Large-attitude-angle dynamic push-broom line frequency calculation and matching method for satellite-borne TDI detector

Abstract

The invention provides a large-attitude-angle dynamic push-broom line frequency calculation and matching method for a satellite-borne TDI detector, which is used for solving the problems that the actual ellipsoid earth shape is not considered in the existing image motion velocity vector calculation model, the calculation error is introduced in the satellite attitude transformation process, or the actual ellipsoid earth shape is considered, so that the calculation error is caused. However, due to a large number of matrixes, differentials and partial derivative solving, the calculation result is complex, the calculation speed is low, and the calculation amount is large. According to the large-attitude-angle dynamic push-broom line frequency calculation and matching method for the satellite-borne TDI detector, the influence of an ellipsoid earth model, satellite attitude change and the like is considered, a vector relation method and a coordinate transformation method are combined, and the object distance and the lower visual angle corresponding to the center point of each detector in the dynamic push-broom process of a camera can be accurately calculated; obtaining an image motion speed on an image plane corresponding to the central point of each detector; therefore, the image motion speed, the line frequency and the drift angle corresponding to the central point of each detector are calculated, and line frequency matching is completed.

Description

Technical Field

[0001] The invention relates to a line frequency calculation and matching method, and in particular to a line frequency calculation and matching method for a large attitude angle dynamic push-scanning of a satellite-borne TDI detector. Background Art

[0002] In recent years, in the field of space remote sensing, as people continue to improve ground resolution, the industry has put forward higher requirements for satellite rapid response capabilities, ground observation efficiency, and imaging width on the basis of continuous pursuit of resolution. Therefore, agile satellites with the characteristics of high efficiency, speed, and flexibility have emerged as a new type of earth observation satellite application. At the same time, researchers have put forward higher and higher requirements for the resolution, field of view, signal-to-noise ratio, volume, and weight of the space cameras carried by agile satellites.

[0003] At present, the time-delay integration detector (TDI) has become the preferred detector as the focal plane device of space cameras. The TDI detector is a detector with a planar array structure and linear array output. It has the function of multiple-stage time-delay integration. Through multiple-stage photosensitive elements, the same target is integrated step by step for multiple times, and the weak signals of each stage of integration are superimposed as strong signal output, which can obtain a higher signal-to-noise ratio and sensitivity, greatly improving the image quality. However, in the imaging process, due to the influence of various factors such as the rotation of the earth, satellite attitude maneuvers, and orbital motion, the image motion velocity vector of each image point on the focal plane of the detector is inconsistent with the transfer velocity vector of the charge packet during the multi-stage output of the detector, resulting in a decrease in imaging quality. Moreover, the more the integration series, the greater the image motion velocity mismatch, and the worse the imaging quality. Therefore, how to achieve image motion compensation for each image point on the focal plane of the detector and establish an accurate image motion velocity vector calculation model has become the focus of research by domestic and foreign scholars.

[0004] In 2004, when establishing the imaging formula for sub-satellite points, Academician Wang Jiaqi calculated the image plane position equation and the image plane velocity equation through the changing relationship of the seven coordinate systems from the ground scene to the image plane, and then obtained the calculation formula for the image plane image motion velocity vector; in 2006, Yuan Xiaokang from the Shanghai Satellite Engineering Research Institute proposed a method for satellite yaw control to achieve camera drift angle compensation, and derived the analytical calculation formulas for the drift angle and target image motion velocity during sub-satellite point and satellite attitude maneuver push-scan imaging; in 2012, Huang Qundong and others from Aerospace Dongfanghong Satellite Co., Ltd. used the coordinate transformation method to derive the mathematical analytical expression of the image motion velocity under dynamic imaging; however, these expressions are all calculated based on the spherical earth model, without considering the actual ellipsoidal earth shape, and directly introduced calculation errors in the process of satellite attitude transformation; in 2016, Li Yongchang from the Changchun Institute of Optics, Fine Mechanics and Physics established the image motion velocity vector expression based on the ellipsoidal earth model and off-axis three-mirror optical lens, taking into account the actual ellipsoidal earth shape, but a large number of matrices, differentials, and partial derivatives made the calculation results complicated, the amount of calculation was large, and the speed was slow. Summary of the invention

[0005] The purpose of the present invention is to address the technical problems that the existing image motion velocity vector calculation model does not take into account the actual ellipsoidal earth shape, which will introduce calculation errors in the process of satellite attitude transformation, or takes into account the actual ellipsoidal earth shape, but a large number of matrices, differentials, and partial derivatives make the calculation results complicated, the calculation speed is slow, and the amount of calculation is large. A method for calculating and matching the dynamic push-scan line frequency of a satellite-borne TDI detector with a large attitude angle is provided.

