80 results about "Star catalogue" patented technology

The invention discloses a multi-modal information fusion odometer construction method for star catalogue positioning, and relates to the technical field of star catalogue patroller positioning. The method comprises the following steps: carrying out space joint calibration on a monocular camera, a laser radar and an inertial measurement unit, reconstructing a laser radar point cloud by using a timestamp of a camera image, and realizing time synchronization of the camera image and the laser radar point cloud; establishing an IMU pre-integration error model; and performing motion compensation distortion removal on the laser point cloud by using an IMU pre-integration result, and extracting geometric features of the distorted laser point cloud based on a neighbor region smoothness calculation method of a fixed measurement distance. By researching a multimodal information fusion odometer method, the accumulative error of motion measurement is reduced, the positioning precision and stability are improved, technical support is provided for design and development of a star catalogue navigation system, and the problems that a single-modal star catalogue positioning method is weak in environment adaptive capacity and poor in algorithm generalization are solved.

The invention discloses a global enhancement method for a wide-area astronomical image. The method comprises the following steps: carrying out high-frame-frequency image acquisition on a starry sky area; converting the reference star from a star catalogue position to an observation position, and resolving a linear negative film model; geometric distortion correction is carried out based on the resolving result; based on the image after geometric distortion correction, matching and identifying a reference star in a full view field, and obtaining celestial coordinate information of all fixed star images in the view field; on the basis of celestial coordinate information, correcting a poorer astronomical effect of the astronomical image, establishing an ideal coordinate system taking the center of a view field as a tangency point, and projecting a time sequence observation image to the ideal coordinate system; translating the processed graph, accumulating all translated images, and averaging all accumulated pixel positions to realize image superposition enhancement, thereby effectively improving the dynamic range of a detector and the detection capability of a wide-area astronomical observation system; and meanwhile, the signal-to-noise ratio of the astronomical image can be effectively improved, and the astronomical image centering and light measuring precision can be further improved.

The invention provides a star catalogue file generation method and device, a celestial body data query method and device, computer equipment and a storage medium. The star catalogue file generation method comprises the steps of obtaining star catalogue data; dividing the celestial sphere surface area corresponding to the plurality of celestial bodies into a plurality of local areas, and determining an identifier of each local area; determining an identifier matched with each celestial body data according to the right ascension and declination included in the celestial body data and the identifier of each local area in the celestial sphere surface area; sorting the celestial body data of the plurality of celestial bodies based on the identifiers corresponding to the celestial body data; and writing the sequenced celestial body data of the plurality of celestial bodies into an initial column storage file matched with the identifier to obtain a target file stored with the celestial body data, and generating file index information corresponding to the target file. The celestial body data is stored by utilizing the column type storage file, so that the problems of high maintenance cost and high use threshold caused by utilizing a database to store data are relieved while the data query efficiency is guaranteed.

The embodiment of the invention discloses an all-day and all-world time measurement method and device. A specific embodiment of the method comprises the following steps: constructing a short-wave infrared astronomical survey star catalogue; constructing a short-wave infrared astronomical geodetic survey star database according to the short-wave infrared astronomical survey star catalogue; optimizing the short-wave infrared astronomical geodetic survey star library to obtain an optimized short-wave infrared astronomical geodetic survey star library, and correcting atmospheric refraction errors in the optimized short-wave infrared astronomical geodetic survey star library; carrying out all-day fixed star point coordinate extraction on the shot multi-frame daytime star map to obtain fixed star point coordinates; and according to the star point coordinates of the fixed star, carrying out all-day astronomical observation world time calculation on the observation fixed star to obtain all-day world time. According to the embodiment, unified comparison of multi-period monitoring data is realized, and the engineering practicability of a monitoring result is improved.

The invention relates to the technical field of camera on-orbit calibration, in particular to a fisheye camera on-orbit calibration method based on a starlight vector, which comprises the following steps of: S1, acquiring a plurality of star maps observed by a fisheye camera on orbit, and extracting and denoising star points to form a star point set; s2, according to fisheye imaging distortion distribution, a star point located in an imaging center area is selected from a star point set, and a starlight vector is constructed based on image point coordinates of the star point in combination with star catalogue data subjected to space-time deviation and propagation path deviation correction; and S3, performing local geometrical relationship star point matching on the starlight vector in the step S2. According to the method, the multiple star maps observed by the fisheye camera in orbit are obtained and processed to form the star point set, so that the problems of poor in-orbit calibration applicability and low precision caused by the fact that most traditional fisheye camera calibration methods adopt a ground pre-calibration or space reference object arrangement mode are solved.

