303results about "Navigation by astronomical means" patented technology

The present invention relates to a solar azimuth estimation method and system based on multi-channel feature enhancement and region-aware attention, belonging to the technical field of intelligent navigation for low-altitude economy unmanned systems. Aiming at the problem of decreased accuracy in solar azimuth estimation based on polarization images under complex cloud cover conditions, the present invention proposes a deep learning framework integrating multi-channel features and direction-aware attention. First, based on polarization light field information acquired by a division-of-focal-plane polarization camera, a three-channel composite input feature composed of a polarization intensity map, an adaptive threshold gradient map, and high-frequency residual edge information is constructed. Second, a ResNet backbone network embedded with a squeeze-and-excitation mechanism is adopted, and a direction-aware polarization attention module is introduced to achieve adaptive fusion of multi-scale features through luminance guidance, deep feature enhancement, and a gradient edge branch.

The invention relates to a sun meridian detection and course angle real-time calculation method based on polarized light field vector characteristics, and aims to solve the problems that a traditional sun meridian detection method is easily interfered in low signal-to-noise ratio scenes such as haze and cloud layer shielding, lens distortion causes polarization angle errors, the false detection rate is high, and the calculation accuracy is high. In order to solve the problems that the real-time performance and robustness of course calculation are affected due to the fact that single polarization angle information is difficult to fully reflect the sun direction, polarization parameter calculation is carried out by utilizing a multi-channel polarization image, and the sun meridian is detected by adopting Hough transform through fisheye lens correction, bilateral filtering and candidate region screening, so that the real-time performance and robustness of course calculation are improved. And a multi-point inversion method is combined to accurately obtain a sun vector and a zenith angle and an azimuth angle thereof, and finally a course angle is calculated in real time. The problems of imaging distortion and insufficient real-time processing in the traditional sun positioning technology can be effectively solved, and a powerful navigation positioning technical guarantee is provided for the fields of unmanned aerial vehicles, autonomous navigation, polarized light navigation and the like.

The present invention relates to a real-time heading angle calculation method based on the vector characteristics of the polarized light field. Aiming at the problems of traditional solar meridian detection methods, such as being easily disturbed in low signal-to-noise ratio scenarios like haze and cloud cover, the occurrence of polarization angle errors and high false detection rates caused by lens distortion, and the difficulty of using single polarization angle information to fully reflect the solar direction, which affects the real-time performance and robustness of heading calculation. This method calculates polarization parameters by using multi-channel polarization images.

Methods and systems are provided for determining navigational information for an entity such as a vehicle using celestial measurements. One method involves determining a Kalman gain based at least in part on inertial measurement data at or before a current point in time associated with the celestial measurement data, determining a celestial measurement error based at least in part on a relationship between the celestial measurement data and a prior estimate for the celestial measurement data, determining a current estimated error associated with the location of the entity based at least in part on a prior estimated error associated with the location, the Kalman gain and the celestial measurement error, and determining an updated estimate of the location of the entity based at least in part on the current estimated error and a prior estimate of the location of the entity.

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 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 relates to the technical field of space target detection, in particular to a dynamic space target detection method based on event information, and the method comprises the steps: reading a target event flow according to a certain time length, and obtaining an initial pseudo image frame; eliminating noise events based on the corresponding event density information by using a pre-established circular local sliding window, and judging whether a certain noise reduction condition is met or not; if not, eliminating noise events based on the corresponding event density information by using the self-adaptive filtering characteristic of a pre-established multi-neighborhood radius local sliding window, and calculating the centroid information of the detection space target; judging whether the centroid information meets a certain precision condition or not; and if not, correcting the motion track by using the data of the inertial measurement unit to obtain centroid information meeting a certain precision condition, and obtaining motion information of the detection space target. Therefore, the problems of low space target extraction precision, difficult tracking and the like in a high-dynamic maneuvering scene are solved.

The invention belongs to the technical field of attitude change detection, and particularly relates to a real-time monitoring system and method for attitude change of a front-rear view surveying and mapping camera. The method comprises the following steps: firstly carrying out ground calibration, then determining a reference moment as a moment when the real-time monitoring system starts to start, then constructing a monitoring link at the reference moment, measuring a corresponding matrix obtained at a working moment, finally confirming the monitoring link at the working moment, and deducing a transformation matrix of the front-view camera and the rear-view camera under a J2000 coordinate system. According to the method, the real-time performance of the measurement process and the comprehensiveness of system monitoring can be considered while the geometric accuracy of the surveying and mapping camera is ensured.

