175 results about "Point target" patented technology

The invention provides a three-dimensional tracking method applied to a single-photon laser radar to detect a far-field dynamic unmanned aerial vehicle point target, and belongs to the technical field of laser radar detection and target tracking. The problems that in the prior art, under the long-distance condition, the target imaging size is smaller than one pixel, and a detection and tracking algorithm based on shape, texture or edge features fails are solved. The method comprises the following steps: constructing a six-dimensional state vector containing a three-dimensional position and a three-dimensional speed of a target; predicting a state vector according to a state transfer function containing air resistance and turning acceleration; and an extended Kalman filtering framework is utilized to update the predicted state and obtain state estimation of the target, and the extended Kalman filtering framework comprises a self-adaptive process noise adjustment mechanism based on innovation feedback and is used for adjusting a process noise covariance matrix on line. The method is mainly used in the field of detection and multi-dimensional tracking of airspace moving targets.

The invention relates to the technical field of forest fire prevention, in particular to an infrared image forest fire point early recognition method based on space-time analysis, which comprises four steps of infrared image sequence continuous acquisition, moving target detection, moving target feature analysis and fire point judgment and result generation. Acquiring an infrared image sequence of the forest area by using an infrared sensor carried by an unmanned aerial vehicle or a satellite; differential processing is carried out through a frame difference method, and a moving target is extracted in combination with morphological operation; calculating the distinction degree of the moving target and the background based on the gray features, and screening possible fire point targets; the fire point is regarded as a singular attractor in a dynamic system, a space-time state space is constructed, dynamic characteristics of the space-time state space are analyzed for discrimination, a dynamic system theory and a multi-time-scale analysis framework are innovatively introduced, the early fire point can be accurately recognized, the development trend of the early fire point can be predicted, the recognition accuracy is remarkably improved, and the method is suitable for popularization and application. And a scientific basis is provided for timely intervention.

The invention relates to the technical field of deep foundation pit monitoring, and discloses a deep foundation pit micro-deformation InSAR remote sensing method and system and a storage medium. The method comprises the following steps: synchronously acquiring data through a ground radar and an InSAR satellite, and obtaining a point target set and an original scattering characteristic sequence; obtaining a net deformation phase sequence without influence through registration residual correction, phase deduction and weighted fusion processing, and carrying out phase consistency quality control and unwrapping processing to obtain an accumulated deformation quantity sequence; constructing a deformation mechanism correlation characteristic matrix based on correlation analysis of the cumulative deformation quantity sequence and radar reflection intensity amplitude attenuation characteristics; and fusing the deformation mechanism correlation feature matrix and the real-time differential interference image group, extracting deformation rate and phase gradient change, and further generating a deep foundation pit local micro-deformation risk early warning index set. According to the invention, the tiny deformation of the surrounding area of the foundation pit can be effectively detected, potential risks are warned in advance, and the safety and monitoring efficiency in the construction process are improved.

The invention provides a construction method for multi-point hoisting in-place of a prefabricated part, and belongs to the technical field of building construction.The construction method includes the steps that a plurality of hoisting point positions are marked on the surface of the prefabricated part, a tension sensor and a hydraulic adjusting device are installed, and a laser range finder is used for establishing a part posture parameter model for calibration before hoisting; starting a synchronous hoisting program, calculating a target tension value of each hoisting point according to the attitude model, realizing stable hoisting and horizontal migration through a hydraulic adjusting module, starting an accurate positioning system for fine adjustment when approaching a target position, and executing in-place operation of reducing the tension value by stages; a tension balance optimization equation set including a force balance equation, a moment balance equation and a dynamic adjustment equation is adopted to optimize the control process, and the technical problems of component deformation and safety risks caused by uneven stress of multiple lifting points in the prefabricated component lifting process are solved.

