220 results about "Geometric relations" patented technology

The invention discloses a mobile robot path planning method and system based on a circular trajectory control obstacle function, and aims to realize trajectory smooth control in an obstacle avoidance process. Firstly, an envelope circle is used for modeling an obstacle, an actual boundary is approached in a continuous and simple geometric form, and the calculation complexity of collision detection is reduced. Secondly, designing a control obstacle function based on a circular trajectory, constructing a derivable constraint in combination with a geometrical relationship between a tangent line and an obstacle boundary, and achieving trajectory smoothing, reducing speed fluctuation and prolonging the service life of an execution mechanism while guaranteeing a safe distance. For disturbance caused by factors such as ground unevenness, historical data are learned by using a Gaussian process, the disturbance trend is predicted in real time, and the motion stability is improved. And finally, through nonlinear optimization solution, generating control input with safety, continuity and disturbance adaptive capability. According to the method, geometric modeling, safety constraint, disturbance prediction and a dynamic adjustment mechanism are fused, and the safety and adaptability of robot path planning are remarkably enhanced.

The invention relates to the technical field of data processing, in particular to a high-noise data intelligent cleaning and credibility evaluation method based on uncertainty quantization, which comprises the following steps: constructing a noise manifold model of a high-dimensional data space through a Riemannian geometry method, and extracting data intrinsic structure features and noise distribution trajectory tensor; according to the noise distribution trajectory tensor, constructing an anisotropic diffusion equation, and generating confidence distribution with data manifold constraint; the geometric invariance of a data set is kept while noise stripping is carried out in a data manifold tangent space, and noise stripping and structure keeping are achieved; calculating an intrinsic credibility index and generating a credibility evaluation map coupled with the data manifold structure; according to the method, the intrinsic characteristics of the data manifold are kept in the cleaning process, the deformation degree of the quantized data structure is calculated through the geodesic deviation, and it is ensured that the intrinsic geometrical relationship of the data is not affected by noise stripping.

The invention belongs to the technical field of smart cities, and discloses a point cloud-based urban building roof wireframe reconstruction method, which comprises the following steps of: fusing a fast point feature histogram and a multi-scale roof geometric descriptor, generating robust point-by-point features, screening candidate angular point clusters in combination with a classification head, and adaptively segmenting the candidate point clusters based on density parameters by utilizing DBSCAN (Density-Based Spatial Clustering of Applications with Noise), so as to reconstruct a point cloud-based urban building roof wireframe. Initial inflection points are extracted through unsupervised clustering, noise is effectively suppressed, and irregular distribution is adapted; then multi-scale geometric information of an initial inflection point neighborhood is aggregated through an inflection point correction network, offset is learned to correct position deviation, and inflection point positioning precision is improved; and finally, the edge classification network automatically deduces the topological connection of the roof wireframe based on the geometrical relationship and feature relevance of prediction inflection points, so that error accumulation caused by dependence on manual rules in a traditional method is avoided, the generalization ability of a complex roof structure is enhanced, the correction network learns offset through a multi-scale context, and the inflection point positioning precision is remarkably improved.

The invention belongs to the technical field of artificial intelligence, and particularly relates to a complex table intelligent analysis method and system based on multi-modal fusion and semantic analysis. The method comprises the following steps: S1, performing preliminary analysis on a document based on a multi-modal fusion technology, identifying position information of a table area, a text and an image, and outputting the position information of the table area; s2, reconstructing the table structure based on the topological graph structure and the geometrical relationship of the table to obtain a reconstructed table; s3, identifying the content of the reconstructed table by utilizing machine vision, and correcting the identified content of the table and the position information of the table area in combination with semantics to obtain all the content of table analysis; and S4, outputting the analyzed table content according to a required format. According to the method, the complex table can be analyzed and corrected.

The invention discloses a dynamic object pose estimation method and system based on multi-ArUco code confidence weighting, and provides a method which does not need a fixed calibration layout, supports random placement of multiple codes, dynamically solves a geometrical relationship between an object and a calibration code, establishes a double confidence mechanism by combining image recognition quality and geometrical consistency, and can estimate the pose of a dynamic object based on multi-ArUco code confidence weighting. And by utilizing multi-frame data fusion, the dynamic target pose can be stably estimated with high precision in complex scenes such as dynamic, inclination, shielding and the like, and accurate positioning in a dynamic environment is realized. The problems that in a dynamic environment, the ArUco code is frequently shielded, the pose is unstable, and the relative relation between the ArUco code and an object is difficult to calibrate are solved.

