Multi-satellite combined observation system positioning error correction method based on rendezvous constraint

Abstract

The invention discloses a multi-satellite combined observation system positioning error correction method based on rendezvous constraints. The method comprises the following steps: (1) acquiring multi-satellite combined observation images at the same moment, in the same area and at different visual angles based on a multi-satellite combined observation system; (2) extracting view field overlapping region connection points in the multi-satellite combined observation image; (3) constructing a geometric positioning model of each sensor of the multi-satellite combined observation system according to a space-based area array photoelectric load geometric imaging principle; (4) on the basis of the geometric positioning model, constructing a common view field area connection point intersection constraint relation in the multi-satellite combined observation system; (5) based on the rendezvous constraint relation, carrying out preliminary correction on the relative positioning error between the multi-satellite combined observation systems; and (6) based on an iterative least square algorithm, performing calibration parameter optimization of the multi-satellite combined observation system, and finally completing error correction. According to the invention, the correction of the positioning error of the multi-satellite combined observation system and the high-precision positioning of the space target can be realized.

Description

Technical Field

[0001] The invention belongs to the technical field of space-based photoelectric detection, positioning and tracking, and in particular relates to a positioning error correction method for a multi-satellite joint observation system based on rendezvous constraints. Background Art

[0002] Space-based infrared detection systems can achieve instant detection of infrared targets in space. However, a single optical satellite can only achieve vector indication of space targets, but cannot achieve space positioning. The multi-satellite joint observation method can achieve the discovery and positioning of high-speed targets in space. The preliminary positioning information can provide accurate guidance information for radar and other systems, and has become one of the core technologies in the field of space detection.

[0003] At present, the commonly used space target positioning method is mainly achieved by radar detection. The radar system continuously emits electromagnetic waves, which reflect the target signal after contacting the target, and then determine the existence, location and movement status of the target by analyzing the reflected signal.

[0004] Radar detection methods face the following problems: (1) Ground-based radars are limited by the curvature of the earth, and the maximum detectable distance of low-altitude, high-speed targets is short, and the effective response window is extremely short. Space-based radars are limited by transmission power and atmospheric losses, and their detection distance is limited, making it difficult to meet actual application requirements. (2) It is difficult to achieve effective detection and positioning of space targets with small scattering cross-sections.

[0005] In recent years, with the development of space-based satellite constellation network construction, multi-satellite joint space target positioning technology has received great attention. The traditional principle of multi-satellite joint positioning is to obtain the observation vectors of the same target at different angles at the same time through joint observation of multiple optical satellites, and then obtain the spatial position of the observed target based on the principle of line of sight intersection.

[0006] For example, publication number CN118604840A discloses a satellite system and method for collaborative detection and imaging of low-orbit targets from a low-orbit orbit. The satellite system includes three sun-synchronous orbit reconnaissance satellites with orbital altitudes of 600km, 800km, and 1000km. The satellites are equipped with optical sensor payloads with optical imaging and detection capabilities. The satellites have three working modes: flyby imaging, fly-by imaging, and joint detection and positioning mode. The advantage is that it can perform real-time multi-angle detection of satellites within the orbital altitude range of 500 to 1100km, provide high-precision positioning and orbit determination of targets; and perform high-frequency flyby imaging, and the minimum imaging distance is short (less than or equal to 100km), the imaging effect is good, and it has multiple observation angles.

[0007] Existing methods can realize the discovery and positioning of space targets based on the characteristics of space-based satellites that they are high and can see far. They have the advantages of long detection distance and strong timeliness, but they face the following difficulties: (1) Affected by factors such as attitude and orbit measurement errors, calibration errors of internal and external orientation elements of sensors, and thermal deformation in space, the line of sight vector of a single satellite often has a certain error, and the target pointing deviates from the actual position; (2) Due to the existence of line of sight errors, the lines of sight of multiple satellites do not actually intersect, and it is difficult to obtain the target's analytical position using approximate optimization methods; (3) Affected by the accuracy of on-orbit calibration, there are relative observation errors between multiple satellites, which affects the accuracy of multi-satellite joint positioning of space targets.

