34 results about "Echo intensity" patented technology

The present application relates to the technical field of concrete height measurement, and provides a concrete pouring height self-adaptive monitoring method and system, which controls a motor drive cloud platform to drive a laser ranging module to automatically scan a monitoring area and determine an effective monitoring point through an edge computing terminal, and sequentially performs automatic measurement, thereby improving monitoring real-time performance and reducing labor costs. During the monitoring process, when the ranging value suddenly changes and the echo intensity meets a preset condition, the cloud platform is controlled to swing and the maximum ranging value in the swinging process is taken as an effective value to actively avoid shielding and obtain a real concrete liquid surface distance. The number of consecutive invalid points is accumulated to automatically eliminate the invalid points, and new points are obtained by supplementally scanning near the eliminated points when the points are insufficient, thereby realizing automatic updating of the monitoring point set. The inclination of the device is obtained in real time through an inclination sensor, and the ranging value is accurately converted into pouring height in combination with the absolute installation height, thereby eliminating the device inclination error. The present application has low implementation cost and is convenient to deploy.

The application relates to the technical field of submarine pipeline investigation, and discloses a submarine pipeline acoustic-optical combined investigation method, system, device and medium. An AUV carrying an acoustic sensor is used to carry out coverage investigation on a task area, acoustic data are collected, and acoustic characteristics of an object to be investigated are extracted, a suspected pipeline candidate area is generated based on echo intensity in the acoustic characteristics and a preset acoustic detection threshold; an AUV carrying an optical imaging device is used to carry out fine imaging on the suspected pipeline candidate area, optical data are collected, and optical characteristics of the object to be investigated are extracted, clustering analysis is carried out based on the optical characteristics to obtain a clustering result containing a suspected target cluster, a noise cluster and an uncertain cluster; and a multi-modal information fusion method is used to jointly judge the object to be investigated according to the acoustic characteristics and the optical characteristics of the suspected target cluster. The wide-area coverage advantage of the acoustic and the high-resolution advantage of the optical are fused, and efficient, accurate and reliable investigation of the submarine pipeline is realized.

This invention discloses a laser dimension measurement device and method for hollow plastic panels, belonging to the field of laser measurement technology. The method obtains the optical signal-to-noise coefficient based on laser echo intensity, surface reflection uniformity, and speckle contrast; it obtains the motion disturbance coefficient based on encoder slip rate, dynamic bow height of the panel, and edge burr fluctuation frequency; and it obtains the medium interference coefficient based on ambient stray light flicker frequency, transmission depth offset, and color saturation. Furthermore, based on the optical signal-to-noise coefficient and motion disturbance coefficient, combined with the resonant frequency of the internal cavity of the panel and the hollow layer collapse coefficient, a resonance-collapse measurability model is used to obtain resonance-collapse measurability. Finally, combining the medium interference coefficient and the current scanning axis acceleration, an optimized scanning axis acceleration is obtained through an acceleration optimization model. This invention can comprehensively evaluate multi-source interference during the measurement process, dynamically optimize scanning parameters, and improve measurement accuracy and stability.

This invention provides a method for identifying and suppressing false echoes from marine radar under calm sea conditions. The specific process is as follows: For a single-frame radar image, extended target information is obtained. The recorded extended target information is converted into point coordinate information, i.e., the wave crest position of the echo is retained, and the azimuth and range information of the wave crest position are extracted. Simultaneously, the echo intensity information of the target is added and stored as an initial target information matrix. Azimuth feature information is judged, and target information that conforms to the azimuth feature of the false echo is saved. Range feature information is judged, and target information that conforms to the range feature of the false echo is saved. The false echo occurrence scenario is judged to determine whether the conditions for false echo occurrence are met. Echo intensity feature information is judged, and target information that does not conform to the echo intensity feature of the false echo is deleted. Simultaneously, the initial target information matrix is ​​updated to a false echo target information matrix. Based on the information in the false echo target information matrix, a suppression threshold for the digital domain of the radar echo data is set to suppress false echoes in the single-frame target information.

The application discloses a kind of multispectral laser imaging radar systems based on APD array and supercontinuum laser, wavelength covering 450~2400nm supercontinuum laser is used as light source, the continuous laser output is collimated after being collimated by laser collimating system, multi-band fast selection is realized by acousto-optic tunable filter, and uniform emission is completed in combination with variable-focus laser emission optical system;Then, large field of view receiving optical system is constructed, and the echo signal is detected by APD array detector to realize multi-pixel parallel detection, the echo intensity data corresponding to different wavelengths are acquired, and the multispectral reflection information of target is formed.Finally, the laser emission time and APD array receiving time are accurately synchronized, based on time-of-flight ranging principle, the high-precision space-time information of target point cloud data and multispectral information is synchronously acquired.The application realizes the high spectral information acquisition accuracy while breaking through the efficiency and resolution limit of traditional single-point imaging mode.

