17 results about "Weighted least squares estimation" patented technology

The invention discloses an InSAR (Interferometric Synthetic Aperture Radar) and GNSS (Global Navigation Satellite System) robust adaptive fusion method for high-precision three-dimensional surface deformation monitoring, which belongs to the technical field of space geodetic survey and remote sensing, and comprises the following steps of: constructing a time sequence deformation field based on a small baseline set time sequence InSAR processing technology, and resampling GNSS observation data to a grid consistent with the InSAR by using Kriging spatial interpolation; a Helmert variance component estimation method is adopted to adaptively estimate variance components of InSAR and GNSS data, and reasonable weight fixing of a multi-source observation value is achieved; iterative reweighted least square estimation is introduced, outlier influences in various observation data are dynamically restrained through a Tukey double-weight function, robust optimization of a fusion model is achieved, and therefore a high-precision three-dimensional deformation field is reconstructed. The method comprises the steps of Helmert weight fixing, IRLS robust, variance component updating and a closed-loop feedback mechanism of weight matrix optimization.

The invention discloses a method for realizing fine terrain analysis through image fusion by integrating multivariate surveying and mapping data, and relates to the technical field of remote sensing surveying and mapping data processing and image fusion of terrain analysis, and the method comprises the steps: generating grid elevation, ground point density and visual angle information based on a point cloud, constructing a risk index, and extracting a residual error; residual errors are calculated in a track transverse window and are related to view angle cosine, and a strip-shaped error mask is generated; estimating a deviation field through weighted least squares based on observation fitting and smoothing along an air route, correcting the earth surface and obtaining a pixel-level weight; the correction result and the exogenous elevation are fused according to the weight, and the fused elevation, the gradient, the curvature and other indexes are output. The method can improve the precision and reliability of the terrain index under the complex earth surface.

The invention relates to a robust elliptical target positioning method and device, communication equipment and a storage medium, and the method comprises the steps: taking a to-be-detected target under target pulse noise as a positioning object, and carrying out the positioning of a to-be-detected target according to a minimum deviation criterion, a pseudo-linear technology, multistage weighted least square estimation, and a bistatic distance measurement equation of a distributed multiple-input-multiple-output radar positioning system; respectively constructing an iterative reweighted pseudo-linear least square estimator and a two-stage iterative reweighted least square estimator; and carrying out positioning processing on a to-be-detected target according to the iterative reweighted pseudo-linear least square estimator and the two-stage iterative reweighted least square estimator to obtain a target position estimation result. According to the invention, through cascading the iterative reweighted pseudo-linear least square estimator and the two-stage iterative reweighted least square estimator, approximately unbiased target position estimation can be derived, and the positioning precision of a to-be-detected target is effectively improved.

The invention discloses an amplitude-phase error self-correction method based on a uniform linear array signal covariance matrix, and relates to the technical field of array signal processing, and the method comprises the steps: obtaining a linear equation set related to an amplitude-phase error according to a received signal of a sensor array, the received signal being a signal considering the internal noise of a receiver; calculating according to the estimated covariance matrix of the received signal to obtain statistical characteristics of noise errors; constructing boundary conditions according to the phase prior information; according to the system of linear equations and the statistical characteristics and boundary conditions of noise errors, constructing a weighted least square estimation problem which contains equality constraints and is related to amplitude-phase errors; and solving a weighted least square estimation problem to obtain an estimated value of the amplitude-phase error, and correcting the received signal by using the estimated value of the amplitude-phase error. According to the method, a more generalized signal model containing internal noise is considered, a high-precision amplitude-phase error correction algorithm with lower calculation cost is constructed, and compared with an existing algorithm, the method is more in line with the actual situation.

The invention provides a distributed electric power data acquisition method, medium and system, and belongs to the technical field of electric variable distributed measurement, and the method comprises the steps: firstly, building a topological graph of a to-be-measured electric power system, and obtaining the voltage, current, frequency, three-phase balance degree and other data collected by each node electric power data acquisition terminal in real time; secondly, establishing data relation equations among the nodes based on the topological graph, and fitting the equations by utilizing historical data; thirdly, constructing a node incidence matrix and a node state estimation matrix, including indexes such as voltage, phase angle, frequency, three-phase unbalance degree and the like; and integrating the matrixes into a weighted least square estimation model, and carrying out optimization processing on power data acquired in real time to obtain corrected power data. And finally, updating a state estimation matrix according to the corrected power data, and storing a distributed power acquisition result. According to the invention, the problem of high quality uncertainty of electric power data acquired in the prior art is solved.

