119 results about "Orbit prediction" patented technology

The invention relates to an autonomous navigation method for lunar satellite formation and a second-order filtering navigation architecture, and the autonomous navigation method comprises the steps: obtaining orbit prediction information based on a kinetic model of the lunar satellite formation, and obtaining collaborative theory observation information based on a collaborative observation model, carrying out fusion processing on orbit prediction information, collaborative theory observation information and multi-source observation data of in-orbit observation by using an extended Kalman filtering algorithm, and estimating an absolute orbit state of the lunar satellite formation; establishing a relative motion model of the slave satellite under the local coordinate system of the master satellite, and establishing a relative measurement model; and taking the absolute orbit state of the master satellite as a reference datum, obtaining a preliminary prediction relative orbit state based on the relative motion model of the slave satellite, and obtaining relative measurement data including distance measurement and angle measurement based on the relative measurement model, and fusing the relative measurement data and the preliminarily predicted relative orbit state through an extended Kalman filtering algorithm to estimate the relative orbit state of the slave satellite. Navigation may be independent of ground support.

The invention relates to the technical field of spacecraft orbit control and space safety, and discloses a space debris orbit prediction and avoidance method, which comprises the following steps that: a ground computing center screens candidate targets and generates enhanced data packets for uploading; the spaceborne computer combines real-time navigation data to carry out geometric feature screening, and an instant high-risk target list is generated; controlling the star sensor to execute optical observation, and resolving an optical measurement relative orbit state by utilizing displacement superposition and Kalman filtering; selecting a high confidence coefficient or a conservative probability threshold according to the optical measurement state acquisition condition, and generating an avoidance instruction when the collision probability exceeds the limit; and the propulsion system responds to the instruction to execute avoidance, verifies the effect by confirming the semi-major axis variation and executes track recovery by selecting an aircraft. According to the method, the ground-air collaborative screening and shift superposition enhancement technology is adopted, the problems that the low-precision ephemeris false alarm rate is high and the detection capability of a satellite-borne sensor on a dark and weak target is insufficient are solved, and the accuracy of evasion decision making and the execution reliability are improved.

The invention discloses a satellite orbit forecasting method based on deep learning physical constraint loss, and the method comprises the following steps: 1, carrying out the normalization preprocessing of input data, forming a training data set and a test data set, and constructing batch processing training data; and 2, performing dimension expansion on sample data points in each window in the batch processing data formed in the step 1, constructing a multi-dimensional feature space of the sample points, and forming a batch processing input data format capable of being introduced into the model. And 3, performing forward reasoning on the batch data formed in the step 2 by using a model, and obtaining a batch processing orbit prediction value output by the model at the next moment through a CNN lightweight spatial-temporal feature extraction module and a BiLSTM bidirectional time sequence neural network module. And 4, taking the track prediction value obtained in the step 3 and the truth value label in the training set obtained in the step 1 as input, calculating to obtain a loss value of a current training iteration batch through a multi-random learning loss module fusing physical constraints, and performing reverse updating of model parameters to complete model training. And step five, through the steps two to four, performing reasoning verification on the model by using the test set formed in the step one, and comparing with a truth value in the test set to obtain a model test result.

The invention relates to the technical field of low-orbit satellite communication, in particular to an orbit optimization method and system for dynamically and autonomously tracking a low-orbit satellite based on a ground station, and the method comprises the steps: collecting TLE orbit element data, constructing an SGP4 orbit prediction model, and obtaining a prediction result; low-earth-orbit satellite orbits with different inclination angles are determined through STK software modeling based on a ground station, and corresponding standard results are obtained; comparing the prediction result with a standard result to obtain an error result; dynamically optimizing the Bstar parameter based on an error result by adopting a genetic algorithm, and determining an optimal Bstar parameter; adjusting the SGP4 orbit prediction model based on the optimal Bstar parameter, and obtaining an optimization result through the adjusted SGP4 orbit prediction model; according to the method, optimization is carried out based on an existing SGP4 model, optimal Bstar parameters are dynamically searched through a genetic algorithm, accumulative errors caused by the fact that TLE data are not updated in time are compensated, stable tracking of a ground station is guaranteed, and the precision of medium and long term orbit forecasting is improved.

