361results about "Instruments for comonautical navigation" patented technology

The invention discloses a satellite collision avoidance system and method based on a satellite edge computing network. The system comprises a space monitoring network, a space traffic management subsystem and the satellite edge computing network. The space monitoring network is used for observing the running state of a space target to obtain multi-source observation data; the space traffic management subsystem is used for integrating the multi-source observation data to generate space target orbit data; the satellite edge computing network further comprises the steps that a GEO satellite broadcasts space target orbit data to an LEO satellite constellation and forwards collision risk screening information to a ground cloud computing center; the LEO satellite constellation calculates collision risk screening information according to the space target orbit data and formulates a collision avoidance control strategy; the LEO / GEO earth station is used for data transceiving and protocol conversion among the GEO satellite, the LEO satellite constellation and the cloud computing center; and the ground cloud computing center stores constellation orbit data through protocol conversion and satellite communication. According to the invention, the real-time performance of satellite collision avoidance is improved.

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 discloses an on-orbit spacecraft attitude estimation method and system based on ISAR image feature selection, and belongs to the field of aerospace control systems. The method comprises the following steps: acquiring an ISAR image of a spacecraft, and acquiring a complex linear structure set and three-dimensional feature points of an on-orbit spacecraft; then, according to the obtained three-dimensional-two-dimensional projection model, the CRLB of each reference structure in the complex linear structure set is deduced to carry out attitude estimation error analysis; calculating the trace of the CRLB covariance matrix of each reference structure to select an optimal feature structure, correcting the scattering point trace of the optimal feature structure by using polynomial fitting, and switching the reference structures as a new optimal feature structure according to the scattering point loss rate and a preset sequence; and optimizing the spacecraft attitude angle solving function by using a particle swarm and LM hybrid algorithm to obtain attitude angle parameters. The target with high-precision target attitude real-time estimation can be completed aiming at the problems that high-order frequency change in a dynamic environment is difficult to capture and resolution and noise suppression are contradictory due to a fixed window time-frequency analysis method.

The invention discloses a fuel-saving control on-satellite autonomous planning method for rapid accompanying flying, fly-around flying and sweeping flying of an elliptical orbit coplanar target, and relates to a fuel-saving control on-satellite autonomous solving method for rapid approaching and high-precision accompanying flying / fly-around flying / sweeping flying from a long-distance position on the same orbit surface. Comprising the following steps: providing a three-time planning and five-time maneuvering long-distance approaching accompanying flight / fly-around / grazing flight configuration forming method; the efficient iteration method is suitable for solving the initial value of a minimum fuel control analytical solution and the final value of an iterative precise solution of a high-precision orbit extrapolation model through a satellite autonomous solution two-body model. The method is suitable for a near-earth space random elliptical orbit satellite to quickly approach a long-distance target on an approximate same orbit to carry out accompanying flight / fly-around / grazing flight, and the control precision can reach a ten-meter level; and the calculation amount is small, and the method is suitable for on-satellite autonomous task planning and solving.

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 provides an integrated navigation method combining starlight refraction positioning with inertial navigation in a near space, and belongs to the technical field of starlight refraction navigation positioning. The method comprises the following steps: firstly, determining a state model of starlight refraction positioning in a near space by taking an error equation of an inertial navigation system of a near space aircraft as a state equation; designing a near space starlight refraction positioning algorithm, identifying a refraction star by using a star sensor on the aircraft, acquiring a refraction angle as a measurement, and establishing a measurement model of starlight refraction positioning in a near space; and obtaining the optimal estimation value of the system state variable by using an extended Kalman filter (EKF) method. The method has the advantages of being suitable for near space, high in reliability, high in autonomy and the like, and can be finally used for pure astronomical positioning and astronomical / inertial integrated navigation.

