643results about "Instruments for comonautical navigation" patented technology

The invention provides an aircraft and satellite cluster collaborative navigation positioning accurate control method and system, and relates to the technical field of aviation, and the method comprises the steps: an aircraft receives a multi-system navigation signal from a satellite cluster, carries out the fusion processing of multi-source navigation information through employing a self-adaptive Kalman filtering algorithm, and carries out the navigation positioning of a satellite cluster based on the fused multi-source navigation information. Calculating the accurate position of the aircraft by adopting a differential positioning technology; and transmitting the optimal control instruction to a flight control system of the aircraft based on the accurate position of the aircraft in combination with a preset flight plan, calculating a correction instruction by using a satellite-ground cooperative trajectory correction algorithm when trajectory deviation is detected, and transmitting the correction instruction to the aircraft through a high-frequency broadband communication system, and closed-loop accurate control of the track of the aircraft is realized.

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 provides a lunar satellite formation autonomous navigation method based on inter-satellite ranging information. The lunar satellite formation autonomous navigation method comprises three parts of orbit dynamics model establishment, collaborative observation model establishment and navigation filtering algorithm data fusion. The invention provides an autonomous navigation method based on inter-satellite distance measurement and angle measurement information, which establishes a high-precision dynamic model containing 165-order moon non-spherical perturbation for moon satellite formation. The system can operate independently of a ground station, and high-precision autonomous navigation of the lunar satellite formation is realized only by using on-orbit observation data.

The invention relates to the technical field of unmanned aerial vehicle route planning, and discloses a low-altitude route risk map construction method and system based on artificial intelligence, and the system comprises a low-altitude environment perception constraint module, a low-altitude route feature extraction module, a dynamic risk constraint judgment module, a low-altitude route map construction module, and a low-altitude route risk analysis module. And the optimal path calibration output module is used for determining a low-altitude air route flight area by acquiring a first constraint condition of low-altitude air route environment perception, extracting key feature parameters from low-altitude air route data, performing second constraint condition analysis on the low-altitude air route, intelligently planning a low-altitude air route route according to an analysis result, and constructing a low-altitude air route map. According to the method, the low-altitude air route is acquired, the constant direction line risk analysis is performed on the low-altitude air route to calibrate the optimal path, the optimal path is output to the user terminal, the path three-dimensional display is performed in the low-altitude air route map, and the execution efficiency and the safety of the flight task are improved.

The invention discloses a Beidou satellite orbit determination method and system, a medium and equipment, and relates to the technical field of satellite geodetic survey, and the method comprises the steps: obtaining inter-satellite link distance measurement observation value data, and carrying out the preprocessing; according to the preprocessed observation value data, obtaining a clock-correction-free combined observation quantity and a clock-correction-free combined observation quantity at the same moment, and establishing a clock-correction-free combined observation model and a geometric-correction-free combined observation model; after the inter-satellite link observation residual error is fitted, a time domain is converted into a frequency domain through Fourier transform, and a periodic signal of the frequency domain is detected; establishing a link observation model, introducing a star-star pair deviation of an inter-satellite link, and adding a cosine term and a sine term of an orbital period parameter to obtain an improved link observation model; converting the refined link observation equation in the observation time period into a normal equation form, superposing all normal equations, and processing through a least square method to obtain to-be-estimated orbit parameters; and performing orbit fitting on the to-be-estimated orbit parameters to obtain orbit parameters, and further confirming a Beidou satellite orbit determination result.

The invention discloses an initial orbit determination method for passive angle measurement of a ring fire orbit for Mars sampling return, and the method comprises the steps: building an absolute dynamic model, obtaining an absolute motion state of a spacecraft, and deducing a relative motion state X; constructing a data set by using the measurement quantities H and X of the sensor; a network architecture is designed, input data I are position and speed coordinates of the tracker in a Mars equator inertial coordinate system and angle information converted from H, and output data are X; and finally, adjusting an observation interval dt and times k according to a ring fire observation condition, training a physical information neural network by using limited observation data, defining a total loss function F comprising a loss function FY and a physical law penalty term FD, and optimizing a weight coefficient and bias by minimizing the loss function through an F gradient descent method. According to the method, the neural network is trained offline, a network mapping model from a target line-of-sight angle measurement sequence to a target orbit is constructed, and the network mapping model is solidified on a returner for online use, so that sampler short-arc passive measurement rapid orbit determination is realized.