The invention provides a two-line element generation method and orbit prediction method adaptive to an analytic propagation model, and the method comprises the steps: obtaining the historical osculating orbit elements at each epoch moment, and carrying out the orbit element optimization step of a plurality of iteration rounds on each historical osculating orbit element through employing the analytic propagation model, obtaining a target osculating orbital element number at each epoch moment, enabling the historical osculating orbital element number to be the same as the target osculating orbital element number, and performing inversion to obtain an average orbital element number; and extracting each average semi-major axis of each average orbital element, fitting each average semi-major axis by adopting a least square method to obtain a semi-major axis attenuation rate, inverting the semi-major axis attenuation rate to obtain an atmospheric resistance parameter, and equivalently converting the atmospheric resistance parameter into a standard resistance term in two rows of elements to obtain the two rows of elements. According to the method, the problems of inconsistent models, insensitive residual errors, unable physical explanation of parameters and the like in the two-line element generation process can be solved, and the ephemeris extrapolation orbit prediction precision is improved.

The invention discloses a satellite group collaborative prediction method based on Lie group differential manifold and covariant optimization, and mainly solves the problems of inaccurate disturbance modeling, poor physical interpretation and large prediction error in the prior art. According to the scheme, the method comprises the following steps: mapping the position and attitude of a satellite to an SE (3) manifold, and describing the movement speed of the satellite by using Lie algebra; establishing a multi-level Lie algebra disturbance decomposition mechanism including absolute perturbation, relative coupling and observation noise; constructing a Riemannian loss function by using the orbit state after Lie group manifold embedding and the orbit state deviation obtained by disturbance decomposition; defining an orbital state updating rule by using a covariant derivative of the function, and iteratively solving the orbital state updating rule on the SE (3) manifold to output an orbital state prediction result of the satellite; for an abnormal state of inter-satellite link interruption, a differential geometric connection form is defined, and virtual relative position observation of an integral generation orbit state is carried out. According to the method, the physical interpretability and long-term prediction stability of orbit prediction can be improved, prediction errors are reduced, and the method can be used for low orbit communication constellation deployment of frequency band inter-satellite links.

The invention discloses a practical training platform three-dimensional scene mass data loading optimization method, and relates to the technical field of computer graphics and three-dimensional visualization. Passive response of data loading is converted into active pre-judgment through an orbit prediction model and prospective visible area calculation, and the real-time performance of data loading is improved. The rendering lag caused by the rapid change of the satellite track is obviously reduced; the combination of the predicted position and the camera vision cone ensures that the point location is scheduled before the vision field is switched; secondly, GPU resource utilization is optimized through dynamic attribute increment updating and a dirty marking mechanism; static and dynamic attribute buffer areas are separated, only change data are updated, the CPU-GPU communication overhead is reduced, the frame rate fluctuation problem caused by batch updating is solved, and the system is still kept smooth under ten-thousand-level point location dynamic updating; in addition, the collaborative design with terrain rendering eliminates point location dislocation during terrain detail level switching through monitoring and double-buffer correction, and improves visual consistency.

The invention relates to an RRC (Radio Resource Control) layer enhanced mobile model simulation method and system based on a 3GPP (3rd Generation Partnership Project) NTN (Network Temporary Network) standard. The method comprises the following steps: S1, constructing a simulation environment conforming to the 3GPP NTN standard; s2, constructing an RRC state machine in the NTN scene, wherein the RRC state machine comprises a user RRC state machine and a satellite RRC state machine; s3, configuring a dynamic conversion condition of the RRC state machine and a corresponding behavior logic; s4, scheduling events and injecting NTN parameters, and performing NTN propagation characteristic simulation based on the simulation environment; and S5, counting performance indexes generated in the simulation process, and outputting an NTN scene simulation report. According to the method, the simulation environment conforming to the 3GPP NTN standard is constructed, the RRC state machine in the NTN scene is constructed, the characteristics of long delay, high mobility and orbit prediction of the satellite are adapted, and the problem that a state machine model of a traditional simulation method is not applicable is solved.

The invention provides a space target orbit maneuver identification method and system based on adaptive LSM, and the method comprises the steps: obtaining the orbit data of a space target, calculating the six orbit elements based on the orbit data, and coding the six orbit elements into a pulse sequence; and inputting the pulse sequence into an improved adaptive LSM for detection to obtain an orbit maneuver behavior identification result of the space target. According to the method provided by the invention, six orbital elements are calculated through the speed and the position of the orbital, then the orbital parameters are input into an improved LSM, and the improved LSM adopts an adaptive threshold neuron as a calculation unit, so that the threshold can be dynamically adjusted according to the current pulse response and attenuated along with time; meanwhile, an improved particle swarm optimization algorithm is combined to carry out optimization setting on an initial value of a neuron, so that the initial performance of the model is improved; and a learnable neuron connection weight based on an attention mechanism is introduced, so that the accuracy and reliability of orbit prediction are improved.