[0008] In summary, in view of the great demand for real-time positioning of space targets, it is urgent to study the positioning error correction method of multi-satellite joint observation system based on rendezvous constraints to meet the needs of practical applications. Summary of the invention

[0009] The present invention provides a method for correcting positioning errors of a multi-satellite joint observation system based on a rendezvous constraint, which can realize correction of positioning errors of the multi-satellite joint observation system and high-precision positioning of space targets.

[0010] A method for correcting positioning errors of a multi-satellite joint observation system based on a rendezvous constraint comprises the following steps:

[0011] (1) Based on the multi-satellite joint observation system, obtain multi-satellite joint observation images of the same time, the same area, and different viewing angles;

[0012] (2) Extracting the connection points of the overlapping areas of the field of view in multi-satellite joint observation images;

[0013] (3) Based on the geometric imaging principle of the space-based array optoelectronic payload, a geometric positioning model for each sensor in the multi-satellite joint observation system is constructed;

[0014] (4) Construct intersection constraints between connection points in the common field of view area of ​​the multi-satellite joint observation system based on connection points;

[0015] (5) Based on the rendezvous constraint relationship, make preliminary corrections to the relative positioning errors between multi-satellite joint observation systems;

[0016] (6) Based on the iterative least squares algorithm, the calibration parameters of the multi-satellite joint observation system are optimized and the error correction is finally completed.

[0017] In step (1), in the multi-satellite joint observation image, there is an overlapping area in the observation field of each satellite. In order to ensure the intersection constraint effect, the minimum overlapping area is not less than 50% of the observation field of each satellite.

[0018] The specific process of step (2) is as follows:

[0019] For the overlapping areas of the field of view in multi-satellite joint observation images, the Moravec corner point extraction operator is used to obtain a large number of connection point pairs from the overlapping areas of the field of view; at the same time, the regional non-maximum suppression algorithm is used to eliminate weak corner points and ensure the uniformity of corner point distribution; finally, the RANSAC algorithm is used to eliminate the mismatched connection point pairs between images to ensure the extraction accuracy of the connection points in the overlapping area. The connection point pairs are represented as follows:

[0020]

[0021] Among them, TiePoints is the set of connection points extracted from the overlapping area of ​​multi-satellite joint observation; is the i-th connection point in the j-th observation satellite image. N is the number of connection points.

[0022] In step (3), the geometric positioning model of each sensor of the multi-satellite joint observation system is constructed, and the expression is as follows:

[0023]

[0024] In the formula, is the spatial coordinates of the image point coordinates (r, c) of the connection point in the on-orbit image pixel coordinate system in the Earth-centered Earth-fixed coordinate system; is the position vector of the satellite projection center in the Earth-centered Earth-fixed coordinate system; λ is the scale factor; is the transformation relationship between the Earth-centered inertial coordinate system and the Earth-centered Earth-fixed coordinate system; is the transformation matrix from the satellite body coordinate system to the geocentric inertial coordinate system, calculated by the satellite attitude angle (p, r, y); p, r, y are the satellite pitch angle, roll angle and yaw angle respectively; is the calibrated installation matrix of the camera sensor in the satellite body coordinate system. The three installation angles (α, β, γ) of the installation matrix have been accurately calibrated before the satellite is launched. (r0, c0) are the coordinates of the principal point of the camera sensor in the pixel coordinate system. Δr0, Δc0 are the principal point offset errors. dx, dy are the offset errors of the image point on the image plane. λ x ,λ y is the size of the pixel in the x and y directions; f is the principal distance of the camera sensor; ||·|| represents the normalized unit vector.