The invention provides an air motion weak point target detection method and system based on an infrared sequence image. The method comprises the following steps: obtaining an infrared sequence image with at least one moving target; the infrared sequence image comprises frame radiation intensity diagrams with continuous time, and the frame radiation intensity diagrams are positive integers greater than 1; processing the frame radiation intensity graph to obtain a frame difference mean value graph; calculating to obtain an optimal segmentation threshold value through a maximum between-class variance method by utilizing the difference mean value diagram; taking the optimal segmentation threshold as a threshold, and performing binarization processing on each differential mean image to obtain a frame candidate point binary image; in the candidate point binary image, a pixel point with a pixel value of 1 is a target position candidate point; adding all the candidate point binary images to obtain a candidate point aggregation image with all the target position candidate points; and obtaining a linear motion track of each moving target based on the target position candidate points in the candidate point aggregation graph.

The invention provides a bistatic synthetic aperture radar track planning method and system based on structure driving, and relates to the technical field of radar track planning, and the method comprises the steps: building a BiSAR echo model based on a target scattering model; analyzing the imaging characteristics of the target under different configurations, and revealing the constraint relationship between the target structure representation and the configuration; constructing a structure-driven multi-stage trajectory planning model based on the constraint relationship between the target structure representation and the configuration; the trajectory optimization is modeled as a multi-objective optimization problem; through a non-dominated sorting genetic algorithm based on target scattering characteristic driving, a multi-target optimization problem is solved so as to plan a platform track in each stage. According to the method, the limitation of a point target model in an existing trajectory planning method can be broken through, all main lobe observation configurations capable of presenting target structure information are optimized, the retention degree of the target structure information in a BiSAR imaging result is effectively improved, and the interpretability of the image is remarkably enhanced.

The invention discloses a cross-sensor long-time-sequence InSAR deformation monitoring method and device, a medium and a product, and relates to the field of synthetic aperture radar interferometry, the method comprises the following steps: obtaining image data sets of a plurality of SAR sensors in a monitoring area, and sequentially carrying out differential interference and time sequence deformation calculation to obtain an LOS direction deformation result; geocoding all results to unify a coordinate system; screening high-coherence point targets and constructing an observation geometry unified analysis model; time information is obtained by combining the images, and a long-time-sequence earth surface deformation resolving function model after observation geometric correction is established; and further introducing a truncated singular value decomposition operator, constructing a cross-sensor long-time-sequence deformation resolving analysis model, and finally resolving to obtain a high-precision and long-time-span earth surface deformation product in the monitoring area. According to the method, the problems of rank deficiency and solution failure caused by time shortage and observation geometric difference in multi-platform InSAR data joint solution are effectively solved, and the precision and applicability of long-time-sequence deformation monitoring are remarkably improved.

A first access point (AP) transmits to a second AP a first frame requesting first restricted target wake time (R-TWT) information of the second AP based on not receiving a beacon frame of the second AP within a first period from a target beacon transmission time (TBTT) of the second AP. The first AP receives from the second AP a second frame comprising the first R-TWT information of the second AP in response to the first frame.

The invention belongs to the technical field of radar signal processing, discloses a plasma sheath multi-order dispersion effect error compensation method, system, equipment, medium and program product based on two-step self-focusing processing, and aims to solve the problem of plasma sheath multi-order dispersion effect error influence of radar in the hypersonic flight vehicle imaging detection process. Obtaining a strong scattering point target in the image through strong point target search, and constructing a dispersion effect error compensation image matrix; based on a maximum contrast self-focusing processing principle and an image focusing theory, iteratively processing and compensating second-order and third-order phase errors of a dispersion effect; outputting an image after the multi-order dispersion effect error compensation, and realizing the accurate compensation of the multi-order dispersion effect error of the target wrapped by the plasma sheath; systems, devices, media for implementing the method, program products including computer programs implementing the method; the method has the characteristics of high dispersion effect error compensation precision, high compensation efficiency, strong adaptability and simple compensation processing steps.

In some implementations, a target user equipment (UE) may receive, from an initiator UE via an SL interface, a discovery request corresponding to an SL positioning session, wherein the target UE comprises a plurality of transmission / reception points (TRPs). The target UE may determine, from the discovery request, the initiator UE is incapable of associating each TRP of the plurality of TRPs with the target UE. Responsive to determining the initiator UE is incapable of associating each TRP of the plurality of TRPs with the target UE, the target UE may participate in the SL positioning session with the target UE by either: (i) using only one TRP of the plurality of TRPs during the SL positioning session, or (ii) using each TRP of the plurality of TRPs such that each TRP operates as a distinct UE.