The invention provides a star catalogue data matching method and device, computer equipment and a storage medium. The method comprises the steps of obtaining a plurality of star catalogue files; aiming at each star catalogue file, generating a target table corresponding to the star catalogue file, and storing serial number information of the celestial body data under multiple levels in the target table; constructing a storage calculation table according to the structure information of the target table and a set storage division strategy, and storing the table content of the target table into the storage calculation table; for any two to-be-matched star catalogue files, taking a column where a target hierarchy indicated by the storage division strategy is located as a connection key, carrying out connection operation on storage calculation tables corresponding to the two to-be-matched star catalogue files, and determining a matching result between multiple pieces of celestial body data with the same serial number information of the target hierarchy in the two storage calculation tables; and when the matching result is that matching succeeds, outputting at least part of data in the multiple pieces of celestial body data. According to the method, cross matching of celestial body data in different star catalogue files is realized, and the matching efficiency is improved.

This disclosure provides a method for segmenting a star catalog. The method includes: acquiring a target star catalog file corresponding to a target celestial sphere, the target star catalog file including observation data of M celestial bodies in the target celestial sphere; dividing the target celestial sphere into N sub-regions and N region numbers corresponding to the N sub-regions based on a predetermined maximum segmentation level K; determining the number of celestial bodies in each region represented by each of the N region numbers based on the observation data of the M celestial bodies in the target star catalog file, obtaining a result determining the number of N celestial bodies; and segmenting the target star catalog file according to the matching result between the result determining the number of N celestial bodies and a predetermined segmentation threshold T, determining multiple star catalog subset files corresponding to the target star catalog file. This disclosure also provides an apparatus, device, and storage medium for segmenting star catalogs.

The application discloses a small-sized separated penetrator for in-situ detection of celestial bodies, and relates to the technical field of penetrator equipment, comprising an aluminum honeycomb buffer module, which comprises an external protective shell and an aluminum honeycomb, and has the beneficial effects that the application is provided with in-situ detection of high-speed penetration of celestial bodies, and discloses a small-sized separated penetrator, which comprises a planet soil penetration module and a star table detection module, and realizes autonomous separation in the impact penetration process, the star table module can realize star table detection and communication with an orbiter, the penetration module is internally provided with an energy storage device and an impact hammer, and can continue to penetrate and dive relying on the energy storage device after impact; the star table module is connected with the penetration module through flexible wires, and can supply power and signal transmission to the latter, the technology enables the penetrator with the modular characteristic to have the in-situ detection capability of planet soil profile, aims to expand the application mode of the penetrator for celestial body detection, and provides a scientific basis for the research of star table structures.

This invention designs a multi-scale star surface impact crater detection method, system, and medium. The method includes the following steps: S1: Acquire star surface images and segment them into image patches of different scales; S2: Construct multiple impact crater detection sub-models; S3: Train each sub-model using star surface image patches of different scales; S4: Input the segmented star surface image to be detected into each pre-trained sub-model to obtain the detection results; S5: Select the bounding boxes with high confidence and large area among all candidate bounding boxes of each impact crater as the final detection result for that impact crater. This invention can simultaneously identify impact craters of different scales in star surface images with high accuracy, especially improving the accuracy and efficiency of identifying small impact craters, providing more accurate and comprehensive data support for lunar science research, and promoting the in-depth development of lunar exploration and geological research.

The present invention relates to a method for collaborative obstacle avoidance for multi-node landers under non-uniform constraints, comprising: controlling the multi-node lander to descend to a preset altitude and acquiring an environmental map of a star catalog; calculating the trajectory of the multi-node lander's virtual center and the position of each node; determining the real-time distance of each node relative to the virtual center and calculating each node's own trajectory based on flexible transformation constraints such as the multi-node lander's configuration potential field, obstacle avoidance potential field, and collision avoidance potential field; and controlling each node to track its own trajectory to achieve collaborative obstacle avoidance. This method enables future asteroid probes to robustly and accurately adhere to landing sites of high scientific value during landing and sample return missions, and to cope with various hazardous terrains, such as steep slopes and narrow valleys.

