263 results about "Point target" patented technology

The invention provides a settlement detection method and device based on machine vision, belongs to the technical field of underground engineering, and is applied to a settlement monitoring area, a measuring point target is arranged in the area, and a reference point target is arranged outside the area; comprising the steps that S1, a settlement monitoring area is continuously shot, a monitoring image set is obtained, and the monitoring image set covers a monitoring point target arranged in the settlement monitoring area and a reference point target arranged outside the settlement monitoring area; s2, processing the monitoring image set to obtain the relative elevation of each measuring point target; and S3, comparing the relative elevation of each measuring point target with the corresponding initial elevation to obtain the settlement amount of each measuring point target. The beneficial effects are that by arranging the measuring point target and the reference point target, the normal operation of road traffic is not interfered, the road traffic is not easily damaged by rolling of running vehicles, the problem of machine vision wide-area monitoring is solved, and the settlement monitoring area can be monitored more comprehensively and accurately.

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 discloses an infrared long-distance spatial adjacent target super-resolution method, and the method comprises the steps: S1, analyzing the imaging characteristics of an optical detection system of a long-distance target and the imaging characteristics of multiple spatial adjacent targets, carrying out the imaging modeling of a point target, and generating a simulation image data set; s2, initializing an input simulation image based on linear mapping; s3, adopting a sparse reconstruction algorithm to realize infrared space adjacent target super-resolution modeling, and constructing a deep expansion network framework; s4, enabling the initialized image to sequentially pass through each stage of the deep expansion network; and S5, constructing a GPU training environment, setting a configuration file training model of a data loader, a model and an evaluator, applying the trained model to a test set, generating a high-resolution image, extracting target coordinate information through post-processing, inputting the target coordinate information into the evaluator, obtaining an evaluation index based on an infrared long-distance space adjacent target, and calculating an average detection rate.

The invention relates to the technical field of visual target analysis, and discloses a dynamic bright spot target statistics and analysis method based on visual tracking. According to the method, a reference video sequence is collected to construct a background model database, a real-time video stream data set is obtained, a visual bright spot target is detected, and an average brightness value is calculated as a detection reference threshold value. And a visual bright spot target is analyzed in combination with the background model database, and a potential abnormal bright spot target is identified and marked. And when a potential abnormal bright spot target exists, extracting spatial position information and movement track characteristics of the potential abnormal bright spot target, and judging whether the potential abnormal bright spot target is a real abnormal bright spot target. And after real abnormity is determined, calculating an initial risk assessment value according to the occurrence frequency, extracting morphological contour and size change features, and performing similarity grouping analysis by using a feature matching algorithm. And judging whether a dynamic flicker bright spot target exists or not according to an analysis result, if so, correcting an initial risk assessment value based on a flicker mode characteristic setting adjustment factor, and adjusting subsequent dynamic tracking frame rate setting according to the corrected value.

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 discloses a key target ship dynamic tracking management method, which comprises the following steps of S1, acquiring marine ship data in a sea area in real time to obtain information and navigation data of each ship; s2, preprocessing the information and data obtained in S1, and removing noise and abnormal values; s3, constructing a risk assessment model, assessing the risk level of each ship inside and outside the region according to a predetermined condition, and taking a high-risk ship as a key target ship; s4, constructing a monitoring and early warning model, monitoring the dynamic behavior of the key target ship in real time, and when an abnormal behavior occurs, triggering early warning and sending an early warning notification to a specified equipment end through a preset communication end; and S5, generating a comprehensive research and judgment report. According to the invention, real-time dynamic tracking of ships is realized, comprehensive, accurate and timely supervision information and research and judgment reports are provided for supervision departments, and the efficiency and accuracy of maritime traffic management and safety supervision are improved.

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.

The invention relates to a spatial adjacent infrared small target unmixing method and network, in particular to a multi-frame spatial adjacent infrared small target unmixing method and network based on model and data dual drive, and solves the problem that the prior art cannot meet the detection requirement of an infrared point target of which the target spatial distance is smaller than the Rayleigh radius. The method comprises the following steps: step 1, inputting slice images of S frames; step 2, initialization is carried out; 3, feature extraction is carried out through W times of iteration; step 4, adding the time sequence information into the mapping image after the Wth iteration; 5, sequentially and independently executing the steps a to b on each sequence image according to the sequence that the first frame to the (2N + 1)-th frame, the second frame to the (2N + 2)-th frame,..., the (S-2N)-th frame and the sequence of the sequences of the images after the time sequence information is added; the steps a to b are as follows: step a: convolution; and b, time deformable alignment is carried out, and then tail convolution is carried out.

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 invention discloses a trace calculation method based on tiny target identification and tracking and a storage medium. The trace calculation method comprises the following steps: extracting an original image of a target video as input, performing image processing, improving the quality of a target video image by adopting a background-based adaptive prediction algorithm, and comparing with the input original image to obtain a target detection image; the target detection image is input into a target extraction algorithm module, a connected domain marking algorithm is adopted to separate motion and noisy point targets, a distribution area is determined, and a feature image is output; tracking and positioning the feature image, calculating by adopting a centroid positioning algorithm, and outputting a centroid coordinate and a pixel gray value of the target; and filtering static noisy points in the video image through threshold segmentation, performing trajectory prediction and calculation on a moving target based on a Kalman filtering method, and outputting the trajectory of the moving target in an image plane coordinate system. The method has higher trajectory calculation precision and calculation speed, and can be used in the field of motion trajectory prediction of small targets such as unmanned aerial vehicles.