The invention relates to the technical field of radars, in particular to a weather radar distance resolution calibration method and system. The method comprises the following steps: collecting oversampling original baseband I / Q data of a point target in a plurality of continuous pulse periods; determining a pulse signal-to-noise ratio, and screening out effective pulses according to a threshold value; carrying out sub-sampling stage time alignment on the effective pulses based on cross-correlation analysis, and carrying out incoherent averaging on power module values of all the aligned pulses to generate an average pulse power envelope; converting the average pulse power envelope to a logarithm domain, and selecting discrete data points in a main lobe region; according to the discrete data points, a nonlinear least square method is adopted to carry out iterative fitting on the generalized Gaussian mathematical model, and a continuous analytic function describing the pulse envelope is obtained; according to the continuous analytic function, determining a pulse time width when the power is reduced to a peak value of-6dB; and determining the real distance resolution according to the pulse time width. The measurement robustness is improved, and sub-meter calibration precision is achieved.

The application discloses an infrared long-distance space adjacent target super-resolution method, wherein the method comprises the following steps: S1, analyzing the imaging characteristics of a long-distance target optical detection system and the imaging characteristics of space adjacent multiple targets, modeling point target imaging, and generating a simulation image dataset; S2, initializing the input simulation image based on linear mapping; S3, realizing infrared space adjacent target super-resolution modeling by adopting a sparse reconstruction algorithm, and constructing a deep unfolding network framework; S4, sequentially passing the initialized image through each stage of the deep unfolding network; S5, constructing a GPU training environment, setting a data loader, a model and an evaluator configuration file, training the model, applying the trained model to a test set, generating a high-resolution image, extracting target coordinate information by post-processing and inputting the target coordinate information into the evaluator, obtaining evaluation indexes based on infrared long-distance space adjacent targets, and calculating an average detection rate.

The invention relates to the technical field of thunder and lightning mode recognition, and discloses a thunder and lightning intelligent target early warning method and system for a local key target, and the method comprises the steps: collecting target feature description, estimating storm motion information based on lightning positioning data and radar echo images at continuous moments, and carrying out the recognition of a thunder and lightning mode. And generating a risk corridor in the upstream direction of each target area, and forming a target area around the target area in combination with the risk corridor. Unified spatio-temporal data is obtained, spatio-temporal feature extraction is carried out to obtain storm features, cross-modal correlation selection and weighting are carried out on the storm features with target feature description as a drive, and target features are constructed. And generating an early warning result in a predetermined time window according to the target feature. And when the thunder risk probability reaches an early warning threshold and the spatial risk distribution intersects with the buffer range of the target area, generating targeted early warning information. According to the invention, thunder and lightning targeted early warning is realized, the hit rate is improved, and false alarms are reduced.

A space-based optical space target detection method fusing track information comprises the following steps: acquiring an image spot position of a point target in a star map of a current position by using a space-based optical camera, and determining a candidate target set according to different motion characteristics of a fixed star and a space target; determining the center-of-mass coordinate and pixel range of the candidate target under the image plane coordinate system according to the orientation of the optical camera, converting the center-of-mass coordinate and pixel range into the sight angle and range under the satellite body coordinate system, carrying out inter-frame trajectory association on the obtained star map sequence, updating the space target library according to trajectory information, and outputting a space target detection result. And repeating the steps to traverse all star maps.

The present application relates to the technical field of visual target analysis, and discloses a dynamic bright spot target statistics and analysis method based on visual tracking. The method collects a reference video sequence to construct a background model database, acquires a real-time video stream data set, detects visual bright spot targets and calculates average brightness values as detection reference thresholds. The visual bright spot targets are analyzed in combination with the background model database to identify and mark potential abnormal bright spot targets. When there are potential abnormal bright spot targets, their spatial position information and motion trajectory features are extracted to determine whether they are real abnormal bright spot targets. After being determined as real abnormal bright spot targets, initial risk assessment values are calculated according to the occurrence frequencies, shape contour and size change features are extracted, and a feature matching algorithm is used for similarity grouping analysis. According to the analysis result, it is determined whether there is a dynamic flickering bright spot target. If there is, an adjustment factor is adjusted based on the flickering mode features to correct the initial risk assessment value, and the subsequent dynamic tracking frame rate is set according to the corrected value.