The invention discloses a robot for detecting a narrow cave on a star catalogue, and belongs to the technical field of space robots. The defects that an existing star catalogue detection robot is large in size, complex in structure and incapable of adapting to narrow caves are overcome. The device comprises an advancing mechanism, a shell and a cave detection mechanism, and the shell is installed on the advancing mechanism and can be driven by the advancing mechanism to move; a mounting cabin is arranged at the front end of the shell, one end of the cave detection mechanism is mounted in the mounting cabin, the other end of the cave detection mechanism can extend out of or retract into the mounting cabin, and the cave detection mechanism can perform bending action so as to complete an omnidirectional detection task after the robot enters a narrow cave on a star catalogue. The method is mainly used for detecting the narrow caves on the star catalogue.

The present application relates to a kind of dark and weak target detection methods of wide-area astronomical image based on deep learning, belong to astronomical image processing technical field, including field of view division to original astronomical image, and pretreatment is carried out;Then the threshold segmentation label generation strategy based on star catalogue prior is established to generate label set;Deep learning semantic segmentation model is constructed and trained to obtain optimization model;With the astronomical image after pretreatment as input, output target segmentation map, and eliminate the connected domain target that does not conform to physical characteristics, based on the roundness feature of target area determination and separate fusion target, obtain the final mask of independent target;Based on final mask, the subpixel level center coordinates of each independent target are calculated using weighted centroid method, effectively improve the detection ability and measurement precision of low signal-to-noise ratio dark and weak target;While being able to adapt to the characteristics of astronomical data of high dynamic range, significantly improve target detection performance, especially in the extremely dark and weak target in signal-to-noise ratio 2 to 5 interval.

The application relates to a robot for exploring a narrow cave of a star table, belonging to the technical field of space robots. In order to solve the defects that the existing star table exploring robot is large in size, complex in structure and cannot adapt to narrow caves, the robot comprises a travelling mechanism, a shell and a cave exploring mechanism, the shell is installed on the travelling mechanism and can be driven to move by the travelling mechanism, the front end of the shell is provided with a mounting cabin, one end of the cave exploring mechanism is installed in the mounting cabin, the other end can be extended out of or retracted into the mounting cabin, and the cave exploring mechanism can perform a bending action to complete an omnidirectional exploration task after the robot enters the narrow cave of the star table. The robot is mainly used for exploring the narrow cave of the star table.

The invention belongs to the technical field of industrial automation, and particularly relates to a Healpix-based star catalogue homogenization segmentation and evaluation method. The method comprises the following steps: S1, acquiring original star catalogue data, and determining Healpix grid level parameters based on an expected subdivision degree of a user; s2, calculating a Healpix pixel index number of each celestial body by adopting a Healpix algorithm based on celestial sphere coordinates of each celestial body in a celestial sphere equator coordinate system contained in the original star catalogue data; s3, constructing a blank star catalogue, and constructing a homogenized star catalogue based on the celestial body set extracted by the sampling strategy and the Healpix pixel index number corresponding to each celestial body contained in the celestial body set; and S4, constructing a Uscore evaluation model, performing Uscore scoring on the homogenized star catalogue by using the Uscore evaluation model, and evaluating the uniformity of each celestial body in the homogenized star catalogue based on the Uscore score. According to the invention, an objective and quantifiable comparison reference is provided for the effects of different homogenization methods.

The invention discloses an embedded star catalogue data storage and query method oriented to a bare computer environment, relates to the technical field of embedded data query processing, solves the problem of mismatch between a DSP system structure and a star map query task in the prior art, and comprises the steps of star block storage, star block query, primary selection of star blocks in star block query and determination of navigation stars. In the star block storage, the GeoHash coding technology is adopted to take the star block as a primary key value, and a B + tree is adopted to store the star block in an easy-to-search form; a star map shot by an astronomical camera is preliminarily decomposed into primarily-selected star blocks in a partition mode, then corresponding storage star blocks in a bare computer environment are inquired respectively, and high flexibility and adaptability are achieved. The method is compatible with the GeoHash coding technology, parallel computing of a multi-core bare computer is facilitated, and the query speed can be doubled.

The application provides a kind of based on ClickHouse column database's massive star table data fast merging method and system, through reducing the complexity of spherical distance calculation and using equidistant grid division index establishment method, the merging process of multi-band star table data is accelerated;The application is aimed at the application scene of astronomical cross identification and star table merging and the data processing demand of CSST high performance, low delay, research uses column database to complete the storage, retrieval and identification process of massive star table data, has good use value, has wide application scene in astronomical data processing field, also provides a new idea and direction for astronomical data processing.