[0006] In order to achieve the above object, the technical solution of the present invention is:

[0007] A method for calculating and matching the line frequency of a large attitude angle dynamic push-scan of a space-borne TDI detector is special in that it comprises the following steps:

[0008] Step 1, establish an ellipsoidal earth model, initialize the parameters of the satellite orbit, the earth and the camera, and define the coordinate system of the ellipsoidal earth model according to the imaging principle of the onboard TDI detector; the coordinate system of the ellipsoidal earth model includes the geocentric equatorial inertial coordinate system, the satellite orbit coordinate system, the satellite body coordinate system, the space camera coordinate system and the camera focal plane coordinate system;

[0009] Step 2: Calculate the inverse matrix of the transformation matrix of the geocentric equatorial inertial coordinate system and the satellite orbit coordinate system respectively The inverse matrix of the transformation matrix between the satellite orbit coordinate system and the satellite body coordinate system and the inverse of the camera mount matrix Establish the geometric relationship constraint equation of the ellipsoid corresponding to the space camera coordinate system and the camera focal plane coordinate system, and combine the obtained matrix matrix and matrix Calculate the position vector between the camera coordinate origin and the target point;

[0010] Step 3, calculate the angle between the line connecting the center point of each detector in the satellite TDI detector and the origin of the camera coordinate system and the line connecting the center point of the focal plane of the satellite TDI detector and the origin of the camera coordinate system, and then calculate the downward viewing angle corresponding to the center point of each detector when the satellite attitude angle changes; then calculate the object distance corresponding to the center point of each detector in combination with the position vector between the origin of the camera coordinate system and the target point obtained in step 2;

[0011] Step 4: convert the absolute velocity vector of the target point caused by the rotation of the earth and the involved velocity vector of the target point caused by the motion of the satellite into the space camera coordinate system, and calculate the image motion velocity corresponding to the center point of each detector in the space camera coordinate system; then, combine the object distance obtained in step 3 to calculate the image motion velocity on the image plane corresponding to the center point of each detector;

[0012] Step 5, when the satellite attitude maneuver push-broom imaging is performed, the ground push-broom speed of the camera is calculated when the camera push-broom trajectory and the camera sub-satellite point trajectory are at different angles;

[0013] Step 6, according to the image motion speed on the image plane corresponding to the center point of each detector obtained in step 4 and the ground push-broom speed of the camera obtained in step 5, the image motion speed, line frequency and drift angle corresponding to the center point of each detector during satellite attitude maneuver push-broom imaging are calculated;

[0014] Step 7, according to the image motion speed, line frequency and drift angle corresponding to the center point of each detector during the satellite attitude maneuver push-scan imaging calculated in step 6, determine the change curve of the modulation transfer function, and then complete the line frequency matching through the change curve of the modulation transfer function.

[0015] Furthermore, in step 2, the inverse matrix of the transformation matrix between the geocentric equatorial inertial coordinate system and the satellite orbit coordinate system is calculated by the following formula:

[0016]

[0017] The inverse matrix of the transformation matrix between the satellite orbit coordinate system and the satellite body coordinate system is calculated by the following formula:

[0018]

[0019] The inverse matrix of the camera installation matrix is ​​calculated by the following formula

[0020]

[0021] Among them, u is the satellite latitude argument, Ω is the right ascension of the orbit ascending node, i is the orbit inclination, ψ is the satellite yaw angle, is the satellite roll angle, and θ is the satellite pitch angle.