The invention discloses a calculation method for determining a visible time period between a satellite and a ground station through TLE data, and relates to the technical field of spaceflight measurement and control and satellite communication scheduling. Through a dynamic sampling mechanism of cluster perception, the time resolution is automatically improved in a dense transit period, the sampling density is reduced in a non-cluster period, the redundancy calculation is remarkably reduced, and the calculation efficiency is improved. The calculation power peak congestion is avoided; a boundary detection algorithm based on elevation angle change rate symbol switching can capture a rapid jump point of a satellite elevation angle, the error merging phenomenon of short interval windows is eliminated, and the precision of an output timestamp reaches a sub-second level; the confidence identification dynamically reflects TLE data timeliness and cluster complexity, a user can intuitively evaluate the window time credibility, and the communication interruption risk caused by orbit prediction errors is reduced.

The invention relates to a GNSS (Global Navigation Satellite System) auxiliary measurement-based autonomous navigation method for a lunar satellite formation release process, which comprises the following steps of: establishing a kinetic model of a primary satellite and a secondary satellite under a lunar center inertial coordinate system J2000; establishing and fusing an inter-satellite measurement model and a distance measurement model of a main satellite fused GNSS signal to obtain a collaborative observation model; and acquiring orbit prediction information based on the kinetic model, acquiring collaborative theory observation information based on the collaborative observation model, performing fusion processing on the orbit prediction information and the collaborative theory observation information by adopting an extended Kalman filtering algorithm, and estimating orbit states of the primary satellite and the secondary satellites. According to the autonomous navigation method, full-autonomous orbit determination can be realized in orbit without depending on the support of a ground station.

The invention relates to the technical field of constellation satellite maintenance regulation and control, and discloses an intelligent regulation and control system and method for low-orbit Walker constellation configuration maintenance, and the method comprises the steps: obtaining the change trend of an in-plane phase angle and an inter-plane distance of an orbit of a satellite in real time through a high-precision orbit prediction model; inputting the in-plane phase angle and the inter-plane spacing into a pre-trained decision model, judging whether the parameters exceed a preset configuration maintenance threshold, and positioning an unstable satellite; if the parameters exceed the limit, the model outputs the optimal orbit maneuvering parameters of the satellite based on dual-target constraints of minimum fuel consumption and shortest service interruption; a phase maintenance demand and an on-satellite observation task are fused, an optimal control scheme is generated, and constellation configuration is maintained in combination with task planning and implementation; continuously monitoring the satellite constellation configuration state, and maintaining the stable operation of the constellation. According to the invention, automatic maintenance of Walker constellation configuration is realized, and the control precision and efficiency are improved.

The invention belongs to the technical field of communication satellite measurement and control technologies, and provides a satellite measurement and control system based on multi-modal fusion, which comprises a multi-modal signal fusion module used for receiving measurement and control data, fusing information from a plurality of signal sources, carrying out data time and space alignment and establishing a state estimation equation for prediction, outputting accurate satellite state data; the intelligent orbit prediction module is used for predicting the orbit of the satellite in real time and calculating the future change of the satellite orbit according to the received satellite state data and external information; the satellite control module is used for controlling and adjusting the orbit and attitude of the satellite in real time, and running the satellite according to the preset orbit and attitude through monitoring and control; and the task planning and instruction scheduling module is used for planning and scheduling satellite tasks, generating corresponding instructions according to task requirements, and reasonably allocating resources by scheduling and evaluating various indexes of satellites so as to enable the instructions to be executed on time.

The application discloses a kind of based on low-orbit giant constellation dynamic inter-satellite communication visibility calculation method, comprising the following steps: obtaining the latest TLE ephemeris data of two satellites under a certain constellation, based on TLE ephemeris data and specific epoch, the spatial position of two satellites is calculated using SGP4 orbit prediction model;Then the inter-satellite line-of-sight visibility between two satellites is calculated, and the result is characterized as a Boolean quantity;Utilize the optical power budget function based on inter-satellite laser link establishment, carry out received optical power budget;The azimuth and elevation of communication antenna under satellite body coordinate system are calculated;Finally, the visibility result of two satellites is calculated, the specific communication antenna number of satellite is determined, and the constellation inter-satellite visibility matrix is established.The application discloses a kind of based on low-orbit giant constellation dynamic inter-satellite communication visibility calculation method, constellation scale and calculation speed have higher flexibility and computing performance, inter-satellite visibility calculation is more in line with actual satellite communication scene.

