A space situational awareness simulation system based on improved Blensor software

Abstract

The present invention discloses a space situational awareness simulation system based on improved Blensor software, which relates to the field of space situational awareness and includes an attitude and orbit dynamics module, a Blensor three-dimensional visualization module, a constellation performance evaluation module, a sensor module, an information acquisition module, an information extraction and processing module, and an orbit determination analysis module. The system implements visual simulation of satellites and satellite constellations in near-Earth space and simulation of the overall process of situational awareness. The attitude and orbit dynamics module environment code script is implanted into the Blensor software to establish the attitude and orbit dynamics of the spacecraft and its three-dimensional model construction. The operation of the system is divided into a full information subsystem and a self-awareness system. The constellation performance evaluation module evaluates the effectiveness of the established satellite constellation model based on its coverage. The present invention discloses a space situational awareness simulation system based on improved Blensor software, which can simulate the overall process of situational awareness of satellites and satellite constellations in near-Earth space and can be applied to computer visualization and digital simulation of space situational awareness.

Description

Technical Field

[0001] The present invention relates to the field of space situational awareness, and in particular to a space situational awareness simulation system based on improved Blensor software. Background Art

[0002] Satellite and satellite constellation launches are expensive, development cycles are long, and the space environment is highly volatile. Using effective digital simulation systems to effectively simulate and reveal the states and processes of perception satellites and constellations operating in near-Earth space is a key approach to improving the effectiveness of perception satellite operations. Information products derived from space situational awareness research require processing acquired information about space targets and the space environment. Within a specific space environment, intelligent processing is performed to capture the relative positions, identities, and capabilities of space targets. This information captures individual space targets, their relationships with groups, and their local and global relationships, providing descriptive products such as documents, charts, and three-dimensional information that meet the requirements of different levels of space activities. Simulating satellite and constellation observations and performing situational awareness is a challenging task. This requires simulating the satellite's attitude and orbit dynamics, sensor observations, onboard and offboard processing, and orbit determination, placing high demands on the information system.

[0003] Currently, both domestic and international software for spacecraft digital simulations is relatively mature, such as STK (foreign) and Spacesim (foreign). STK (foreign) can implement satellite attitude and orbit dynamics and maneuvers, simulate 2D camera observations, establish constellations, and transmit satellite links. However, it lacks open source support and cannot simulate onboard processing and calculations, nor does it implement final situational prediction. Regarding actual space situational awareness, mature business processes exist abroad, including mission planning and information support systems, space target surveillance and identification systems, and space environment monitoring and early warning systems. However, this process and system lacks research and practical application in China.

[0004] Therefore, it is necessary to provide a space situational awareness simulation system based on improved Blensor software to solve the above problems. Summary of the Invention

[0005] The purpose of this invention is to provide a space situational awareness simulation system based on improved Blensor software, which implements digital simulation of the perception of known and unknown targets in space, as well as situation prediction and orbit determination. The perception system implemented with the improved Blensor software features a series of computational modules, including constellation coverage benefit assessment, multi-sensor, target extraction, target positioning, and orbit determination. It is suitable for computer-based space perception simulation of single spacecraft and satellite constellations, and achieves the requirements for three-dimensional visualization of the process.

[0006] To achieve the above objectives, the present invention provides a space situational awareness simulation system based on improved Blensor software, including an attitude and orbit dynamics module, a Blensor 3D visualization module, a constellation performance evaluation module, a sensor module, an information acquisition module, an information extraction and processing module, and an orbit determination analysis module. The system specifically includes the following steps:

[0007] S1: The attitude and orbit dynamics module is written in Python and connected to the Blensor 3D visualization module through its API. It uses program statements to implement programmatic attitude, orbit, and 3D model modeling.

[0008] S2: The constellation performance evaluation module selects the required detection target range and number of sampling points to evaluate the constellation coverage and geometric distribution characteristics;

[0009] S3: Add sensor modules to the established Blensor 3D model, generate corresponding models based on the sensor style, parameters, attitude, and offset, and generate the full information subsystem and self-perception system based on the different spacecraft identifications;

[0010] S4: Establish a constellation model of our own spacecraft in our own perception system, conduct an overall assessment and analysis based on the target coverage area, and implement a distribution uniformity index assessment and display of under-distributed areas based on distribution characteristics.