The invention provides a relaxation-regularization-based power network multi-error parameter identification method and device, and the method comprises the steps: building a multi-measurement section considering error parameter number constraint and a mixed integer nonlinear programming model of regularization weighted least square estimation based on a state estimation model of weighted least square of a power system; converting the mixed integer nonlinear programming model on the basis of a residual equation, so that the quantity of variables is reduced and cannot be increased along with the increase of the quantity of measurement sections, solving the converted model by utilizing IPOPT, sorting continuous variables si of all parameters in a descending order after solving, selecting the first k parameters as suspicious parameters, and calculating the number of the suspicious parameters; checking each suspicious parameter one by one, and identifying wrong parameters by using a state augmentation method; according to the invention, a plurality of coupling error parameters can be correctly identified at the same time.

The invention discloses a robot high-sensitivity collision detection method based on a base six-dimensional force sensor. The robot high-sensitivity collision detection method comprises the steps that 1, a robot linearization dynamic model based on base six-dimensional force is constructed; 2, designing a minimum inertia parameter set and a regression matrix of the robot kinetic model; 3, designing a robot periodic excitation track based on regression matrix condition number weighted optimization, and collecting joint motion data and base six-dimensional force sensor data; 4, designing a weighted least square estimation algorithm of kinetic parameters based on measurement noise distribution, identifying the kinetic parameters and obtaining a kinetic identification model; and 5, calculating a base reaction force through a dynamic identification model, comparing the base reaction force with an actual measurement value to obtain an external acting force estimation value, and realizing real-time detection of robot collision by judging whether the estimation value exceeds a safety threshold value or not. The system can realize real-time detection of collision of any part of the whole body of the robot, and has the advantages of high sensitivity and high reliability.

This invention discloses a PID control method and related apparatus based on topology data analysis, belonging to the field of PID control technology. The method includes: mapping the time series of feedback signals representing the output state of the controlled object in a closed-loop control system into a two-dimensional point cloud; extracting the topological complexity features of the point cloud; generating fitting weights for each point cloud data point; constructing a weighted least squares estimator to extract the differential estimate of the two-dimensional point cloud; and replacing the differential term in the traditional PID controller with the differential estimate. Through point cloud mapping and weighted fitting, noise points can be suppressed, high-frequency noise amplification can be avoided, and inherent signal jitter can be suppressed. Dynamically adjusting the weights using topological features overcomes the defect that fixed differential gain cannot respond to signal changes. The adaptive weight adjustment mechanism of this invention can balance noise suppression and response speed without relying on a large fixed smoothing window, thus avoiding the introduction of large phase lag.

This invention discloses a data processing method and system for time-series synthetic aperture radar interferometry (InSAR), comprising: performing differential interferometry processing on N SAR images to obtain M interferograms and P highly coherent points; correcting the terrain residual phase, orbital error, and vertical atmospheric phase at the highly coherent points using a function model; and re-establishing a function model between the corrected phase and surface deformation. The core innovation lies in the fact that this invention deeply considers and establishes the variance and covariance matrices of turbulent atmospheric noise and decoherent noise in the spatiotemporal domain, thereby constructing a stochastic model that accurately characterizes the spatiotemporal correlation of noise. Based on this stochastic model, weighted least squares estimation is used to inversely derive the time-series surface deformation results and their uncertainties. This invention aims to improve the accuracy and reliability of time-series InSAR deformation monitoring by refining the modeling of the noise characteristics of the interferometric phase.

This invention proposes a multi-station passive sensor target localization method based on angle measurement. The steps are as follows: constructing a target localization scenario based on angle measurement; an information acquisition module collects angle information and sensor position observation information; an information processing module constructs a pseudo-linear observation matrix and a pseudo-linear measurement vector; obtaining the least squares estimate of the target position coordinates; calculating the total measurement variance of the azimuth and elevation angles; calculating the weight matrix; calculating the weighted least squares estimate of the target position coordinates; and performing deviation compensation on the weighted least squares estimate. This invention effectively improves the target localization accuracy by compensating for the deviation of the weighted least squares estimate of the target position coordinates. Furthermore, when using weighted least squares to estimate the target position coordinates, it considers both angle measurement errors and the sensor's own localization errors, further enhancing the target localization accuracy.

The application discloses a power grid monitoring and risk early warning method and system based on digital twinning and AI, which comprises the following steps: comparing, under the same time slice, the synchronous acquisition data with the nodal and branch flow calculation results and reference quantities of the digital twinning power grid model, and generating a residual vector; constructing an influence relationship matrix based on the power flow Jacobian matrix, the branch power balance relationship and the upstream and downstream power conservation relationship; solving each cause group disturbance variable by using weighted least squares estimation and sparse group constraint, and determining the confidence; correcting the digital twinning power grid model according to the confidence, updating the data reliability and labeling the historical acquisition samples; training the load prediction model based on the labeled samples, generating representative working conditions, performing power flow calculation, counting the out-of-limit conditions and obtaining the risk ranking. The application can improve the accuracy of power grid anomaly attribution, load prediction and risk early warning.