The invention discloses a near-earth space all-day star sensing system based on a sub-wavelength metal grating and a working method thereof, and belongs to the technical field of star sensors. In order to increase the number of fixed stars which can be detected by the near-earth space all-time star-sensitive system, the near-earth space all-time star-sensitive system comprises an optical system, an InGaAs detector, a spectrum optical filter, a micro-polaroid array, a memory, a processor, a control unit and a time unit, the InGaAs detector is respectively connected with the micro-polaroid array, the memory and the control unit; the micro-polaroid array is connected with the optical system, and the optical system is connected with the spectrum optical filter; the memory is respectively connected with the processor and the time unit; and the processor is connected with the control unit. According to the invention, the polarization filtering work of the sky background is realized, and the number of observable fixed stars is effectively increased on the basis of ensuring the miniaturization of a near-earth space all-day star-sensitive system.

The invention provides an inertial navigation aided navigation positioning method and system, and the method comprises the steps: calculating the coordinate of each navigation satellite in an ECEF coordinate system according to the satellite ephemeris of a satellite navigation system; according to the navigation satellite coordinate and the inertial navigation system positioning result, the azimuth angle and the pitch angle of the navigation satellite relative to the optical detection equipment under the ENU coordinate system are solved, and the navigation satellite is tracked; acquiring star maps collected by the optical detection equipment, matching the star maps through a star map recognition algorithm, resolving a coordinate transformation matrix between two continuous frames of star maps, and recognizing fixed stars and satellites in the star maps based on the transformation matrix; converting the identified fixed star in the field of view into an ECEF coordinate system, calculating an observation angular distance between the fixed star and the satellite, and calculating a satellite observation vector in the ECEF coordinate system according to the observation angular distance; and performing error correction on the positioning result of the inertial navigation system based on the satellite observation vector. Through the scheme, the positioning precision of the inertial navigation system can be improved, and the influence of interference deception signals is reduced.

The invention discloses a star sensor fixed star detection capability analysis method based on a polarization degree image, and belongs to the technical field of star sensor detection. In order to solve the problems of few detection means and low utilization rate of sky light radiation information during star observation of a near-earth space all-time star sensor, the method comprises the following steps: constructing a star sensor integrated with a focal plane micro-polarizer array, and acquiring four gray star maps through short exposure by using the star sensor integrated with the focal plane micro-polarizer array; a star sky Stokes vector diagram is calculated; calculating star sky polarization degree distribution to obtain a polarization degree star map; constructing a fixed star polarization signal-to-noise ratio calculation formula in the polarization degree star map by utilizing a physical process of converting radiation energy into polarization degree; the calculation formula calculates the polarization signal-to-noise ratio of the fixed star in the field of view; and comparing the polarization signal-to-noise ratio of the fixed star with a signal-to-noise ratio threshold value detected by the near-earth space all-time star sensor, and judging the detectable capability of the fixed star in the polarization degree star map. According to the method, the robustness of the near-earth space all-day star-sensitive technology to a complex environment is improved.

The invention discloses a star point motion parameter estimation method for a high-dynamic star sensor. The method specifically comprises the following steps: (1) acquiring a star map under a dynamic condition through a fixed star sensor; (2) carrying out filtering preprocessing on the fixed star sensor image obtained in the step (1); (3) carrying out threshold segmentation on the image processed in the step (2) and carrying out connected domain extraction to obtain rough star points; (4) selecting the brightest star point in the star points obtained in the step (3); (5) obtaining a sub-pixel star point track by using the brightest star point adjacent area obtained in the step (4) and adopting a Zernike moment sub-pixel edge extraction method; and (6) utilizing the sub-pixel star point trajectory obtained in the step (5), and adopting least square fitting to obtain star point motion parameters. The method has the beneficial effects that the precision of star point trailing length and angle estimation is improved, so that the extraction precision of star points in a dynamic environment is improved, and the precision of a fixed star sensor is improved.