[0022] Furthermore, in step 2, the geometric relationship constraint equation of the ellipsoid corresponding to the space camera coordinate system and the camera focal plane coordinate system is established, and the obtained matrix matrix and matrix The calculation of the position vector between the camera coordinate origin and the target point is as follows:

[0023] Step a, establish the ellipsoid geometric relationship constraint equation corresponding to the space camera coordinate system and the camera focal plane coordinate system, the expression is:

[0024]

[0025] Where, X I , Y I , Z I are the target point position vectors The components in three directions, is the vector pointing from the origin of the camera coordinate system to the ground target point in the space camera coordinate system, is the relative position vector between the camera coordinate origin and the satellite coordinate origin in the satellite body coordinate system, that is, the installation position of the camera, is the translation vector, r is the distance from the satellite orbit to the Earth’s center, r = R e +H0,R e is the average radius of the Earth, H0 is the orbital altitude; p1 and p2 are the horizontal and vertical coordinates of the focal plane position vector, f is the focal length of the camera, and a e is the Earth's semi-major axis, b e is the Earth's semi-minor axis; X c , T c , Z c are the position vectors from the camera coordinate origin to the target point Components in three directions;

[0026] Step b: solve X according to the geometric relationship constraint equations corresponding to the space camera coordinate system and the camera focal plane coordinate system. c , Y c , Z c , get the position vector between the camera coordinate origin and the target point

[0027] Furthermore, in step 3, the angle between the line connecting the center point of each detector in the space-borne TDI detector and the origin of the camera coordinate system and the line connecting the center point of the focal plane of the space-borne TDI detector and the origin of the camera coordinate system is calculated by the following formula:

[0028] ag i =arc tan(S i *p s *pixels / f)

[0029] In the formula, ag i is the angle between the line connecting the center point of the i-th detector in the space-borne TDI detector and the origin of the camera coordinates and the line connecting the center of the focal plane of the TDI detector and the origin of the camera coordinates, i = 1, 2, ..., N, N is the total number of detectors in the space-borne TDI detector, S i is the center point position of the i-th detector, ps is the pixel size, and pixels is the pixel size.

[0030] Furthermore, in step 3, the center point position S of each detector is i The formula for determining is:

[0031] S i =-N / 2+0.5, -N / 2+1.5,..., N / 2-0.5.

[0032] Furthermore, in step 3, the lower viewing angle α corresponding to the center point of the i-th detector when the satellite attitude angle changes is calculated by the following formula: i :

[0033]

[0034] The object distance L corresponding to the center point of the i-th detector is calculated by the following formula i :

[0035]

[0036] Furthermore, step 4 is specifically as follows:

[0037] Step 4.1: Substitute the absolute velocity vector v of the target point caused by the Earth's rotation into a and the target point's associated velocity vector v caused by the satellite motion e All are converted to the space camera coordinate system, combined with the formula v r =v a -v e , calculate the image motion velocity corresponding to the center point of the i-th detector in the space camera coordinate system

[0038] Step 4.2: Calculate the image motion velocity v on the image plane corresponding to the center point of the i-th detector according to the following formula:i :

[0039]

[0040] Furthermore, in step 5, the ground push-sweep speed v of the camera is calculated by the following formula when the camera push-sweep trajectory and the camera sub-satellite point trajectory are at different angles: ηi :

[0041]

[0042] In the formula, w η is the camera push-scan angular velocity, β i is the geocentric angle corresponding to the i-th detector,

[0043] Furthermore, in step 6, the image motion velocity V corresponding to the center point of the i-th detector during satellite attitude maneuver push-scan imaging is calculated by the following formula: i , line frequency f TDIi and the deflection angle alpha_d i :

[0044]

[0045] Furthermore, in step 7, the variation curve MTF of the modulation transfer function is determined by the following formula:

[0046]

[0047] Where Δv = V m -V i , under the same speed condition, V m is the image moving speed of the center point of the focal plane of the TDI detector, V i is the image moving speed of the center point of each detector; under different speed conditions, V m is the edge image motion speed of each detector.

[0048] Compared with the prior art, the present invention has the following beneficial effects:

[0049] 1. The present invention provides a method for calculating and matching the line frequency of a satellite-borne TDI detector with a large attitude angle dynamic push-scanning, which takes into account the influence of the ellipsoidal earth model, satellite attitude changes, etc., and combines the vector relationship method with the coordinate transformation method. It can accurately calculate the object distance and the downward viewing angle corresponding to the center point of each detector on the TDI detector during the dynamic push-scanning of the camera, and then obtain the precise image motion speed on the image plane. The method of the present invention has a simpler calculation process, a fast calculation speed, and clear and analyzable component expressions, which is easier to realize engineering applications.

