13 results about "Horizontal coordinate system" patented technology

A kind of compound inertial system attitude simulation test method, compound inertial system obtains launch system initial attitude angle by initial alignment mode;In dynamic loading process, the inertial data of compound inertial system is collected, and the angle signal of attitude simulation platform excitation is synchronously acquired;The attitude of compound inertial system is converted from launch system to local horizontal coordinate system by navigation solution method, while the angle signal of attitude simulation test platform is converted to the attitude angle of local horizontal coordinate system, and relevant operation is carried out, to obtain the dynamic performance parameter of compound inertial system.

The invention discloses a deepwater collaborative operation platform dynamic relative positioning system and method, and relates to the field of deep sea engineering, and the system comprises a first operation platform which is symmetrically provided with a first beacon and a second beacon along a central axis; a third beacon and a fourth beacon are symmetrically arranged on the second working platform along the central axis; the dynamic positioning network is formed by continuously carrying out bidirectional distance measurement among beacons; the edge calculation unit is arranged on the second operation platform and comprises a data acquisition interface and a data processing mechanism; the data acquisition interface is used for receiving original distance observation data and attitude data and depth data of each beacon; and the data processing mechanism unifies all beacon coordinates to a horizontal coordinate system by fusing the distance measurement data, the depth data and the attitude data, and solves the three-dimensional relative position and the relative yaw angle between the two platforms. According to the system and method, multi-source data fusion and edge calculation are utilized, the problem of deepwater transmission delay can be solved, and high-precision real-time feedback of dynamic relative poses between collaborative operation platforms can be achieved.

The invention provides a method and a device for determining the area of a side slope slippage region, and electronic equipment, relates to the technical field of side slope slippage detection, and is used for automatically detecting the side slope slippage region and accurately outputting the area of the side slope slippage region. The method comprises the following steps: determining Beidou coordinates of a target corresponding to a Beidou detection station; determining a point cloud coordinate of each target from the detection point cloud; mapping the detection point cloud into a Beidou coordinate system to obtain an absolute point cloud; mapping the reference point cloud and the absolute point cloud into a slope horizontal coordinate system to obtain a reference horizontal point cloud and an absolute horizontal point cloud; a plane formed by a horizontal axis and a longitudinal axis of the slope surface horizontal coordinate system is parallel to the main plane of the slope; constructing slope surface horizontal grids, determining the elevation difference of each slope surface horizontal grid based on the reference horizontal point cloud and the absolute horizontal point cloud, and identifying at least one continuous slip area based on the elevation difference of the slope surface horizontal grids; and obtaining the area of the slope slippage region based on the grid area corresponding to the continuous slippage region.

The invention provides an inertial navigation error correction method and device based on photoelectric equipment image target detection, and belongs to the technical field of photoelectricity, and the method comprises the following steps: obtaining a photoelectric image of a to-be-detected target based on a pre-correction attitude angle of photoelectric equipment; performing target detection on the photoelectric image to obtain a target deviation angle; obtaining a horizontal coordinate system deviation angle based on the target deviation angle and the image rotation angle; obtaining an inertial navigation correction angle of the photoelectric equipment based on the horizontal coordinate system deviation angle and the tracking turntable direction; and performing inertial navigation error correction on the photoelectric equipment based on the inertial navigation correction angle. According to the inertial navigation error correction method and device based on photoelectric equipment image target detection, the inertial navigation error can be effectively reduced, and the pointing precision of photoelectric equipment is improved.