The invention discloses a fixed star detection capability improving method fusing energy and polarization information, and belongs to the technical field of star sensor detection. In order to solve the problem that a near-earth space all-day star sensor is insufficient in fixed star detection capability in a strong atmospheric background stray light interference environment, the method comprises the following steps: exposing the sky once by using a star sensor integrated with a focal plane micro-polarizer array to obtain four gray star maps; calculating a polarization degree calculation value to obtain a polarization degree star map, and determining the sky background polarization degree; setting a polarization degree segmentation threshold value; performing threshold segmentation on the polarization degree star map to obtain a polarization degree star map segmentation result; determining a weight coefficient according to the radiation energy ratio of the fixed star to the sky background; and comparing the sky background polarization degrees, and performing weighting processing on the gray star map or the accumulated star map with the highest signal-to-noise ratio based on different conditions to obtain a final processed high-signal-to-noise-ratio star map. According to the invention, the fixed star detection capability is effectively improved.

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.

This paper discloses a polarization fusion orientation method for occluded environments. First, a polarization camera is used to capture a polarized image of the sky. The heading angle output by the E-vector polarization orientation method is used as the state variable, and the heading angle output by the fitted symmetry axis polarization orientation method is used as the observation variable. The heading angle fusion is achieved using a multi-frequency variational Bayesian strong tracking volumetric Kalman filter (MF-VBSTCKF). Different methods are selected to update the optimal heading angle at the sampling point and during the sampling interval. This method solves the problem that polarized light cannot achieve high-precision and high-robust heading angle measurement in occluded environments. It can improve the accuracy and robustness of polarization light orientation methods in occluded environments while ensuring high-frequency output of heading angles.

The application discloses a kind of combined navigation system online calibration method, system, storage medium and terminal, comprising: establishing the state space model of combined navigation system online calibration, the state space model includes the space installation error of auxiliary sensor, the constant drift of gyroscope, scale factor error and the bias error of accelerometer, while introducing the reference information provided by multiple auxiliary sensors;Error correction is carried out to the calibration parameter and navigation parameter of the online calibration model;The output information of different navigation sensors is information fusion;The state space model is carried out observability analysis and design maneuver trajectory.The present application can solve the problem that part of calibration parameter cannot be estimated and the observability of IMU scale factor error is weak in the existing combined navigation system online calibration method, while improving the calibration efficiency and precision of combined navigation system.

The invention provides an integrated calibration method, device and equipment for photoelectric non-uniformity of an optical star measurement sensor, and relates to the technical field of spacecraft celestial navigation. The method comprises the following steps: constructing lattice structure light to form array image spots on a star sensor, resampling to establish an actual PSF model, and realizing optical system aberration calibration of a corresponding area; sequentially displacing the array image spots, and calibrating the electrical response non-uniformity of each pixel by using the mapping relation between imaging data and PSF; and performing precise positioning on the image spot array after pixel response correction to obtain an image spot high-precision positioning result, and calibrating optical distortion of each pixel according to the high-precision positioning result. Therefore, the problems of photoelectric non-uniform coupling and limited calibration precision in calibration of the star measurement sensor are effectively solved, and high-precision and integrated calibration of optical aberration, distortion and electrical response of the star measurement sensor is realized.

The embodiment of the invention provides a data processing method and device and electronic equipment, and relates to the technical field of satellites.The method comprises the steps that star sensor data obtained by collecting spacecraft attitude information through a star sensor and gyroscope data obtained by collecting spacecraft attitude information through a gyroscope are obtained and comprise data from the k-n moment to the k moment; carrying out fusion and linear interference filtering processing on the data of the star sensor and the gyroscope at each moment by using Kalman filtering to obtain preliminary prediction data of attitude information, and calculating a first residual value of the data of the star sensor; the star sensor data, the gyroscope data and the first residual value from the k-n moment to the k moment are input into the trained LSTM network, a second residual value of the preliminary prediction data at the k moment is predicted, and the second residual value represents an error of nonlinear interference; and compensating the second residual value to the preliminary prediction data to obtain attitude information of the spacecraft at the moment k. According to the embodiment of the invention, the error of spacecraft attitude information acquisition is reduced.

A navigation method of a vehicle equipped with a star tracking device, a first inertial measurement device and a satellite positioning device, the star tracking device and the first inertial measurement device being connected to a single support. The method includes controlling movements of the support; simultaneously with these movements, calculating, in a horizontal plane, first positions of the vehicle, and second positions of the vehicle; calculating first deviations between the first positions and the second positions corresponding to each tracking heading and depicting them in a polar reference frame as a function of the corresponding heading and the values of the first deviations; carrying out a circular regression on said first deviations to determine, in this polar reference frame, a first circle; and determining a radius of the circle and a second deviation between a centre of the first circle and an origin of the polar reference frame.