[0011] S5: Use the acquisition script embedded in the Blensor software to realize the automatic acquisition function of the sensor module and output the acquisition results. Different sensor types set in the sensor module output the corresponding acquisition data result format;

[0012] S6: Input the data output in step S5 into the feature extraction processing module to extract the centroid and shape feature values;

[0013] S7: The information extracted in step S6 is input into the orbit determination analysis module. The orbit determination analysis module selects the corresponding scenario algorithm to perform orbit determination calculation. The calculated result is input into the own perception system and the orbit and current position of the perceived target are displayed in three dimensions in the system.

[0014] Preferably, in step S1, each dynamic environment is established according to the time in the Blensor software and the position and attitude commands in the script, and the existing modeling model is added to realize the rapid addition of the spacecraft three-dimensional model.

[0015] Preferably, in step S3, the full information subsystem includes an attitude and orbit dynamics module, a Blensor three-dimensional visualization module, a constellation performance evaluation module and a sensor module, and also includes all created spacecraft models, space debris models and celestial body models such as the earth, which are used to simulate the real physical environment.

[0016] Preferably, in step S3, the own perception system includes an information extraction and processing module and an orbit determination analysis module for obtaining own spacecraft information, celestial body information and perceived information, and the own spacecraft is equipped with a sensor module and an information acquisition module.

[0017] Preferably, in step S4, the following steps are specifically included:

[0018] S41: Using the geometric dilution of precision (GDOP) as the core indicator, analyze coverage characteristics and uniform distribution in the target coverage area.

[0019] S42: Conduct different process analyses based on the types of target missions established, including global surface coverage and near-Earth space coverage;

[0020] S421: Global land coverage is achieved by setting up sampling points evenly on the earth, with the number of sampling points set according to computer performance;

[0021] S422: performing GDOP calculation on the three-dimensional coordinates of the sampling points set in step S421 and the three-dimensional coordinates of the constellation to obtain the total GDOP values ​​of various parts of the world and a four-dimensional distribution map;

[0022] S423: The four-dimensional distribution map uses color as the GDOP measurement value on the three-dimensional earth map to display the distribution value and statistics. The under-distributed areas are displayed as areas with higher GDOP values.

[0023] S424: Near-Earth space coverage is achieved by setting the altitude range of the near-Earth space according to the target mission and establishing evenly distributed sampling points based on computing performance.

[0024] S425: performing GDOP calculation on the three-dimensional coordinates of the uniformly distributed sampling points and the three-dimensional coordinates of the constellation in step S424 to obtain the GDOP value of the target near-Earth space and a distribution four-dimensional map, and displaying the under-distributed areas as areas with higher GDOP values.

[0025] Preferably, in step S6, different models are adopted for different types of sensor outputs, and after noise reduction processing is performed using a denoising module, different extraction methods are adopted according to the differences in target traces in the two-dimensional image and the three-dimensional image, specifically including:

[0026] Point target location extraction: using χ 2The initial center of mass is obtained by fitting, and the current value is used as the initial value to establish an effective point spread function, and the target is fitted to obtain the final center of mass position;

[0027] Initial linear target extraction: Based on the existing posture of the own sensor and the position of the linear target's pixels in the image, the target's orientation information within the exposure time is calculated;

[0028] Depth image target positioning and extraction: For the target information in the depth image, the centroid method is used to perform preliminary centroid positioning, and then the digital correlation method is used to accurately locate the target.

[0029] Preferably, in step S7, the model in the orbit determination analysis module adopts a dual-vector orbit determination model, a three-vector orbit determination model or a multi-observation vector orbit determination model.

[0030] Preferably, the sensor module includes a 2D planar camera, a depth camera, a laser radar, a phased array radar and a synthetic aperture radar.