The utility model discloses a coaxial needle intervenes and establishes a channel needle relates to medical instrument technical field, including needle tube and needle holder, one end of needle tube is fixedly connected with needle holder, and the other end is puncture end, and the outside of needle tube is equipped with three groups gradient spiral groove, and three groups gradient spiral groove interval 120 degree array distribution, and three groups gradient spiral groove axial feed every rotation 1mm in advance, and the depth of groove is from near puncture end 0.15mm to far end 0.25mm linearly increasing, through gradient spiral groove axial pitch change, make the reflection of gradient spiral groove of different positions to ultrasonic wave form different reflection section, improve ultrasonic echo intensity, promote needle tip dynamic tracking ability, through the recess depth linearly increasing, can produce modulated ultrasonic signal when reflecting ultrasonic wave, realize accurate positioning to needle tip position, improve the axial resolution when displaying, make when still keep clear imaging in fat layer thickness three centimeters.

The application discloses a target radar cross section estimation method and system, and relates to the technical field of radio and radar detection; the method comprises the following steps: forming a main scanning beam, a left accompanying beam and a right accompanying beam in a residence period, collecting echo samples to obtain an echo sample set, recording a beam serial number and a pointing angle to obtain a multi-beam pointing table, and obtaining a multi-beam power group from the echo intensity of three beams; obtaining a direction map deviation segment from the multi-beam power group and the multi-beam pointing table; aligning the direction map deviation segment with the echo sample set, and obtaining a channel consistency correction table according to a background echo segment; obtaining a de-drift echo power sequence and a maneuvering decoupling weight according to the channel consistency correction table and a tracking error sequence; the application can effectively solve the problems of the mixing of sidelobe energy caused by the beam pointing error in the prior art and the asymmetric drift of the radar cross section estimation caused by the change of the beam shape with the pointing.

The present application relates to the technical field of marine geological exploration, especially to a shallow seabed classification method and system based on multi-scale and multi-direction feature fusion, the method comprising: acquiring multi-source acoustic data of the shallow seabed, preprocessing the acquired multi-source acoustic data, constructing a spatial correlation model based on the preprocessed multi-source acoustic data, extracting seabed topographic features according to the water depth value of the MBES data, extracting multi-scale and multi-direction texture features by using the SSS image output by the spatial correlation model, optimizing the acquired topographic features and texture features, taking the core feature set as input, training a multi-class classifier and constructing a multi-model collaborative decision mechanism, outputting the seabed classification result and evaluating the classification accuracy through quantitative indicators, the present application takes the echo intensity image as the core, solves the problem of poor spatial consistency in traditional multi-source data registration, avoids classification errors caused by feature space misplacement, and improves the classification reliability.

The application discloses a kind of based on ultrasonic scanning's tomography flowmeter method, comprising the following steps: in river channel, uniformly arranging inclined closed conduit, motor drive ultrasonic probe is stepped along conduit;Set scan starting position, step interval, scanning speed and sampling frequency;At each depth, gather echo intensity, echo delay and Doppler frequency shift to form raw data;Acoustic analysis identifies water surface and silt interface and calculates layered flow velocity to generate layered data set;Interpolation fitting constructs cross section tomography model, determines layered effective flow area and average flow velocity;Layered integration obtains cross section total flow and generates real-time flow data;Monitoring signal quality triggers self-cleaning.The application realizes the same journey to obtain interface and speed and outputs total flow by layered integration, structure simplification, data consistency, applicable to on-line flow measurement.

The application relates to the technical field of agricultural automation control, in particular to a seedling tray falling speed self-adaptive adjusting method based on a laser radar, which comprises the following steps: obtaining point cloud data obtained by scanning a seedling tray bottom surface by the laser radar; wherein the point cloud data comprises three-dimensional coordinates, distance values and echo intensities of a plurality of measuring points; performing confidence degree screening on the measuring points based on the point cloud data to obtain an effective measuring point set; according to the echo intensities of the measuring points in the effective measuring point set, calibrating single-point confidence degree weights of the measuring points, and performing confidence degree weighting on the distance values of the measuring points to obtain confidence degree weighted distance values of the measuring points. The application can automatically distinguish three regions of a convex edge, a concave groove and a flat bottom surface through partition identification of the seedling tray bottom surface, and can perform self-checking and error correction on the partition result, so that the partition result is closer to the actual structure of the bottom surface, lays a foundation for subsequent differential processing of the regions, and improves the accuracy of speed adjustment.

