1862results about "Angle measurement" patented technology

The invention relates to a steel truss girder digital pre-assembly method and system based on three-dimensional laser scanning, and belongs to the technical field of constructional engineering. The method comprises the following steps: calculating a three-dimensional coordinate and a scanning angle of a scanning observation station based on a steel truss girder design model and field environment point cloud data to obtain observation station layout position parameters; controlling a three-dimensional laser scanner to scan the steel truss girder section by section according to the arrangement position parameters of the observation station, and acquiring original point cloud data of each section of the steel truss girder; performing spatial alignment and noise reduction processing on the original point cloud data to obtain standardized point cloud data; based on the standardized point cloud data, feature parameters of all the segments are segmented and extracted, digital splicing is carried out, and a steel truss girder three-dimensional point cloud model is generated; based on the steel truss girder design model and the steel truss girder three-dimensional point cloud model, the displacement deviation value and the angle deviation value between the segments are calculated, and an assembly error result is obtained; and generating a construction correction parameter set based on the assembly error result. The assembling precision of the steel truss girder can be improved.

The invention discloses an adaptive genetic algorithm multi-satellite cooperative task dynamic scheduling planning method based on fusion and merging observation, and the method comprises the steps: firstly, decomposing regional tasks through equal-ratio sampling, and constructing discrete observation points; secondly, tasks are converted into a weighted meta-task set, and selectable satellites and time windows are calculated in combination with satellite resources, tasks and attitude constraints; further, detecting and combining the meta-tasks meeting conditions, and constructing a combined observation model taking the maximum observation benefit as a target; and finally, solving is optimized by adopting a self-adaptive genetic algorithm, constraint is ensured to be met, and an executable multi-satellite collaborative observation scheduling scheme is generated. In the regional task planning and scheduling process, a regional discrete adaptive sampling method is adopted to quickly decompose regional tasks into point tasks, and the completion rate of regional observation tasks is increased; in addition, an effective meta-task merging observation method is designed, and the multi-satellite dynamic task planning benefit is effectively improved.

The invention discloses a hydraulic gate operation posture monitoring and early warning device and method. The device comprises a force measuring sensor, an acceleration sensor and a rocking-turn sensor which are arranged on the surface of a hydraulic gate metal structure, and meanwhile a controller module, a power module and a communication module are arranged on the top of a gate leaf. Through sensors arranged at specific positions, monitoring data such as gate opening and closing force F, gate attitude (a ', omega', alpha, beta and gamma) information and operation excitation acceleration (vibration frequency f and amplitude h) are obtained, then the monitoring data of the sensors are processed in a centralized mode through a monitoring control module, and an information frequency spectrum of the gate operation attitude is extracted; and obtaining the operation attitude of the gate according to a maximum membership principle fuzzy comprehensive evaluation method, and verifying and comparing the operation attitude with the limit value and the inherent frequency to identify the operation safety attitude of the gate.

The invention relates to the technical field of machine vision, and provides a visual inertial mileage pose positioning method based on cross attention and dynamic weight, which performs positioning prediction of visual inertial mileage pose information by means of a visual inertial mileage pose prediction model. In the visual inertial mileage pose prediction model, a cross-modal feature association between a visual optical flow feature and an inertial variable feature is established by using a cross attention mechanism, so that the attention of a space region highly related to inertial variable information in the visual optical flow feature is enhanced; meanwhile, by means of a dynamic weight fusion mechanism, dynamic balance between different modal features is achieved through a learnable weight distribution strategy, the problem of falling into a local optimal solution is helped to be avoided, and the accuracy of visual inertial mileage pose information positioning prediction and the stability and reliability for different scenes are remarkably improved.

The invention discloses a method for measuring an attitude angle of a free throwing object in a wind tunnel test through a binocular system, and belongs to the field of aerodynamics tests based on a photogrammetry technology. Comprising the steps that a binocular system is arranged in a wind tunnel, and internal and external parameters of the binocular system are calibrated through a cross scale; reconstructing the surface mark points of the calibration plate by photogrammetry outside the wind tunnel and establishing a local coordinate system; placing a calibration plate in the wind tunnel, wherein each vector of a local coordinate system is parallel or vertical to an incoming vector, and calibrating a wind tunnel coordinate system by adopting a resection method; carrying out photogrammetry and initial pose installation on mark points on the surface of a thrown object; acquiring each state image of the thrown object and reconstructing the three-dimensional coordinates of the surface mark points; taking the attitude angle of the thrown object as 0 degree as a reference state, and comparing the rigid body transformation relationship between the blowing state point cloud and the reference state point cloud to obtain attitude angle data. Alignment of a wind tunnel coordinate system and a binocular system coordinate system can be achieved, limitation of the appearance of the thrown object is avoided, and attitude angle data of the thrown object are calculated in a non-contact and high-precision mode.