The invention discloses a spacecraft attitude estimation method based on a prior model and an ISAR image, and relates to the technical field of spacecraft in-orbit attitude estimation, and the method comprises the steps: S1, employing a target detection network YOLOv8 to extract key points from an ISAR (inverse synthetic aperture radar) image; s2, reading a three-dimensional key point on the priori three-dimensional model, and projecting the three-dimensional key point to a two-dimensional imaging plane in a posture adjustment mode to obtain a projection point; s3, calculating an error between the projection point and the key point so as to calculate a loss value through a weighted loss function; and S4, optimizing the function for solving the attitude angle of the spacecraft by adopting a particle swarm optimization (PSO) algorithm to obtain an attitude estimation result of the ISAR image. According to the spacecraft attitude estimation method based on the prior model and the ISAR image, the key points of the ISAR image and the key points of the prior model are matched, accurate attitude estimation can be achieved only through a small number of key points, and the anti-noise performance and estimation robustness are remarkably improved.

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 discloses a non-cooperative spacecraft attitude estimation method and system based on a laser radar, and the method comprises the steps: obtaining a scanning point, observed by the laser radar, of a non-cooperative spacecraft, carrying out the attitude initialization of the scanning point, obtaining a scanning point cloud, constructing a reference model of the non-cooperative spacecraft, and carrying out the attitude estimation of the non-cooperative spacecraft. The scanning point cloud is matched with the reference model to obtain a matching result, attitude tracking is performed on the matching result based on an iterative nearest point algorithm and a Kalman filter to complete attitude estimation of the non-cooperative spacecraft, and the problem of attitude tracking of the non-cooperative spacecraft of an airborne LiDAR system is solved. The limitation of an attitude initialization method based on template matching and point cloud registration is overcome, and the relative state of the non-cooperative spacecraft can be accurately estimated.

The invention discloses an astronomical positioning method for a space target elongated astronomical image of a large-field-of-view space-based monitoring platform, relates to the technical field of astronomical observation, and solves the problem that the elongated astronomical image is abandoned due to incapability of target association and precise orbit determination caused by inaccurate centering of the elongated astronomical image and low precision of a positioning method of an existing monitoring platform. According to the method, an observation image is divided into 16 sub-view fields, and each sub-view field is an independent view field and is calculated by an independent processor; removing fixed stars in the observation image by adopting an adjacent frame image difference method and extracting a space target star image; secondly, describing the length and angle of the lengthened astronomical image by adopting a minimum enclosing rectangle, and constructing a degradation model; performing motion blurred image restoration on the elongated star image; error points with large errors are eliminated by adopting a mutual comparison method, and track association of the space target is completed; and finally completing precise astronomical positioning of the elongated astronomical image and the like. According to the method, the processing efficiency is greatly improved, and a large number of lengthened astronomical images which are abandoned before are fully utilized again.

Techniques for maneuvering a space vehicle are presented. The techniques can include: obtaining a representation, in a computer, of a multi-segment planned position, planned velocity, and planned acceleration of the space vehicle along a planned continuous trajectory; tracking, using at least one navigation sensor, an indication of an actual position, actual velocity, and actual acceleration of the space vehicle; and maneuvering the space vehicle, using a closed-loop controller, and based on the tracking, to return to the planned position, planned velocity, and planned acceleration.

The invention provides a lunar polar region sun synchronization # imgabs0 # path planning method, which can be applied to the technical field of celestial body image processing and path planning. The method comprises the following steps: independently training a plurality of enhanced U-Net models by using training data with time sequence slices and fusion types and a mixed loss function; dividing and extracting the reasoning data with a time sequence slice type and a time sequence fusion type by using a plurality of trained enhanced U-Net models to obtain a lunar polar region friendly illumination region, and preprocessing the reasoning data with the lunar polar region friendly illumination region and gradient data corresponding to the lunar polar region friendly illumination region; and based on the reasoning data after time alignment and the gradient data after space alignment, constructing a heuristic function by using mixed cost, and performing heuristic path planning by using an improved # imgabs1 # path planning algorithm with a time one-dimensional function and an in-situ waiting function to obtain a sun synchronization planning path of the lunar polar region.