This invention discloses an automatic frequency-elevation map measurement method and system based on residual networks, enabling rapid and automatic extraction of key ionospheric parameters from frequency-elevation maps acquired by digital altimeters. The method first parses the header information and echo intensity data from the original binary file of the altimeter to generate a frequency-elevation map image. Then, a small number of samples are manually labeled to establish a training set with critical frequencies such as foF2 and h'F2 as ground truth. Based on this, an end-to-end model including a backbone residual network, pooling layers, and a feature extraction head is built. This model is trained to convergence through backpropagation and further fine-tuned using expanded sample data to obtain an engineering-deployable model. Finally, the frequency-elevation map to be processed is input into the model, and the predicted values ​​of the target parameters are output and written to the results file. This method reduces the workload of manual interpretation and verification and improves the measurement accuracy of irregular and disturbed frequency-elevation maps.

The present application relates to the technical field of ship navigation early warning, in particular to a collision risk early warning method and device in ship navigation. In each observation period of ship navigation, the acoustic signal parameters (amplitude, delay, phase) and echo intensity time series data of each interference source are obtained simultaneously. The sound waves emitted by the sonar are reflected by objects, and the amplitude, phase and other parameters of the sound waves are attenuated due to the influence of interference sources. The fluctuations and differences of echo intensity time series data are analyzed in depth, the deviation of acoustic signal parameter time series data and preset comparison data is compared, the navigation comprehensive performance index is calculated, the echo intensity fluctuation is related to the nature of the interference source and the environmental conditions, the relative position of the ship and the interference source is analyzed, the environmental influence index is quantified by combining the echo intensity fluctuation characteristics. Finally, according to the navigation comprehensive performance index and the environmental influence index in each observation period, the acoustic signal and echo intensity data of the to-be-measured period are processed, which helps to improve the accuracy and timeliness of early warning.

This invention discloses a phased array radar calibration and monitoring method and system based on fiber optic time delay, relating to the field of phased array weather radar data processing and calibration technology. It includes setting up a calibration system in the far field, comprising a fiber optic time delay module, a transceiver module, and a measurement module. A fixed time delay is introduced using fiber optics, making the distance of the echo in the radar base data much larger than the actual physical distance, thus avoiding interference from ground objects. A formula for calculating the reflectivity factor reference value considering atmospheric loss compensation error is derived, and absolute calibration is achieved by comparing the radar's measured values ​​with the theoretical reference value. The radar's mechanical elevation angle is adjusted so that beams with different normal deviation angles point towards the calibration system, and the echo intensity is extracted to assess the performance differences of each beam. Through long-term extraction of echo intensity in calibration mode or service mode, combined with system loss, stability parameters are calculated and time series are analyzed to achieve long-term monitoring and early warning of radar stability.

This invention discloses a method, system, medium, and equipment for real-time monitoring of scour at wharf foundation beds. The method includes: acquiring sensor data at different time points, including uncompensated bed elevation, attitude parameters, near-bed velocity, and echo intensity; obtaining relative scour data based on the attitude parameters and uncompensated bed elevation; obtaining Shields parameters based on the near-bed velocity; obtaining suspended sediment concentration based on the echo intensity; and determining the real-time monitoring result at the current time point based on the relative scour data, Shields parameters, echo intensity, and suspended sediment concentration. This invention overcomes the limitations of traditional single-sensor monitoring by using multi-dimensional sensor data; it also enhances anti-interference capabilities in complex marine environments through multi-source data, avoiding monitoring errors caused by environmental factors that are easily affected by single-type monitoring methods. Furthermore, the multi-parameter coverage enables large-scale real-time monitoring of the wharf front foundation bed, allowing for timely and accurate monitoring of foundation bed scour.

A method for differential diagnosis of gallbladder adenoma and cholesterol polyps based on the fusion of deep learning and clinical features in ultrasound images includes: performing deep learning on ultrasound images using a deep learning network to output an adenoma / polyp risk score; the deep learning network is selected from one of VGG, ResNet, DenseNet, GoogLeNet, Vision Transformer, and Inception; the adenoma / polyp risk score and clinical features are input into a trained machine learning model for learning to obtain the final probability of identifying the polyp as a gallbladder adenoma rather than a cholesterol polyp; the clinical features include: echo intensity, maximum polyp diameter, and age; the machine learning model is selected from one of Logistic Regression, Gradient Boosting, K-nearest neighbors, Gaussian naïve Bayes, AdaBoost, Random Forest, ExtraTrees, and SVM.