The invention relates to the technical field of data processing, and discloses a VICTS antenna attitude estimation and correction method and system based on satellite pointing feedback, and the method comprises the steps: constructing a tight coupling depth fusion system with extended Kalman filtering as a frame, introducing satellite communication antenna pointing information as a new observation source on the basis of traditional IMU / GNSS fusion, and carrying out the satellite communication antenna attitude estimation and correction. By deducing the Jacobian matrix of the carrier attitude, effective fusion of the observed quantity is realized, so that the attitude estimation precision and robustness of the carrier are reversely corrected and remarkably improved, the three-axis attitude error is estimated and corrected more comprehensively and steadily, and the problem of lack of roll angle observation is fundamentally solved. Observation information of different dimensions is unified into the same state estimation framework through accurate mathematical modeling, and the precision, autonomy and robustness in a complex environment of the system are greatly improved.

The invention relates to pipeline circumferential weld detection, and discloses a pipeline circumferential weld defect detection method and system based on deep learning, multiple sensors are arranged on the surface layer of a pipeline to collect multi-modal signals, an inertial measurement device is combined to carry out pose correction, and a multi-modal time sequence data matrix is constructed; performing preprocessing and segmentation, calculating to obtain a dynamic reference band, and outputting upper and lower bounds; performing broken line fitting on each segment to extract a phase change factor triple, and comparing with a reference band to screen event candidate segments; constructing a multi-segment time domain coupling relation graph based on the candidate segments, and generating a dominant response mode candidate set; inputting a multi-branch time sequence coding network to extract a three-mode feature and generate a time sequence fusion feature; and performing similarity matching with a defect prototype library to obtain a defect category probability sequence, performing single-mode ablation and time sequence playback verification to obtain a high-confidence index, mapping the high-confidence index to a spatial position, and outputting a defect category and severity in combination with a feature index. According to the method, high-precision defect detection and reliable classification under the trenchless condition can be realized.

The invention discloses an alignment method for a vehicle-mounted radar and related equipment, and relates to the technical field of navigation calibration, and the method comprises the following steps: obtaining inertial measurement unit data and horizontal tilt angle sensor data of the vehicle-mounted radar; generating an initial attitude matrix based on the inertial measurement unit data; determining a horizontal attitude data difference based on the horizontal tilt angle sensor data and the initial attitude matrix; and obtaining an alignment result of the vehicle-mounted radar based on the horizontal attitude data difference and a Kalman filtering algorithm. The initial attitude matrix is generated by fusing the inertial measurement unit data and the horizontal tilt angle sensor data, fine alignment is performed by combining the horizontal attitude data difference and the Kalman filtering algorithm, the azimuth angle alignment precision of the vehicle-mounted radar in a dynamic environment is improved, dependence on external satellite signals is not needed, and the accuracy of the azimuth angle alignment is improved. High-precision autonomous alignment can be realized under complex working conditions such as shaking and vibration, meanwhile, the hardware cost and the system complexity are reduced, and the method has wide applicability.

The invention relates to the technical field of engineering monitoring, in particular to a multi-parameter fusion deformation monitoring method, system and equipment and a medium. The method is applied to a multi-parameter fusion deformation monitoring system, the system comprises a radar module, a machine vision module and an inclination angle measurement module, and the method comprises the following steps: executing a target spot positioning step once every preset duration, and calculating a positioning difference value between current target spot positioning information and initial target spot positioning information obtained by executing the target spot positioning step every time, judging whether the positioning difference value exceeds a preset difference value threshold value or not, wherein the initial target spot positioning information is target spot positioning information obtained by executing the target spot positioning step for the first time; if the positioning difference value exceeds a preset difference threshold value, it is judged that deformation exists in the monitoring site, and a deformation warning signal is generated and sent to terminal equipment of a manager. According to the invention, the deformation condition of on-site building facilities can be found and monitored in time.