The present invention discloses a target positioning method based on multi-point ranging data from an unmanned aerial vehicle (UAV), with the purpose of improving the positioning accuracy of the UAV positioning method. The technical solution is to construct a target positioning system consisting of a data acquisition module, a coarse position estimation module, and a fine position estimation module. The data acquisition module constructs a data set (Data) based on the data acquisition accuracy specified in the UAV user manual and data collected by the UAV laser payload and the UAV navigation system. The coarse position estimation module reads Data and uses an optimal linear unbiased estimation method to obtain a first estimate #imgabs0# containing the target position and a weighted least squares estimation method to obtain a second estimate #imgabs1# containing the target position. The fine position estimation module constructs a parameter β to be estimated based on the relationship between the elements within #imgabs2# and uses a weighted least squares estimation method to accurately locate the target. The present invention can obtain high-precision target positioning results and a high-precision three-dimensional position of the target.

The invention discloses a double-layer network atmospheric phase error correction and height estimation method based on an optimized reference network. The method comprises the following steps: acquiring data of a plurality of preprocessed two-dimensional single-view complex images; sPS candidate points are extracted, an initial Delaunay reference network is constructed, correction of atmospheric phase errors is realized by using the constructed and connected phase difference signals, minimum spanning tree optimization is carried out based on the residual energy ratio of each side, and a final reference network is generated; performing height estimation on the SPS point in the final reference network relative to a certain reference SPS point by adopting weighted least square estimation; pS candidate points are extracted to be connected with adjacent SPS points in the reference network, a star network is generated, and height estimation of the PS points is completed after atmospheric phase error correction; and generating an elevation map result based on the height information of all the points acquired by the double-layer network. The atmospheric phase does not need to be separated in advance, and atmospheric phase error correction and PS point recognition can be directly achieved by performing phase difference on adjacent pixels; the three-dimensional imaging result is more accurate, and noisy points are fewer.

The invention belongs to the technical field of synthetic aperture radars, and particularly relates to a geosynchronous orbit synthetic aperture radar sea moving target RD positioning method based on time sequence information, which comprises the following steps of: firstly, establishing a radar-target motion model based on position vectors and velocity vectors of a satellite and a target; utilizing the radar-target motion model to calculate azimuth position offset caused by target motion speed; secondly, establishing a time sequence RD object image relation model according to the azimuth position offset, and obtaining a time sequence RD equation based on the relation model; and finally, aiming at the time sequence RD equation, calculating the position speed of the target by adopting weighted least square estimation.

The invention belongs to the technical field of satellite navigation and wireless positioning, and particularly discloses a combined positioning and orbit correction method and system based on Doppler observation. According to the method, the coupling model of the receiver position and the satellite orbit error is constructed, the receiver height priori constraint is introduced, the unestimated orbit error is equivalent to the measurement noise, and the weighted least square estimation model is established, so that synchronous estimation of the receiver position and the satellite orbit error is realized. The method is suitable for a scene in which an unauthorized user cannot acquire the precise ephemeris. Experimental results show that the positioning error is reduced by about 62% compared with a traditional TLE ephemeris method, the positioning error is also remarkably improved compared with an existing weighting compensation method, and the method has good practicability and popularization potential and is suitable for navigation enhancement, satellite orbit measurement, high-dynamic passive positioning and other scenes.

The present invention belongs to the field of underwater positioning technology, and discloses a semi-definite programming positioning method and system for underwater single beacon that can estimate unknown sound speed. Based on the pseudo-linear positioning equation, a constrained least squares problem is constructed, and auxiliary variables are further introduced to construct linear constraints. Based on the semi-definite relaxation principle, the optimization problem is converted into a semi-definite programming problem, and a numerical solution is performed based on the interior point method to obtain preliminary estimates of the AUV position and sound speed; the preliminary estimate error is explicitly expressed and brought back to the virtual long baseline positioning equation to obtain a weighted least squares estimate of the preliminary estimate error; the estimated error is used to correct the preliminary estimate of the semi-definite programming to obtain a more accurate estimate of the AUV position and sound speed. Compared with the single beacon positioning method that does not consider the unknown sound speed, the method of the present invention can obtain better positioning accuracy and enhance the practical application capability of the underwater single beacon positioning system.

This invention provides a distributed power data acquisition method, medium, and system, belonging to the field of distributed measurement technology of electrical variables. The method includes: First, establishing a topology diagram of the power system under test and acquiring real-time data such as voltage, current, frequency, and three-phase imbalance from power data acquisition terminals at each node. Then, establishing a set of data relationship equations between nodes based on the topology diagram and fitting these equations using historical data. Next, constructing a node correlation matrix and a node state estimation matrix, including indicators such as voltage, phase angle, frequency, and three-phase imbalance. Integrating these matrices into a weighted least squares estimation model to optimize the real-time acquired power data, obtaining corrected power data. Finally, updating the state estimation matrix based on the corrected power data and storing the distributed power acquisition results. This invention solves the problem of high uncertainty in the quality of power data acquired by existing technologies.