[0050] 2. The present invention provides a method for calculating and matching the dynamic push-scan line frequency of a satellite-borne TDI detector at a large attitude angle. By analyzing the change curve of the modulation transfer function, the real-time frequency modulation of the single-chip detector is determined, thereby achieving high-precision matching of the satellite-borne TDI detector with a large field of view under large attitude angle conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 It is a flow chart of an embodiment of a method for calculating and matching the line frequency of a large attitude angle dynamic push-scan of a satellite-borne TDI detector according to the present invention;

[0052] Figure 2 Schematic diagram of the relationship between parameters during push-scan imaging of satellite attitude changes in step 6 of an embodiment of the present invention;

[0053] Figure 3 Schematic diagram of the calculation result of the image motion velocity difference in step 7 of the embodiment of the present invention, wherein (a) is a schematic diagram of the calculation result of the image motion velocity difference under the same speed condition, and (b) is a schematic diagram of the calculation result of the image motion velocity difference under the different speed condition with one slice and one line frequency;

[0054] Figure 4 is the modulation transfer function change curve of the sub-satellite point, where the red curve represents the modulation transfer function change curve under the same speed condition, and the blue curve represents the modulation transfer function change curve under the different speed condition;

[0055] Figure 5 It is the modulation transfer function change curve of the side swing angle of 30°, where the red curve represents the modulation transfer function change curve under the same speed condition, and the blue curve represents the modulation transfer function change curve under the different speed condition;

[0056] Figure 6 It is the modulation transfer function change curve when the roll is 45°, the pitch is 30°, and the pitch angular velocity is -0.5°. The red curve represents the modulation transfer function change curve under the same speed condition, and the blue curve represents the modulation transfer function change curve under the different speed conditions. DETAILED DESCRIPTION

[0057] In order to make the advantages and features of the present invention more clear, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0058] A method for calculating and matching the line frequency of a space-borne TDI detector with large attitude angle dynamic push-scanning. Figure 1 As shown, the specific steps include:

[0059] Step 1: Establish an ellipsoidal earth model, initialize the parameters of the satellite orbit, ellipsoidal earth model and camera, and define the coordinate system of the ellipsoidal earth model.

[0060] Step 1.1, the initialized satellite orbit parameters include: orbit ascending node right ascension Ω, orbit inclination i, satellite latitude argument u, orbit altitude H0, terrain altitude h, satellite angular velocity w along the orbit a , subsatellite latitude γ, satellite side swing angle Satellite pitch angle θ, satellite yaw angle ψ, satellite lateral angular velocity Satellite pitch angular velocity Satellite yaw rate Time t.

[0061] The parameters of the initialized ellipsoid earth model include: the earth's major semi-axis a e , Earth's semi-minor axis b e , the average radius of the Earth is R e , the Earth's rotation angular velocity w e .

[0062] The initialized camera parameters include: camera focal length f, integration series M, installation position Focal plane position vector And the installation matrix M cb .

[0063] In this embodiment, the initialization values ​​of some parameters of the satellite orbit, the earth and the camera are shown in Table 1. The initialization values ​​of the parameters not shown in Table 1 are all 0.

[0064] Table 1 Initialization values ​​of some parameters of satellite orbit, earth and camera

[0065]

[0066]

[0067]

[0068] Step 1.2, based on the principle of spaceborne TDICMOS imaging, define the coordinate system of the ellipsoidal earth model, including:

[0069] (1) Geocentric equatorial inertial coordinate system: O e -x I y I z I , referred to as I series;

[0070] The origin of the coordinate system of the I system is the center of the earth O e , O e x I Located in the equatorial plane, pointing to the J2000.0 vernal equinox, O e z I Perpendicular to the equatorial plane, pointing to the North Pole, consistent with the direction of the Earth's rotation angular velocity vector, O e yI Perpendicular to O e x I , O e z I Two coordinate axes.

[0071] (2) Satellite orbit coordinate system: O s -x o y o z o , referred to as o series;

[0072] The origin of the coordinate system of the o system is located at the satellite's center of mass O s , O s x o Located in the satellite orbit plane, pointing in the direction of satellite motion, O s z o Pointing to the center of the earth e , O s y o Perpendicular to O s x o and O s z o Coordinate axis, which orbits in the I system at the angular velocity of the satellite.