The invention discloses a vertical retaining structure displacement automatic monitoring device and a monitoring method thereof, and relates to the technical field of displacement automatic monitoring, and the device comprises a data acquisition unit which is used for configuring monitoring nodes, obtaining sensor data monitored at the top of a retaining wall, and preprocessing the sensor data to obtain effective inclination angle data; the displacement conversion unit is used for recognizing and optimizing the attitude angle by using a dynamic Kalman filtering algorithm, and calculating a displacement value of the vertical soil retaining structure by combining the vertical distance from the bottom to the top of the soil retaining wall; the monitoring and early warning unit is used for uploading the displacement value of the vertical retaining structure to a remote data platform, constructing a monitoring network, analyzing and predicting the deformation trend of the retaining wall and triggering early warning according to an analysis result; and the battery management unit is used for providing battery state monitoring and management. The displacement of the top of the retaining wall can be accurately sensed and monitored through the inclination angle data, and comprehensive and accurate monitoring is ensured by adopting an attitude solver and a dynamic Kalman filtering algorithm.

The invention relates to a course axis drift suppression method and device, a holder and a medium, and the method comprises the steps: receiving original data of a current course, the original data comprising an absolute angle outputted by a course encoder, and an acceleration and an angular velocity outputted by an IMU module; the original data are converted into a unified coordinate system through a rotation matrix, and mechanical installation deviation is compensated; performing data fusion on the compensated original data through a preset fusion algorithm; and outputting the fused absolute angle to a servo mechanism of the holder, and by adopting the method, through real-time sensor data alignment, a dynamic compensation algorithm and a fusion algorithm, a course drift suppression mechanism which is resistant to dynamic interference and low in cost is constructed, and static drift lt can be realized; the dynamic tracking error is 1t, 0.01 degree / h and 1t; and the technical index is 0.05 degree.

The invention discloses a flying bird micro-motion parameter extraction method based on laser micro-Doppler echoes, and belongs to the field of laser radar application detection and identification. The method comprises the following steps: step 1, establishing flapping wing motion models of a bird with multiple scattering points, a one-section flapping wing unmanned aerial vehicle and a two-section flapping wing unmanned aerial vehicle; 2, simulating to obtain time-frequency spectrums of the flying bird, the one-section flapping-wing unmanned aerial vehicle and the two-section flapping-wing unmanned aerial vehicle under different azimuth angles and pitch angles; and step 3, extracting identification micro-motion parameters of the bird motion model and the flapping-wing unmanned aerial vehicle motion model. According to the micro-motion parameter extraction method based on the frequency shift characteristic of the forearm of the flying bird, the length of the forearm of the flying bird, the wing flapping angle and the wing sweeping angle can be effectively estimated, and a brand new technology is developed for application of a laser micro-Doppler detection technology in target accurate detection and recognition.

The invention belongs to the technical field of space remote sensing surveying and mapping, and particularly relates to a monitoring system and method for a front and rear view visual axis included angle and absolute direction of a surveying and mapping camera. The method comprises the following steps: S1, through side sway of a satellite platform, taking a time for sky imaging calibration as a reference time; s2, calculating a rotation matrix from a front and rear view ground camera measurement coordinate system to a star camera coordinate system at a reference moment; s3, calculating respective thermal deformation matrixes of the star camera coordinate system, the front-view camera measurement coordinate system and the rear-view camera measurement coordinate system; s4, obtaining a real-time rotation matrix from the measurement coordinate system of the front-view camera to the coordinate system of the star camera and a real-time rotation matrix from the measurement coordinate system of the rear-view camera to the coordinate system of the star camera at the measurement moment; and S5, carrying out arc cosine calculation on the two absolute pointing vectors to obtain a visual axis included angle between the front-view camera and the rear-view camera at the measurement moment. According to the invention, while the geometric accuracy of the surveying and mapping camera is ensured, the real-time performance of measurement and the comprehensiveness of subsystem monitoring are realized at the same time.