The invention provides a star catalogue data merging method and device, computer equipment and a storage medium. The method comprises the steps of obtaining a target star catalogue file; according to right ascension and declination included in the celestial body data, determining serial number information of each piece of celestial body data under the target hierarchy, and dividing the celestial body data with the same serial number information in the target star catalogue file into the same data group to obtain a plurality of data groups; for each data group, determining an adjacent data group corresponding to the data group according to the number information corresponding to the data group; for each piece of celestial body data in the data group, determining a matching result between the celestial body data and other celestial body data in the data group, and a matching result between the celestial body data and each piece of celestial body data in the adjacent data group; and generating an index file corresponding to the target star catalogue file according to a matching result among the multiple pieces of celestial body data. According to the method, the whole table crossing and merging processing of the star catalogue file is realized, the number of repeated crossing times is reduced, and the star catalogue data crossing and merging efficiency is improved.

The invention discloses a satellite low-brightness design and analysis method based on a satellite thermal control model, and belongs to the technical field of satellites. The method comprises the steps of task analysis, star catalogue thermal control low-brightness design, satellite thermal control-brightness analysis integrated modeling, thermal control feasibility analysis, satellite brightness analysis based on a thermal control model, index satisfaction degree analysis and the like. At present, a theoretical calculation method of a simplified model is generally used for brightness analysis of a satellite, and can not be effectively iterated and updated in time according to a thermal control star catalogue design condition of the satellite. According to the design and analysis method, the thermal control design and the brightness design and analysis of the satellite are integrated, and the low-brightness design is realized while the thermal control design is performed; and establishing an analysis model with unified thermal control and brightness analysis, and carrying out statistical analysis of the satellite brightness based on thermal analysis model data. According to the method, the satellite low-brightness design and the thermal design are organically combined, and the efficiency and the accuracy of the brightness design are improved.

The star map recognition method based on radial features and interstellar angular distance relates to the field of star map recognition in astronomical navigation, solves the problems that the existing star map recognition algorithm has less number of stars to be recognized at one time, and the recognition speed and robustness are difficult to be compatible, and the method comprises the following steps: a navigation star table is made, radial recognition feature library and interstellar position relationship library are constructed according to the position distribution features of each navigation star and surrounding near neighbor stars; the interstellar position relationship library is used for storing the star number and radial ring number of the surrounding near neighbor stars of each navigation star; then, initial recognition and accurate recognition are carried out. In the process of matching by using the radial feature library, an angular distance error tolerance is set, and a weight value is set for each ring number, so that the star position noise has strong robustness. After the initial recognition, the accurate recognition is carried out, the surrounding near neighbor stars of the main star are used, and the method has strong robustness to false star noise and missing stars. The method realizes the recognition of multiple stars at one time, and improves the initial attitude solution accuracy.

The application discloses an astronomical cross-identification method for a heterogeneous many-core processor, and comprises the following steps: S1, obtaining the strip id of two star catalogs based on declination and the multi-node data distribution in strip units; S2, determining the number of heterogeneous many-core processors of each computing node and the maximum number of threads that can be simultaneously run by each heterogeneous many-core processor; S3, rearranging the star catalog data in each strip in strip units, and dividing the star catalog data into grids based on right ascension; S4, judging whether the right ascension span of each strip is too large during internal identification, so as to select the identification calculation of the CPU end in step S5 in a multi-thread parallel mode or the identification calculation on the heterogeneous many-core processor in step S6; S7, determining the identification selected result; and S8, obtaining the ID of a star body in two star catalogs respectively. The method can guarantee the calculation accuracy and integrity, improve the parallelism of the cross-identification algorithm and the use efficiency of the heterogeneous many-core processor, and realize the improvement of the overall calculation performance of the astronomical cross-identification.

The invention provides a multi-modal time sequence astronomical data training method and device based on graph contrast learning and a storage medium, and belongs to the field of astronomical data processing. The limitation of an existing deep learning method in processing multi-modal astronomical data fusion is solved; the method comprises three key steps: the astronomical data composition model is responsible for structuring original data; a multi-modal astronomical time series data fusion model based on a self-attention mechanism can effectively integrate data from different observation periods and different modals, and deeper feature fusion is realized; the feature learning model based on graph contrast learning further extracts features with higher distinction degree and representativeness in a graph structure level; according to the method, feature fusion is performed on multi-modal data of astronomical image data, spectral data, star catalogue data and text data in combination with data of different time dimensions, and more specific features are mined from the perspective of a graph by utilizing graph comparison learning in a graph composition-fusion-re-graph composition mode.