[0073] (3) Satellite body coordinate system: O s -x b y b z b , referred to as b series;

[0074] The origin of the coordinate system of the b system is located at the satellite's center of mass O s , coincides with the origin of the o system. When the satellite has no attitude motion, O s x b , O s y b , O s z b The three-axis attitude of the satellite refers to the three-axis attitude of the b system in the o system. s x b , O s y b , O s z b They are the roll, pitch and yaw axes of the satellite attitude motion respectively.

[0075] (4) Space camera coordinate system: O c -x c y c z c , referred to as C series;

[0076] The origin of the coordinate system of the c system is the camera imaging center, and the principal point of the optical system is Oc , O c z c To point to the ground target point along the optical axis, O c x c , O c y c In the camera objective plane.

[0077] (5) Camera focal plane coordinate system: O p -x p y p z p , referred to as p series;

[0078] The origin of the coordinate system of the p system is the focal center O of the camera p , O p x p Located in the camera focal plane, c x c Axis parallel, along the TDI integration direction, O p y p Located in the focal plane of the camera, perpendicular to the integration direction of TDI and O c y c Axis parallel, O p z p is the focal plane normal, and O c z c The axes are in the same direction.

[0079] Step 2, obtain the position vector between the camera coordinate origin and the target point.

[0080] Step 2.1, after substituting the data in step 1, calculate the inverse matrix of the transformation matrix of the I system and the o system respectively by the following formula The inverse matrix of the transformation matrix between the o system and the b system and the inverse of the camera mount matrix

[0081]

[0082] Step 2.2: For the ellipsoidal earth model, establish the geometric relationship constraint equations corresponding to the C system and the P system, solve the geometric relationship constraint equations corresponding to the C system and the P system, and obtain the position vector between the camera coordinate origin and the target point.

[0083] Specifically, the geometric relationship constraint equations corresponding to the c system and the p system are expressed as follows:

[0084]

[0085] Where, X I , YI , Z I are the target point position vectors The components in three directions, is the vector pointing from the origin of the camera coordinate system to the ground target point. is the relative position vector between the camera coordinate origin and the satellite coordinate origin in the satellite body coordinate system, that is, the installation position of the camera, is the translation vector, r is the distance from the satellite orbit to the Earth’s center, r = R e +H0,R e is the average radius of the Earth, H0 is the orbital height; p1 and p2 are the horizontal and vertical coordinates of the focal plane position vector, respectively, X c , Y c , Z c are the position vectors from the camera coordinate origin to the target point Components in three directions.

[0086] Step 3: Calculate the lower viewing angle and object distance corresponding to the center point of each detector.

[0087] Step 3.1, in this embodiment, the number of detectors N in the satellite-borne TDI detector is 15, then the positions corresponding to the center points of each detector are -7, -6, ..., 7, the pixel size ps is 10 μm, and the pixel size pixels is 1200.

[0088] The angle between the line connecting the center point of the i-th detector in the space-borne TDI detector and the origin of the camera coordinates and the line connecting the center point of the focal plane of the TDI detector and the origin of the camera coordinates is calculated according to the following formula: Figure 2 As shown:

[0089] ag i =arctan(S i *ps*pixels / f)

[0090] In the formula, ag i is the angle between the line connecting the center point of the i-th detector in the space-borne TDI detector and the origin of the camera coordinates and the line connecting the center point of the focal plane of the TDI detector and the origin of the camera coordinates, i = 1, 2, ..., N, S i is the center point position of the i-th detector.

[0091] In this embodiment, the angles between the line connecting the center points of the 15 detectors and the camera coordinate origin and the line connecting the center point of the focal plane of the TDI detector and the camera coordinate origin are: -0.0034, -0.0029, -0.0024, -0.0019, -0.0014, -0.0010, -0.0005, 0, 0.0005, 0.001, 0.0014, 0.0019, 0.0024, 0.0029, 0.0034.

[0092] Step 3.2: When the satellite attitude angle changes, the lower viewing angle α corresponding to the center point of the 15 detectors i According to the formula After calculation, they are: 0.9084, 0.9089, 0.9093, 0.9098, 0.9103, 0.9108, 0.9113, 0.9117, 0.9122, 0.9127, 0.9132, 0.9137, 0.9141, 0.9146, 0.9151.