The invention discloses a synthetic aperture radiometer darkroom phase calibration method and device. The method comprises the following steps: installing a synthetic aperture radiometer and a point target emission source in a microwave anechoic chamber; in the first-stage test, unit antenna output ports are connected with equal-length test cables and connected to a microwave test instrument, a synthetic aperture radiometer is set to be in an antenna observation mode, and a point target observation unit antenna phase difference test is carried out; in the second-stage test, the output end of the unit antenna is connected with each receiving channel of the synthetic aperture radiometer, the synthetic aperture radiometer is set to be in an antenna observation mode, and a point target observation full-system phase difference test is carried out; in the third stage of testing, the synthetic aperture radiometer is set to be in a common noise injection calibration mode, and common noise injection calibration is carried out; and calculating and counteracting a near field effect phase difference, a unit antenna phase difference and a receiver channel phase difference to obtain an accurate noise distribution network phase difference parameter. Darkroom phase calibration is achieved under the near-field condition, the result is accurate, and the method is simple, convenient and practical.

The application provides a point target wide-area high-precision positioning method, device and equipment combined with imaging model fine and coarse calibration, relates to the technical field of optical imaging precision measurement, and aims to realize point target wide-area high-precision positioning. The method comprises the following steps: collecting point target images located at different sub-pixel positions, calibrating the PSF of a first pixel on an image detector to obtain a reference PSF model; mapping the reference PSF model to a second pixel and fitting the imaging data of the second pixel to obtain an extended PSF model; wherein the extended PSF model represents the pixel response values corresponding to different positions of the center of the image spot from the center of the pixel; and positioning the wide-area point target images collected by the image detector by using the extended PSF model and the maximum likelihood method to obtain a positioning result.

The invention discloses a three-dimensional sonar phase self-correction method, and relates to the technical field of underwater acoustic engineering and array signal process.The method comprises the steps that a three-dimensional sonar image is generated through sonar original multi-channel signals, a plurality of strong display point targets which can be separated from the three-dimensional sonar image are extracted, and the signal-to-noise ratio of the strong display point targets is higher than a threshold value; sound path distance difference phase compensation is carried out on echo signals of each strong display point target, a channel common phase deviation is estimated by using a compensated residual complex signal, then an image entropy and a target peak value are set as convergence criteria, the criteria are deeply combined with an iterative reweighting mechanism, step-by-step optimization is carried out to obtain the phase deviation estimation precision, and the estimation precision of the channel common phase deviation is improved. And finally, obtaining an optimal inherent phase deviation, and carrying out global phase correction on the multi-channel echo signal by using the optimal inherent phase deviation. According to the invention, real-time online self-correction can be realized, the problem of imaging blur caused by phase inconsistency between channels is effectively compensated, and the contrast ratio of three-dimensional sonar imaging and the target visualization quality are remarkably improved.

This invention discloses an automatic calibration method for airborne lidar placement deviation based on voxel sharpness. The method includes: selecting a natural calibration site containing building facades, linear markers, and point targets; collecting point cloud and POS data via a UAV flying in multiple headings; modeling the placement deviation to be calibrated using six parameters; optimizing the parameters using a genetic algorithm; using voxel sharpness as the fitness function; voxelizing the point cloud in the region of interest; counting the number of points within each voxel and calculating the sharpness score; a higher sharpness score indicates a more pronounced clustering of point clouds in the feature region; and iteratively optimizing the method through selection, crossover, and mutation operations to output the optimal placement deviation parameters. This invention uses an ordinary basketball court as a natural calibration site, eliminating the need for artificial targets. After calibration, the point cloud sharpness is improved by more than 150%, and the positioning accuracy reaches the centimeter level.

The invention discloses a cold background point target application-oriented infrared detector test evaluation method, which comprises the following steps of: according to radiation characteristics of an actual background and a target, camera parameters and infrared detector test system parameters, enabling a cold background and a cold background superposition point target to be equivalent to a surface source black body temperature tested by an infrared detector; and the performance of the infrared detector is tested and evaluated in the cold background infrared detector test cold cabin. The cold cabin is connected with the focal plane refrigeration and temperature measurement and control module, the black body refrigeration and temperature measurement and control module, the acquisition module and the vacuum pump, and can provide high-vacuum low-background test conditions for extremely low dark current and various photoelectric properties of the high-sensitivity infrared detector. The infrared detector performance parameters obtained by the method can provide test data support for actual performance evaluation of the cold background point target detection camera.

