector of the u-axis of the azimuth sidelobe reference coordinate system is... It is the direction of the cross product of the satellite beam pointing and the point response function's normal vector on the ground tangent plane; the basis vector of the v-axis of the azimuth sidelobe reference coordinate system. Based on the orthogonality of the two axes, it can be obtained by the right-hand rule, that is, the basis vector of the v-axis of the azimuth sidelobe reference coordinate system. The direction is orthogonal to the basis vector direction of the u-axis of the azimuth sidelobe reference coordinate system.

[0088] S202. Set the basis vector of the v-axis of the distance from the sidelobe reference coordinate system to be consistent with the distance of the point response function on the ground plane towards the sidelobe, and determine the direction orthogonal to the direction of the basis vector of the v-axis of the distance from the sidelobe reference coordinate system as the basis vector of the u-axis of the distance from the sidelobe reference coordinate system, so as to establish the distance from the sidelobe reference coordinate system.

[0089] The distance sidelobe reference coordinate system includes two coordinate axes, the u-axis and the v-axis, and the basis vectors corresponding to the two axes are respectively... and

[0090] Specifically, the basis vectors of the v-axis of the sidelobe reference coordinate system are... Since the distance of the point response function on the ground plane towards the sidelobe is set to be consistent, according to the imaging geometry relationship of the distance of the point response function on the ground plane towards the sidelobe, the basis vector of the v-axis of the sidelobe reference coordinate system is... It is the direction of the cross product of the satellite velocity component perpendicular to the satellite beam pointing and the point response function in the ground tangent plane; the basis vector of the u-axis of the sidelobe reference coordinate system. Based on the orthogonality of the two axes, it can be obtained by the right-hand rule, that is, the basis vector of the u-axis of the sidelobe reference coordinate system. The direction is orthogonal to the direction of the basis vector of the v-axis of the sidelobe reference coordinate system.

[0091] S203. Set the basis vector of the u-axis of the two-dimensional reference coordinate system of range and azimuth to be consistent with the azimuth sidelobe direction of the point response function on the ground plane, and set the basis vector of the v-axis of the two-dimensional reference coordinate system of range and azimuth to be consistent with the distance sidelobe direction of the point response function on the ground plane, so as to establish the two-dimensional reference coordinate system of range and azimuth.

[0092] Among them, the azimuth sidelobe reference coordinate system, the range sidelobe reference coordinate system, and the range-azimuth two-dimensional reference coordinate system are all used to image multiple point targets within a preset scene area.

[0093] The two-dimensional reference coordinate system for range and azimuth includes two coordinate axes, the u-axis and the v-axis, with the basis vectors corresponding to the two axes being respectively... and

[0094] S204. Set the u-axis of the beam scanning consistency coordinate system to the same direction as the direction of beam footprint movement, and set the v-axis of the beam scanning consistency coordinate system to the direction of beam projection on the ground plane, so as to establish the beam scanning consistency coordinate system.

[0095] Specifically, in oblique view mode, the sidelobe directions of the point response function on the ground plane are non-orthogonal, and the basis vectors of the range and azimuth two-dimensional reference coordinate system u-axis are... Set as the azimuth sidelobe direction of the point response function on the ground plane, i.e., the basis vector of the azimuth two-dimensional reference coordinate system u-axis. It is the direction of the cross product of the satellite beam pointing and the point response function's normal vector on the ground tangent plane; the basis vectors of the range and azimuth two-dimensional reference coordinate system v-axis. The point response function is set as the distance-to-side lobe direction on the ground plane, i.e., the basis vector of the v-axis of the two-dimensional reference coordinate system of distance and azimuth. It is the direction of the cross product of the satellite velocity component perpendicular to the satellite beam pointing and the normal vector of the point response function on the ground tangent plane. After establishing the above-mentioned azimuth sidelobe reference coordinate system, range sidelobe reference coordinate system, and range-azimuth two-dimensional reference coordinate system, a beam scanning consistency coordinate system, i.e., scene coordinate system 4, can also be established.