This invention discloses a virtual simulation method and system for marine radar, comprising the following steps: constructing a virtual test environment consistent with the real marine environment, including an unmanned vessel, marine radar, and maritime targets; using a quaternion calculation method to transform measurements in the local coordinate system of the virtual radar to the world coordinate system; determining the radar field of view through horizontal and vertical scanning coverage; realizing simulated ray tracing and collision detection of the marine radar beam; calculating echo distance and angle, calculating echo intensity, and generating standardized radar echo data records; dynamically adjusting the echo intensity through adjustable gain control and range compensation mechanisms, and mapping the echo data to a color space; persistently storing and time-attenuating the echo data to simulate radar afterglow effects; and drawing range rings, azimuth markers, and dynamic scan lines on the radar display interface to construct a complete radar visualization system.

The application discloses a kind of photovoltaic panel under soil monitoring method, device, electronic equipment and storage medium.The method comprises: based on the first point cloud data of obtained target area, a plurality of target photovoltaic panels are obtained by photovoltaic panel identification;First point cloud data is mapped based on the spatial arrangement features of target photovoltaic panel to determine the target soil point under target photovoltaic panel;Based on the target spectral information corresponding to each target soil point obtained, the echo intensity corresponding to target soil point is normalized, to determine the target echo intensity corresponding to target soil point;Based on the target echo intensity corresponding to target soil point, the target feature vector of the soil under target photovoltaic panel is constructed;At least two soil inversion models are obtained, and the target soil parameters are determined based on soil inversion model and the target feature vector, and the spatial distribution map of target area is generated based on all target soil parameters.The application realizes the observability and stability of soil data under shading condition.

This invention relates to the field of lidar technology, and in particular provides a method for processing 2D lidar point cloud data. The method includes: setting a distance threshold and an echo intensity threshold for data processing; acquiring a ring of point cloud data to obtain the actual measured distance and echo intensity of the lidar; retaining point cloud data with distances less than a preset distance, and setting data points with distances greater than a preset distance as invalid values, thus obtaining a new ring of data; determining the boundary of the target object based on the invalid values, and obtaining the boundary index value; setting a sliding window and a number of sliding steps based on the echo intensity characteristics, comparing the average echo intensity within adjacent windows, and if the difference is greater than a set threshold or reaches a set number of sliding steps, retaining the point cloud and exiting data processing; otherwise, deleting edge-widening points. This method effectively eliminates the widening problem at the edges of the target object, restoring the true contour of the scanned target object.

This invention discloses a method for dynamically adjusting radar transmit power, comprising the steps of: using a transmitting device to scan the environment under test through a transmit beam; using a receiving device to receive echo signals reflected by targets in the environment under test; using an analog-to-digital converter to convert the echo signals into digital signals to statistically analyze the distance and echo intensity of the targets; using a control module to set a transmit power threshold value based on the distance and echo intensity, and to calculate a transmit power configuration based on the transmit power threshold value; and generating a control signal based on the transmit power configuration; and using an attenuator to adjust the transmit power used by the transmitting device when scanning the targets based on the control signal. This invention also discloses a system for dynamically adjusting radar transmit power and a portable imaging system.

This invention discloses a multi-echo detection method for a multi-beam echo sounding system with combined amplitude and phase features. The pre-detection step includes: segmenting the beam output signal; for each unit to be detected, obtaining an amplitude detection threshold using the unit average constant false alarm rate (CFAR) method based on background noise estimation from the reference units on the left and right sides; extracting the instantaneous phase from the signals of each receiving channel using Hilbert transform, and obtaining the phase coherence factor between each receiving channel from statistical characteristics; dynamically adjusting the amplitude detection threshold as an adaptive weight to construct a detection threshold for combined amplitude and phase features; initializing weighting coefficients based on echo intensity differences, and dynamically optimizing them in conjunction with the intensity value of the phase coherence factor to obtain an adaptive weighted amplitude and phase joint detection threshold; merging sampling points exceeding the adaptive weighted amplitude and phase joint detection threshold, removing interfering targets, and identifying and extracting multiple independent effective target intervals.