The invention belongs to the technical field of space photoelectric detection, and provides a high-precision tracking and pointing system and method capable of autonomously formulating an observation task in orbit. The system comprises an information processing unit, a power supply management unit, a task management unit, a thermal control unit, a GNSS unit, a star sensor unit, a gyroscope unit, a tracking and pointing calculation unit and a servo turntable unit. The system can receive a platform instruction, integrate information of sensors such as a GNSS, a star sensor and a gyroscope, calculate the accurate position of a tracked celestial body, and adjust the direction of a servo turntable in real time so as to accurately track a target. The working method comprises the steps of system starting and initializing, observation task making, tracking and aiming mode preparing, aiming direction correcting, observation target tracking and aiming, exception handling and the like. The system can realize high-precision observation of a celestial body target without depending on attitude adjustment of a spacecraft platform, improves the observation efficiency and reliability, and is suitable for observation of celestial bodies such as pulsar on a space station platform.

The invention discloses a double-layer optimization method and system for direct transfer between earth-moon special orbits under an ephemeris model, relates to the technical field of detector transfer design between the earth-moon special orbits, and aims to solve the technical problem that a traditional method cannot be suitable for direct transfer between the earth-moon special orbits with higher precision requirements. According to the technical key points, the method comprises the following steps: constructing a high-precision ephemeris dynamic model, and correcting an obtained discrete orbit data initial value by using the high-precision ephemeris dynamic model; constructing a direct transfer optimization model based on the corrected discrete orbit data with the time label and a high-precision ephemeris dynamical model; splitting and reconstructing the direct transfer optimization model; and iteratively solving the split and reconstructed direct transfer double-layer optimization model by using a multivariate universe optimization algorithm and a sequential quadratic programming algorithm with adjustment capability to obtain an index evolution iteration curve and a transfer orbit curve. According to the method, the optimal design of the direct transfer orbit between the earth and moon special orbits under the ephemeris model with higher precision requirements is realized.

The present disclosure relates to an information processing device and an information processing method for providing an imaging service for performing imaging with a camera mounted on an artificial satellite.An information processing device includes a display control unit that causes a first screen to be displayed, the first screen including a map display unit that displays an artificial satellite that orbits around a celestial object and an orbit of the artificial satellite on a map of the celestial object, and a time information display unit that displays time information on the orbit of the artificial satellite. The display control unit causes the first screen to synchronously display the position of the artificial satellite on the map of the celestial object on the map display unit and the time information about the artificial satellite on the time information display unit. The technology according to the present disclosure can be applied to an information processing device or the like that provides an imaging service for performing imaging with a camera mounted on an artificial satellite, for example.

The invention provides an optical navigation method and device for an earth-moon spacecraft, electronic equipment and a storage medium. The method comprises the steps that an optical image of the moon is shot through image acquisition equipment, the optical image is analyzed according to imaging parameters of the image acquisition equipment, the angle diameter of the moon is obtained, the target distance of the earth-moon spacecraft relative to the moon is calculated according to the angle diameter of the moon, and the optical image comprises the surface of the moon; measuring starlight angular distance information between the earth-moon spacecraft and the moon by adopting a star sensor, wherein the starlight angular distance information is used for representing the angular distance between the navigation star and the centroid of the moon detected by the star sensor; and calculating the current orbit position and the current attitude of the earth-moon spacecraft by adopting a navigation solution algorithm according to the target distance and the starlight angle distance information.

The invention discloses a lunar satellite orbit determination method and device based on radio and laser ranging, and relates to the technical field of lunar satellite orbit calculation, and the method comprises the steps: obtaining observation data of a radio tracking station and a laser station; establishing a high-precision kinetic model of the lunar satellite; establishing a lunar satellite radio and laser ranging mathematical model, and processing observation data according to an observation equation to obtain a kinetic parameter resolving value of the satellite at the initial orbit determination moment; and substituting the kinetic parameter resolving value into the satellite shot motion equation, and resolving to obtain an orbit determination result of the lunar satellite. According to the method, radio ranging and laser ranging are combined for orbit determination, precise orbit determination of the lunar satellite is achieved, compared with a traditional orbit determination mode, the precision and reliability are greatly improved, the requirements for the arrangement number and geometric distribution of ground stations are reduced, and the measurement and control pressure of existing ground stations is relieved.

The invention relates to a starlight atmospheric refraction navigation method and device based on ray tracing and electronic equipment, and the method comprises the following steps: simulating a transmission process of real starlight in the earth atmosphere according to ray tracing on the basis of a global atmospheric refraction index field by utilizing a refracted starlight observed quantity obtained by observation of a star sensor; and establishing an iterative algorithm to estimate the refraction apparent height, and positioning the spacecraft through the mapping relation between the apparent height and the position of the spacecraft. The method can effectively reduce the influence of global atmospheric temporal and spatial change on starlight atmospheric refraction navigation, and improves the autonomous navigation precision of a spacecraft.