[0025] The specific process in step (4) is as follows:

[0026] Taking three satellites as an example, for a pair of connection points obtained by the multi-satellite joint observation system, the intersection constraint relationship of the connection point pair is obtained according to the internal and external orientation elements initially calibrated by each camera sensor and the position and attitude data of the satellites in orbit at the time of observation:

[0027]

[0028] in, is the outgoing vector of the i-th connection point in the three camera sensor coordinate systems, j = 1, 2, 3; is the position vector of the ith connection point in the Earth-centered Earth-fixed coordinate system; the subscript numbers in the above formula represent the satellite numbers; Represents the position vector of the satellite projection center in the Earth-centered Earth-fixed coordinate system.

[0029] The specific process of step (5) is as follows:

[0030] First, according to the calibrated internal and external orientation elements of the camera sensor carried by satellite 1 and the position and attitude data at the time of observation, the object space coordinates corresponding to the connection points obtained by satellite 1 are calculated through the geometric positioning model; then, the connection points of satellite 1 and their corresponding ground coordinates are combined into ground control point pairs, and the calibration and update of the internal and external calibration parameters of the camera sensors of satellite 2 and satellite 3 are completed based on this control reference;

[0031] Similarly, according to the calibrated internal and external orientation elements of the camera sensor carried by satellite 2 and the position and attitude data at the time of observation, the object space coordinates corresponding to the connection points obtained by satellite 2 are calculated through the geometric positioning model; then, the connection points of satellite 2 and their corresponding ground coordinates are combined into ground control point pairs, and the calibration and update of the internal and external calibration parameters of the camera sensors of satellite 1 and satellite 3 are completed based on this control reference;

[0032] By analogy, after satellite 3 completes the above operations, it completes the preliminary correction of the relative positioning error between the multi-satellite joint observation systems.

[0033] The specific process of step (6) is as follows:

[0034] Assume that the connection points of satellite 1 and their corresponding ground coordinates form ground control point pairs to complete the calibration of the internal and external calibration parameters of satellite 2 camera sensor and satellite 3 camera sensor; then, according to the geometric positioning models of the calibrated satellite 2 camera sensor and satellite 3 camera sensor, the ground coordinates of their corresponding connection points are obtained respectively. and Based on the iterative least squares algorithm, the model parameters are optimized by minimizing the error between the two satellite connection points and the ground coordinates, as follows:

[0035]

[0036] Repeat the iterative calculation until the ground distance error of the connection point is less than the set threshold, and the threshold is set to 0.1 pixel; N is the number of connection points;

[0037] Similarly, the ground coordinate errors of the connection points between satellite 1 sensor and satellite 3 sensor, and satellite 1 sensor and satellite 2 sensor are optimized based on the iterative least squares algorithm:

[0038]

[0039] In the formula, X I represents the calibration parameters in the satellite camera sensor, X E Represents the external calibration parameters of the satellite camera sensor.

[0040] Based on the above method, the relative error correction of the multi-satellite joint positioning system can be completed. When the number of satellites is more than three, the method of the present invention is also applicable.

[0041] Compared with the prior art, the present invention has the following beneficial effects:

[0042] The present invention extracts the connection points of the on-orbit images acquired by the multi-satellite joint observation system at the same time, the same area, and different observation angles, constructs the spatial constraint relationship between the connection points, realizes the relative calibration between the sensors of the multi-satellite joint observation system, eliminates the relative positioning error between the sensors of the joint positioning system, and improves the positioning accuracy and stability of the space target. The present invention can ultimately realize the correction of the positioning error of the multi-satellite joint observation system and the high-precision positioning of the space target. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 This is a flow chart of a positioning error correction method for a multi-satellite joint observation system based on intersection constraints according to the present invention;

[0044] Figure 2 Schematic diagram of a multi-satellite joint positioning system in an embodiment of the present invention. DETAILED DESCRIPTION

[0045] The present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be pointed out that the embodiments described below are intended to facilitate the understanding of the present invention and do not have any limiting effect on the present invention.