The present invention relates to the field of unmanned aerial vehicles, and provides a method, system and medium for detecting the attitude of unmanned aerial vehicles based on solar images, including: obtaining a solar image by photographing with a camera carried by an unmanned aerial vehicle; determining the pixel coordinates of the solar center point in the solar image; calculating the actual solar altitude angle and the actual solar azimuth angle in the camera coordinate system according to the pixel coordinates of the solar center point; establishing a relative position relationship model among the earth, the sun and the unmanned aerial vehicle, and calculating the theoretical solar altitude angle and the theoretical solar azimuth angle based on the time information and position information of the unmanned aerial vehicle photographing the solar image; calculating the deviation between the actual solar altitude angle and the theoretical solar altitude angle, and between the actual solar azimuth angle and the theoretical solar azimuth angle, and obtaining the attitude of the unmanned aerial vehicle. The present invention uses solar information for attitude detection, and is not affected by complex electromagnetic environments; it can be used for initial attitude calibration of unmanned aerial vehicles, especially calibration of heading.

The invention discloses a laser radar attitude measurement positioning method and device for an aviation electromagnetic detection suspension system, and belongs to the technical field of aviation electromagnetic detection, attitude measurement and coordinate positioning. According to the invention, real-time space positioning information and attitude information of the aviation soft suspension flight pod subsystem are accurately obtained by adopting a non-contact laser remote sensing measurement mode, and attitude and positioning devices do not need to be fixedly installed on the suspension flight pod subsystem. Electromagnetic interference or dynamic stability of the attitude and positioning device and related auxiliary electronic equipment on the soft suspension flight pod subsystem is avoided, the accuracy of electromagnetic signals and data reliability in the detection process are ensured, and therefore the precision of aviation electromagnetic detection is improved.

The invention relates to an end-to-end spacecraft pose measurement method based on deep learning, and belongs to the field of spacecraft pose measurement, the method uses a sliding window transformer as a feature extraction backbone network, introduces a multi-layer large kernel convolution module, and is used for enhancing a global receptive field and feature expression ability. A rotating head detection network and a position head detection network are arranged in parallel after the backbone network, a rotating head is used for predicting a 3D key point and a projection weight thereof, a position head is used for predicting a 2D key point, a 2D-3D corresponding relation is sent to a differentiatable EPro-PnP module for pose solving, it is ensured that a gradient can be completely transmitted back to a feature extraction layer, and a feature extraction layer is obtained; therefore, a globally optimal solution is obtained, and integrated network training of feature learning and geometric pose solution is realized. According to the method, a complex loss function is constructed, through multi-angle supervision and complementary optimization, it is ensured that the model can accurately predict the 6D pose of the spacecraft, and robustness and generalization performance in a complex environment are enhanced.

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 provides an attitude monitoring method and system in navigation of an aircraft, and the method comprises the steps: determining a process noise covariance matrix through a high-frequency energy component of an angular velocity signal measured by a current gyroscope in each filtering period; predicting a prior state vector and a prior covariance matrix at the current moment according to the state vector at the previous moment, the angular velocity measured by the current gyroscope and the process noise covariance matrix; generating an asymmetric Sigma point set and determining a measurement noise covariance matrix; the asymmetric Sigma point set is substituted into a measurement model, and a predicted measurement value and a predicted measurement covariance are obtained through unscented transformation; calculating Kalman gain based on the predicted measurement covariance and the measurement noise covariance matrix, and performing weighted gating test on innovation formed by a real measurement value and a predicted measurement value; and updating a state vector and a covariance matrix on the basis of the adjusted Kalman gain and information so as to obtain attitude information of the aircraft at the current moment.

The invention discloses an offshore small target radar detection method and system, and relates to the technical field of radio detection. The method comprises the following steps: acquiring radar echo data, a visible light image, an infrared image, an AIS signal and navigation attitude data in real time; performing sea clutter suppression and pre-filtering on the radar echo data, and correcting target plots in combination with a historical radar plot set to obtain a radar single-source target track set; performing target detection on the visible light image and the infrared image to obtain an optical target detection set and an infrared target detection set; the radar single-source target track set, the optical target detection set, the infrared target detection set, the AIS signals and the navigation attitude data are associated and fused, and finally deception feature recognition and consistency verification are performed to obtain an updated fused target track set; according to the method, man-made confrontation and cheating behaviors on the sea can be accurately identified, and reliable support is provided for safety monitoring on the sea, maritime affair supervision and emergency response.