The invention belongs to the technical field of visual navigation, and particularly relates to a detector pose measurement system and method.The detector pose measurement system is arranged on a detector and comprises a camera and a laser range finder; the camera is arranged at the bottom of the detector and faces the lower part of the detector; the laser range finder is arranged on a supporting leg of the detector and faces the lower part of the detector; the number of the supporting legs is at least three, each supporting leg is provided with a laser range finder, and the laser range finders are arranged around the camera; and laser points of the at least three laser range finders are located in the view field range of the camera. Compared with the prior art, the problems that in the prior art, a perception system for visual navigation is low in integration level and a calculation method is high in complexity are solved, the perception system with the high integration level and the calculation method with the low complexity are achieved, and soft landing of a detector on the surface of a planet can be well served.

The invention discloses a dynamic threat-based LGVF-APF-SAC spacecraft path planning method, a storage medium and an electronic device, and the method specifically comprises the following steps: firstly, building a real-time risk function according to a dynamic threat (radar detection exposure risk), and further generating an early warning region according to the risk function (radar radiation); based on the early warning area, an improved dynamic time-varying LGVF is used to construct a guide potential field based on the dynamic time-varying LGVF, so that the spacecraft is guided to avoid the early warning area to reach a target point. Then, an end-to-end reinforcement learning framework is developed; according to the framework, a maximum entropy RL (SAC) algorithm is selected, and a constructed guide potential field is integrated into a learning process in a reward function form so as to evaluate and optimize decision actions of a spacecraft. According to the algorithm provided by the invention, the dynamic adaptive capacity and reliability of path planning can be improved while the dynamic overload condition of the spacecraft is ensured to be met.

The invention relates to the field of aerospace thermal control, in particular to a star sensor light shield based on foam carbon and phase change materials, which comprises a foam carbon main body, and two phase change materials with different melting points are filled in pores of the foam carbon main body; the graphene film is co-cured on the outer surface of the foam carbon main body and completely covers the outer surface of the foam carbon main body; the heating sheets are adhered to the outer surface of the graphene film in the circumferential direction of the foam carbon main body to form different heating areas; the thermistors are adhered to the positions, corresponding to the heating areas, of the outer surface of the graphene film; the outer surface of the graphene film is covered with the multi-layer heat insulation assembly; and the temperature controller is used for adjusting the output power of the heating sheet by adopting a self-adaptive temperature control algorithm according to the temperature data acquired by the thermistor and the state of the phase change material, and controlling the temperature of the star sensor light shield within a preset temperature range. The direct solar radiation heat flow on the light shield can be effectively inhibited and dredged, and the high thermal stability control of the light shield is realized.

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 relates to the technical field of fault detection, and discloses a redundant strapdown inertial measurement unit fault diagnosis and isolation method and system, so as to improve the overall performance of fault processing. The method comprises the following steps: determining target objects of fault diagnosis, wherein the target objects are grouped gyroscopes or add tables in the same redundant strapdown inertial measurement unit; the method comprises the following steps: calculating a variation trend and a constant of any gyroscope or accelerometer in a target object based on previous continuous frames based on a least square method, then calculating a predicted value of a current frame according to the variation trend and the constant, then calculating whether a difference value between the predicted value of the current frame and a measured value is greater than a set prediction threshold value, and if so, judging whether the difference value is greater than the set prediction threshold value. And judging that the corresponding gyroscope or accelerometer has a fault, and performing isolation processing on the gyroscope or accelerometer having the fault.

The invention provides a low-orbit constellation autonomous orbit determination method and system based on Beidou B2b and space between satellites, and belongs to the technical field of low-orbit navigation constellation orbit determination. Comprising the following steps: acquiring Beidou B2b correction data of a low-orbit satellite and correcting the Beidou B2b correction data to obtain an observation data set; obtaining original inter-satellite distance measurement data between two low-orbit satellites by using a bidirectional observation mode, and obtaining an inter-satellite distance solution; a Kalman filtering model is constructed based on the observation data set and the inter-satellite distance solution, and a dynamic orbit is predicted and corrected; and converting the Kalman filtering model into a square root information filtering model, and outputting a high-precision orbit solution through real-time joint filtering. According to the invention, on the basis of reducing calculation delay and burden, completely autonomous navigation and high-precision orbit determination based on inter-satellite links can be realized.

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.