This invention discloses a blind zone detection method for handheld point cloud scanning based on the interaction between the acquisition area and the boundary, relating to the fields of 3D scanning and point cloud data processing technology. The method first acquires the device pose and local point cloud, preprocesses it, and then transfers it to a global horizontal coordinate system. A boundary feature extraction engine is used to identify room boundary lines and project them to form a 2D boundary contour map. Simultaneously, an effective acquisition loop is dynamically constructed and projected based on the effective measurement range parameters of the laser scanner and the current ambient lighting conditions. Boolean operations are performed on the effective acquisition loop and the boundary contour map to identify uncovered boundary segments as potential blind zones. The occlusion state is determined using the temporal information of continuous frame point clouds and a ray casting algorithm to identify the effective blind zone. This invention reduces the 3D integrity determination to 2D planar geometric intersection, eliminating the need for prior models and enabling real-time identification of dynamic occlusion and acquisition blind zones. This results in high computational efficiency and significantly improves the success rate and coverage integrity of handheld scanning operations.

The invention provides a testing machine non-horizontal state high-speed camera exterior orientation element calibration method. The method comprises the following steps: 1, obtaining a space three-dimensional coordinate of a to-be-measured point; 2, constructing a reference plane by using the fuselage left side front-back pitching control points and the fuselage right side front-back pitching control points; 3, solving an intersection line P1P2 of the reference plane and the plane XOY of the measurement coordinate system; 4, converting the space three-dimensional coordinate of the point to be measured into a first temporary coordinate system; 5, converting the space three-dimensional coordinate of the point to be measured from the first temporary coordinate system to a second temporary coordinate system; 6, converting the space three-dimensional coordinate of the point to be measured under the second temporary coordinate system to be under the initial coordinate system of the testing machine; 7, converting the space three-dimensional coordinate of the point to be measured under the initial coordinate system of the testing machine to a third temporary coordinate system; and 8, performing coordinate conversion on the spatial three-dimensional coordinates of the to-be-measured point in the third temporary coordinate system to obtain the spatial three-dimensional coordinates of the to-be-measured point in the final airframe horizontal coordinate system.

The application discloses a deep water cooperative operation platform dynamic relative positioning system and method, and relates to the field of deep sea engineering.The system comprises: a first operation platform, which is provided with a first beacon and a second beacon symmetrically along a central axis; a second operation platform, which is provided with a third beacon and a fourth beacon symmetrically along a central axis; a dynamic positioning network, which is formed by continuously performing bidirectional ranging between the beacons; an edge computing unit arranged on the second operation platform, which comprises a data acquisition interface for receiving original distance observation data, attitude data and depth data of the beacons and a data processing mechanism; and the data processing mechanism unifies all beacon coordinates to a horizontal coordinate system by fusing ranging data, depth data and attitude data, and calculates a three-dimensional relative position and a relative yaw angle between the two platforms.The system and method utilize multi-source data fusion and edge computing, can overcome the problem of deep water transmission delay, and can realize high-precision real-time feedback of the dynamic relative position and pose between the cooperative operation platforms.

The invention discloses a sun tracking method based on an underwater Snell window external polarized light field, which belongs to the technical field of underwater polarized light navigation, and comprises the following steps: calculating an underwater observation vector elevation angle under a horizontal attitude according to attitude angle information; the method comprises the following steps: acquiring an underwater Snell window external polarized light image under a horizontal coordinate system, performing Stokes vector calculation on the underwater Snell window external polarized light image, and constructing an incident light coordinate system after solving a polarization angle image outside a Snell window; deducing a polarization E-vector corresponding to each pixel position under a horizontal coordinate system by using a relation between the polarization E-vector and an incident light coordinate system; according to the polarization E-vector, combining geometric constraints of the polarization E-vector and the underwater refracted sunlight vector to derive the underwater refracted sunlight vector; and according to the underwater refracted sunlight vector, calculating an atmospheric incident sunlight vector, and calculating a zenith angle and an azimuth angle of the atmospheric incident sunlight vector. According to the method, the accuracy of resolving the solar azimuth of the polarized light field outside the Fresnel window in the complex underwater environment is improved.

