206 results about "Weighted least squares method" patented technology

The invention discloses a field personnel positioning method cooperating with multi-view images and spatial vectors of an unmanned aerial vehicle, and the method comprises the steps: detecting a personnel target in real time through a pre-trained lightweight model, obtaining a surrounding radius in combination with a self-adaptive surrounding radius algorithm, and achieving the collection of a multi-view image sequence; carrying out quality quantitative analysis on the multi-view image sequence by adopting a multi-source fixed weight quality evaluation algorithm; a DBOF coordinate system is established, and coordinate conversion is completed; extracting high-frequency matching points based on a cross-image bidirectional matching mechanism, and performing composite distortion correction on the high-frequency matching points; carrying out weighted least square method solution on the multi-view observation equation set to generate a three-dimensional space coordinate of the target point in a DBOF coordinate system; and introducing a robust iterative optimization strategy to eliminate abnormal values, and outputting geographic coordinates. On the basis of low-cost monocular vision, the real-time performance and robustness of personnel positioning in a complex field environment are improved through a dynamic surround sampling and geometric resolving mechanism, and spatial data support is provided for field rescue.

The invention discloses a mining equipment positioning system and method based on radar, ultra wide band and inertial navigation, and the system is characterized in that a multi-source sensor unit, a data synchronization and collection module and a preprocessing module are connected in sequence, and a state fusion module is connected with the preprocessing module, a UWB ranging error compensation module, a radar motion estimation module and a pose output module; the upper computer is connected with the pose output module; the method comprises the steps of collecting multi-source data; timestamp alignment and format conversion processing are carried out, and feature and speed constraint information extraction is carried out on the point cloud data; fitting correction is carried out on the ranging data by adopting a weighted least square method, and position information is obtained through an error weighted average algorithm; feature matching is carried out, and in combination with a KISS-ICP point cloud registration method, a speed estimation result is obtained; carrying out data fusion, and obtaining a pose estimation result by adopting an extended Kalman filtering algorithm; and outputting equipment position and attitude information. According to the invention, high-precision real-time estimation of the attitude and position information of the mining equipment can be realized.

The invention provides a multipath fusion phased array radar antenna unit coordinate determination method and system, and the method comprises the steps: obtaining an antenna array surface power distribution diagram, recognizing the boundary and geometric center of an array, and planning a spiral and cross-shaped composite sampling path; on the planned sampling path, collecting phase data at a plurality of inclination angles and frequencies; based on the signal-to-noise ratio and the angle correction factor, carrying out adaptive weighted fusion calculation on the adjacent point phase difference under multiple conditions; establishing an overdetermined equation set by using the fused phase difference, and iteratively solving the accurate coordinates of the antenna unit through two rounds of weighted least squares; and establishing a drift model to perform dynamic compensation, and performing real-time calibration by using a unit with determined coordinates as a reference point. According to the invention, through a multi-angle and multi-frequency redundancy measurement strategy and in combination with a signal-to-noise ratio-based adaptive weighting algorithm, environmental interference can be effectively identified and suppressed. Even in a complex electromagnetic environment, the system can still keep stable measurement precision.

The invention discloses a multi-source fusion positioning method, positioning system and equipment for resisting non-line-of-sight interference. The method comprises the following steps: S1, acquiring RSS (Received Signal Strength), TDOA (Time Difference Of Arrival) and AOA (Attention Of Arrival) of N base stations; s2, selecting a base station with the strongest signal as an initial reference station according to the RSS mean value, and generating all base station combinations containing the reference station; s3, constructing a joint positioning equation for each base station combination, and carrying out initial position calculation on each combination by adopting a weighted least square method to obtain an intermediate position estimated value and a corresponding residual error; s4, identifying the NLOS base station by using sliding window-based multi-feature residual dynamic threshold judgment and effective combination-based NLOS weight penalty verification respectively; and S5, calculating the base station combination according to the residual error and the geometric precision factor to obtain high-precision position estimation. According to the method, unreliable NLOS base station signals can be intelligently identified in a complex electromagnetic environment, the weights of the unreliable NLOS base station signals are reduced, and finally more accurate target position estimation is fused.