Embodiments of the present application provide a space target orbit prediction method, a prediction device, an electronic device and a medium. The method comprises: obtaining two-line orbital elements of a space target at a current time, space environment data and perturbation coefficients, the perturbation coefficients being coefficients in a space target orbit prediction model; correcting the two-line orbital elements and / or the perturbation coefficients based on a pre-trained parameter correction model, the two-line orbital elements, the perturbation coefficients and the space environment data, to obtain corrected data, the corrected data comprising corrected two-line orbital elements and / or corrected perturbation coefficients; and predicting orbit information of the space target at a preset future time based on the space target orbit prediction model and the corrected data. The method makes the predicted orbit information more accurate.

The invention provides a non-singular semi-analytical method for forecasting a low-thrust perturbation orbit. The method comprises the following steps: firstly, establishing a Gaussian variational equation for describing spring equinox orbital element evolution under small thrust control based on a periodic small thrust hypothesis; thirdly, constructing a long-term equation and a short-period term based on the average spring equinox orbital elements, performing large-step integration on the long-term equation to obtain a flat root, and then performing orbital element correction through the short-period term to finish high-precision orbital forecasting; and finally, establishing an analytic form error estimation model through a semi-major-axis second-order long-term equation, and using the analytic form error estimation model to evaluate orbit forecast errors. The semi-analytic low-thrust orbit forecasting method provided by the invention achieves good balance between calculation efficiency and precision, avoids the problem of singularity, and is suitable for high-precision forecasting of any low-thrust elliptical orbit; the error estimation model provided by the invention can effectively quantify the prediction error and enhance the reliability of the orbit prediction results of most small eccentricity rate on-orbit satellites.

The invention discloses a satellite orbit forecasting method based on in-orbit calibration of model parameters. Belongs to the technical field of remote sensing satellite measurement, operation and control and particularly relates to the technical field of remote sensing satellite orbit forecasting. According to the method, the satellite windward side-to-mass ratio in an atmospheric resistance model is calibrated regularly according to actually measured orbit data, the resistance coefficient in the atmospheric resistance model is calibrated in real time, and more accurate model parameters are used for modeling a perturbative force model in the satellite orbit forecasting process, so that the error of the atmospheric resistance model is reduced, and the orbit forecasting precision is improved. In the time period that the space weather changes gently, the atmospheric resistance modeling precision is improved to 90% or above from about 60%-80% of a traditional method through the method.

The application relates to the technical field of satellite intelligent access, and discloses a multi-satellite intelligent access method, system and equipment based on AI prediction, which comprises the following steps: collecting satellite orbit data and user terminal position data of a multi-satellite system, and performing satellite position prediction through an orbit prediction neural network to obtain satellite predicted positions and communication window information; each intelligent agent perceives communication environment parameters and constructs an environment perception vector; a multi-agent strategy network is driven based on the satellite predicted positions and the environment perception vector to generate a first access strategy; each intelligent agent performs resource conflict processing according to the first access strategy to obtain a second access strategy; the application adopts a multi-agent architecture to replace traditional centralized control, each intelligent agent has independent decision-making capability and realizes cooperation through a distributed negotiation protocol, single-point failure problems are avoided, robustness and scalability are improved, and resource competition and access conflicts are effectively reduced.

The invention discloses an on-orbit failure probability estimation method for a single-particle hard error of a wide bandgap semiconductor device, and aims to support on-orbit prediction of the single-particle hard error failure probability of the wide bandgap semiconductor device. Wide bandgap semiconductor devices such as silicon carbide (SiC), gallium nitride (GaN) and the like are easy to generate hard errors such as single-particle burnout and single-particle gate-through under the radiation of high-energy particles, and the risk of the hard errors in aerospace application needs to be comprehensively predicted and evaluated. Therefore, the invention provides a method for estimating the in-orbit failure probability of the single-particle hard error of the wide bandgap semiconductor device, which considers the influence of a failure section angle and particle distribution characteristics in different orbit environments, and provides data support for model selection.