[0046] like Figure 1As shown in the figure, a method for correcting positioning errors of a multi-satellite joint observation system based on intersection constraints is provided. Firstly, on-orbit images of the same time, the same area and different observation angles are obtained based on the multi-satellite joint observation system; then, the connection point extraction algorithm is used to extract the same-name connection point pairs in the overlapping area of ​​the multi-satellite joint observation images; secondly, a strict positioning model of each sensor of the multi-satellite joint observation system is constructed according to the attitude and orbit data of the on-orbit satellites and the design parameters of the optical sensor imaging system, and the intersection constraint relationship between the multiple satellites is established based on the connection points; finally, the positioning error correction of the multi-satellite joint observation system is realized based on the spatial constraint relationship, and the iterative least squares algorithm is used to optimize the calibration parameters to obtain the global optimal solution of the calibration parameters of the multi-satellite joint observation system, so as to realize the relative calibration between the sensors of the multi-satellite joint observation system, eliminate the relative positioning error between the sensors of the joint positioning system, and improve the positioning accuracy of space targets.

[0047] The present invention mainly comprises the following steps:

[0048] S01. Obtain multi-star joint observation data at the same time, in the same area, and from different perspectives.

[0049] like Figure 2 As shown in the figure, each satellite in the multi-satellite joint positioning system is equipped with a large field of view optical sensor. At time t, each satellite in the multi-satellite joint positioning system obtains the joint observation image of the target area, and there is an overlapping area in the observation field of each satellite. In order to ensure the rendezvous constraint effect, the minimum overlapping area is not less than 50% of the field of view. Figure 2 The shaded area shown in the figure is the joint observation image acquired by the multi-satellite joint observation system at the same time, in the same area, and at different observation angles. This data lays the data foundation for the subsequent correction of relative positioning errors between sensors.

[0050] S02. Extraction of connection points in the common field of view area of ​​multi-satellite joint observation images.

[0051] For the images in the overlapping areas of the multi-satellite joint observation field of view, the Moravec corner point extraction operator is used to obtain a large number of connection point pairs from the overlapping areas of the multi-satellite joint observation images. At the same time, the regional non-maximum suppression algorithm is used to eliminate weak corner points and ensure the uniformity of corner point distribution. Finally, the RANSAC algorithm is used to eliminate the mismatched connection point pairs between images to ensure the extraction accuracy of the connection points in the overlapping areas. The connection point pairs are represented as follows:

[0052]

[0053] Among them, TiePoints is the set of connection points extracted from the overlapping area of ​​multi-satellite joint observation; is the i-th connection point in the j-th observation satellite image; N is the number of connection points.

[0054] S03. Construction of strict positioning model for sensors in multi-satellite joint observation system

[0055] According to the geometric imaging principle of the space-based array optoelectronic payload, a strict geometric positioning model of each sensor in the multi-satellite joint observation system is constructed, and the expression is:

[0056]

[0057] in, is the spatial coordinates of the image point coordinates (r, c) of the connection point in the on-orbit image pixel coordinate system in the Earth-centered Earth-fixed coordinate system; is the position vector of the satellite projection center in the Earth-centered Earth-fixed coordinate system; λ is the scale factor; is the transformation relationship between the Earth-centered inertial coordinate system and the Earth-centered Earth-fixed coordinate system; It is the transformation matrix from the satellite body coordinate system to the geocentric inertial coordinate system. Usually, the satellite attitude angle (p, r, y) is calculated. p, r, y are the three attitude angles of the satellite: pitch angle, roll angle and yaw angle. is the calibrated installation matrix of the camera in the satellite body coordinate system. The three installation angles (α, β, γ) of the installation matrix have been accurately calibrated before the satellite is launched. α, β, γ are the three installation angles of the payload. (r0, c0) are the coordinates of the camera principal point in the pixel coordinate system. Δr0, Δc0 are the principal point offset errors. dx, dy are the offset errors of the image point on the image plane. λ x ,λ y are the dimensions of the pixel in the x and y directions; f is the camera principal distance; ||·|| represents the normalized unit vector.