The invention provides a high-precision real-time multi-channel cooperative control method and system. The method comprises the following steps: establishing a conversion relation among a geodetic coordinate system, a geocentric coordinate system and a station center coordinate system; each device solves the observation data of the target into the global ECEF coordinate of the target through the conversion relation according to the geographic coordinate of the device; fusion of observation data of multiple cameras (integrated in a turntable cabin) is realized by adopting an iterative weighted least square method, and the optimal estimation of the initial position of a target is obtained; and taking the fused position as an observed quantity, inputting the observed quantity into a Kalman filter constructed based on a uniform-speed motion model, dynamically adjusting an observation noise covariance and a process noise covariance, and predicting and tracking a target motion state, thereby realizing multi-camera cooperative control.

The invention discloses a satellite time-varying gravity field inversion method based on adaptive de-mixing, and belongs to the technical field of satellite gravity measurement. Constructing a normal equation; accumulating the normal equations and solving parameter initial values through a weighted least square method; calculating a post-test residual error of the observation value and recovering a pre-elimination parameter; applying zero mean constraint to the daily time-varying gravity field parameters; establishing an autoregressive model to describe time correlation of the day solution sequence, applying autoregressive model constraint, updating a normal equation and jointly solving a time-varying gravity field model; outputting a daily time-varying gravity field model and a monthly time-varying gravity field model according to a parameter estimation result; evaluating the time-varying gravity field model through spectral domain analysis; according to the satellite time-varying gravity field inversion method based on self-adaptive de-mixing, self-adaptive de-mixing errors can be achieved, the stability and precision of time-varying gravity field inversion are improved, and the influence of background model mixing errors in satellite time-varying gravity field inversion is effectively weakened.

The invention belongs to the technical field of image processing, and particularly relates to a PCB plug hole flatness detection method and system based on 3D point cloud data, and the method comprises the steps: obtaining the original 3D point cloud data of a PCB, and intercepting a plug hole center and a local point cloud block according to a design file; a copper ring point cloud set is extracted, and the fitting weight of each sampling point is calculated based on the distance from each sampling point in the set to the center of the plug hole, the unit normal vector of the sampling point and the original height of the sampling point; performing weighted least square fitting on all the copper ring point clouds by using the fitting weight to obtain a virtual reference curved surface; extracting an effective point cloud set, calculating the correction height of the effective point cloud, and calculating a flatness index in combination with the mean value of the correction height and the module length of the local gradient; the flatness index of the physical space is obtained, and whether the flatness of the plug hole is qualified or not is judged. According to the method, the problem of misjudgment caused by board warping is effectively solved, and the detection precision and the anti-noise capability are improved.

The invention discloses an underwater target positioning method based on data-model dual drive. The method specifically comprises the following steps: data acquisition: acquiring initial data by using a receiver; performing sight distance reasoning: constructing and training a sight distance information reasoning neural network based on data driving, preprocessing the collected initial data, inputting the preprocessed data into the neural network, and outputting arrival time estimation of a sight distance path; joint estimation: adopting a model driving method, calculating the arrival time difference of sound signals received by a receiver by using the obtained sight distance arrival time, designing underwater target position and signal propagation speed joint estimation based on the arrival time difference, and calculating initial estimation values of the target position and the propagation speed by using a weighted least square method; and robust iteration: based on a maximum likelihood estimation function, performing robust iteration optimization on the obtained preliminary estimation value to obtain a stable and convergent final joint estimation result. The target positioning method is convenient to popularize and apply in different underwater environments, and has relatively high adaptability and expansibility.