[0093] Step 3.3, the object distance L corresponding to the center point of each detector i By formula After calculation, they are: 875770.1625, 876450.6872, 877132.6663, 877816.1042, 878501.0053, 879187.3741, 879875.2151, 880564.5328,881255.3316, 881947.6162, 882641.3911, 883336.6609, 884033.4302, 884731.7035, 885431.4856.

[0094] Step 4: Calculate the image motion velocity v corresponding to the center point of each detector in the space camera coordinate system ri and the image motion velocity v on the image plane i .

[0095] Step 4.1, based on the traditional photography ground speed, there is the following formula:

[0096] v r =v a -v e

[0097] In the formula, v a is the absolute velocity vector of the target point D caused by the rotation of the earth, v a =w e ×R e , v e is the velocity vector caused by the satellite motion, v e =wa ×R e , v r is the image motion speed in the space camera coordinate system.

[0098] The absolute velocity vector v of the target point caused by the rotation of the earth a and the target point's associated velocity vector v caused by the satellite motion e All are converted to the space camera coordinate system to obtain the image motion velocity corresponding to the center point of each detector in the space camera coordinate system.

[0099] Step 4.2: The image motion velocity v on the image plane corresponding to the center point of each detector i According to the formula After calculation, they are: 0.1727, 0.1726, 0.1724, 0.1723, 0.1721, 0.1720, 0.1718, 0.1717, 0.1715, 0.1714, 0.1712, 0.1711, 0.1709, 0.1708, 0.1706.

[0100] Step 5, calculate the ground push-broom speed of the camera during satellite attitude maneuver push-broom imaging.

[0101] When the camera push-scan trajectory and the camera sub-satellite point trajectory have different included angles η, the camera ground push-scan speed v ηi By formula Calculate, where w η is the camera push-scan angular velocity, β i is the geocentric angle corresponding to the i-th detector, In this embodiment, the geocentric angles corresponding to the 15 detectors are: 1.113, 1.114, 1.115, 1.116, 1.117, 1.117, 1.118, 1.119, 1.12, 1.121, 1.122, 1.123, 1.124, 1.125, 1.126.

[0102] Correspondingly, the ground push-scan speed of the camera They are: -17281.45, -17328.29, -17375.42, -17422.86, -17470.58, -17518.62, -17566.96, -17615.61, -17664.58, -17713.86, -17763.45, -17813.38, -17863.62, -17914.20, -17965.11.

[0103] Step 6, such as Figure 2As shown in the figure, it is a schematic diagram of the parameter relationship when the satellite attitude changes and push-broom imaging is performed. The image motion velocity V corresponding to the center point of each detector during the satellite attitude maneuver push-broom imaging is calculated by the following formula: i , line frequency f TDIi and the deflection angle alpha_d i :

[0104]

[0105] In this embodiment, the image movement speeds corresponding to the center points of the 15 detectors are:

[0106]

[0107] Step 7: Based on the line frequency result obtained in step 6, the image motion velocity V corresponding to the center point of each detector during satellite attitude maneuver push-scan imaging i , line frequency f TDIi and the deflection angle alpha_d i , determine the MTF change curve of the modulation transfer function, and then complete the line frequency matching through the change curve of the modulation transfer function.

[0108] In the present invention, the variation curve MTF of the modulation transfer function is determined by the following formula:

[0109]

[0110] Where Δv is the image motion speed difference, Δv = V m -V i , under the same speed condition, V m is the image moving speed of the center point of the focal plane of the TDI detector, V i is the image moving speed of the center point of each detector. Under different speed conditions, V m is the edge image moving speed of each detector. Figure 3 (a) is a schematic diagram showing the calculation of the image motion velocity difference Δv under the same speed condition. Figure 3 (b) is a schematic diagram for calculating the image motion velocity difference Δv of one image per line frequency under different speed conditions.

[0111] like Figure 4 As shown, it is the modulation transfer function change curve of the sub-satellite point in this embodiment, Figure 5 is the modulation transfer function variation curve when the side swing angle is 30° in this embodiment, Figure 6 is the modulation transfer function variation curve when the roll angle is 45°, the pitch angle is 30°, and the pitch angular velocity is -0.5° in this embodiment, Figure 4-Figure 6The red curve in the middle represents the modulation transfer function change curve under the same speed condition, and the blue curve represents the modulation transfer function change curve under the different speed condition. It can be seen that the line frequency matching accuracy under the different speed condition is higher than that under the same speed condition, which can guide the line frequency matching of the satellite during the on-orbit process.