The invention relates to a lunar satellite formation collaborative navigation method, which comprises the following steps of: inputting an orbit state and an observation residual error of a lunar satellite formation at a previous moment into an LSTM (Long Short Term Memory) prediction network of a navigation algorithm to predict a process noise covariance matrix and an observation noise covariance matrix, and multiplying the process noise covariance matrix and the observation noise covariance matrix by a scaling factor for scaling, obtaining a scaled prediction process noise covariance matrix and a scaled observation noise covariance matrix; and inputting the orbit state of the lunar satellite formation at the previous moment, the multi-source observation data at the current moment and the scaled process noise covariance matrix and observation noise covariance matrix into a self-adaptive extended Kalman filtering module in a navigation algorithm to predict the orbit state of the lunar satellite formation at the current moment.

The invention discloses a star point coordinate extraction and star sensor attitude optimization method based on deep learning. The whole process of pseudo star map generation, star point coordinate extraction and attitude calculation is optimized. Multi-factor interference such as spacecraft jitter and optical distortion is simulated through dynamic star point modeling, and a high-fidelity pseudo star map is generated; a noise adaptive detection network is designed to fuse denoising and key point detection, and star point positioning precision in a low signal-to-noise ratio environment is improved; and optimizing attitude solution, constructing a loss function based on star point coordinates, and performing back propagation to optimize attitude parameters to realize an algorithm closed loop. According to the method, real data can be expanded to realize effective training of the model, and the positioning precision is improved; the star point coordinate positioning precision is improved to a sub-pixel level (RMSElt; 0.3 pixel); an end-to-end optimization framework reduces error accumulation in a traditional assembly line, and the robustness of the system is improved by 40%.

The invention discloses a landing positioning method and system based on fusion of vision and inertial navigation. The method comprises the following steps: collecting vision information of a current landing area; the visual information of the front landing area is mapped to an aligned grid of a map coordinate system through homography transformation, correlation matching is conducted on the visual information and a map through a frequency domain FFT algorithm, a matching result of rough matching is obtained, and rough matching is completed; the method comprises the following steps of: mapping an area subjected to rough matching and positioning to a grid aligned with a map coordinate system by utilizing homography transformation, performing spatial domain multi-window division on a larger range of images around the area subjected to rough matching and positioning, selecting a landmark area in each sub-window by applying an interest operator, performing spatial correlation matching on the landmark area and a map by utilizing a spatial correlation method, and performing spatial correlation matching on the landmark area and the map by utilizing a spatial correlation method. Finishing fine matching; inputting all matched observation results into an extended Kalman filter, and carrying out joint estimation on the matched observation results and the observation results of the inertial measurement unit; the method has the advantages that the robustness, the precision and the engineering applicability of an existing navigation positioning method are improved.

The present invention belongs to the field of signal processing technology and relates to a non-reconstruction direct positioning method based on mobile receiver data compression. The present invention aims to provide a non-reconstruction direct positioning method based on mobile receiver data compression. This method utilizes the characteristics of the Hadamard matrix to directly estimate the source position in the compressed measurement domain without the need for signal reconstruction and TDOA and FDOA parameter extraction. The present invention demonstrates that signals can still retain TDOA and FDOA information after Hadamard matrix compression, thereby reducing transmission throughput while maintaining positioning accuracy.

The invention discloses a dual-path non-cooperative spacecraft pose estimation method based on uncertainty perception, and belongs to the technical field of spacecraft pose estimation. According to the method, a dual-path prediction framework based on a shared backbone network is constructed and comprises a geometric reasoning path and a global context sensing path. In the training stage, prediction results of the two paths are aligned through a geometric consistency loss function, and joint optimization is carried out by combining multi-task losses such as key point regression, classification, rotation and translation regression and the like. In the inference stage, the pose estimation result is adaptively fused according to the predicted variance output by each path, when the variance is low, the output of the global context sensing path is directly adopted, otherwise, the key point projections of the two paths are combined, and the final pose is recovered. The method has higher estimation precision, robustness and interpretability in complex space environments such as shielding, illumination variation and large-scale variation, and provides reliable visual navigation support for on-orbit autonomous tasks.