The invention belongs to the technical field of three-dimensional surface reconstruction, and particularly relates to a robust three-dimensional surface reconstruction method based on multi-scale fusion. Acquiring three-dimensional point cloud data, fitting local implicit curved surfaces of neighborhood points by adopting a weighted least square method, and generating a geometric reconstruction grid model; extracting geometric features in different receptive fields through multi-scale convolution, introducing channel attention, space attention and a gating mechanism to perform weighted fusion on the geometric features in different receptive fields, enhancing a global dependency relationship by adopting a feature mixing operation, and generating a deep learning grid model; performing double-branch fusion on the geometric reconstruction grid model and the deep learning grid model, highlighting a geometric sensitive area, and obtaining a fused enhanced feature; inputting the fused enhanced features into an implicit function decoder, and predicting a signed distance function value of each vertex; and based on the predicted signed distance function field, a contour surface extraction algorithm is adopted to generate a triangular mesh model, so that three-dimensional surface reconstruction is completed.

The invention discloses a ship water gauge scale line fitting algorithm, and relates to the technical field of ship water gauge scale calculation, and the method comprises the steps: obtaining a ship water gauge region image through an image collection device to extract a measurement point coordinate, and building a mapping relation between a pixel position and a physical draft; a weighted least square method is adopted to perform nonlinear curve fitting, a weight coefficient is calculated based on a local neighborhood standard deviation, a polynomial order p is dynamically adjusted according to an adjusted decision coefficient, and the decision coefficient is iteratively optimized to improve the balance between amplitude and model complexity. And the system repeatedly corrects model parameters through a dynamic verification mechanism of the residual sum of squares and a preset threshold value, and finally an accurate water gauge scale fitting curve is generated. The method effectively solves the problems that traditional manual observation is prone to environmental interference and large in measurement error, high robustness is kept in a complex water area environment, and reliable data support can be provided for the fields of ship load evaluation, channel safety management and the like.

The invention discloses a power grid power flow real-time calculation and state estimation method and system based on a PMU, and belongs to the technical field of electric measurement and electric fault positioning. The method comprises the following steps: synchronously measuring electrical variables, including a voltage phasor and a current phasor, of a power grid node through PMU equipment to obtain synchronous phasor data, and verifying time and topology consistency; the power grid observability grade is judged based on PMU configuration node distribution corresponding to the verified electric measurement data; directly generating a real-time state estimation result through linear calculation based on PMU electric measurement data if the whole domain is observable; and if a part is observable, fusing PMU and SCADA data, carrying out nonlinear state estimation through a weighted least square method, distributing a high weight for the PMU electrical measurement data, and dynamically adjusting the SCADA weight to suppress bad data. According to the method, through observability adaptive judgment, the precision and efficiency of state estimation are improved, a data basis is provided for power grid fault positioning, and the method is suitable for practical application scenes of various PMU coverage degrees.

The invention relates to the technical field of satellite navigation and wireless communication, and discloses an indoor positioning method and system based on feeder multiplexing Beidou double-frequency, and the method comprises the steps: receiving outdoor B1I and B2a signals through a high-gain Beidou double-frequency receiving antenna, carrying out the frequency separation and signal conditioning through a double-frequency separation filter, and carrying out the positioning of the B1I and B2a signals; and transmitting the B1I signal to an indoor distributed antenna for broadcasting through the existing communication feeder network, and transmitting the B2a signal to a central directional antenna to establish a time synchronization reference. A mobile terminal receives a dual-frequency signal, capturing and tracking are carried out through digital signal processing, and pseudo-range and carrier phase observation values are extracted. And performing pairing processing on observation data of the same antenna, calculating a dual-frequency pseudo-range difference value, eliminating system errors, and performing position calculation by adopting a weighted least square method and Kalman filtering. The method solves the problem that the traditional GPS signal cannot cover the indoor environment, and has a good application prospect in the scenes of underground commercial complexes, tunnels, parking lots and the like.

The invention discloses an active and passive fusion water depth inversion method based on adaptive spectrum weighting, and the method comprises the steps: carrying out the atmospheric correction of a multispectral satellite image, extracting a target region, and removing a land region and a deepwater region; the method comprises the following steps: acquiring a seawater point cloud of a satellite-borne photon counting laser radar in a target area, extracting sea surface and seabed information, and performing refractive index correction and tide correction to obtain a reference water depth; matching each pixel in the multispectral satellite image with a reference water depth, and dividing the multispectral satellite image into a reference pixel and a to-be-measured pixel; according to the spectral value of the multispectral satellite image, the Euclidean distance between each to-be-measured pixel and all reference pixels is calculated, and the reciprocal of the distance is used as the weight of each reference pixel; and introducing a weight-to-weighted least square method, and fitting a relationship from the spectral value to the water depth for each pixel to be measured to realize water depth inversion of the pixels to be measured. The method can effectively improve the active and passive fusion water depth inversion precision when the water depth distribution is uneven and the shallow sea area environment is complex.