[0112] The above description is only used to illustrate the technical solution of the present invention rather than to limit it. For ordinary professional and technical personnel in the field, the specific technical solution recorded in the above embodiment can be modified, or some of the technical features therein can be replaced by equivalents, and these modifications or replacements do not make the essence of the corresponding technical solution deviate from the scope of the technical solution protected by the present invention.

Claims

1. A method for calculating and matching the line frequency of a large attitude angle dynamic push-scan of a satellite-borne TDI detector, characterized in that: The following steps are involved: Step 1, establish an ellipsoidal earth model, initialize the parameters of the satellite orbit, the earth and the camera, and define the coordinate system of the ellipsoidal earth model according to the imaging principle of the onboard TDI detector; the coordinate system of the ellipsoidal earth model includes the geocentric equatorial inertial coordinate system, the satellite orbit coordinate system, the satellite body coordinate system, the space camera coordinate system and the camera focal plane coordinate system; Step 2: Calculate the inverse matrix of the transformation matrix of the geocentric equatorial inertial coordinate system and the satellite orbit coordinate system respectively The inverse matrix of the transformation matrix between the satellite orbit coordinate system and the satellite body coordinate system and the inverse of the camera mount matrix Establish the geometric relationship constraint equation of the ellipsoid corresponding to the space camera coordinate system and the camera focal plane coordinate system, and combine the obtained matrix matrix and matrix Calculate the position vector between the camera coordinate origin and the target point; Step 3, calculate the angle between the line connecting the center point of each detector in the satellite TDI detector and the origin of the camera coordinate system and the line connecting the center point of the focal plane of the satellite TDI detector and the origin of the camera coordinate system, and then calculate the downward viewing angle corresponding to the center point of each detector when the satellite attitude angle changes; then calculate the object distance corresponding to the center point of each detector in combination with the position vector between the origin of the camera coordinate system and the target point obtained in step 2; Step 4: convert the absolute velocity vector of the target point caused by the rotation of the earth and the involved velocity vector of the target point caused by the motion of the satellite into the space camera coordinate system, and calculate the image motion velocity corresponding to the center point of each detector in the space camera coordinate system; Combined with the object distance obtained in step 3, the image motion speed on the image plane corresponding to the center point of each detector is calculated; Step 5, when the satellite attitude maneuver push-broom imaging is performed, the ground push-broom speed of the camera is calculated when the camera push-broom trajectory and the camera sub-satellite point trajectory are at different angles; Step 6, according to the image motion speed on the image plane corresponding to the center point of each detector obtained in step 4 and the ground push-broom speed of the camera obtained in step 5, the image motion speed, line frequency and drift angle corresponding to the center point of each detector during satellite attitude maneuver push-broom imaging are calculated; Step 7, according to the image motion speed, line frequency and drift angle corresponding to the center point of each detector during the satellite attitude maneuver push-scan imaging calculated in step 6, determine the change curve of the modulation transfer function, and then complete the line frequency matching through the change curve of the modulation transfer function.

2. The method for calculating and matching the line frequency of a satellite-borne TDI detector with a large attitude angle dynamic push-scanning according to claim 1, characterized in that: In step 2, the inverse matrix of the transformation matrix between the geocentric equatorial inertial coordinate system and the satellite orbit coordinate system is calculated by the following formula: The inverse matrix of the transformation matrix between the satellite orbit coordinate system and the satellite body coordinate system is calculated by the following formula: The inverse matrix of the camera installation matrix is ​​calculated by the following formula Among them, u is the satellite latitude argument, Ω is the right ascension of the orbit ascending node, i is the orbit inclination, ψ is the satellite yaw angle, is the satellite roll angle, and θ is the satellite pitch angle.