The application provides a radar water level monitoring-based reflection avoidance algorithm and device, and belongs to the technical field of hydrological water level monitoring; the radar water level monitoring-based reflection avoidance algorithm comprises multi-feature echo analysis, inclination auxiliary physical space constraint, dynamic learning and verification based on historical data, and decision and output, and does not simply rely on echo intensity or first echo; a radar transceiver module transmits an FMCW modulated signal at a sampling frequency of 5Hz, radar waves are received by a receiving end after being reflected by a water surface and surrounding structures, and are transmitted to a signal processing unit; the signal processing unit performs denoising, filtering and FFT transformation processing on the echo signal, and extracts all significant echo peaks, including a preset echo intensity threshold of 10dB. In the above scheme, the radar water level monitoring-based reflection avoidance algorithm significantly improves the accuracy and reliability of radar water level measurement, reduces water level measurement error at a monitoring point with complex structure, and meets the demand of high-precision hydrological monitoring.

The application discloses a kind of fishery abnormal retention behavior determination methods for sturgeon breeding pond, comprising the following steps: step S1: obtain the sonar image of fish school by multiple imaging sonar equipment, generate panoramic sonar graph;Step S2: the adaptive threshold segmentation is carried out to the panoramic sonar graph based on echo intensity statistical characteristics, and fish school target area is extracted;Step S3: based on the spatial structure characteristics of sonar echo, extract pool bottom echo boundary line and divide bottom layer area;Step S4: the bottom layer distribution density and movement intensity of fish school are calculated;Step S5: the bottom layer retention time of fish school is calculated;Step S6: bottom layer distribution density, movement intensity and retention time are fused to construct abnormal determination model, realize fish school abnormal retention state detection.The application is suitable for the behavior monitoring of industrialized sturgeon culture, can provide accurate data support for sturgeon health management, effectively improve the detection rate of sturgeon abnormal behavior, provide reliable technical support for intelligent aquaculture system.

This invention discloses a pseudo-color processing method for forward-looking sonar images to mitigate the impact of water turbidity. The core of this method lies in dynamically determining a threshold based on the statistical analysis of current sonar echo intensity and then linearly normalizing the statistical intensity range. A custom Jet color bar is generated based on the characteristics of the forward-looking sonar image, and this custom Jet color bar is dynamically adjusted according to different water turbidity levels to achieve pixel-level adaptive color mapping. This method can significantly increase the visualization quality and target recognition of sonar images in water environments with varying turbidity, improving the operator's perception and judgment of underwater targets. It overcomes the detail loss problem caused by existing technologies that only use fixed pseudo-color mapping, has broad application prospects, and requires only software implementation, possessing good compatibility and promotional value.

The application discloses a weather modification data collection processing and analysis rain enhancement potential method and system, including the following steps: cloud layer radar data and cloud layer temperature data are fused to construct a cloud layer temperature-thickness-echo intensity distribution map, and image cutting processing is carried out to remove image regions less than a cloud layer thickness threshold; a rain enhancement catalysis target region is selected from the cutting-processed cloud layer temperature-thickness-echo intensity distribution map by setting a catalytic echo intensity threshold range, and rain enhancement catalysis potential volume ratio calculation processing is carried out; the rain enhancement catalysis target region is determined in each growth stage based on the rain enhancement catalysis potential volume ratio at different moments, and cloud layer regions with high catalytic efficiency are screened out from the rain enhancement catalysis target region to carry out regional volume calculation; the cloud layer rain enhancement catalysis potential degree is determined based on the duration of each growth stage of the cloud layer region with high catalytic efficiency, the volume grown in each growth stage and the supercooled water content; and the rain enhancement catalysis operation effect is ensured.

The application discloses a laser radar road surface type identification method based on multi-modal information fusion, and relates to the technical field of intelligent driving environment perception, comprising the following steps: fixing a multi-line laser radar in front of a vehicle to collect height signals and echo intensity signals of a road surface in a preview area; after point cloud preprocessing, height and intensity original matrices are obtained through gridding; a multi-quadratic surface radial basis function is used for interpolation of a null grid surface, and a characteristic image is generated through orthographic projection and resampling; an improved MobileNetV4 is used to extract depth features and perform PCA dimension reduction, and 9-dimensional statistical features such as mean, variance, skewness and kurtosis are extracted from two original matrices; four groups of features are normalized and concatenated into a fusion vector, and the fusion vector is stacked into a time sequence matrix by a sliding window; the RoadFormer model is input, multi-layer Transformer coding and time sequence semantic modeling are performed, and a road surface type is output, so that all-weather high-precision and high-robust real-time road surface identification is realized.