The invention discloses a satellite internet of things intelligent access device based on orbit prediction and multi-satellite cooperation, which belongs to the field of low orbit satellite internet of things communication and comprises a main control and calculation unit, a multi-satellite access and radio frequency unit, an ephemeris storage and orbit prediction unit, a positioning and time service unit and a data buffering and service adaptation unit. Wherein the multi-satellite access and radio frequency unit is integrated with at least two sets of independent radio frequency front-end channels and supports parallel processing of signals of a plurality of satellites; and the ephemeris storage and orbit prediction unit is used for calculating accurate orbit parameters of future visible satellites. The core of the device is that the main control and calculation unit can actively generate an access and switching plan according to a track prediction result and service requirements, and control multiple radio frequency channels to cooperatively work in a main-standby or load balancing mode. According to the invention, the problem of unstable connection of the low-orbit satellite Internet of Things terminal caused by high-speed movement of the satellite is fundamentally solved, and the communication continuity, reliability and system efficiency are remarkably improved.

The invention discloses a satellite orbit prediction method based on an attention mechanism long-short term memory network, and relates to the technical field of satellite orbit prediction. The method comprises the following steps: preprocessing broadcast ephemeris data and precise ephemeris data, subtracting the two processed data to obtain a correction number sequence, and normalizing the correction number sequence to obtain standardized data; inputting the standardized data into a satellite orbit prediction model to obtain a multi-step correction number prediction result; and performing broadcast ephemeris correction according to a correction number prediction result to obtain final predicted orbit information. Wherein the satellite orbit prediction model adopts an Attention-LSTM (Long Short Term Memory) model, and captures an implicit relationship among input characteristics and a non-linear uncertain time trend of a time sequence for a plurality of fully connected layers of a periodic term. According to the method, the real-time orbit data is calculated by using the precise ephemeris data and the broadcast ephemeris, and high-precision and real-time prediction of the satellite orbit is realized according to the satellite orbit prediction model.

The application relates to a target over-screen detection method of a V-shaped electronic fence, and belongs to the technical field of space target monitoring. According to the motion law of a target, sufficient conditions of target over-screen detection are set, when a target simultaneously satisfies a longitude constraint of a vertical projection screen, a azimuth angle constraint of passing through the vertical projection screen and a maximum latitude constraint that can be reached by a target subsolar point, the target can be considered to simultaneously pass through the V-shaped fence screen. The method does not need to directly search whether the target can pass through the screen, avoids the compromise selection of operation time and orbit prediction accuracy, and effectively improves the calculation efficiency of target over-screen detection.

The invention relates to the technical field of space imaging, and provides a space target space-based microwave imaging system design method and device. The method comprises the following steps: firstly, determining an intersection process of an observation satellite and a space target based on an orbit dynamics simulation method, and further determining an imaging observation window; determining beam scanning geometry by combining relative motion characteristics of an observation satellite and a space target in the imaging observation window and the maximum scanning capability of the phased-array antenna, and generating a beam scanning strategy; secondly, realizing accurate capturing and locking of a wave beam by optimizing an orbit forecast error of a space target; and finally, according to the beam scanning strategy and the optimized orbit parameters of the space target, high-precision imaging of the space target is realized in combination with a synthetic aperture imaging algorithm and error compensation, double-high-speed motion imaging feasible position determination can be realized, a stable and efficient phased array beam scanning strategy is constructed, and the imaging accuracy is improved. High-precision beam pointing of a non-cooperative target is realized, and the precision and reliability of space target imaging are improved.

The invention relates to a lunar satellite formation orbit forecasting method based on a physical information neural network model, and the method comprises the steps: building a non-spherical perturbation acceleration model for a physical loss function under the inertial coordinates of the lunar center; designing a physical information neural network model: selecting a full-connection deep neural network as a network architecture of the model, and using a composite loss function containing a data loss function and a physical loss function as a loss function of the full-connection deep neural network; training a physical information neural network model; and using the physical information neural network model to predict the orbit state of the satellite formation. The physical information neural network model can output a high-precision orbit state within milliseconds through forward propagation, error accumulation of traditional integration is avoided, calculation complexity is remarkably reduced, and efficient, stable and high-precision online orbit state forecasting can be achieved.

The application belongs to the technical field of aerospace, and relates to a distance-keeping game control framework and method for a maneuvering non-cooperative target. The framework comprises a rolling control window, an event perception window arranged in each rolling control window, and an event triggering mechanism arranged in each event perception window. The event perception window predicts an orbit state through a two-body dynamics model, the event triggering mechanism calculates a relative distance between an active satellite and a target satellite at each discrete point according to an orbit prediction result, and judges whether the relative distance constraint is met. If the relative distance constraint is met, an impulse maneuver strategy of the active satellite as a decision output is calculated through a game strategy optimization algorithm. Simulation results show that the application can realize long-time distance keeping, and the success rate reaches 98% in a 12-hour maintenance task, which is increased by 308.3% compared with a traditional algorithm.