The application discloses a hotspot target tracking method and device based on load detection and star sensitivity reset, and belongs to the field of spacecraft attitude control. The method comprises the following steps: according to the time scale of load target detection information and historical load visual axis ground pointing point information, the latitude, longitude and altitude information of the target are estimated; according to the maximum attitude maneuvering ability of the system and the five-order polynomial guide model, the fastest time of target recapture is determined by taking time as an iteration amount, the target attitude of the target recapture process is autonomously planned, and closed-loop control is carried out; after the target recapture, the control system carries out closed-loop control according to the real-time detection information of the load, ensures that the target is located at the center of the visual field of the load, and the load continuously images; after the tracking imaging is completed, the guide process of returning to scanning imaging is autonomously planned; in the whole process, the current attitude is reset according to the double-vector attitude determination result of the high-precision star sensitive sensor with angular velocity as a constraint, so that the pointing accuracy is ensured.

A target path changing system for an accessory device is provided, which can improve work efficiency of an operation to change a target path of a specific portion of the accessory device. An object point selection unit (15) is configured to allow an operator to select one of target points (72) as a change object point (73). A range setting unit (15) is configured to set a movable range (E) in which the change object point (73) is movable. An object point moving unit (15) allows the operator to move the change object point (73) within the movable range (E). A target path resetting unit (15) is configured to reset the target path (71a) between a change start point (74) and a change end point (75) so that the target path (71) passes through a post-change object point (73a).

The application provides a wide-area infrared point target detection tracking cooperative satellite system, which comprises a camera subsystem, a target processing subsystem, a task planning subsystem, an intersatellite network subsystem, an imaging quality guarantee subsystem and a light shield subsystem; the camera subsystem is used for imaging infrared point targets in a wide-area range to generate a wide-area monitoring range image containing weak infrared radiation targets; the target processing subsystem extracts two-dimensional plane coordinates of the targets from the infrared image, generates three-dimensional positions and speeds of the targets, and reasonably distributes different targets to different satellites for data fusion; the task planning subsystem calculates orbit positions and observation capabilities of other cooperative satellites according to the three-dimensional positions of the targets, and performs observation task planning on the other cooperative satellites; the intersatellite network subsystem is responsible for receiving two-dimensional angular trajectories provided by other satellites, providing the two-dimensional angular trajectories to the target processing subsystem, and sending information such as cooperative planning generated by the task planning subsystem to other satellites.

The invention relates to a hardware-in-the-loop remote space target sensing ground equivalent test system, and belongs to the technical field of space target detection and identification. The system comprises a dynamics simulation machine, a motion control upper computer, a comprehensive control system, a relative motion simulation system, a system calibration machine, an information processing system and an application evaluation machine. According to the invention, rapid and stable acquisition and precision evaluation of the mass center position of the long-distance space target are realized by adopting a double-arm collaborative visual perception motion system based on dynamic driving, ground test verification of a detection tracking technology of a long-distance point target in a typical space task scene is completed, and the method has the advantages of high simulation precision, high reliability and the like.

The application provides a modeling method for a center track of a point target trail image of a camera. The method first integrates three-axis angular velocities of the camera into a total angular velocity vector; constructs a cone with a unit vector of the total angular velocity as a main axis, and a point target incident light ray sweeps around the main axis to form a conical surface; establishes a conic surface equation of the conical surface; establishes an image array plane equation in a same reference coordinate system as that of the angular velocity unit vector; and obtains an intersection line equation of the conic surface and the image array plane, which is a center track of the point target trail image of the point target. According to different distribution conditions of a point target line-of-sight direction and an angular velocity vector direction relative to the camera, possible dynamic trail tracks are listed as four kinds of geometric descriptions, i.e., a circular arc, a trail circular arc, a parabola and a hyperbola. The application correctly reveals a geometric mechanism of the trail track, the model is complete in an analytical form, and theoretically solves an accurate modeling problem of the point target trail image track under a dynamic imaging working condition.