The invention belongs to the field of vehicle calibration, and particularly discloses an all-round view online calibration method and device for a truck and the truck, and the method comprises the steps: calculating the vertical offset, the vertical pitch angle, the horizontal offset angle and the horizontal offset of each camera according to vehicle information; the angle change of the vehicle in the horizontal direction is calculated; constructing a vertical angle correction matrix, a horizontal angle correction matrix, a vertical direction offset correction matrix and a horizontal direction offset correction matrix through the parameters; the vertical angle correction matrix, the horizontal angle correction matrix and the current rotation matrix are multiplied to obtain a correction rotation matrix, the vertical direction offset correction matrix, the horizontal direction offset correction matrix and the current translation matrix are multiplied to obtain a correction translation matrix, and the correction rotation matrix and the correction translation matrix form new look-around external calibration parameters. When the state of the vehicle is changed, the calibration parameters are automatically recalculated according to the vehicle information, and the looking-around precision of the vehicle under different conditions is improved.

The invention provides an open pit coal mine safety detection and production evaluation method based on unmanned aerial vehicle surveying and mapping. The method comprises the steps of obtaining surveying and mapping data of a target mine field through unmanned aerial vehicle oblique photography surveying and mapping; obtaining geographic information data including a digital orthoimage, a digital elevation model, an oblique photography model and digital vector data based on the surveying and mapping data; constructing a three-dimensional digital twinborn scene of the target mine field based on the geographic information data; performing profile detection on the three-dimensional digital twinborn scene, constructing a vertical profile, and performing safety detection on the slope angle, the step height and the width based on the vertical profile; and performing filling or excavation measurement on the coal mining area, the coal piling area or the soil piling area of the target mining area, and calculating the volume to obtain a production evaluation result. The problems that in the prior art, a geographic surveying and mapping method is low in efficiency and disordered in data, and a safety detection and production evaluation method depends on detection equipment, so that safety detection and production evaluation of open pit coal mining are poor in accuracy and low in efficiency are solved.

The invention relates to the technical field of automatic control, in particular to a detection equipment attitude real-time correction system which comprises an attitude trajectory extraction module, a trajectory stability evaluation module, an interference area recognition module, a light spot trajectory reconstruction module and an attitude correction control module. According to the invention, through comprehensive extraction of the direction change trend, the angle difference and the trajectory overlapping condition in the light spot image sequence, the trajectory trend of the attitude change between continuous frames is established, so that the identification of the attitude offset evolution process is more detailed, the attitude change stability analysis is realized in the time sequence dimension, and the accuracy of the attitude change is improved. Interference area identification is carried out by means of luminance continuity and spatial distribution consistency of light-emitting pixels, real light spots and lagging residual signals can be effectively distinguished, a light spot track path is reconstructed on the basis of interference removal, and real-time calculation of a track dynamic offset direction and an angle change amplitude is combined with track correction rule setting, so that the accuracy of track correction is improved. And the specific correction action matching of the deviation state is realized.

The embodiment of the invention provides a temperature compensation method of a tilt angle sensor, the tilt angle sensor comprises an accelerometer, and the temperature compensation method comprises the following steps: obtaining an initial output value of a target object through the accelerometer; acquiring a current temperature and a temperature trend of the target object; acquiring a corresponding temperature compensation parameter based on the current temperature, the temperature trend and a pre-trained temperature compensation model; and determining an inclination angle value of the target object according to the initial output value and the corresponding temperature compensation parameter. According to the technical scheme, the current temperature and the temperature trend can be combined for temperature compensation, the measurement error of the tilt angle sensor in the actual temperature change environment can be reduced, the influence of the hysteresis effect is reduced, and the tilt angle output precision and stability are improved.