[0031] Therefore, the present invention utilizes the aforementioned space situational awareness simulation system based on improved Blensor software, achieving digital simulation of the perception of known and unknown targets in space, as well as situation prediction and orbit determination. The perception system implemented with the improved Blensor software features a series of computational modules, including constellation coverage benefit assessment, multi-sensor, target extraction, target positioning, and orbit determination. It is suitable for computer-based spatial perception simulation of single spacecraft and satellite constellations, and achieves the requirements for three-dimensional visualization of the process.

[0032] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 This is a schematic diagram of the composition of the space situational awareness digital simulation system provided by the present invention;

[0034] Figure 2 This is a diagram showing the effect of the constellation performance evaluation module provided by the present invention when it is running;

[0035] Figure 3 This is a diagram showing the effect of the full information subsystem provided by the present invention when it is running;

[0036] Figure 4 This is a diagram showing the effect of the self-perception subsystem provided by the present invention when it is in operation. DETAILED DESCRIPTION

[0037] The technical solution of the present invention is further described below with reference to the accompanying drawings and embodiments.

[0038] Unless otherwise defined, technical or scientific terms used in the present invention shall have the same meaning as commonly understood by one of ordinary skill in the art to which the present invention belongs.

[0039] The words “include” or “comprising” and similar words used in the present invention mean that the elements before the word include the elements listed after the word, and do not exclude the possibility of also including other elements. The orientation or position relationship indicated by the terms “inside”, “outside”, “upper”, “lower”, etc. is based on the orientation or position relationship shown in the accompanying drawings. It is only for the convenience of describing the present invention and simplifying the description, and does not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation of the present invention. When the absolute position of the described object changes, the relative position relationship may also change accordingly. In the present invention, unless otherwise clearly stipulated and limited, the terms such as “attachment” should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral whole; it can be directly connected or indirectly connected through an intermediate medium, and it can be the internal connection of two elements or the interaction relationship between two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to the specific circumstances.

[0040] like Figure 1 As shown, the present invention provides a space situational awareness simulation system based on improved Blensor software, including an attitude and orbit dynamics module, a Blensor 3D visualization module, a constellation performance evaluation module, a sensor module, an information acquisition module, an information extraction and processing module, and an orbit determination analysis module. The sensor module includes a 2D planar camera, a depth camera, a lidar, a phased array radar, and a synthetic aperture radar. Specifically, the system includes the following steps:

[0041] S1: The attitude and orbit dynamics module is written in Python and connected to the API interface of the Blensor 3D visualization module. The modeling of programmed attitude, orbit and 3D model is realized through program statements. In step S1, the establishment of each dynamic environment is realized according to the time in the Blensor software and the position and attitude commands in the script, and the existing modeling models are added to realize the rapid addition of the spacecraft 3D model.

[0042] S2: The constellation performance evaluation module selects the required detection target range and the number of sampling points to evaluate the constellation coverage and geometric distribution characteristics; the evaluation results are as follows: Figure 2 shown.

[0043] S3: Add sensor modules to the established Blensor 3D model, generate corresponding models according to the sensor style, parameters, attitude and offset, and generate full information subsystem and self-perception system according to the different spacecraft identification; in step S3, if Figure 3 As shown in the figure, the full information subsystem includes the attitude and orbit dynamics module, the Blensor 3D visualization module, the constellation performance evaluation module, and the sensor module. It also includes models of all spacecraft, space debris, and celestial bodies such as the Earth, used to simulate the real physical environment. The constellation performance evaluation module evaluates the effectiveness of the established satellite constellation model based on its coverage.

[0044] In step S3, Figure 4 As shown, the own perception system includes an information extraction and processing module and an orbit determination analysis module, which are used to obtain the own spacecraft information, celestial body information and perceived information. The own spacecraft is equipped with a sensor module and an information acquisition module.

[0045] S4: A constellation model of the own spacecraft is established in the own perception system, and an overall assessment and analysis is performed based on the target coverage area. Based on the distribution characteristics, a distribution uniformity index assessment and under-distributed area display are implemented. In step S4, the following steps are specifically included:

[0046] S41: Using the geometric dilution of precision (GDOP) as the core indicator, analyze coverage characteristics and uniform distribution in the target coverage area.