This invention relates to the field of wireless radar equipment technology, and in particular to a method and apparatus for wireless radar attitude reconstruction based on deep learning. It acquires multiple frames of radar motion point clouds and wireless echo signals, uses echo intensity to guide the propagation of local coherent structures in the point clouds, achieving dynamic completion of sparse radar point clouds to obtain dynamically dense point cloud aggregates; constructs a smooth topological field and calculates structural loss through tensor decomposition to achieve structural alignment between the source and target point clouds, and identifies suspended point cloud regions based on attitude-invariant description; employs BEV (Bird's-eye View) enhanced coding and anchor frame detection to constrain coarse attitude view bounding boxes, and completes the inversion and backtracking of suspended point clouds through deep learning surface projection with cross-attention, obtaining attitude inversion projection points and suspended vectors; constructs a rigid skeleton and dynamic implicit space based on a seed attitude point cloud mesh, and uses suspended vectors to drive attitude reconstruction. This invention achieves dynamic reconstruction of wireless radar detection attitude, improving and optimizing attitude reconstruction accuracy and robustness.

This invention discloses a pseudo-color processing method for forward-looking sonar images. It linearly normalizes the statistical intensity range by using a dynamic threshold based on the current sonar echo intensity. A custom Jet color bar is generated based on the characteristics of the forward-looking sonar image, achieving pixel-level adaptive color mapping. This method significantly increases the visualization quality and target identification of sonar images, improving the operator's perception and judgment of underwater targets. It overcomes the detail loss problem caused by existing technologies using only fixed pseudo-color mapping, has broad application prospects, and requires only software implementation, possessing good compatibility and promotional value.

This invention discloses an intelligent echo recognition method and system, belonging to the field of industrial process automation technology, including the following steps: Step 1: Convert microwave echo signals or ultrasonic echo signals into a raw digital signal array S[size]; Step 2: Generate a dynamic threshold curve T[D] based on the raw digital signal array S[size]; Step 3: Perform threshold judgment on the raw digital signal array S[size] according to the dynamic threshold curve T[D], and select N valid echoes; Step 4: Traverse the N valid echoes, and for the j-th valid echo (1≤j≤N), extract the peak value feature, area feature, position feature, and width feature of each valid echo from the two-dimensional array Echo[j][k]; Step 5: Select the target algorithm according to the requirements of the measurement application scenario. This invention is perfectly adapted to scenarios with large fluctuations in the echo intensity of solid / liquid materials, effectively distinguishing between real echoes and environmental noise.

The application relates to the field of radar technology and particularly discloses a Beidou positioning and radar cooperative low-altitude target detection method, which comprises the following steps: obtaining Beidou ephemeris data to solve a Beidou receiver position sequence, and establishing a time corresponding relationship by using radar pulse emission and the arrival time recorded by the Beidou receiver to obtain a continuous deviation trajectory of a radar local clock relative to Beidou time. Under a unified time reference, echo candidate points are extracted from radar echo signals to form echo trajectories, a propagation time sequence is obtained from the trajectories that pass the stability verification, target direction information is inversed by combining the beam pointing angles and echo intensity distribution recorded in the radar scanning process, the target distance is obtained according to the propagation time, the position of the target in a radar coordinate system is determined together with the direction information, the target space position is obtained by combining the Beidou receiver position sequence, and stable detection of the low-altitude target is realized.

This invention belongs to the field of pipeline non-destructive testing and image processing technology, and relates to a method for three-dimensional reconstruction and sedimentation morphology analysis of pipelines using multi-beam sonar. The method performs polar coordinate transformation and intensity annotation on frame-by-frame sonar echo data to generate cross-sectional point clouds; performs rigid registration on adjacent frames and generates confidence metrics based on the median and interquartile range of the residuals; searches for temporally non-adjacent but spatially similar frame pairs to establish loop closure constraints; constructs a pose graph with the poses of each frame as nodes and registration and loop closure constraints as edges, and uses confidence-weighted global optimization to eliminate cumulative drift; and separates the pipe wall and sedimentation surface based on nominal cross-sectional geometric priors combined with echo intensity features and calculates sedimentation morphology parameters. This invention effectively eliminates the global geometric drift caused by the unidirectional accumulation of frame-by-frame registration errors in long-distance pipeline inspection, ensuring the consistency of the elevation benchmark and the reliability of the quantitative analysis of sedimentation morphology.