This invention belongs to the field of positioning technology and discloses a method, system, computer equipment, and storage medium for locating agricultural machinery vehicles in greenhouses. The method includes: acquiring several consecutive photos of working scenes and IMU data of each photo; obtaining camera relative pose data and IMU relative pose data for each photo; constructing a 3D camera position map and extracting the camera relative coordinates of each photo from the 3D camera position map; obtaining the gravity, camera velocity, and camera scale of each photo based on the camera relative pose data and IMU relative pose data; transforming the camera relative coordinates of each photo in the 3D camera position map to a horizontal coordinate system; and finally fusing GNSS satellite data and the camera relative coordinates of each photo in the horizontal coordinate system to obtain the positioning coordinates of the agricultural machinery vehicles. This method can accurately determine the positioning coordinates of agricultural machinery vehicles, ensuring accurate positioning, and is cost-effective.

A self-calibration method for frame non-orthogonality error and accelerometer error in a dual-axis frame inertial system is proposed. Under static base conditions, the platform is locked at 10 frame angular positions, accelerometer measurements are collected, and the specific force measurement of the inertial system in the platform coordinate system at each locked position is calculated. The attitude matrix of the inertial system from the platform coordinate system to the local horizontal coordinate system at each locked position is also calculated, yielding the acceleration of the inertial system in the local horizontal coordinate system at each locked position, which is used as the error observation. The residuals of the error coefficients are calculated using a total least squares algorithm, and the estimated values ​​of the measured parameters are corrected. Iterative calculations are performed until the iterative convergence criterion is met, obtaining the self-calibration results for each error coefficient. Through the self-calibration and compensation of the error coefficients, the accuracy of attitude measurement of the dual-axis frame inertial system carrier or base affected by the non-orthogonality error of the axis system can be improved.

The application discloses a method for obtaining a gear shifting compensation amount of a gear shifting finger and a gear shifting compensation method, and relates to the field of vehicles. The method for obtaining the gear shifting compensation amount of the gear shifting finger comprises the following steps: establishing a calibration reference line of the gear shifting finger in a horizontal coordinate system of a space coordinate measuring device, and calibrating an end point of a cantilever to obtain an initial calibration point; performing multiple gear shifting tests on the gear shifting finger, and calibrating the end point of the cantilever based on the calibration reference line in the horizontal coordinate system of the space coordinate measuring device once every first preset number of tests to obtain multiple test calibration points; and calculating multiple gear shifting compensation amounts according to the coordinates of the multiple test calibration points and the initial calibration point in the horizontal coordinate system of the space coordinate measuring device. The method for obtaining the gear shifting compensation amount of the gear shifting finger can obtain a gear shifting compensation amount with higher precision.

The application discloses a kind of identification and positioning method and device of aerial visual angle blind area target, belong to computer vision and remote sensing field.The method includes: obtaining the multisensor data of laser radar, camera, IMU and GNSS;Laser radar point cloud is converted to local horizontal coordinate system, and the region with elevation mutation feature is identified as blind area detection candidate area;The specific type and pixel range of aerial visual angle blind area target are identified;The point cloud data corresponding to target mask is extracted, combined with the pose and coordinate information of unmanned aerial vehicle, the three-dimensional coordinates of target under geocentric coordinate system are solved, and the center position is calculated to realize accurate positioning.The technical route of the application is coarse positioning by laser radar point cloud detection candidate area, accurate identification by image semantic segmentation, coordinate mapping solution, solves the problem that existing technology cannot be efficiently identified and positioned, and the accuracy is low, realizes the type identification and high-precision positioning of aerial visual angle blind area target.

The invention relates to a data fusion method for a detection radar, a radio reconnaissance radar and an acoustic radar to detect a target object, and belongs to the technical field of computer information. The method comprises the following steps: converting position information of three types of detection equipment and a command center and data information of a tracked target acquired by the three types of detection equipment into data information relative to the command center; the method comprises the following steps: respectively calculating distances in a radio detection conversion data set and an acoustic equipment conversion data set with a distance in a radar equipment conversion data set in a horizontal coordinate system, and reserving a minimum value in the distances; obtaining a fusion data set at the same moment; and obtaining a reasonable unmanned aerial vehicle fusion information sequence by adopting a Kalman filtering algorithm.