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.

The invention discloses a millimeter wave detection method based on a near-field target echo characteristic representation model. According to the method, ground electromagnetic scattering characteristics of a detection range are analyzed, electromagnetic scattering coefficients are analyzed by using a random rough surface, a ground electromagnetic scattering model is established, a geometrical relationship model of a detector and the ground is constructed, scattering units are divided from an equal slope distance angle, and finally echoes of the scattering units are superposed. Deriving a representation model of the echo characteristics of the surface target; model construction is more rigorous, errors caused by approximately neglecting echo signals as point target echo signals are avoided, and comprehensiveness and reliability of effective information features in an echo signal model are improved; millimeter wave detection is carried out based on the model, the detection precision and efficiency are effectively improved, and the accuracy of detection result analysis is improved.

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 an interpolation method and device, equipment and a medium, and relates to the technical field of geographic information, and the method comprises the steps: obtaining data needed by the interpolation of a target geographic element, and carrying out the preprocessing of the data; different types of data points in the preprocessed data are embedded into multi-dimensional feature vectors to serve as tokens of the corresponding data points; and for any target point, inputting the token of the data point in the set space-time neighborhood of the target point into the trained interpolation model so as to carry out interpolation on the target geographic element of the target point. In this way, the relationship between the geographic elements of the data points and the target geographic elements of the target points can be better modeled, the interpolation model can better deduce the target geographic element values of the target points, the interpolation precision is improved, and the interpolation result better conforms to the actual distribution and change trend of the target geographic elements. The method has the characteristics of good universality, high precision, high automation degree and the like.

The invention provides a target high-resolution range profile echo simulation method, device, system and equipment, a medium and a program product. The method comprises the steps that the number, position coordinates and RCS values of scattering points are set; projecting the position coordinates of the scattering points to a radar sight line direction according to the radar azimuth angle to obtain projection position coordinates of the scattering points; calculating delay time by using the coordinates of the projection positions of the scattering points, and delaying the radar signals; calculating a phase difference by using the projection position coordinates of the scattering points, and obtaining modulation data by combining with the RCS value; and processing the delayed radar signal by using the modulation data to obtain a radar echo, and further obtaining a high-resolution range profile echo of the target. For the received radar signal, the target generated by the method is no longer a simple'point 'target but a'line' target obtained by projecting different scattering points on the target in the radar line-of-sight direction, so that the scattering characteristic of the real target can be reflected more vividly, and the pertinence and effectiveness of radar system test verification are improved.

The invention discloses a method and a system for measuring and calculating a signal-to-noise ratio of an uncooled infrared detection system, relates to the technical field of infrared target detection, and solves the problems that parameters of an uncooled detector are lost during research and development of a low-cost infrared system and detection effects of different view field angles of a large-view-field system are different. The radiance at the entrance pupil is calculated through the target radiance and the atmospheric transmittance, the irradiance and the illuminance from the pupil to the center of an image plane are derived based on optical system parameters, the irradiance related to a field angle is obtained according to a geometrical relationship for large-field edge illuminance attenuation, and the irradiance related to the field angle is obtained according to a geometrical relationship for a point target which is not filled with a photosensitive element. Calculating the projection on the photosensitive element and the signal radiation quantity received by the pixel; the noise equivalent temperature difference is tested by adopting a collimation method, and the value is obtained by combining a collimator and the spectral transmittance of an optical system so as to calculate the noise power; and the signal-to-noise ratio is calculated by combining the signal amplitude-flux. The method solves the problem of parameter loss through actually measured noise equivalent temperature difference value estimation, considers view field energy attenuation in the evaluation process, and is suitable for fine evaluation of a large view field system.

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 high-resolution long-acting-distance synthetic aperture radar signal preprocessing method, and relates to the technical field of radar signal processing. The method comprises the following steps: determining a sampling rate and a sampling point number; performing analog-to-digital conversion on the analog intermediate-frequency signal, and acquiring data to obtain a digital intermediate-frequency signal; performing dechirp processing to obtain a point target radar echo signal; performing filtering processing to obtain a radar echo signal of the region of interest; reducing the radar echo signal of the region of interest into a linear frequency modulation signal through frequency modulation reconstruction; sampling the signal after frequency modulation reconstruction to obtain a corresponding signal sample sequence; reducing the length of the signal sample sequence in a data accumulation mode; and performing pulse compression on the signals in the accumulated signal sample sequence by adopting a preset pulse compression method. According to the invention, the difficulty of pulse compression, the requirements on hardware storage space and computing resources, the implementation difficulty of an analog receiver, and the pressure and processing difficulty of subsequent recording are reduced.

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.