The invention relates to a method (PREF) for referencing at least one artificial satellite (SAT) in a star catalogue (CTG), comprising a step of positioning at least one star projected onto a celestial sphere (SC). The method comprises: a step (E10) of obtaining coordinates (Oqd,) of an observed position of the at least one artificial satellite (SAT) and orbit parameters (TLE) of the at least one artificial satellite (SAT); a step (E50) of projecting the satellite (SAT) onto the celestial sphere (SC) in a viewing direction determined from the orbital parameter (TLE) and the observation position; -a step (E80) of recording the coordinates of the satellites (SAT) projected onto the celestial sphere (CS) into the star catalogue (CTG), in which the coordinates of the fixed star and of the at least one artificial satellite (SAT) are expressed in the same geocentric reference frame, referred to as fixed star catalogue reference frame.

This invention belongs to the field of industrial automation technology, and particularly relates to a method for uniform segmentation and evaluation of star catalogs based on Healpix. The method includes: S1: acquiring original star catalog data and determining the Healpix grid level parameters based on the user's desired subdivision level; S2: calculating the Healpix pixel index number of each celestial body in the original star catalog data using the Healpix algorithm, based on the celestial coordinates of each celestial body in the celestial equatorial coordinate system; S3: constructing a blank star catalog and building a uniform star catalog based on the set of celestial bodies extracted by a sampling strategy and the corresponding Healpix pixel index numbers of each celestial body contained in the set; S4: constructing a U_score evaluation model and using the U_score evaluation model to score the uniform star catalog, and evaluating the uniformity of each celestial body in the uniform star catalog based on the U_score score. This invention provides an objective and quantifiable benchmark for comparing the effects of different uniformization methods.

The invention relates to the technical field of computers, and discloses a PSF-guided adaptive sparse Patch Transformer-based astronomical faint target detection method and system. The method comprises the following steps: inputting an astronomical image for preprocessing; dynamically acquiring and calibrating a point spread function (PSF) parameter; generating an adaptive sparse Patch based on PSF parameter guidance, and generating a sparse attention mask; feature extraction is carried out based on an adaptive sparse Patch Transform, a feature interaction weight is calculated through a multi-head sparse self-attention layer, and PSF parameter cross-modal attention is fused; the method comprises the following steps: performing target detection and preliminary screening, generating candidate targets by adopting a double-stage detection head, removing false alarms through PSF parameter form verification, outputting a preliminary screening result for post-processing optimization, removing fixed stars through star catalogue matching or configuration matching, performing multi-frame trajectory association by adopting a multi-hypothesis tracking method, and executing sub-pixel positioning and star magnitude calibration. And constructing a quality scoring system and outputting a standardized result. According to the invention, both the detection precision and the calculation efficiency can be considered, and the cross-equipment adaptation capability is realized.

The application discloses an explainable attribution method and system based on a star atlas semantic segmentation model, a device and a storage medium, and belongs to the technical field of deep space exploration image processing. The star atlas image is subjected to gray processing and gradient calculation, and the image is divided into super-pixel regions based on a gradient minimum strategy; a regional-level topological structure diagram is constructed, and node links are established based on spatial adjacency and brightness gradient similarity; the structural importance of each region is calculated, a center point of a mask is sampled, a directional elliptical Gaussian perturbation mask set is generated according to a gradient main direction angle; the perturbation mask is applied to the original image, and a semantic segmentation model is input to calculate a saliency score; and saliency information is propagated in the topological structure diagram based on a graph attention mechanism, and a structural saliency explanation diagram is constructed. Through regional division and topological propagation of terrain perception, model explanation of spatial continuity and terrain consistency is realized, and the technical problems that a traditional method ignores the physical characteristics of terrain structure and lacks a propagation path description are solved.