The invention discloses a method for carrying out correlation and orbit determination on a space target based on a double-star optical observation result, and the method comprises the steps: obtaining the observation vectors of two observation stars for a certain space target in the respective visual fields, calculating the shortest distance between the observation vectors, and if the distance is always smaller than a threshold value in a time sequence, determining that the space target does not exist. And if not, determining that the two observation stars observe the same space target, calculating a midpoint of two observation vector common vertical lines of the same space target by the two observation stars as an orbit determination point, and performing orbit determination on the space target based on an orbit determination point sequence. According to the method, a low-cost space-based optical orbit determination mode is adopted, space target association is completed through an algorithm with low calculation cost, target consistency is judged based on observation vector distance constraints, a complex model or a large amount of calculation power is not needed, efficient processing can still be performed when the number of targets is large and the data size is large, and the cost and efficiency advantages are remarkable.

The invention belongs to the technical field of data processing, and discloses a Mars rover non-contact trafficability estimation method and system based on thermal inertia, and the method comprises the steps: obtaining a ground surface temperature time sequence and environment parameters of a target region; constructing a thermal inertia estimation model, and inputting the earth surface temperature time sequence and the environmental parameters into the thermal inertia estimation model to obtain a thermal inertia estimation value of the fire soil; constructing a thermal inertia and trafficability index relation model, inputting the thermal inertia estimation value of the fire soil into the thermal inertia and trafficability index relation model, and outputting a predicted trafficability index; and determining a trafficability state grade according to the predicted trafficability index, and generating a navigation control suggestion, so that the Mars rover passes through the target area according to the Mars rover navigation control suggestion. According to the method, the trafficability index of the Mars rover is predicted by extracting the thermal inertia estimation value of the fire soil in the target area, the evaluation precision of the Mars rover passing through the target area can be effectively improved, and the driving safety of the Mars rover is ensured.

The invention relates to an ephemeris orbit calculation method suitable for orbit extrapolation on an elliptical orbit satellite. The ephemeris orbit calculation method comprises the following steps: calculating ephemeris orbit base point parameters on the ground; ephemeris orbit base point parameters which are injected from the ground are provided; and performing orbit extrapolation by using the ephemeris orbit base point parameters to calculate the position and the speed of the satellite in the inertial coordinate system. According to the method, orbit extrapolation is carried out on the basis of ephemeris orbit base point parameters injected on the ground, the calculation amount is low, the method is suitable for satellite-borne calculation, the calculation precision is high, the high-precision requirement of real-time orbit forecasting in the elliptic orbit satellite inter-satellite communication period can be met, the calculation capacity constraint of a satellite service system can be met, and the completion degree of an inter-satellite communication task is improved.

The invention discloses a moon leap trajectory planning method, system and device and a medium. The method comprises the steps of obtaining target landing point data; based on the acquired data, establishing a moon surface leap device kinetic model by defining a specific coordinate system and a state variable; based on the kinetic model, discretizing the kinetic equation through a numerical integration algorithm, constructing and solving a leap trajectory convex optimization problem with optimal burnup, and obtaining an obstacle avoidance-free optimal trajectory; based on the obstacle avoidance-free optimal trajectory, performing obstacle avoidance iteration through an iteration obstacle increase strategy to obtain a static obstacle avoidance trajectory; and on the basis of the static obstacle avoidance trajectory, the flight trajectory is adjusted again by calculating the trajectory error band width and the maximum extension distance, and a dynamic safety enhanced trajectory is obtained. According to the method, safe, robust and efficient moon surface leap trajectory planning in a complex and uncertain environment is realized.