The invention relates to the technical field of embankment inspection, and provides an embankment inspection robot environment detection method and system, which can determine a motion blur direction, extract linear features of an image and determine a linear feature direction by acquiring an embankment image and performing motion blur judgment when the image has motion blur. And on the basis, according to the geometrical relationship between the motion blur direction and the linear feature direction, whether the linear feature is the embankment crack or not is judged. By using the motion blur direction as a judgment basis, a pseudo crack and a real crack caused by motion blur can be effectively distinguished, and early-stage potential safety hazard detection omission caused by image quality reduction is avoided, so that the accuracy and the reliability of embankment crack detection are remarkably improved, and the continuity and the effectiveness of an embankment inspection task are guaranteed.

A processor-implemented method including selecting a first reference landmark from among a first plurality of candidate landmarks related to a parking area of a vehicle in a first frame image corresponding to a first timepoint, determining positioning information of the vehicle by using geometric relationship information of the selected first reference landmark with respect to the vehicle, selecting a second reference landmark from among a second plurality of candidate landmarks in a second frame image corresponding to a second timepoint, the second timepoint being temporally subsequent to the first timepoint, and updating the positioning information using the geometric relationship information of the selected second reference landmark with respect to the vehicle.

The invention provides a tunnel surrounding rock deformation rolling time sequence prediction method and system considering excavation disturbance, and the method comprises the steps: obtaining a geometrical relationship from a tunnel face to a monitoring point, an excavation area and an excavation footage in a tunnel excavation process, and calculating a construction disturbance factor according to the obtained data; constructing and training a surrounding rock deformation prediction model, wherein the surrounding rock deformation prediction model is obtained by fusing a convolutional neural network, a bidirectional long-short term memory neural network and an attention mechanism layer; acquiring tunnel surrounding rock monitoring data, and preprocessing the monitoring data; and taking the preprocessed monitoring data and the calculated construction disturbance factor as input data of the trained surrounding rock deformation prediction model to obtain a final deformation prediction result. According to the method, the dynamic disturbance characteristics of stress redistribution in the tunnel excavation process are quantified into the construction disturbance factors, the nonlinear coupling relation between surrounding rock deformation and construction disturbance is analyzed through the hybrid model, and the tunnel surrounding rock deformation prediction accuracy is improved.

The invention discloses a sparse view angle 3D-DSA reconstruction method based on a three-dimensional Poisson generative model. The method comprises the following steps: obtaining pairing data of a sparse view angle 2D-DSA projection drawing and a 3D-DSA reconstruction image; extracting features of a projection image by using a projection domain encoder, then converting features of two-dimensional projection into a three-dimensional image domain according to a geometrical relationship of the cone beam CT, and then obtaining a prior image by using an image decoder; the method comprises the following steps: constructing a three-dimensional Poisson generation model, adding noise to a three-dimensional image patch in a training stage to obtain a disturbance image, outputting a network reconstruction image by taking a prior image as a condition and the three-dimensional image patch before noise addition as a target image, and calculating loss of the output image and the target image to update network parameters; the mean square error loss and the mean square error loss of the maximum intensity projection images of the three orthogonal planes are used during loss calculation; in the sampling stage, random noise is used as input, a prior image is used as a condition, noise of a noise image is continuously denoised within a limited step length, and finally a reconstructed 3D-DSA image is obtained.

The invention discloses a road sign arrangement method based on geometric analysis, which comprises the following steps of: modeling through a CAD (Computer Aided Design) design drawing to generate a three-dimensional model, drawing signs, acquiring data, and simulating the shielding conditions of the signs at different road sections of an expressway; road geometric information, sign position information and vehicle information are extracted from the data, the sign distances are ranked from near to far, and the accumulated distance between each sign and the road starting point is calculated; calculating the sight distance range of a vehicle driver by combining the vehicle speed and the response time; establishing a shielding model, judging a shielding geometrical relationship by using a tetrahedron volumetric method, judging whether the sign is shielded by other objects or the sign in the vehicle driving process according to the shielding geometrical relationship, and evaluating the visibility of the sign; and based on the shielding analysis result, the layout of the sign is optimized, and the visibility and the use effect of the sign are improved. According to the method, the shielding condition of the sign under different vehicle heights, vehicle speeds and road environments can be accurately evaluated, and the visibility and driving safety of the sign are improved.

The invention provides a frequency dispersion curve calculation method based on a decoupling type Legendre-Gauss-Labatto spectral element method, and belongs to the technical field of discrete solution of guided wave propagation in a thin plate, and the method comprises the following steps: S1, constructing a wave equation which comprises a Cartesian space coordinate system based on an orthotropic plate, and combining a constitutive equation, a geometrical relationship under the coordinate system and guided wave displacement to obtain a wave dispersion curve; substituting into a control equation when the volume force is zero to obtain an improved three-dimensional elastic wave equation; s2, a differential matrix is constructed, wherein discretization and decoupling are carried out on a wave equation on the basis of a Lagrange interpolation basis function of a Legendre-Gauss-Labatto node; s3, explicitly embedding the stress free boundary condition into the solving process through matrix line transformation, and solving to obtain a frequency dispersion curve, the derivation process is simplified, the boundary and the interior of the material are decoupled, and the physical significance is clearer. And meanwhile, the high-precision advantage of the spectrum method is maintained, and the calculation rate is remarkably improved.