[0047] S42: Conduct different process analyses based on the types of target missions established, including global surface coverage and near-Earth space coverage;

[0048] S421: Global land coverage is achieved by setting up sampling points evenly on the earth, with the number of sampling points set according to computer performance;

[0049] S422: performing GDOP calculation on the three-dimensional coordinates of the sampling points set in step S421 and the three-dimensional coordinates of the constellation to obtain the total GDOP values ​​of various parts of the world and a four-dimensional distribution map;

[0050] S423: The four-dimensional distribution map uses color as the GDOP measurement value on the three-dimensional earth map to display the distribution value and statistics. The under-distributed areas are displayed as areas with higher GDOP values.

[0051] S424: Near-Earth space coverage is achieved by setting the altitude range of the near-Earth space according to the target mission and establishing evenly distributed sampling points based on computing performance.

[0052] S425: performing GDOP calculation on the three-dimensional coordinates of the uniformly distributed sampling points and the three-dimensional coordinates of the constellation in step S424 to obtain the GDOP value of the target near-Earth space and a distribution four-dimensional map, and displaying the under-distributed areas as areas with higher GDOP values.

[0053] S5: Use the acquisition script embedded in the Blensor software to realize the automatic acquisition function of the sensor module and output the acquisition results. Different sensor types set in the sensor module output the corresponding acquisition data result format;

[0054] S6: The data output in step S5 is input into the feature extraction processing module to extract the centroid and shape feature values. In step S6, different models are adopted for different types of sensor outputs. After noise reduction processing is performed using the denoising module, different extraction methods are adopted according to the different target traces in the two-dimensional image and the three-dimensional image. Specifically, the following methods are used:

[0055] Point target location extraction: using χ 2 The initial center of mass is obtained by fitting, and the current value is used as the initial value to establish an effective point spread function, and the target is fitted to obtain the final center of mass position;

[0056] Initial linear target extraction: Based on the existing posture of the own sensor and the position of the linear target's pixels in the image, the target's orientation information within the exposure time is calculated;

[0057] Depth image target positioning and extraction: For the target information in the depth image, the centroid method is used to perform preliminary centroid positioning, and then the digital correlation method is used to accurately locate the target.

[0058] S7: The information extracted in step S6 is input into the orbit determination analysis module. The orbit determination analysis module selects the corresponding scenario algorithm to perform orbit determination calculation. The calculated result is input into the own perception system and the orbit and current position of the perceived target are displayed in three dimensions in the system.

[0059] In step S7, the model in the orbit determination analysis module adopts a dual-vector orbit determination model, a three-vector orbit determination model or a multi-observation vector orbit determination model.

[0060] Therefore, the present invention utilizes the aforementioned space situational awareness simulation system based on improved Blensor software, enabling simulation of space target situational awareness using sensors onboard satellites and constellations on a computer. This system can be configured with different observation tasks for different application scenarios, expanding the digital simulation methodologies for situational awareness in near-Earth space and enabling verification of algorithms for constellation architecture, control, and orbit determination.