The embodiment of the invention provides an interactive multi-model factor graph integrated navigation method based on tight coupling attitude constraint. In a specific embodiment, the method comprises the following steps: constructing an integrated navigation system; constructing an inertial measurement unit factor pre-integrated by the inertial navigation system; constructing a direct celestial navigation factor and a refraction celestial navigation factor which are respectively and tightly coupled with an inertial measurement unit factor based on the star sensor observation condition of the celestial navigation system; constructing a horizontal radio navigation factor and a vertical radio navigation factor based on the position information of the land-based radio navigation system; acquiring height measurement data of the barometric altimeter to construct barometric altimeter factors; dynamically adjusting the weight ratio of the height measurement data of the vertical radio navigation factor to the height measurement data of the barometric altimeter factor through an interactive multi-model algorithm; and carrying out global state estimation of the integrated navigation system on a factor graph framework formed by the factors.

A kind of star sensor star detection capability analysis method based on polarization degree image belongs to star sensor detection technical field.For solving the problem that less detection means and low utilization rate of sky light radiation information when near-earth space all-time star sensor observes star, the present application includes the star sensor of integrated focal plane micro-polaroid array is built, four gray star maps are collected by short exposure using the star sensor of integrated focal plane micro-polaroid array;Calculate the sky Stokes vector diagram;Calculate the polarization degree distribution of starry sky to obtain the polarization degree star map;Utilize the physical process of radiation energy to polarization degree conversion to construct the polarization signal-to-noise ratio calculation formula of star in polarization degree star map;The polarization signal-to-noise ratio of star in field of view is calculated;The polarization signal-to-noise ratio of star is compared with the signal-to-noise ratio threshold value of near-earth space all-time star sensor detection, and the detectable ability of star in polarization degree star map is judged.The present application improves the robustness of near-earth space all-time star sensor technology to complex environment.

Examples of the present disclosure include a method for approximating a non-carth imaging camera model for a non-earth sensor includes obtaining a physical camera model, receiving a target range value, determining a plurality of space-based coordinates of a plurality of points about a line of sight of the sensor in proximity to a distance corresponding to the received target range value, for each of the plurality of locations, determining line and sample coordinates on an image thereof via the physical camera model based on the space-based coordinates of the plurality of points, and based on the determined line and sample coordinates for each of the plurality of points, fitting an approximate camera model thereto.

This invention discloses a polarization orientation method based on the antisymmetry of the atmospheric polarization pattern. First, a UNet convolutional neural network is used to perform binary segmentation on the polarization image of the sky acquired by a polarization camera to obtain a de-obstructed polarization image of the sky. The separated sky is then divided into multiple circular rings centered at the zenith, and the corresponding positive and negative feature points within each ring are obtained. The antisymmetry of the atmospheric polarization pattern is used to fit the solar meridian, ultimately completing the calculation of the heading angle. This invention solves the problem of traditional polarization orientation methods failing due to complex weather conditions, especially large-scale obstructions, and effectively improves the robustness of polarization orientation methods under complex weather conditions.

This invention discloses a polarization-oriented light method based on Rayleigh point information, comprising: acquiring a sky polarization image and calculating the measured polarization angle of each measurement point in the sky polarization image; calculating the ideal polarization angle of each measurement point in the sky polarization image, and obtaining the polarization angle error of each measurement point based on the measured polarization angle and the ideal polarization angle; selecting Rayleigh points from all measurement points based on the polarization angle error, and performing polarization-oriented light orientation based on all Rayleigh points to obtain the heading angle of the carrier. This invention is applied to the field of polarization-oriented light navigation. By comparing the measured polarization angle with the theoretical polarization angle of each measurement point before polarization-oriented light orientation, and selecting Rayleigh points in the sky polarization image based on the polarization angle error between the measured and theoretical polarization angles, and then performing polarization-oriented light orientation only using the selected Rayleigh points, the accuracy of polarization-oriented light orientation is significantly improved.