The application discloses an astronomical cross-identification confidence calculation method for memory access optimization, and steps are as follows: S1, flattening the astronomical cross-identification result into a one-dimensional main source index array and a one-dimensional candidate source index array; S2, constructing an offset array; S3, respectively constructing a plurality of columnar one-dimensional continuous celestial body attribute arrays of main star table celestial bodies and candidate star table celestial bodies; S4, generating an unnormalized logarithmic score array through candidate pair level linear scanning calculation; S5, obtaining the normalized probability of each candidate pair in a candidate group and the total confidence of the candidate group through candidate group level segmented reduction normalization; S6, judging based on a set threshold value, and outputting a candidate pair with high reliability; the method solves the problems of low memory access efficiency and memory redundancy in astronomical big data calculation under the premise of keeping 99.9% of the decision consistency rate of the traditional method, reduces the data structure redundancy caused by complex nested objects, and improves the advantages of memory access and calculation efficiency under the pressure of large-scale candidate bodies.

The application discloses a CPU-DCU architecture-oriented astronomical identification calculation memory access optimization method, and steps are as follows: S1, performing grid processing on celestial body data of to-be-identified star catalog A and star catalog B, and respectively vectorizing the star catalog A and the star catalog B in a star catalog-strip-grid hierarchical manner, and recording boundary information of each grid; S2, according to the maximum thread concurrency number of each DCU, dividing the celestial body data in the star catalog A and the star catalog B into a plurality of transmission sub-tasks corresponding to each DCU in a strip unit; S3, setting a calculation task of a single thread in the DCU; S4, setting a kernel function, so that each thread of the DCU completes identification calculation by executing the kernel function; S5, using the method in step S4 to perform identification calculation between celestial bodies in the star catalog A and the star catalog B; the method can improve the memory access performance of astronomical grid calculation on the DCU while ensuring calculation accuracy and integrity, and realizes the improvement of overall calculation performance.

The present invention provides a method for autonomous navigation of a star chart rover using cross-temporal feature search, comprising: step S1, encrypting and interpolating laser radar and visual camera point cloud data based on the density of input point cloud data; step S2, using a sliding window to detect cross-temporal feature smoothness, defining a smoothness c value, and extracting plane feature points and edge feature points based on the order of the smoothness c value; step S3, introducing a local subgraph and performing local odometry for high-frequency coarse positioning estimation; step S4, using an improved Levenberg-Marquette optimization method for global optimization and low-frequency fine mapping, completing low-frequency, high-precision global mapping using the interval period calculated using the local subgraph; and step S5, establishing a system cumulative error evaluation mechanism, revisiting locations where the system error entropy increase ΔI exceeds a threshold, and improving the overall pose estimation accuracy ΔE through a global loop-revisit detection mechanism. The present invention improves the estimation accuracy, robustness, and real-time performance of autonomous navigation.

The present disclosure provides a star field geometric calibration method considering space-time decoupling and non-steady imaging, which comprises: constructing a star point extraction operator with star motion compensation function according to the GAIA star catalog, the optical remote sensing satellite attitude performance catalog and the satellite adapted star field, to identify star points based on the star field generated satellite image field star map features, to obtain star control points, to make astronomical correction on proper motion, parallax and aberration in star coordinates, to obtain observable limit stars and star imaging window values according to the point spread function PSF of the image optical system, to adaptively weight the reliability of star observation coordinates, to construct an adaptive distortion model of camera interior orientation elements, to correct the attitude stability under the non-steady imaging condition of the satellite according to the star control points, to construct a star field geometric calibration model, and to solve the star field geometric calibration model based on the random sampling consistency method and the partial least squares method to obtain the geometric calibration parameters.

The invention relates to a sliding window opening and closing mechanism for star catalogue detection, and belongs to the field of star catalogue detection. The window body assembly is horizontally arranged; the driving assembly is axially and horizontally arranged on the side wall of the window body assembly; the guide assembly is axially and horizontally arranged in a frame of the window body assembly; the cover body assembly is of a rectangular plate-shaped structure; the cover body assembly covers the upper surface of the window body assembly; the dustproof assembly is arranged at the joint of the cover body assembly and the window body assembly; the cover body assembly is in butt joint with the driving assembly, the driving assembly drives the cover body assembly to move horizontally relative to the window body assembly, and opening and closing of the window body assembly are achieved. The bottom of the cover body assembly is matched with the guiding assembly, and when the window body assembly translates, guiding assistance is provided through the guiding assembly; the position monitoring assembly is arranged in a frame of the window body assembly; the device can bear large mechanical loads, is opened and closed repeatedly in a wide-temperature range and star surface floating dust environment, has dustproof and heat preservation functions, and has the advantages of being diversified in function, high in environmental adaptability, simple in structure, high in reliability and the like.