The invention relates to the technical field of space imaging, and provides a space target space-based microwave imaging parameter optimization method and device. According to the method, through predicting a target intersection section of a detection satellite and a space target, an average relative speed, a minimum intersection distance and an orbit prediction error component of the detection satellite and the space target are extracted from the target intersection section; determining the optimized detection time length and the optimized detection frequency of the detection satellite at least based on the minimum intersection distance and the orbit forecast error component, and determining the optimized imaging time length of the detection satellite at least based on the average relative speed and the minimum intersection distance, and multi-constraint cooperative solution is carried out on the pulse repetition frequency PRF of the detection satellite at least based on the average relative speed and the minimum intersection distance to obtain the optimized PRF, microwave imaging parameter optimization design of quantitative model and actual scene constraint is realized, the efficiency is high, the application scene is wide, and the method is suitable for large-scale popularization and application. And powerful support is provided for precision improvement and engineering landing of a space-based microwave imaging technology.

This invention relates to the field of collision warning technology, specifically to a spacecraft collision warning method for a large number of space targets. The method includes: selecting a multi-data parallel screening warning approach; screening secondary target orbits within the TLE data set of the complete collision target orbits using set pre-screening thresholds for date expiration, apogee / perigee pre-screening safety margins, orbital intersection pre-screening thresholds, and time pre-screening thresholds; performing SGP4 orbit prediction on the primary target orbit and the initially screened secondary target orbits; obtaining the minimum spatial distance and collision probability between spacecraft within the primary and secondary target orbits; summarizing the primary and secondary target orbit numbering information, as well as the minimum spatial distance, collision probability, and the time corresponding to the minimum spatial distance, into a collision warning result; and summarizing all collision warning results to output a collision warning set information. This invention can filter out targets that are unlikely to intersect with the spacecraft to the greatest extent possible, reducing the computational load of subsequent orbit prediction.

The application relates to the technical field of space imaging, and provides a space target space-based microwave imaging system design method and device. The method firstly determines the intersection course of an observation satellite and a space target based on an orbit dynamics simulation method, and then determines an imaging observation window; then, the relative motion characteristics of the observation satellite and the space target in the imaging observation window and the maximum scanning capability of a phased array antenna are combined to determine a beam scanning geometry and generate a beam scanning strategy; next, precise acquisition and locking of the beam are realized by optimizing the orbit prediction error of the space target; finally, high-precision imaging of the space target is realized by combining a synthetic aperture imaging algorithm and error compensation according to the beam scanning strategy and the optimized orbit parameters of the space target, double high-speed motion imaging feasible position determination is realized, a stable and efficient phased array beam scanning strategy is constructed, high-precision beam pointing of a non-cooperative target is realized, and the precision and reliability of space target imaging are improved.

The application provides an autonomous star observation method for super low orbit satellites, comprising: setting a whole satellite mode word; judging whether an autonomous working condition trigger enable flag is enabled according to the whole satellite mode word; if yes, judging an orbit height decision working condition, and starting a star observation task according to the working condition; if no, setting a working condition through a ground instruction, and starting a star observation task according to the working condition. Meanwhile, an autonomous star observation system for super low orbit satellites is provided. The application can adapt to star observation task requirements under super low orbit height conditions, can overcome large aerodynamic interference moments under super low orbit conditions and large rotation moments caused by a turntable motor, can autonomously switch super low orbit star observation working conditions according to orbit heights, can reduce errors caused by ground orbit prediction, and can retain the ability of ground intervention whole satellite tasks, and can switch whole satellite autonomous observation and ground forced observation at any time.

The application discloses a TLE target library matching method and system for radar observation data, and belongs to the field of space target monitoring; the method comprises the following specific steps: S1, using an SGP4 model to derive and store position information of all targets in a TLE library; S2, converting radar measurement data into position coordinates of targets in an inertial system; S3, using an extended Laplace algorithm to perform initial orbit determination on a measurement arc segment; S4, screening targets in the TLE library according to the orbit determination result; S5, performing coarse matching of an observation arc segment and a space target by taking position mean square error as a criterion, and obtaining candidate targets; and S6, considering observation error and TLE orbit error, and determining a matching result according to covariance analysis; the application reduces the calculation amount of orbit prediction by using Lagrange interpolation technology, and screens TLE by using initial orbit determination results, so that unnecessary matching calculation can be avoided, coarse matching and fine matching are combined, the target matching speed can be ensured, and the matching precision can also be ensured.