[0096] Establishing the scene coordinate system 4 specifically involves setting the u-axis of the beam-scanning-consistent coordinate system to the direction consistent with the direction of beam footprint movement, and setting the v-axis of the beam-scanning-consistent coordinate system to the direction of beam projection onto the ground plane. The advantage of this coordinate system is that the scene processing order is consistent with the SAR data collection order. The disadvantage is that the design principle of the coordinate system is incompatible with the beam support of the imaging geometry. Therefore, when considering the establishment of the optimal imaging coordinate system, the spectral compression performance and spectral spatial variation tilt distribution of this coordinate system are no longer analyzed.

[0097] Figure 3The diagram schematically illustrates the settings of four scene coordinate systems, where ρ represents the beam center direction, and V... S V represents the direction of satellite velocity. pr ρ is the velocity component of the satellite perpendicular to the beam center. pr e is the projection of the satellite beam pointing to ρ on the ground. n Let be the normal vector of the ground tangent plane. Figure 3 (a) shows the setup of the azimuth sidelobe reference coordinate system, and the basis vector of the u-axis of the azimuth sidelobe reference coordinate system. It is the direction of the cross product of the satellite beam pointing and the point response function's normal vector on the ground tangent plane; the basis vector of the v-axis of the azimuth sidelobe reference coordinate system. The direction is orthogonal to the basis vector direction of the u-axis of the azimuth sidelobe reference coordinate system. Figure 3 (b) shows the setup of the distance sidelobe reference coordinate system, including the basis vectors of the v-axis of the distance sidelobe reference coordinate system. It is the direction of the cross product of the satellite velocity component perpendicular to the satellite beam pointing and the point response function in the ground tangent plane; the basis vector of the u-axis of the sidelobe reference coordinate system. This is the direction orthogonal to the basis vector direction of the v-axis of the range sidelobe reference coordinate system. 3(c) shows the setup of the range-azimuth two-dimensional reference coordinate system, where the basis vector of the u-axis of the range-azimuth two-dimensional reference coordinate system is... It is the direction of the cross product of the satellite beam pointing and the point response function in the ground tangent plane normal vector; the basis vector of the v-axis of the range-azimuth two-dimensional reference coordinate system. It is the direction of the cross product of the satellite velocity component perpendicular to the satellite beam pointing and the normal vector of the point response function on the ground tangent plane. 3(d) shows the setting of the beam scanning consistency coordinate system, where the u-axis of the coordinate system is set to the same direction as the direction of the beam footprint movement, and the v-axis of the beam scanning consistency coordinate system is set to the direction of the beam projection on the ground plane.

[0098] S205. Under the azimuth sidelobe reference coordinate system, the range sidelobe reference coordinate system, and the range-azimuth two-dimensional reference coordinate system, determine the spectral compression result map and spectral tilt distribution of the corresponding multiple point targets respectively.

[0099] Specifically, under the azimuth sidelobe reference coordinate system, the range sidelobe reference coordinate system, and the range-azimuth two-dimensional reference coordinate system, the spectral compression results and spectral tilt distribution of multiple point targets are determined respectively, including:

[0100] Step A1: Determine the azimuth sidelobe reference coordinate system, the range sidelobe reference coordinate system, and the range-azimuth two-dimensional reference coordinate system, and obtain the spectral compression results in the same range direction but different azimuth directions.

[0101] As an optional implementation of this invention, an azimuth sidelobe reference coordinate system, a range sidelobe reference coordinate system, and a two-dimensional range-azimuth reference coordinate system are determined. Spectral compression result diagrams for the same range direction but different azimuth directions are shown, including:

[0102] Step A11: Select multiple point targets within the scene area that are at the same distance but in different directions;

[0103] Step A12: Image multiple point targets with the same range but different azimuth directions in the azimuth sidelobe reference coordinate system, the range sidelobe reference coordinate system, and the range-azimuth two-dimensional reference coordinate system, and determine the spectral compression result map corresponding to each scene coordinate system.

[0104] There can be up to 11 point targets, and the scene area can be 10km × 100km.

[0105] Specifically, under the condition of a 60° oblique angle of ground for medium- and high-orbit SAR, 11 point targets in the same range direction and different azimuth directions (11 point targets evenly distributed on the u axis) within a 10km×100km scene are selected. Imaging is performed in the azimuth sidelobe reference coordinate system, the range sidelobe reference coordinate system, and the range-azimuth two-dimensional reference coordinate system, and the spectral compression result map of the 11 point targets corresponding to each scene coordinate system is drawn.