The invention discloses a robust adaptive fusion filtering astronomical attitude determination method and system, and belongs to the technical field of radio navigation. The method comprises the following steps: constructing an integrated navigation model of a starlight and inertial integrated navigation system based on Lie group description; obtaining an observation residual error and an observation residual error covariance of a corresponding mode; robust and adaptive mode parallel sub-filtering is carried out, and posterior states and covariances in the two modes are updated; updating the mode probability; and fusing the updated posterior state with the covariance to obtain fusion output of parallel sub-filtering, taking the fusion output of the parallel sub-filtering as final estimation of the starlight and inertial integrated navigation system based on Lie group description, and outputting an astronomical attitude determination result containing an azimuth angle, a pitch angle and a roll angle. The high-precision astronomical attitude determination method has strong adaptability, strong robustness and accuracy when coping with complex noise and measuring outliers, and can realize high-precision astronomical attitude determination of starlight and inertial integrated navigation in a complex dynamic environment.

The invention relates to a lunar satellite formation orbit adaptive estimation method based on EM-EKF. Comprising the steps that an extended Kalman filtering module of a navigation algorithm predicts the orbit state of the lunar satellite formation at the current moment based on the orbit state of the lunar satellite formation at the previous moment, observation data at the current moment, a process noise covariance matrix and an observation noise covariance matrix; and updating a process noise covariance matrix and an observation noise covariance matrix by an expectation maximization module of a navigation algorithm based on a state sequence formed by a series of orbit states output by the extended Kalman filtering module within a period of time. According to the method provided by the invention, the process noise covariance matrix and the observation noise covariance matrix can be dynamically estimated, and online adaptive updating of the extended Kalman filtering parameters is realized.

Spacecrafts are disclosed herein. The spacecraft can include a primary payload sensor, the primary payload sensor being aligned to capture images in a direction of a first axis, and at least one secondary imaging system for determining a position of the spacecraft, the at least one secondary imaging system being aligned to capture images in the direction of a second axis. The at least one secondary imaging system can include a housing, the housing including a first end and a second end, wherein the first end includes an opening into an internal portion of the housing, an image sensor positioned within the internal portion of the housing, and an optical element positioned within the internal portion of the housing, wherein the optical element has a length parameter and a width parameter, wherein one of the length parameter and the width parameter is larger than the other parameter.

The invention discloses a spatial distributed observation method based on irregular region geometric feature sampling, and belongs to the technical field of aerospace. The implementation method comprises the following steps: establishing a coordinate system for describing the motion of the spacecraft; establishing a spacecraft dynamic model under the coordinate system; six initial orbit elements of a satellite can be obtained based on existing low-orbit constellation orbit data, the spatial position is calculated through the orbit elements, and then position components are converted into latitude and longitude coordinates, namely sub-satellite point coordinates; defining vertex coordinates of the polygon, and constructing a planar polygon by connecting the vertex coordinates end to end; discretizing the internal region of the closed polygon; on the basis of the kinetic model, on the basis of the coordinates of the sub-satellite point and the center coordinates of the discrete sampling circle, calculating the characteristic distance from the sampling point in the observation area to the sub-satellite point, and on the basis of the size relationship between the characteristic distance and the radius of the observation view field, judging whether the irregular area can be successfully observed in a preset time constraint interval; therefore, spatial distributed observation is realized.

The invention discloses a GEO binocular orbit determination method and system based on inter-satellite communication, and belongs to the technical field of aerospace, and the method comprises the steps: predicting the priori estimation of the state variable of a binocular orbit determination system through unscented transformation according to an orbit dynamics model of the binocular orbit determination system; simulating and generating space-based observation data based on an observation model of a binocular orbit determination system; according to the principle of unscented Kalman filtering, the priori estimation of the state variable and the space-based observation data are fused, and the posteriori estimation of the state variable of the binocular orbit determination system is obtained; repeatedly iterating until the posteriori estimation orbit determination precision of the state variable of the binocular orbit determination system meets the task requirement; according to the method, target observation data is obtained through binocular observation, observation data between observation satellites is obtained by considering inter-satellite communication, prediction data and the observation data are fused through an unscented Kalman filtering algorithm, and a high-precision orbit determination method is provided for a GEO spacecraft.