The present application belongs to the technical field of vehicle mass online estimation, in particular to a vehicle mass online estimation method based on fuzzy logic and weighted least square method, comprising the following steps: 1) obtaining longitudinal acceleration sensor measurement value signal, longitudinal speed signal, engine output torque signal, gear signal, throttle opening signal, brake pedal signal and steering wheel angle signal from vehicle CAN bus; 2) correcting the measurement value of longitudinal acceleration sensor; 3) calculating equivalent driving force and equivalent acceleration; 4) calculating working condition fitness degree by using fuzzy logic algorithm; 5) estimating vehicle mass by using weighted least square method; and 6) suspending and starting vehicle mass estimation. The structure is reasonable, and the accuracy and working condition adaptability of vehicle mass online estimation can be improved during use.

The invention relates to the technical field of image processing, and discloses a laser wavefront distortion correction system and method based on adaptive optics, and the system comprises a first module which is used for calculating a noise covariance matrix and an interaction matrix; the second module is used for solving a control matrix and a phase reconstruction matrix; the third module is used for calculating to obtain a current slope vector; the fourth module is used for updating a deformable mirror command; the fifth module is used for calculating to obtain a point spread function; and the sixth module is used for calculating an image quality index and outputting a correction result. According to the method, a noise covariance matrix and an interaction matrix are accurately constructed under reference light, and a weighted least square method with double regularization is combined, so that the influence of measurement noise is effectively inhibited, the stroke constraint of an actuator is balanced, and the robustness of a correction model is greatly improved; by means of combination of integral control, leakage processing and amplitude limiting design, saturation of an actuator due to command accumulation is avoided, and correction error superposition is prevented.

The invention relates to a water supply network multi-leakage node positioning method based on hydraulic model and WLS-GA fusion, and belongs to the technical field of water supply network leakage detection. According to the technical scheme, the method comprises the steps that firstly, a weighted least square method WLS is adopted to conduct single-leakage-point leakage amount estimation on all nodes of a pipe network, candidate leakage points with the high leakage possibility are screened out based on residual errors and a sensitivity matrix, then the candidate leakage points are combined, finally, an optimized combined solution serves as an initial population, and the leakage amount of all the nodes of the pipe network is estimated. The improved genetic algorithm GA is adopted to carry out multi-leakage-point accurate positioning, and the final multi-leakage-point position and leakage amount are determined through adaptive crossover probability and elitist retention strategy iterative optimization. The method has the beneficial effects that the search space of the genetic algorithm is reduced through weighted least square method pre-screening, the calculation efficiency is improved, the algorithm is prevented from falling into local optimum by improving iterative optimization of the adaptive cross strategy and the elitist retention strategy, and the convergence speed of the genetic algorithm is improved.

The invention belongs to the technical field of coal quality detection, and particularly relates to a method for rapidly predicting coal quality parameters based on Raman spectrum in combination with machine learning. According to the method, a Raman spectrum technology and machine learning are combined, a Raman spectrum systematic preprocessing process is adopted, an adaptive iteration reweighted least square method Air-PLS is applied, spectral signals and baseline drift are accurately separated, Savitzky-Golay filtering is applied, peak shape features are reserved, random noise is effectively suppressed, and the method is suitable for large-scale popularization and application. Maximum-minimum normalization or Z-score standardization processing is provided, and the intensity difference between samples is eliminated; moreover, a data-driven Raman spectrum intelligent feature screening mechanism is introduced, and an optimal feature wavelength subset which is highly related to coal quality parameters and low in redundancy is screened out through automatic iteration; according to the method, the data quality in Raman spectrum coal quality detection is improved, the feature correlation is enhanced while the feature dimension is reduced, the model precision and generalization ability are improved, and rapid, lossless, high-precision and high-robustness coal quality parameter prediction is realized.