[0106] Figure 4 The diagram schematically illustrates the spectral compression of multiple point targets in the same range direction within the azimuth sidelobe reference coordinate system. In other words, it represents the spectral compression of 11 point targets in the same range direction within a scene area of ​​10km × 100km, within the azimuth sidelobe reference coordinate system. Figure 4 (a) is the original spectrum. Figure 4 (b) is the two-dimensional wavenumber spectrum after the first step of compression. Figure 4 (c) shows the two-dimensional wavenumber spectrum after two-step compression. The horizontal axis of each figure represents the wavenumber domain vector k. u The vertical axis represents the wavenumber domain vector k. v ,from Figure 4 (b) It can be seen that, in the azimuth sidelobe reference coordinate system, after the first step of spectrum compression, the range of the wavenumber support region is uniformly moved to the center of the grid; from Figure 4 (c) It can be seen that after the second step of spectrum compression, the wavenumber support regions at different distance frequencies are aligned, which shows that the spectrum compression performance is good in the azimuth sidelobe reference coordinate system.

[0107] Figure 5The diagram schematically illustrates the spectral compression of multiple point targets in the same range direction within the range sidelobe reference coordinate system. Alternatively, it can be described as the spectral compression of 11 point targets in the same range direction within a scene area of ​​10km × 100km, within the range sidelobe reference coordinate system. Figure 5 (a) is the original spectrum. Figure 5 (b) is the two-dimensional wavenumber spectrum after the first step of compression. Figure 5 (c) shows the two-dimensional wavenumber spectrum after two-step compression. The horizontal axis of each figure represents the wavenumber domain vector k. u The vertical axis represents the wavenumber domain vector k. v ,from Figure 5 (a) It can be seen that, in the coordinate system of the sidelobe reference, the original spectrum exhibits a gridded appearance; from Figure 5 (b) It can be seen that after the first step of compression, the spectrum exhibits a severe skew; from Figure 5 (c) It can be seen that after the second step of compression, the spectrum has a high number of side lobes, which indicates that there are certain problems with the spectral compression in coordinate system 2.

[0108] Figure 6 The diagram schematically illustrates the spectral compression of multiple point targets in the same range direction within a two-dimensional range-azimuth reference coordinate system. Alternatively, it can be described as the spectral compression of 11 point targets in the same range direction but different azimuth directions within a 10km × 100km scene area, within a two-dimensional range-azimuth reference coordinate system. Figure 6 (a) is the original spectrum. Figure 6 (b) is the two-dimensional wavenumber spectrum after the first step of compression. Figure 6 (c) shows the two-dimensional wavenumber spectrum after two-step compression. From Figure 6 It can be seen that the spectral compression performance is almost identical to that of the azimuth reference coordinate system under the two-dimensional reference coordinate system of range and azimuth. It can effectively unify the wavenumber support region to the grid center and align the wavenumber support regions of different range frequencies. Therefore, the spectral compression performance under the two-dimensional reference coordinate system of range and azimuth is good.

[0109] Depend on Figures 4-6 The spectral compression results show that, without the two-step compression, the original spectrum is blurred in both dimensions, but the spectrum in the range sidelobe reference coordinate system is gridded. After the first step of compression, the spectra of point targets in different azimuth directions are aligned at the center frequency, but the spectrum in the range sidelobe reference coordinate system is severely tilted. After the two-step compression, the spectra of point targets in different azimuth directions are well aligned at all range frequencies, but the spectrum in the range sidelobe reference coordinate system shows high sidelobes, making the image blurry. In summary, from... Figures 4-6 It can be seen that the azimuth sidelobe reference coordinate system and the range-azimuth two-dimensional reference coordinate system have good spectral compression performance for the same range-direction point target.

[0110] Step A2: Determine the azimuth sidelobe reference coordinate system, the range sidelobe reference coordinate system, and the range-azimuth two-dimensional reference coordinate system, and obtain the spectral compression results in different azimuth and range directions.

[0111] As an optional implementation of this invention, an azimuth sidelobe reference coordinate system, a range sidelobe reference coordinate system, and a two-dimensional range-azimuth reference coordinate system are determined, and spectral compression result diagrams are obtained in different azimuth directions and different range directions, including:

[0112] Step A21: Select multiple point targets within the scene area that are in different orientations and at different distances;

[0113] Step A22: Image multiple point targets in different azimuth and range directions in the azimuth sidelobe reference coordinate system, the range sidelobe reference coordinate system, and the range-azimuth two-dimensional reference coordinate system, and determine the spectral compression result map corresponding to each scene coordinate system.