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 discloses a multi-source data fusion dynamic reference frame conversion method and a related device, and relates to the technical field of celestial body survey and space navigation, and the method comprises the steps: obtaining multi-source observation data, including pulsar timing data and VLBI absolute position measurement data; according to the multi-source observation data, a joint observation model and a high-order rotation model are established, the joint observation model is a mathematical model comprising a calendar error correction term and a coupling coefficient, and the high-order rotation model is a model which is established based on a quaternion parameterized rotation matrix and introduces a secondary correction term for nonlinear correction; on the basis of the combined observation model, a self-adaptive weighted least square algorithm is adopted, and rotation parameters are obtained through estimation; and based on the rotation parameter and the secondary correction term, performing error tracing and iterative optimization by adopting a Monte Carlo simulation method to obtain a dynamic reference framework conversion result. According to the invention, the conversion precision of the dynamic reference frame can be improved, and high-precision space reference conversion is realized.

The application relates to the technical field of photoelectric attitude sensors, and discloses a linear array infrared earth sensor, which comprises a control unit, a shell and a power supply unit arranged in the shell. Four earth boundary infrared radiation detection units for receiving infrared radiation from different parts of the earth are arranged on the shell. A front-end light signal conversion electric signal amplification unit for converting light signals detected by the earth boundary infrared radiation detection units into electric signals and a rear-end electric signal information processing unit for performing attitude and solving on the electric signals are further arranged in the shell. The sensor has high generality and wide detection range.

The invention discloses a satellite orbit single-point state forecasting method based on deep learning. An orbit precision ephemeris is used as training data, a six-dimensional position speed state at a current moment is used as input, a state at a next moment is used as a target value, a prediction network in which LSTM and a one-dimensional CNN are connected in series is constructed, and a CBAM attention module is introduced to realize adaptive weighting of channel and time sequence features. And designing a weighted loss function, carrying out weighted fusion on a mean square error of the model to a real ephemeris, an HPOP equal-step prediction result and a residual mean square error output by the model, and improving prediction rationality through physical constraints. And training and evaluating through the training set, the verification set and the test set, and outputting a predicted ephemeris. According to the method, a historical sequence or TLE is not needed, high-precision and rapid forecasting can be achieved only through a single-point state, and unmodeled perturbative force is implicitly compensated.

The application discloses a target initial orbit determination method and device based on spatial filtering velocity measurement, which comprises the following steps: acquiring a star position image; determining an observation target according to the star position image, and establishing a mapping relationship between a measurement coordinate and an angle position of the observation target; modulating the star position image to obtain a distribution signal of target brightness of the observation target changing with time; acquiring a velocity of the observation target according to the distribution signal of the target brightness changing with time; obtaining an angular velocity and an acceleration of the observation target according to the velocity of the observation target through the mapping relationship between the measurement coordinate and the angle position of the observation target; and obtaining a position vector and an initial orbit velocity of the observation target relative to the earth center through an initial orbit determination algorithm. Compared with a traditional initial orbit determination method, the application directly measures the angular velocity of the target, reduces the coupling between the angle position error and the angular motion quantity, improves the initial orbit determination precision of the target under the observation error condition, and realizes the rapid orbit determination of the target.

This invention discloses an event-triggered unscented Kalman filter spacecraft orbit estimator, comprising: a spacecraft orbit system module for establishing the state equation and measurement equation of the spacecraft's motion along its orbit; an event triggering module for determining whether an event triggering condition is met, and based on the determination result, determining whether to transmit the current ground station measurement information to the unscented Kalman filter estimation module; and an unscented Kalman filter estimation module for estimating the orbit at the current moment based on the spacecraft's state equation and measurement equation, combined with the current ground station measurement information transmitted from the event triggering module, and determining whether the current orbit deviates from the spacecraft's predetermined orbit based on the current orbit estimation result. The estimator described in this invention can reduce the communication rate while ensuring estimation effectiveness, thus solving the problem of limited communication resources during information transmission between the spacecraft and the ground station.