The invention relates to a fault positioning method and system for a multi-terminal hybrid DC power transmission system, and the method comprises the steps: calibrating a fault moment, and improving a Bergeron model; intercepting a theoretical current traveling wave of a preset time window; performing waveform processing on the intercepted theoretical current traveling wave at low, medium and high frequencies by adopting a time redistribution multi-synchronous compression transformation method based on wavelet transformation, and performing waveform correction in combination with a random forest to obtain a reconstructed current traveling wave; performing weighted least square fitting on the reconstructed current traveling wave to obtain a fitted current traveling wave; constructing a waveform reference library comprising a plurality of interval reference current traveling waves according to the fitting current traveling waves; and calculating a current traveling wave at any fault position, performing similarity calculation on the current traveling wave and the reference current traveling wave of each interval in the waveform reference library based on the arrival time and the amplitude to obtain a comprehensive similarity, and positioning a fault interval according to the comprehensive similarity.

The invention discloses a qualitative and quantitative detection method for vitamin A and vitamin E in food. The qualitative and quantitative detection method comprises the following steps: step 1, pre-treating a sample and accurately adding an isotope internal standard: adding d6-alpha-tocopheryl acetate and d8-retinol acetate into the sample before saponification and preparing a blank matrix; 2, pre-treatment parameter QbD-DOE collaborative optimization, wherein a response surface method is adopted for conducting center composite design on the saponification temperature, time and BHT concentration, and the interaction effect of all the factors is analyzed to determine an optimal operation window; step 3, intelligently optimizing chromatography-mass spectrometry conditions and tuning parameters; step 4, constructing a matrix matching calibration curve and performing WLS quantitative analysis: performing gradient dilution on a standard substance by utilizing a blank matrix extracting solution, adding an isotope internal standard to prepare a 5-7-point matrix matching calibration curve, fitting the curve by adopting a weighted least square method, and verifying the correlation and intercept change of the calibration curve every day; and 5, multi-dimensional qualitative confirmation and intelligent diagnosis system operation.

The invention discloses a multi-region linear fitting error compensation method and system for an air pressure sensor. The method comprises the steps that original data of the air pressure sensor are acquired and preprocessed; identifying the preprocessed data based on an inflection point detection algorithm of a second derivative, and dividing intervals according to identified inflection points; performing linear fitting in each divided interval by applying a weighted least square method, calculating fitting parameters and goodness of fit of each interval, removing abnormal points in the interval, and performing fitting again; judging whether the adjacent intervals meet a merging condition or not, and performing merging and fitting optimization on the adjacent intervals meeting the condition; generating a calibration parameter table, outputting an SVG fitting curve graph according to the calibration parameter table, and correcting an error of a measured value of the air pressure sensor; by analyzing distribution characteristics of error data, intervals with similar error characteristics are divided in a self-adaptive mode, a linear fitting model is independently constructed for each interval, and averaging errors of a single model on a non-linear area are avoided.

The invention provides flexible device alignment detection equipment and a detection method thereof. The flexible device alignment detection equipment comprises a jig platform, a shaping mechanism, a main detection module and a control module. The bearing plane of the jig platform is provided with a positioning reference edge to establish a workpiece coordinate system; the main detection module obtains an unshaped first state reference image and a shaped second state reference image. The control module matches the two-state reference features under a workpiece coordinate system, obtains feature coordinates and solves initial plane rigid body transformation parameters; inversely mapping the second state feature coordinates to the first state to obtain a residual deformation quantity vector, and reconstructing a residual deformation field; and determining and normalizing an adaptive weight coefficient according to the residual modulus value, and solving by adopting weighted least squares to obtain a global alignment deviation of a shaping state relative to a workpiece coordinate system. The equipment can improve the robustness and stability of alignment calculation when in-plane deformation exists.