[0114] Multiple point targets can be 11×11 point targets, and the scene area can be 100km×100km.

[0115] Specifically, under the condition of a 60° oblique angle of ground for medium- and high-orbit SAR, 11×11 point targets (uniformly distributed on the v-axis and u-axis) in different azimuth and range directions within a 100km×100km scene are selected. Imaging is performed in the azimuth sidelobe reference coordinate system, the range sidelobe reference coordinate system, and the range-azimuth two-dimensional reference coordinate system, and the spectral compression result map of the 11×11 point targets corresponding to each scene coordinate system is drawn.

[0116] Figure 7 The diagram schematically illustrates the spectral compression of multiple point targets in different azimuth and range directions within the azimuth sidelobe reference coordinate system. In other words, when the scene area is 100km × 100km, the spectral compression of all 11 × 11 point targets in the scene is shown in coordinate system 1. Figure 7 (a) is the original spectrum. Figure 7 (b) is the two-dimensional wavenumber spectrum after the first step of compression. Figure 7 (c) shows the two-dimensional wavenumber spectrum after two-step compression. The horizontal axis in each figure represents the wavenumber domain vector k. u The vertical axis represents the wavenumber domain vector k. v ,from Figure 7 It can be seen that, under the azimuth sidelobe reference coordinate system, after the swath width is expanded from 10km to 100km, the spectral compression performance and Figure 4The processing results are almost identical, and the wavenumber support region can be well unified to the center of the grid and the wavenumber support regions at different distance frequencies can be aligned, indicating that the point target compression performance is similar at different distances. Therefore, it can be concluded that the spectral compression performance is good in the azimuth sidelobe reference coordinate system.

[0117] Figure 8 The diagram schematically illustrates the spectral compression of multiple point targets in different azimuth and range directions within the range sidelobe reference coordinate system. In other words, when the scene area is 100km × 100km, the spectral compression of all 11 × 11 point targets in the scene is shown in coordinate system 2. Figure 8 (a) is the original spectrum. Figure 8 (b) is the two-dimensional wavenumber spectrum after the first step of compression. Figure 8 (c) shows the two-dimensional wavenumber spectrum after two-step compression. The horizontal axis in each figure represents the wavenumber domain vector k. u The vertical axis represents the wavenumber domain vector k. v ,from Figure 8 It can be seen that, under the range sidelobe reference coordinate system, after the swath width is expanded from 10km to 100km, after the second compression step, the spectrum is poorly arranged when the range frequency deviates from the grid center, and even exceeds the azimuth-frequency range. Therefore, it can be concluded that the spectral compression performance under the range sidelobe reference coordinate system cannot meet the imaging requirements of medium and high orbits in the large oblique viewing mode.

[0118] Figure 9 This schematically illustrates the spectral compression diagrams of multiple point targets in different azimuth and range directions within a two-dimensional reference coordinate system. In other words, when the scene area is 100km × 100km, this represents the spectral compression diagrams of all 11 × 11 point targets in the scene within a two-dimensional reference coordinate system. Figure 9 (a) is the original spectrum. Figure 9 (b) is the two-dimensional wavenumber spectrum after the first step of compression. Figure 9 (c) shows the two-dimensional wavenumber spectrum after two-step compression. The horizontal axis in each figure represents the wavenumber domain vector k. u The vertical axis represents the wavenumber domain vector k. v ,from Figure 9 It can be seen that, under the two-dimensional reference coordinate system of range and azimuth, after the swath width is expanded from 10km to 100km, the spectrum is relatively neatly arranged in the center after the first compression step; after the second compression step, the spectrum compression result is not much different from the first compression result. Therefore, it can be concluded that the spectrum compression performance under the two-dimensional reference coordinate system of range and azimuth cannot meet the imaging requirements of medium and high orbits in the large oblique viewing mode.