3. The method for calculating and matching the line frequency of a satellite-borne TDI detector with a large attitude angle dynamic push-scanning according to claim 2, characterized in that: In step 2, the geometric relationship constraint equation of the ellipsoid corresponding to the space camera coordinate system and the camera focal plane coordinate system is established, and the obtained matrix matrix and matrix The calculation of the position vector between the camera coordinate origin and the target point is as follows: Step a, establish the ellipsoid geometric relationship constraint equation corresponding to the space camera coordinate system and the camera focal plane coordinate system, the expression is: In the formula, X I , Y I , Z I are the target point position vectors The components in three directions, is the vector pointing from the origin of the camera coordinate system to the ground target point in the space camera coordinate system, is the relative position vector between the camera coordinate origin and the satellite coordinate origin in the satellite body coordinate system, that is, the installation position of the camera, is the translation vector, r is the distance from the satellite orbit to the Earth’s center, r = R e +H0,R e is the average radius of the Earth, H0 is the orbital altitude; p1 and p2 are the horizontal and vertical coordinates of the focal plane position vector, f is the focal length of the camera, and a e is the Earth's semi-major axis, b e is the Earth's semi-minor axis; X c , Y c , Z c are the position vectors from the camera coordinate origin to the target point Components in three directions; Step b: solve X according to the geometric relationship constraint equations corresponding to the space camera coordinate system and the camera focal plane coordinate system. c , Y c , Z c , get the position vector between the camera coordinate origin and the target point 4. The method for calculating and matching the line frequency of a space-borne TDI detector with a large attitude angle according to claim 3, characterized in that: In step 3, the angle between the line connecting the center point of each detector in the space-borne TDI detector and the origin of the camera coordinate system and the line connecting the center point of the focal plane of the space-borne TDI detector and the origin of the camera coordinate system is calculated by the following formula: ag i =arctan(S i *ps*pixels / f) In the formula, ag i is the angle between the line connecting the center point of the i-th detector in the space-borne TDI detector and the origin of the camera coordinate system and the line connecting the center of the focal plane of the TDI detector and the origin of the camera coordinate system, i = 1, 2, ..., N, N is the total number of detectors in the space-borne TDI detector, S i is the center point position of the i-th detector, ps is the pixel size, and pixels is the pixel size.

5. The method for calculating and matching the line frequency of a space-borne TDI detector with a large attitude angle dynamic push-scanning according to claim 4, characterized in that: In step 3, the center point position S of each detector is i The formula for determining is: S i =-N / 2+0.5,-N / 2+1.5,...,N / 2-0.5。 6. A method for calculating and matching the line frequency of a space-borne TDI detector with large attitude angle dynamic push-scanning according to claim 4 or 5, characterized in that: In step 3, the lower viewing angle α corresponding to the center point of the i-th detector when the satellite attitude angle changes is calculated by the following formula: i : The object distance L corresponding to the center point of the i-th detector is calculated by the following formula i :

7. The method for calculating and matching the line frequency of a satellite-borne TDI detector with a large attitude angle dynamic push-scanning according to claim 6, characterized in that: Step 4 is as follows: Step 4.1: Substitute the absolute velocity vector v of the target point caused by the Earth's rotation into a and the target point's associated velocity vector v caused by the satellite motion e All are converted to the space camera coordinate system, combined with the formula v r =v a -v e , calculate the image motion velocity corresponding to the center point of the i-th detector in the space camera coordinate system Step 4.2: Calculate the image motion velocity v on the image plane corresponding to the center point of the i-th detector according to the following formula: i :

8. The method for calculating and matching the line frequency of a space-borne TDI detector with a large attitude angle dynamic push-scanning according to claim 7, characterized in that: In step 5, the ground push-sweep speed v of the camera is calculated by the following formula when the camera push-sweep trajectory and the camera sub-satellite point trajectory are at different angles: ηi : In the formula, w η is the camera push-scan angular velocity, β i is the geocentric angle corresponding to the i-th detector, 9. The method for calculating and matching the line frequency of a space-borne TDI detector with a large attitude angle dynamic push-scanning according to claim 8, characterized in that: In step 6, the image motion velocity V corresponding to the center point of the i-th detector during satellite attitude maneuver push-scan imaging is calculated by the following formula: i , line frequency f TDIi and the deflection angle alpha_d i :

10. The method for calculating and matching the line frequency of a space-borne TDI detector with a large attitude angle dynamic push-scanning according to claim 9, characterized in that: In step 7, the modulation transfer function (MTF) is determined by the following formula: Where, △v=V m -V i , under the same speed condition, V m is the image moving speed of the center point of the focal plane of the TDI detector, V i is the image moving speed of the center point of each detector; under different speed conditions, V m is the edge image motion speed of each detector.

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