[0058] As shown in formula (1), the principal point, principal distance and distortion are the internal orientation parameters of the large array payload on orbit, and the installation angle between the payload and the satellite platform is the external orientation parameter. On-orbit positioning is to achieve positioning model parameter correction by accurately solving the internal and external orientation parameters. In order to avoid the correlation of internal parameters, a two-dimensional pointing angle model is used for characterization, and the emission vector in the camera coordinate system is obtained as:

[0059]

[0060] Among them, a0…a9, b0…b9 are the calibration parameters of the two-dimensional pointing angle model, (r,c) are the row and column coordinates of the pixel, is the outgoing vector in the corresponding camera coordinate system, It is the two-dimensional pointing angle of the pixel (r,c) in the x and y directions.

[0061] Then formula (1) can be simplified as

[0062]

[0063] The definitions of the variables are the same as those in formula (1).

[0064] S04. Construction of intersection constraint relationship of connection points in the common field of view area of ​​multi-satellite joint observation system.

[0065] If Figure 2 As shown in FIG. 1 , TP1, TP2 and TP3 are a pair of connection points obtained by the multi-satellite joint positioning system in step S2. According to the internal and external orientation elements initially calibrated by each payload and the position and attitude data of the satellites in orbit at the time of observation, the intersection constraint relationship of the connection point pair can be obtained as follows:

[0066]

[0067] in, is the outgoing vector of the i-th connection point in the three payload camera coordinate systems; is the position vector of the ith connection point in the geocentric fixed coordinate system; the definitions of the variables are the same as those in equation (1), and the subscripts represent the satellite numbers.

[0068] S05. Positioning error correction of multi-satellite joint observation system based on rendezvous constraints.

[0069] First, based on the calibrated internal and external orientation elements of the sensor carried by satellite 1 and the position and attitude data at the time of observation, the object coordinates corresponding to the connection points obtained by satellite 1 are calculated through a strict geometric positioning model (Formula 1) as follows:

[0070]

[0071] in, Connection point for satellite 1 The corresponding position coordinates in the Earth-centered Earth-fixed coordinate system; F represents formula (1);

[0072] Then, the connection points of satellite 1 and their corresponding ground coordinates are combined into ground control point pairs, and the calibration and update of the internal and external calibration parameters of the satellite 2 sensor and the satellite 3 sensor are completed based on this control reference;

[0073] Similarly, based on the calibrated internal and external orientation elements of the sensor carried by Satellite 2 and the position and attitude data at the time of observation, the object coordinates corresponding to the connection points obtained by Satellite 2 are calculated through a strict geometric positioning model (Formula 1) as follows:

[0074]

[0075] in, Connection point for satellite 2 The corresponding position coordinates in the geocentric fixed coordinate system; F represents formula (1);

[0076] The connection points of satellite 2 and their corresponding ground coordinates are combined into ground control point pairs, and the calibration and update of the internal and external calibration parameters of satellite 1 and satellite 3 sensors are completed based on this control reference;

[0077] According to the calibrated internal and external orientation elements of the sensor carried by satellite 3 and the position and attitude data at the time of observation, the object coordinates corresponding to the connection points obtained by satellite 3 are calculated through a strict geometric positioning model (Formula 1) as follows:

[0078]

[0079] in, Connection point for satellite 2 The corresponding position coordinates in the geocentric fixed coordinate system; F represents formula (1);

[0080] The connection points of satellite 3 and their corresponding ground coordinates are combined into ground control point pairs, and the calibration and update of the internal and external calibration parameters of satellite 1 sensor and satellite 2 sensor are completed based on this pair of ground control points.

[0081] The above steps can complete the preliminary correction of the relative positioning error between multi-satellite joint observation systems.