The star sensor acquires a star point image through a detector, a data processor scans the obtained star point image using a 3*3 template; judges whether the gray value of the pixel point in the center of the template is greater than an image threshold T1 and whether the gray values of the 8 pixels around the pixel point are all less than the image threshold T1, and obtains a star point image after removing isolated points; the data processor divides the star point image after removing isolated points into blocks, divides the size of a sub-block into 32*32 pixels, and then calculates the image mean value in each sub-block; judges the mean value of each sub-block, and filters out the background and noise with high gray value; performs a pixel traversal operation on the star point image after removing isolated noise using the determined image threshold T1, and sends the pixels not less than the threshold T1 to a target extraction module. The star point image processing method under a complex background can judge and filter the star point image under a complex background, and can stably output the attitude information of the star sensor.

The invention discloses a method and a system for determining an optimal attitude of a high-dynamic star sensor, and belongs to the technical field of spaceflight measurement and control. Aiming at anisotropic distribution of centroid positioning errors caused by'trailing 'of a star point image under high dynamic condition, the method comprises the following steps: acquiring a trailing star point image and extracting an observation star vector; calculating a prior attitude matrix; analyzing the anisotropy error and trajectory orientation of the center of mass in the motion trajectory direction and the vertical direction; calculating an error component in an image plane coordinate axis direction; and constructing a weighted least square problem based on the error component, and updating a prior attitude to obtain an optimal attitude matrix. By accurately matching the weight of anisotropy error distribution, noise in a large error direction is effectively suppressed, and information in a high-confidence direction is fully utilized, so that the limitation of a traditional method is overcome, attitude estimation under a high-dynamic condition is ensured to meet the minimum variance unbiased estimation requirement, and the accuracy of attitude estimation is improved. And the precision and reliability of attitude determination are obviously improved.

The application provides a spacecraft autonomous navigation method and electronic equipment. The spacecraft autonomous navigation method comprises the following steps: determining technical indexes of an optical sensor according to navigation requirements, and determining a configuration of the optical sensor according to orbit information of the spacecraft; collecting a star map by using the optical sensor with the determined technical indexes and configuration, processing the star map, identifying a refraction star and extracting a refraction angle; and using a Kalman filtering algorithm to perform information fusion on information output by an inertial navigation system and a refraction apparent height calculated based on the refraction angle, so as to correct navigation errors and obtain corrected navigation information. The application corrects drift errors of the inertial navigation by astronomical navigation, maintains continuous navigation information by using the inertial navigation when the astronomical system is unavailable, and achieves the purpose of improving navigation accuracy.

The application discloses a pulsar signal denoising method based on EWT, and specifically comprises the following steps: S1, acquiring a pulsar cumulative pulse profile x(t), wherein t represents a time variable; S2, performing EWT decomposition on the pulsar cumulative pulse profile x(t); S3, performing FFT on M EMFs {emf m (t), m=1, 2, …, M}; S4, calculating a frequency domain feature set {EMA m , m=1, 2, …, M}; S5, determining a starting layer number K of high-frequency EMF components; S6, directly removing the Mth layer EMF component emf M (t) as noise; S7, performing denoising processing on emf K (t)~emf M‑1 (t) by using a wavelet threshold method, and denoising results are recorded as S8, performing denoising processing on the low-frequency EMF components emf1(t)~emf K‑1 (t) by using a Savitzky-Golay smoothing filtering method, and denoising results are recorded as S9, and a denoised pulsar signal is obtained. The method can effectively improve the signal-to-noise ratio of the pulsar cumulative profile and improve the quality of the pulsar cumulative profile.

The application discloses a kind of non-cooperative target centroid intelligent positioning method and system fusing multi-dimensional physical constraint.The method is directed to sparse, noisy point cloud data, and constructs a comprehensive evaluation function containing four-dimensional information of geometry, orbital dynamics, time sequence continuity and surface physical properties;Using a two-stage solution framework of surrogate model and hybrid optimization, first, a lightweight neural network surrogate model is used with a differential evolution algorithm for global coarse search, and then switching to a high-fidelity orbit model combined with an adaptive particle swarm optimization algorithm for local fine search;Finally, the optimal state estimation and its covariance matrix, evaluation decomposition and other decision support information are output.The application improves the accuracy, robustness and computational efficiency of centroid positioning, and enhances the interpretability of the results, suitable for on-orbit servicing, space debris removal and other high-risk space missions.