[0119] Depend on Figures 7-9 The spectral compression results show that when the range swath is extended from 10 km to 100 km, the spectral compression performance of the azimuth sidelobe reference coordinate system and Figures 4-6 The similar spectral performance indicates good two-step compression performance of the azimuth sidelobe reference coordinate system. The spectrum of the range sidelobe reference coordinate system is poorly aligned when the range frequency deviates from the center, even exceeding the azimuth-frequency range. The spectrum of the two-dimensional azimuth and range reference coordinate systems is neatly aligned at the central frequency range after the first compression step and symmetrical in the azimuth-frequency direction, but the spectral spread after the second compression step is not significantly different from the result of the first compression step. Upsampling the image through zero-filling will result in the same ambiguity as in the range sidelobe reference coordinate system. In summary, from... Figures 7-9 It can be seen that the azimuth sidelobe reference coordinate system has the best spectral compression performance for point targets in different range and azimuth directions.

[0120] Step A3: Determine the spectral tilt distribution corresponding to the azimuth sidelobe reference coordinate system, the range sidelobe reference coordinate system, and the range-azimuth two-dimensional reference coordinate system.

[0121] Specifically, the spectral tilt distribution under the azimuth sidelobe reference coordinate system, the range sidelobe reference coordinate system, and the range-azimuth two-dimensional reference coordinate system is plotted. The performance of spectral compression is related to the spatial variation of the spectral tilt in the imaging scene.

[0122] Figure 10 The spectral tilt distribution diagrams under the azimuth sidelobe reference coordinate system, the range sidelobe reference coordinate system, and the two-dimensional reference coordinate system of range and azimuth are schematically shown. Figure 10 (a)- Figure 10 (c) Spectral tilt distribution diagrams in the azimuth sidelobe reference coordinate system, the range sidelobe reference coordinate system, and the two-dimensional azimuth-range reference coordinate system, respectively. The horizontal and vertical axes of each diagram are the two axes of the scene coordinate system: the u-axis and the v-axis, respectively. The red lines are isoclimax lines, and the blue lines are equidistant lines. Figure 10 It can be seen that the isoclinal lines in the azimuth sidelobe reference coordinate system are symmetrically distributed along the u-axis, and the isoclinal lines (along the v-axis) at different distances are almost constant. The tilt angles in the range sidelobe reference coordinate system are different in both dimensions. In the range and azimuth two-dimensional reference coordinate systems, due to the non-orthogonality of the coordinate systems, the rate of change of the tilt angle shows significant differences at different locations in the scene. Through comparative analysis, only the azimuth sidelobe reference coordinate system can meet the requirement of obtaining good compression performance over a large swath range.

[0123] S206. Based on the spectral compression results and the spectral tilt distribution, the condition for maximizing the imaging scene is determined to be that the spectral compression results are aligned with the center and the top and bottom, and the spectral tilt distribution is consistent along the v-axis of the coordinate system and symmetrical along the u-axis of the coordinate system.

[0124] S207. Based on the condition of maximizing the imaging scene, determine that the direction of the basis vector of the u-axis of the maximized scene coordinate system is consistent with the gradient direction of the spectral tilt angle.

[0125] S208. Determine the direction orthogonal to the basis vector direction of the u-axis of the maximized scene coordinate system as the basis vector direction of the v-axis of the maximized scene coordinate system, so as to establish the maximized scene coordinate system.

[0126] S209. Determine whether the angle between the u-axis of the coordinate system and the beam movement direction is less than the preset angle.

[0127] Determine whether the angle between the u-axis of the coordinate system and the beam movement direction is less than the preset angle.

[0128] The preset angle can be 30°, or it can be any other value. There is no limitation on the preset angle here.

[0129] S210. If the angle between the u-axis of the coordinate system and the beam movement direction is not less than the preset angle, then select the beam scanning consistent coordinate system for imaging.

[0130] Specifically, it is determined whether the angle between the u-axis of the coordinate system and the beam movement direction is less than the preset angle. If not, the beam scanning consistent coordinate system is selected for imaging.

[0131] S211. If the angle between the u-axis of the coordinate system and the beam movement direction is less than the preset angle, then determine whether the size of the scene area is greater than the preset size.

[0132] Determine whether the angle between the coordinate system's u-axis and the beam movement direction is less than a preset angle. If so, determine whether the size of the scene area is greater than a preset size.

[0133] The preset size is 200km×200km. Specifically, it is determined whether the size of the scene area is greater than 200km×200km. If the size of the scene area is greater than 200km×200km, then step S212 is executed; if the size of the scene area is not greater than 200km×200km, then step S213 is executed.