The invention discloses an intelligent automobile sensor data correction method and system based on safety monitoring, and relates to the technical field of intelligent driving environment perception, and the method comprises the steps: carrying out the grading of safety feature codes based on a safety rule library, carrying out the mode matching through combining with a historical fault case library, and generating an abnormality diagnosis report of original monitoring data; a physical topology network of the intelligent automobile sensor is constructed, the node state of the physical topology network is dynamically adjusted according to the abnormity diagnosis report, and a physical topology network reconstruction instruction is obtained and executed; and correcting the original monitoring data twice based on the node state of the reconstructed physical topology network to generate vehicle safety monitoring data. According to the method, the weighted residual correction is combined with the iterative reweighted least square method, two-stage correction is performed on the monitoring data on the basis of the reconstructed node weight distribution table, progressive error compensation under the condition of dynamic performance degradation of the sensor network is realized, and the reliability and environmental adaptability of output data are improved.

The invention discloses a freight spaceship reentry recovery attitude cooperative control method. The method comprises the following steps: S1, determining key attitude indexes in a freight spaceship reentry recovery process; s2, collecting atmospheric environment parameters in a reentry process, and meanwhile, obtaining earth gravitational field distribution data to provide environment input for a subsequent attitude control algorithm; s3, based on the Newton's second law and the Euler equation, establishing a kinetic model of the freight spaceship, establishing an attitude kinematics model by adopting a quaternion method or an Euler angle method, and establishing an execution mechanism model for a propulsion system of the freight spaceship; through sub-filter local estimation and main filter global weighting, noise and abnormal values are effectively filtered, attitude estimation precision is improved, instruction distribution adopts a pseudo-inverse method in combination with a weighted least square method, an initial instruction is obtained through the pseudo-inverse method, then secondary optimization is performed in combination with execution mechanism constraints, instruction oversaturation is avoided, and attitude estimation accuracy is improved. Extra redundant execution mechanisms are not needed, and the hardware cost is reduced.

The application discloses a time difference positioning method based on random robust least square, mainly solves the threshold effect of the existing time difference positioning method when the measurement error increases, and leads to the problem of sharp deterioration of positioning accuracy, and the implementation scheme is as follows: a plurality of observation stations and noise measurement errors are set, the time difference positioning equation is obtained by using the position parameters and the measurement errors, an auxiliary variable is defined, the auxiliary variable is introduced into the time difference positioning equation to establish a constraint equation, the constraint equation is processed by using a random robust least square method to obtain a cost function, the cost function is solved by using a least square method to obtain a target position, a new constraint equation is established according to the internal relation of the auxiliary variable elements, the new constraint equation is solved by using a weighted least square method to obtain a positioning error, the target position is linearly corrected by using the positioning error to obtain a final positioning result, and the target positioning is completed. The application reduces the positioning error, improves the positioning accuracy and the robustness of positioning, and can be used in aerospace, navigation and electronic warfare.

The application discloses a macro modeling method for ensuring direct current precision, and the method comprises the following steps: reading n-port network parameters; initializing sampling points for constructing a macro model; initializing the order of the macro model; initializing the pole of the macro model; establishing a weighted linear system according to the current order, the sampling points and the pole; solving a linear equation set, judging convergence according to an error, and obtaining the macro model; and outputting the optimized macro model by applying a residue matrix disturbance to optimize the macro model. The macro modeling method for ensuring direct current precision provided by the application controls the direct current precision in two stages. In the first stage, a weighted least square method is adopted on the basis of a linear system established by a traditional vector fitting algorithm to preliminarily control the direct current precision. In the second stage, a small disturbance is applied to the residue matrix of the macro model, so that the disturbed macro model has accurate direct current characteristics.