[0061] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit the same. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that they can still modify or replace the technical solutions of the present invention with equivalents, and these modifications or equivalent replacements cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A space situational awareness simulation system based on improved Blensor software, characterized by: It includes attitude and orbit dynamics module, Blensor 3D visualization module, constellation performance evaluation module, sensor module, information acquisition module, information extraction and processing module, and orbit determination analysis module. Specifically, it includes the following steps: S1: The attitude and orbit dynamics module is written in Python and connected to the Blensor 3D visualization module through its API. It uses program statements to implement programmatic attitude, orbit, and 3D model modeling. S2: The constellation performance evaluation module selects the required detection target range and number of sampling points to evaluate the constellation coverage and geometric distribution characteristics; S3: Add sensor modules to the established Blensor 3D model, generate corresponding models based on the sensor style, parameters, attitude, and offset, and generate the full information subsystem and self-perception system based on the different spacecraft identifications; S4: Establish a constellation model of our own spacecraft in our own perception system, conduct an overall assessment and analysis based on the target coverage area, and implement a distribution uniformity index assessment and display of under-distributed areas based on distribution characteristics. In step S4, the following steps are specifically included: S41: Using the geometric dilution of precision (GDOP) as the core indicator, analyze coverage characteristics and uniform distribution in the target coverage area. S42: Conduct different process analyses based on the types of target missions established, including global surface coverage and near-Earth space coverage; S421: Global land coverage is achieved by setting up sampling points evenly on the earth, with the number of sampling points set according to computer performance; S422: performing GDOP calculation on the three-dimensional coordinates of the sampling points set in step S421 and the three-dimensional coordinates of the constellation to obtain the total GDOP values ​​of various parts of the world and a four-dimensional distribution map; S423: The four-dimensional distribution map uses color as the GDOP measurement value on the three-dimensional earth map to display the distribution value and statistics. The under-distributed areas are displayed as areas with higher GDOP values. S424: Near-Earth space coverage is achieved by setting the altitude range of the near-Earth space according to the target mission and establishing evenly distributed sampling points based on computing performance. S425: performing GDOP calculation on the three-dimensional coordinates of the uniformly distributed sampling points and the three-dimensional coordinates of the constellation in step S424 to obtain the GDOP value of the target near-Earth space and a four-dimensional distribution map, and displaying the under-distributed areas as areas with higher GDOP values; S5: Use the acquisition script embedded in the Blensor software to realize the automatic acquisition function of the sensor module and output the acquisition results. Different sensor types set in the sensor module output the corresponding acquisition data result format; S6: Input the data output in step S5 into the feature extraction processing module to extract the centroid and shape feature values; S7: The information extracted in step S6 is input into the orbit determination analysis module. The orbit determination analysis module selects the corresponding scenario algorithm to perform orbit determination calculation. The calculated result is input into the own perception system and the orbit and current position of the perceived target are displayed in three dimensions in the system.

2. A space situational awareness simulation system based on improved Blensor software according to claim 1, characterized in that: In step S1, the establishment of each dynamic environment is realized according to the time in the Blensor software and the position and attitude commands in the script, and the existing modeling model is added to realize the rapid addition of the spacecraft three-dimensional model.

3. A space situational awareness simulation system based on improved Blensor software according to claim 1, characterized in that: In step S3, the full information subsystem includes the attitude and orbit dynamics module, the Blensor three-dimensional visualization module, the constellation performance evaluation module and the sensor module. It also includes all the created spacecraft models, space debris models and Earth celestial body models to simulate the real physical environment.

4. The space situational awareness simulation system based on the improved Blensor software according to claim 1, characterized in that: In step S3, the own perception system includes an information extraction and processing module and an orbit determination analysis module, which are used to obtain the own spacecraft information, celestial body information and perceived information. The own spacecraft is equipped with a sensor module and an information acquisition module.

5. The space situational awareness simulation system based on the improved Blensor software according to claim 1, characterized in that: In step S6, different models are adopted for different types of sensor outputs. After noise reduction processing is performed using a denoising module, different extraction methods are adopted according to the differences in target traces in the two-dimensional image and the three-dimensional image. Specifically, the following methods are used: Point target location extraction: using The initial center of mass is obtained by fitting, and the current value is used as the initial value to establish an effective point spread function, and the target is fitted to obtain the final center of mass position; Initial linear target extraction: Based on the existing posture of the own sensor and the position of the linear target's pixels in the image, the target's orientation information within the exposure time is calculated; Depth image target positioning and extraction: For the target information in the depth image, the centroid method is used to perform preliminary centroid positioning, and then the digital correlation method is used to accurately locate the target.

6. The space situational awareness simulation system based on the improved Blensor software according to claim 1, characterized in that: In step S7, the model in the orbit determination analysis module adopts a dual-vector orbit determination model, a three-vector orbit determination model or a multi-observation vector orbit determination model.

7. The space situational awareness simulation system based on the improved Blensor software according to claim 1, characterized in that: The sensor modules include 2D planar cameras, depth cameras, lidars, phased array radars, and synthetic aperture radars.

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