This invention belongs to the field of object detection and provides a keypoint object detection method and system based on multiple correspondences. Addressing the problem that keypoint-based object detection algorithms cannot effectively distinguish multiple objects when their keypoints overlap, this invention utilizes a multiple correspondence relationship in the network, where one location corresponds to multiple predicted boxes to achieve our goal. To achieve this, the method mainly includes the following two parts. First, the keypoint pooling method is improved. Existing keypoint pooling methods focus on emphasizing keypoints, but this invention considers that keypoint detection should emphasize keypoints while suppressing the surrounding environment. Second, to better match corners to the correct center point, a pointing offset is used to match keypoints. Specifically, corner points are matched to the center point through their offset. To better predict the pointing offset, a corner-to-center module is designed to improve the matching effect.

This invention discloses a target simulation trajectory generation method for verifying dual-band infrared passive ranging technology. The method first simplifies the target into a Lambertian cylindrical model and sets a uniform straight-line flight path. Then, it calculates the critical distance at which the target is identified as a "point target" and an "area target." Next, through iterative calculations, it sequentially solves for the target's azimuth, pitch, actual distance, projected area, number of image pixels, radiation intensity, and image grayscale value in each simulation cycle, until the target completes its entire flight path. Finally, it outputs a dataset containing the target's actual distance, projected area, number of pixels, and grayscale value at the end of each cycle for algorithm verification of dual-band infrared passive ranging technology. This invention replaces field testing with fully digital simulation, enabling efficient and low-cost generation of high-precision verification data, and solving the problem of dependence on real targets and complex hardware systems in the R&D and verification phase of dual-band infrared passive ranging technology.

The application discloses a heterogeneous networked radar space registration method based on adaptive grid reconstruction, which comprises the following steps: 1, constructing a radar network system model, presetting related parameters of the radar network system, and initializing the related parameters; 2, obtaining a space sampling unit association group of each grid, and merging grids with the same space sampling unit association group into a reconstructed overlapping area; 3, obtaining a space sampling unit association group of each reconstructed overlapping area, and forming a set; according to the set, an average registration rate of a plurality of randomly distributed point targets is obtained, and a local mismatch rate of each radar station and other radar stations is obtained; if the average registration rate is greater than or equal to a preset average registration rate threshold value, and the local mismatch rate is less than or equal to a preset local mismatch rate threshold value, the optimal grid side length is determined; 4, obtaining a calibration point of the reconstructed overlapping area corresponding to the optimal grid side length. The application effectively improves the registration accuracy.

The invention discloses a high-orbit multi-source point target cross-domain fusion method based on modal characteristic distillation, and relates to the technical field of modern aerospace monitoring. The method comprises the following steps: extracting invariance features related to target essential attributes from visible light, infrared and radar data through a teacher network, and fusing the invariance features to generate teacher knowledge vectors; and taking the teacher knowledge vector as an optimization target of a student network, and performing iterative optimization by adopting a composite loss function including knowledge distillation loss, physical attribute loss, modal alignment loss and task loss, thereby realizing accurate identification of a point target. Through the feature extraction and knowledge distillation mechanism guided by physical constraints, the problem of feature heterogeneity among multi-modal data is effectively solved, the recognition accuracy and tracking stability of point targets such as space debris in a complex space environment are improved, meanwhile, the model is lightweight and efficient, and the on-orbit real-time processing requirement is met.

This invention relates to the field of RCS testing technology, specifically to an image-domain-based near-field anomalous scattering filtering method. The method first obtains a raw near-field image by near-field imaging of the acquired near-field swept data. Second, based on set anomalous scattering judgment conditions, the anomalous scattering centers are identified and extracted. Then, using a point target as a reference object, the scattering field distribution in the determined filtering area is simulated and reconstructed to generate a new near-field image. Finally, it is determined whether the new near-field image meets the anomalous scattering judgment conditions. If not, a filtered near-field image is generated. By identifying and removing scattering centers that do not belong to the test target from the two-dimensional image generated by the near-field imaging, near-field clutter suppression and higher-precision radar cross section testing are achieved.