The invention relates to an electric explosion-proof safety assessment method for an explosion dangerous area. The method belongs to the technical field of electrical explosion-proof safety evaluation. The method comprises the following steps: (1) constructing an electrical explosion-proof safety evaluation index system; (2) calculating a weight by an analytic hierarchy process; (3) calculating a weight by an entropy method; (4) calculating a weight through a Bayesian network; and (5) index weight integration: obtaining corresponding weight vectors through three methods of AHP, EWM and BN, and integrating the weight vectors by using a least square method, so that the Euclidean distance quadratic sum of the vector and the three given directional vectors is minimum. According to the method, the analytic hierarchy process is combined with the advantages of objective weighting of historical data, Bayesian network information fusion and dynamic calculation based on expert experience and the entropy method, the weighted least square method is adopted to comprehensively calculate the index weights of the three methods, and finally the weights obtained by the three methods and the comprehensive evaluation method are compared and analyzed. Through example application verification, the method has high practicability and credibility, and subjective and objective comprehensive evaluation of the electrical explosion-proof safety level of the explosion dangerous area is achieved.

The present application relates to the technical field of ultra-short baseline direction measurement data processing, and particularly relates to a direction estimation method of a multi-element stereo hydrophone array. The method approximates sound waves as plane waves and establishes a mathematical relationship between time difference of arrival (TDOA) and a direction vector, takes TDOA as an observation value, calculates a direction vector estimation value according to a weighted least square method, then calculates the equivalent weight of the observation value according to an equivalent weight function, further replaces the original observation value weight array with an equivalent weight array, and recalculates the direction vector according to the weighted least square method, iteratively calculates the equivalent weight and the direction vector, until the difference between the direction vectors of two consecutive times is less than a manually set threshold, and the direction vector is output as the direction of the multi-element stereo hydrophone array. The present application can weaken the influence of the sound ray bending which is not considered in the direction estimation function model, and consider the influence of the array element spacing and the target direction on the direction estimation, thereby improving the accuracy and reliability of the direction estimation of the multi-element stereo hydrophone array.

The invention discloses a positioning error compensation method and device for a UWB single base station positioning system, and relates to the technical field of wireless positioning, and the method comprises the steps: taking a single base station as a center, determining an equilateral triangle according to the wavelength of a UWB signal, and setting a UWB antenna at each vertex of the equilateral triangle, so as to form an equilateral triangle array antenna; calculating the arrival angles of the received signals by different UWB antennas by using the phase differences of the UWB signals arriving at the UWB antennas through a signal processing algorithm and combining the geometrical relationship of the equilateral triangle array antennas; constructing an equation set in combination with triangular constraint conditions; solving the equation set by using a weighted least square method to obtain initial position information of the positioning tag; and smoothing the initial position information by using Kalman filtering to obtain the position information of the positioning tag. According to the invention, the special antenna array structure is constructed on the single base station, and the information carried by the UWB signal is fully mined by using the triangulation positioning principle, so that the positioning precision is improved.

The present application relates to a kind of based on hydraulic model and WLS-GA fusion's water supply network multi-leakage node positioning method, belong to water supply network leakage detection technical field.The technical scheme is: firstly, using weighted least squares WLS to each node of pipe network is carried out single-leakage-point leakage estimation, based on residual and sensitivity matrix, filter out the candidate leak point with higher leakage possibility, subsequently, candidate leak point is combined, finally, the optimized combination solution is used as initial population, using improved genetic algorithm GA to carry out multi-leakage-point accurate positioning, through adaptive crossover probability and elite reservation strategy iteration optimization, determine the final multi-leakage-point position and leakage quantity.The beneficial effects of the present application: weighted least squares pre-screening reduces the search space of genetic algorithm, improves the calculation efficiency, through the improved adaptive crossover strategy and elite reservation strategy iteration optimization, avoid algorithm to fall into local optimum, improve the convergence speed of genetic algorithm.

A system and method for distributed temperature and strain sensing using Chirp-Pulse Coherent Optical Time-Domain Reflectometry (CP-COTDR) utilizes optical flow processing. The method involves constructing a two-dimensional (2-D) waterfall data array from collected CP-COTDR frames. Optical flow processing is applied directly to the 2-D data to estimate the local shift of features caused by external perturbations. The optical flow is preferably calculated using a weighted least squares method with an adaptive analysis window based on the local flatness of signal derivatives. This approach provides versatile and high spatial resolution, reduces accumulative errors, and enables efficient data processing compared to conventional cross-correlation techniques.