[0134] S212. If the size of the scene area is larger than the preset size, then maximize the scene coordinate system for imaging.

[0135] Determine if the size of the scene area is larger than the preset size. If so, maximize the scene coordinate system for imaging.

[0136] S213. If the size of the scene area is not larger than the preset size, then select the azimuth sidelobe reference coordinate system for imaging.

[0137] The system determines whether the size of the scene region is larger than a preset size. If not, it selects the azimuth sidelobe reference coordinate system for imaging. In other words, if the size of the scene region is less than or equal to the preset size, the azimuth sidelobe reference coordinate system is selected for imaging.

[0138] Because the curvature varies at different locations on the Earth's ellipse, the optimal imaging coordinate system is close to the azimuth sidelobe reference coordinate system. However, at low latitudes, it may deviate from the azimuth sidelobe reference coordinate system, with a maximum error of 10°. If the scene area is no larger than 200km × 200km, the azimuth sidelobe reference coordinate system can be used directly.

[0139] The purpose of this invention is to propose an optimal scene coordinate system establishment method for rapid temporal imaging using medium- and high-orbit SAR. First, addressing the limitation that existing technologies are only suitable for frontal side-view imaging modes, this invention establishes four scene coordinate systems based on the sidelobe direction of the point response function on the ground plane under large oblique-view mode. Second, based on the spectral compression performance and spatially varied spectral tilt distribution characteristics under different coordinate systems, this invention proposes the conditions that the optimal scene coordinate system must satisfy, and develops an optimal scene coordinate system based on these conditions. Finally, the effectiveness of the scene coordinate system proposed in this invention for data focusing under the large oblique-view imaging mode of medium- and high-orbit SAR is verified through the processing results of point target data and scene target data. Under the optimal scene coordinate system, the mapping bandwidth of a single processing session can be maximized, reducing the number of scene sub-blocks, reducing limitations in imaging processing, and improving the flexibility and efficiency of imaging processing.

[0140] The effectiveness of the embodiments of the present invention can be further illustrated by the following simulation.

[0141] Simulation content and result analysis:

[0142] This simulation experiment utilizes the simulation parameters set by the first L-band medium-high orbit SAR satellite, with the latitude of the satellite collecting echo data at 45°. The ground squint angle is set to 60°, indicating that the system is operating in a large squint mode, optimizing bandwidth and integration time to maintain a 20m resolution (major axis of the ground resolution ellipse). Specific simulation parameters are shown in Table 1.

[0143] Table 1 Simulation Parameters

[0144]

[0145] The simulation data is processed using the method of this invention and real data: Figure 11 The diagram schematically illustrates the distribution of point targets in the scene coordinate system. The horizontal and vertical axes represent the u-axis and v-axis of the scene coordinate system, respectively. The scene is built on the Earth's surface, with dimensions of 500km × 400km. 51 × 41 scatterers are set on the scene grid, with a spacing of 10km in both the range and azimuth directions (e.g., ...). Figure 11 (As shown). Considering the amount of raw and intermediate data during imaging processing and the computational power of the processing nodes, the entire image is divided into several or dozens of blocks, and each block is processed sequentially in parallel. In the simulation experiment of this invention, the entire scene grid is divided into 10 blocks only in the distance direction. Each image block covers a scene of 102km × 450km, retaining a small amount of redundant areas to avoid image edge artifacts. Point targets P, O, and Q are selected, and the imaging results in the azimuth sidelobe reference coordinate system (optimal imaging coordinate system) are verified using the method of this invention.

[0146] Figure 12 Three sub-block images at close, medium, and long distances are schematically shown, in which... Figure 12 (a) is a sub-block image at close range. Figure 12 (b) is a mid-range sub-block image. Figure 12 (c) shows the image of a distant sub-block, with the horizontal axis representing the azimuth direction and the vertical axis representing the range direction. From Figure 12 It can be seen that the sub-block images at different distances are well focused, and the distribution of the set point targets can be clearly seen.