[0082] S06. Calibration parameter optimization of multi-satellite joint observation system based on iterative least squares.

[0083] According to the method described in step S5, it is assumed that the connection points of satellite 1 and their corresponding ground coordinates form ground control points to complete the calibration of the internal and external calibration parameters of the satellite 2 sensor and the satellite 3 sensor. Then, according to the strict geometric positioning model of the calibrated satellite 2 sensor and the satellite 3 sensor, the ground coordinates of the corresponding connection points can be obtained respectively. and Based on the iterative least squares algorithm, the model parameters can be optimized by minimizing the error between the two satellite connection points and the ground coordinates, as follows:

[0084]

[0085] Repeat the iterative calculation until the ground distance error of the connection point is less than the set threshold. This method can set the constraint threshold to 0.1 pixel. N is the number of connection points.

[0086] Similarly, the ground coordinate errors of the connection points between satellite 1 sensor and satellite 3 sensor, and satellite 1 sensor and satellite 2 sensor are optimized based on the iterative least squares algorithm:

[0087]

[0088] Based on the above method, the relative error correction of the multi-satellite joint positioning system can be completed. When the number of satellites is more than three, the method of the present invention is also applicable.

[0089] The embodiments described above provide a detailed description of the technical solutions and beneficial effects of the present invention. It should be understood that the above are only specific embodiments of the present invention and are not intended to limit the present invention. Any modifications, supplements and equivalent substitutions made within the scope of the principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A positioning error correction method for a multi-satellite joint observation system based on conjunction constraints, characterized in that: The following steps are involved: (1) Based on the multi-satellite joint observation system, obtain multi-satellite joint observation images of the same time, the same area, and different viewing angles; (2) Extracting the connection points of the overlapping areas of the field of view in multi-satellite joint observation images; (3) Based on the geometric imaging principle of the space-based array optoelectronic payload, a geometric positioning model for each sensor in the multi-satellite joint observation system is constructed; (4) Construct intersection constraints between connection points in the common field of view area of ​​the multi-satellite joint observation system based on connection points; (5) Based on the rendezvous constraint relationship, make preliminary corrections to the relative positioning errors between multi-satellite joint observation systems; (6) Based on the iterative least squares algorithm, the calibration parameters of the multi-satellite joint observation system are optimized and the error correction is finally completed.

2. The positioning error correction method of a multi-satellite joint observation system based on conjunction constraint according to claim 1 is characterized in that: In step (1), in the multi-satellite joint observation image, the observation field of each satellite has an overlapping area, and the minimum overlapping area is not less than 50% of the observation field of each satellite.

3. The positioning error correction method of a multi-satellite joint observation system based on conjunction constraint according to claim 1 is characterized in that: The specific process of step (2) is as follows: For the overlapping areas of the field of view in multi-satellite joint observation images, the Moravec corner point extraction operator is used to obtain a large number of connection point pairs from the overlapping areas of the field of view. At the same time, the regional non-maximum suppression algorithm is used to eliminate weak corner points and ensure the uniformity of corner point distribution. Finally, the RANSAC algorithm is used to eliminate the mismatched connection point pairs between images to ensure the extraction accuracy of the connection points in the overlapping areas.