The application provides a celestial body orientation parameter solving method and system based on inverse VLBI interferometry and a medium. The method comprises the following steps: firstly, a rotation orientation physical model of a celestial body and an inverse VLBI differential measurement model are established, a lander coordinate and a celestial body orientation parameter are introduced into the model by combining the conversion between a non-inertial system and an inertial system coordinate. High-precision differential measurement tracking data of inverse VLBI are obtained, and based on the principle of the least square method, a lander position and a celestial body orientation model parameter are determined, so that the residual square sum between the calculated theoretical observation value of inverse VLBI and the ground observation value is minimum, and high-precision extraterrestrial celestial body orientation parameters are obtained. The application can realize precise positioning of a lander and solving of celestial body orientation parameters, the obtained data are high in precision, high-precision inverse VLBI differential measurement data can significantly improve the solving precision of the celestial body orientation model parameters, and then information about the internal structure and surface mass distribution change of the celestial body is provided, and additional constraints for the improvement of the celestial body physical model are provided.

The invention provides a spacecraft attitude orbit navigation initial value on-orbit establishment method and device, and belongs to the technical field of spacecraft navigation.The method comprises the steps that a navigation system single-machine product configuration scheme and a single-machine installation layout scheme are designed; judging whether the platform is successfully separated from the mother platform or not; the self angular rate is damped; performing slow rotation search around two axes of the body, and preliminarily establishing an inertial system attitude initial value; carrying out slow rotation search around two axes of the body, and preliminarily establishing an initial speed value of the earth fixed connection position; performing attitude maneuver based on the inertial system attitude initial value and the earth fixed connection system position speed initial value, and adjusting the attitude to a final stable direction capable of capturing the attitude and the position speed at the same time; and according to the attitude and position speed result, calculating the position speed and attitude result under the expected reference system as a final inertial navigation initial value. According to the invention, a software and hardware interface for information transmission does not need to be arranged between the spacecraft and the release mother platform, and the capability of on-orbit self-establishment of inertial navigation attitude and position speed initial values is realized.

The invention discloses a constellation communication-navigation coupling task scheduling method based on load balancing, and belongs to the technical field of aerospace mission planning. The method mainly improves the resource distribution efficiency under the device-level constraint, and achieves the purpose of meeting the geometric precision requirement of navigation service while guaranteeing the completion of a communication task. According to the method, satellite ephemeris data and task demand parameters are used as input, a multi-target mixed integer linear programming MILP model is constructed, an optimal binary allocation variable is solved through an MILP solver, service satellites and service time slots of tasks are extracted from the optimal binary allocation variable, and then a scheduling table is generated; according to the method, the problem of navigation task failure caused by the fact that a communication task occupies a multi-satellite convergence window in separated planning is avoided, simulation shows that the overall task completion rate is averagely increased by 12.3%, and the load variation coefficient is reduced by 66%-88%.

This invention proposes a method and system for autonomous orbit determination of low-orbit constellations based on BeiDou B2b and intersatellite distances, belonging to the technical field of orbit determination for low-orbit navigation constellations. The method includes acquiring BeiDou B2b correction data from low-orbit satellites and performing corrections to obtain an observation dataset; utilizing a bidirectional observation mode to acquire raw intersatellite ranging data between two low-orbit satellites and obtain an intersatellite distance solution; constructing a Kalman filter model based on the observation dataset and the intersatellite distance solution to predict and correct dynamic orbits; and converting the Kalman filter model into a square root information filter model, outputting a high-precision orbit solution through real-time joint filtering. This invention enables fully autonomous navigation and high-precision orbit determination based on intersatellite links while reducing computational latency and burden.