[0147] Figure 13 The simulation results of point target P are shown schematically. The coordinates of point target P in the image coordinate system are (-200km, -250km). Figure 14 The simulation results of point target O are shown schematically. The coordinates of point target O in the image coordinate system are (0km, -230km). Figure 15 The simulation results of point target Q are shown schematically. The coordinates of point target Q in the image coordinate system are (200km, -200km). Figure 13 (a) is a two-dimensional contour map of point target P. Figure 13 (b) is a azimuth sidelobe profile of point target P. Figure 13 (c) is a range sidelobe profile of point target P. Figure 14 (a) is a two-dimensional contour map of point target O. Figure 14 (b) is an azimuth sidelobe profile of point target O. Figure 14 (c) is a range-direction sidelobe profile of point target O. Figure 15 (a) is a two-dimensional contour map of point target Q. Figure 14 (b) is an azimuth sidelobe profile of point target Q. Figure 14 (c) is a range sidelobe profile of point target Q. In each figure (a), the horizontal axis is the u-axis of the scene coordinate system, and the vertical axis is the v-axis. In figures (b) and (c), the horizontal axis is the azimuth direction, and the vertical axis is the range direction. Figures 13-15Table 2 below shows the peak sidelobe ratio (PSLR) and integral sidelobe ratio (ISLR) results for point targets P, O, and Q, quantitatively demonstrating the focusing performance. From the azimuth and range sidelobe profiles and the PSLR and ISLR results for the three point targets, it can be seen that the PSLR of the selected point targets is below -13.07 dB and the ISLR is below -10.16 dB in both the azimuth and range directions. This indicates that the azimuth sidelobe reference coordinate system (optimal imaging coordinate system) proposed in this invention can achieve accurate focusing of medium- and high-orbit SAR data in large-angle and large-scene modes.

[0148] Table 2 evaluates the focusing results using the azimuth sidelobe reference coordinate system (optimal imaging coordinate system).

[0149]

[0150] In conclusion, the simulation experiments verified the correctness, effectiveness, and reliability of the present invention.

[0151] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for optimal scene coordinate system establishment for medium-high orbit SAR fast time-domain imaging, characterized in that, The method comprises: determining a plurality of spectral compression result maps and spectral dip angle distributions of a plurality of point targets respectively in an azimuth side lobe reference coordinate system, a range side lobe reference coordinate system and a range-azimuth two-dimensional reference coordinate system; determining a condition for maximizing an imaging scene according to the spectral compression result maps and the spectral dip angle distributions, wherein the condition is that the spectral compression result is a result meeting central alignment and up-down alignment, and the spectral dip angle distribution meets a condition that the spectral dip angle is uniformly distributed along a v-axis of the coordinate system and symmetrically distributed along a u-axis of the coordinate system; determining a gradient direction and a normal direction of the spectral dip angle according to the condition for maximizing the imaging scene, and establishing a maximized scene coordinate system according to the gradient direction and the normal direction of the spectral dip angle; judging whether an angle between the u-axis of the coordinate system and a beam moving direction is less than a preset angle; if the angle between the u-axis of the coordinate system and the beam moving direction is not less than the preset angle, selecting a beam scanning consistent coordinate system for imaging; if the angle between the u-axis of the coordinate system and the beam moving direction is less than the preset angle, judging whether a size of the scene region is greater than a preset size; if the size of the scene region is greater than the preset size, selecting the maximized scene coordinate system for imaging; if the size of the scene region is not greater than the preset size, selecting the azimuth side lobe reference coordinate system for imaging.

2. The method of claim 1, wherein, Before the plurality of spectral compression result maps and the spectral dip angle distributions of the plurality of point targets are determined respectively in the azimuth side lobe reference coordinate system, the range side lobe reference coordinate system and the range-azimuth two-dimensional reference coordinate system, the method further comprises: setting a base vector of a u-axis of the azimuth side lobe reference coordinate system to be consistent with an azimuth side lobe direction of a point response function on a horizontal plane; determining a direction orthogonal to a direction of the base vector of the u-axis of the azimuth side lobe reference coordinate system as a base vector of a v-axis of the azimuth side lobe reference coordinate system, so as to establish the azimuth side lobe reference coordinate system.

3. The method of claim 1, wherein, Before the plurality of spectral compression result maps and the spectral dip angle distributions of the plurality of point targets are determined respectively in the azimuth side lobe reference coordinate system, the range side lobe reference coordinate system and the range-azimuth two-dimensional reference coordinate system, the method further comprises: setting a base vector of a v-axis of the range side lobe reference coordinate system to be consistent with a range side lobe direction of a point response function on a horizontal plane; determining a direction orthogonal to a direction of the base vector of the v-axis of the range side lobe reference coordinate system as a base vector of a u-axis of the range side lobe reference coordinate system, so as to establish the range side lobe reference coordinate system.