The embodiment of the invention relates to the technical field of photovoltaic adjustment, and particularly discloses a method and a system for adjusting a vector angle of an offshore photovoltaic supporting device. According to the embodiment of the invention, real-time environment perception is carried out on the offshore photovoltaic area by determining the offshore photovoltaic area; based on the environment perception data, carrying out support stability analysis, and determining a stable angle range; based on the environmental perception data, photovoltaic optimization analysis is carried out, and a target vector angle is determined; and according to the target vector angle, vector angle adjustment is carried out on the plurality of photovoltaic support devices, and dynamic optimization adjustment is carried out in a stable angle range. Real-time environment perception can be performed on an offshore photovoltaic area, support stability analysis is performed based on environment perception data, a stable angle range is determined, a target vector angle is determined in the stable angle range, and dynamic optimization adjustment is performed, so that the safety of photovoltaic support is improved under the condition of ensuring that photovoltaic power generation meets the requirements; and the risk of damage to the photovoltaic module is effectively avoided.

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.

The invention discloses a device and method for monitoring settlement of an earth rock cofferdam, and relates to the technical field of concrete curing, the device comprises a monitoring sensor unit 1, the monitoring sensor unit 1 comprises a settlement sensor for measuring tiny settlement change, an inclination sensor for monitoring whether the cofferdam is inclined in the settlement process, and a data collector, the data collector is connected with the detection sensor unit, the data collector is used for collecting data measured by the settlement sensor and the inclination sensor, and the data collector is further provided with a wireless transmission module used for wirelessly transmitting the collected data to a remote monitoring center; according to the device and method for monitoring settlement of the earth rock cofferdam, monitoring data can be displayed and stored in real time, a report is generated through data analysis and a visual tool, and engineering management personnel can conduct risk assessment and construction progress management conveniently. The decision-making efficiency is improved, and comprehensive control over the safety of the cofferdam is enhanced.

The invention relates to the technical field of bionic navigation orientation and positioning, in particular to a carrier course angle measuring method based on polarized light imaging in a non-Rayleigh atmosphere. Comprising the steps of real-time sky polarized light imaging, atmospheric polarization mode resolving based on Mueller matrix imaging, non-Rayleigh polarization information interference removal, polarization orientation resolving based on Rayleigh scattering, space projection conversion and sun position information resolving. Alignment information of the sun in a carrier coordinate system is obtained by utilizing a Rayleigh scattering model and actual sky polarization imaging, and then a carrier course angle is obtained according to the orientation of the sun in a local geographic coordinate system, so that an orientation function is realized; meanwhile, the error influence caused by image registration and time-sharing rotation measurement of the multi-view-field polarization detector and the interference of environmental factors on a single point are avoided, the method can adapt to sunny and cloudy weather, is also applicable to cloudy and other non-Rayleigh weather, and is wide in application range.

The invention discloses a pose decoupling kinematics calibration method, device and equipment and a storage medium. The method comprises the following steps: constructing a pose decoupling motion model based on an equivalent rotation vector and a rigid body motion transformation rule; a pose error is introduced, pose space decomposition is carried out through the pose decoupling motion model, and a pose error expression and a position equivalent expression are obtained; analyzing the coupling influence of the attitude change on the position according to the attitude error expression and the position equivalent expression to obtain a pose coupling increment; constructing a target decoupling calibration model according to the pose coupling increment and the initial decoupling calibration model; and adopting a least square method to carry out geometric error solution of different degrees of freedom on the target decoupling calibration model according to the preset axis pose error to obtain a calibration error. The technical problem that the calibration and compensation effects are poor due to the fact that the influence of the posture in a multi-degree-of-freedom motion system on the position is not considered in the prior art and the error difference between different degrees of freedom is difficult to eliminate can be solved.

The invention relates to a heading machine pose measurement and control method and system based on visual direction finding and communication distance measurement. The system comprises a base station end measuring system in a roadway, a mobile end measuring system on a heading machine body and a motion control module. The method comprises the following steps: S1, establishing a base station end coordinate system; s2, establishing a mobile terminal coordinate system; s3, the base station side identifies and measures the vector information of the characteristic light source of the mobile terminal through a visual sensor; s4, the base station end and the mobile end measure the distance between the base station end and the mobile end through communication ranging equipment; s5, calculating the three-dimensional position of the mobile terminal in the coordinate system of the base station terminal based on the vector information and the distance information; s6, according to the three-dimensional position and the inertial measurement data of the mobile terminal, carrying out combined navigation calculation based on an EKF algorithm; and S7, performing pose control based on a combined navigation calculation result. According to the invention, a means of combining visual direction finding, communication distance measurement and inertial measurement is adopted, so that the position measurement precision is improved.