4. The positioning error correction method of a multi-satellite joint observation system based on conjunction constraint according to claim 1 is characterized in that: In step (3), the geometric positioning model of each sensor of the multi-satellite joint observation system is constructed, and the expression is as follows: In the formula, is the spatial coordinates in the Earth-centered Earth-fixed coordinate system corresponding to the image point coordinates (r, c) of the connection point in the on-orbit image pixel coordinate system; is the position vector of the satellite projection center in the Earth-centered Earth-fixed coordinate system; λ is the scale factor; is the transformation relationship between the Earth-centered inertial coordinate system and the Earth-centered Earth-fixed coordinate system; is the transformation matrix from the satellite body coordinate system to the geocentric inertial coordinate system, calculated by the satellite attitude angle (p, r, y); p, r, y are the satellite pitch angle, roll angle and yaw angle respectively; is the calibrated installation matrix of the camera sensor in the satellite body coordinate system. The three installation angles (α, β, γ) of the installation matrix have been accurately calibrated before the satellite is launched. (r0, c0) are the coordinates of the principal point of the camera sensor in the pixel coordinate system. Δr0, Δc0 are the principal point offset errors. dx, dy are the offset errors of the image point on the image plane. λ x ,λ y is the size of the pixel in the x and y directions; f is the principal distance of the camera sensor; ||·|| represents the normalized unit vector.

5. The positioning error correction method of a multi-satellite joint observation system based on conjunction constraint according to claim 4 is characterized in that: The specific process of step (4) is as follows: Taking three satellites as an example, for a pair of connection points obtained by the multi-satellite joint observation system, the intersection constraint relationship of the connection point pair is obtained according to the internal and external orientation elements initially calibrated by each camera sensor and the position and attitude data of the satellites in orbit at the time of observation: in, is the outgoing vector of the i-th connection point in the three camera sensor coordinate systems, j = 1, 2, 3; is the position vector of the ith connection point in the Earth-centered Earth-fixed coordinate system; the subscript numbers in the above formula represent the satellite numbers; Represents the position vectors of the three satellite projection centers in the Earth-centered Earth-fixed coordinate system.

6. The positioning error correction method of a multi-satellite joint observation system based on conjunction constraint according to claim 4 is characterized in that: The specific process of step (5) is as follows: First, according to the calibrated internal and external orientation elements of the camera sensor carried by satellite 1 and the position and attitude data at the time of observation, the object space coordinates corresponding to the connection points obtained by satellite 1 are calculated through the geometric positioning model; then, the connection points of satellite 1 and their corresponding ground coordinates are combined into ground control point pairs, and the calibration and update of the internal and external calibration parameters of the camera sensors of satellite 2 and satellite 3 are completed based on this control reference; Similarly, according to the calibrated internal and external orientation elements of the camera sensor carried by satellite 2 and the position and attitude data at the time of observation, the object space coordinates corresponding to the connection points obtained by satellite 2 are calculated through the geometric positioning model; then, the connection points of satellite 2 and their corresponding ground coordinates are combined into ground control point pairs, and the calibration and update of the internal and external calibration parameters of the camera sensors of satellite 1 and satellite 3 are completed based on this control reference; By analogy, after satellite 3 completes the above operations, it completes the preliminary correction of the relative positioning error between the multi-satellite joint observation systems.

7. The positioning error correction method of a multi-satellite joint observation system based on conjunction constraint according to claim 6 is characterized in that: The specific process of step (6) is as follows: Assume that the connection points of satellite 1 and their corresponding ground coordinates form ground control point pairs to complete the calibration of the internal and external calibration parameters of satellite 2 camera sensor and satellite 3 camera sensor; then, according to the geometric positioning models of the calibrated satellite 2 camera sensor and satellite 3 camera sensor, the ground coordinates of their corresponding connection points are obtained respectively. and Based on the iterative least squares algorithm, the model parameters are optimized by minimizing the error between the two satellite connection points and the ground coordinates, as follows: Repeat the iterative calculation until the ground distance error of the connection point is less than the set threshold; N is the number of connection points; Similarly, the ground coordinate errors of the connection points between satellite 1 sensor and satellite 3 sensor, and satellite 1 sensor and satellite 2 sensor are optimized based on the iterative least squares algorithm: Where, X I represents the calibration parameters of the satellite camera sensor, X E Represents the external calibration parameters of the satellite camera sensor.

8. The positioning error correction method of a multi-satellite joint observation system based on conjunction constraint according to claim 7 is characterized in that: Set the threshold to 0.1 pixel.

Images