4. The method of claim 1, wherein, Before the plurality of spectral compression result maps and the spectral dip angle distributions of the plurality of point targets are determined respectively in the azimuth side lobe reference coordinate system, the range side lobe reference coordinate system and the range-azimuth two-dimensional reference coordinate system, the method further comprises: setting a base vector of a u-axis of the range-azimuth two-dimensional reference coordinate system to be consistent with an azimuth side lobe direction of a point response function on a horizontal plane; setting a base vector of a v-axis of the range-azimuth two-dimensional reference coordinate system to be consistent with a range side lobe direction of the point response function on the horizontal plane, so as to establish the range-azimuth two-dimensional reference coordinate system.

5. The method of claim 1, wherein, Before the spectrum compression result graphs and the spectrum dip angle distributions of the corresponding multiple point targets are determined in the azimuth side lobe reference coordinate system, the range side lobe reference coordinate system and the range-azimuth two-dimensional reference coordinate system, the method further comprises: The u-axis of the beam scanning uniform coordinate system is set to be consistent with the direction of the movement of the beam footprint; The v-axis of the beam scanning uniform coordinate system is set to be the direction of the projection of the beam on the ground plane, so as to establish the beam scanning uniform coordinate system.

6. The method of claim 1, wherein, The spectrum compression result graphs and the spectrum dip angle distributions of the corresponding multiple point targets are determined in the azimuth side lobe reference coordinate system, the range side lobe reference coordinate system and the range-azimuth two-dimensional reference coordinate system, comprising: The spectrum compression result graphs of the azimuth side lobe reference coordinate system, the range side lobe reference coordinate system and the range-azimuth two-dimensional reference coordinate system are determined in the same distance direction and different azimuth directions; The spectrum compression result graphs of the azimuth side lobe reference coordinate system, the range side lobe reference coordinate system and the range-azimuth two-dimensional reference coordinate system are determined in different azimuth directions and different distance directions; The spectrum dip angle distributions of the azimuth side lobe reference coordinate system, the range side lobe reference coordinate system and the range-azimuth two-dimensional reference coordinate system are determined.

7. The method of claim 6, wherein, The spectrum compression result graphs of the azimuth side lobe reference coordinate system, the range side lobe reference coordinate system and the range-azimuth two-dimensional reference coordinate system are determined in the same distance direction and different azimuth directions, comprising: Multiple point targets in the same distance direction and different azimuth directions in the scene region are selected; The multiple point targets in the same distance direction and different azimuth directions are imaged in the azimuth side lobe reference coordinate system, the range side lobe reference coordinate system and the range-azimuth two-dimensional reference coordinate system, respectively, to determine the spectrum compression result graphs corresponding to each scene coordinate system.

8. The method of claim 6, wherein, The spectrum compression result graphs of the azimuth side lobe reference coordinate system, the range side lobe reference coordinate system and the range-azimuth two-dimensional reference coordinate system are determined in different azimuth directions and different distance directions, comprising: Multiple point targets in different azimuth directions and different distance directions in the scene region are selected; The multiple point targets in different azimuth directions and different distance directions are imaged in the azimuth side lobe reference coordinate system, the range side lobe reference coordinate system and the range-azimuth two-dimensional reference coordinate system, respectively, to determine the spectrum compression result graphs corresponding to each scene coordinate system.

9. The method of claim 1, wherein, The maximum scene coordinate system is established according to the gradient direction and the orthogonal direction of the spectrum dip angle by the imaging scene maximization condition, comprising: The base vector direction of the u-axis of the maximum scene coordinate system is set to be consistent with the gradient direction of the spectrum dip angle by the imaging scene maximization condition; The direction orthogonal to the base vector direction of the u-axis of the maximum scene coordinate system is determined as the base vector direction of the v-axis of the maximum scene coordinate system, so as to establish the maximum scene coordinate system.

10. The method of claim 2, wherein, The base vector of the u-axis of the azimuth side lobe reference coordinate system is set to be consistent with the cross product direction of the satellite beam pointing direction and the ground tangent plane normal vector of the point response function.

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