A system includes proximal and distal structures and a processor system. The processor system determines a first commanded motion of the proximal structure; determine a second commanded motion for joint(s) of the distal structure or an imaging device, wherein when the first and second commanded motions are performed in conjunction, a field of view of the imaging device is maintained relative to a workspace; and in response to determining that driving the joint(s) in accordance with the second commanded motion would cause the distal structure or the imaging device to violate a constraint: determines an alternate commanded motion for the joint(s) to maintain a defined geometric relationship between a first geometric feature fixed relative to the imaging device and a second geometric feature fixed relative to the workspace, drives the proximal structure in accordance with the first commanded motion, and drives the joint(s) in accordance with the alternate commanded motion.

The invention discloses a three-dimensional scene reconstruction method based on Gaussian splashing, and belongs to the technical field of three-dimensional scene processing, and the method comprises the following steps: S1, obtaining an initial three-dimensional scene, and generating a three-dimensional Gaussian splashing sphere according to a plurality of feature points of the initial three-dimensional scene; s2, screening a to-be-reconstructed region in the initial three-dimensional scene by using a three-dimensional Gaussian splashing sphere; and S3, smoothing the to-be-reconstructed region to complete three-dimensional scene reconstruction. According to the method, the adaptive smoothing weight is designed based on the geometrical relationship between the Gaussian sphere and the to-be-reconstructed region, the weight distributes high smoothing intensity in the flat region to suppress noise, the smoothing intensity is reduced in the feature region to retain details, efficient three-dimensional scene reconstruction is realized, and the reconstruction efficiency is improved. The method is especially suitable for fine modeling of complex dynamic scenes and low-texture areas, and an innovative technical solution is provided for the field of three-dimensional vision.

The invention relates to the technical field of numerical control systems and five-axis calibration, in particular to a five-axis RTCP parameter calibration method based on an iterative algorithm, and the method comprises the steps: (1) calibration device deployment: fixing a standard ball on a workbench, installing a displacement sensor on a flange surface of a main shaft through a tool clamp, and correcting the deviation; (2) data acquisition: a mobile sensor is tangent to a standard ball, joint coordinates and displacement are recorded, and data cover a spherical surface; (3) mathematical model establishment: deriving a sensor tail end sphere center coordinate formula based on a five-axis kinematic model (double swing heads, double rotary tables and single rotary table single swing head); (4) constructing a target optimization function: according to the tangent geometrical relationship of the two balls, establishing an optimization function taking the RTCP parameter and the center coordinate of the standard ball as variables; and (5) iterative solution: carrying out iterative calculation by adopting a differential evolution algorithm, taking an optimization function value as fitness, and outputting an RTCP parameter after a precision requirement is met. The method is easy and convenient to operate, high in precision, high in universality and suitable for RTCP parameter calibration of the low-end five-axis machine tool.

The invention discloses a point cloud-based reverse modeling curved surface generation method and system, and relates to the field of electric digital data processing, and the method comprises the steps: obtaining three-dimensional point cloud data of a to-be-processed engineering design product, and projecting the three-dimensional point cloud data to a preset cutting plane to obtain a two-dimensional projection point set; and performing dimension reduction processing on each projection point, calculating a local geometrical relationship between the projection point and a neighborhood point, and mapping the local geometrical relationship to a one-dimensional parameter space to obtain a one-dimensional parameter value. Clustering analysis is conducted on the two-dimensional projection point set based on the one-dimensional parameter values, the two-dimensional projection point set is divided into a plurality of point cloud clusters, and each point cloud cluster corresponds to one geometric feature curve. And sorting the projection points in each point cloud cluster according to a spatial position relationship to obtain an ordered point sequence. And identifying the geometric feature type of each ordered point sequence, performing curve fitting, and extracting parameter information to obtain the feature parameters of the engineering design product. And generating an accurate curved surface model according to the characteristic parameters. By implementing the method, the accuracy of point cloud clustering can be improved.

The invention provides a method and a program product for simulating human thinking to intelligently solve plane geometry questions, and relates to the technical field of intelligent symbol reasoning. The method for intelligently solving the plane geometry questions by simulating human thinking comprises the following steps of: expressing a geometrical relationship in a question by using a statement in a form of predicate and parameter so as to perform literal translation on the question, establishing a graph structure, and maintaining reasoning steps and process results; geometric derivation and algebraic calculation are alternately carried out until a target conclusion is obtained; wherein the geometric derivation provides a new equation for the algebraic relationship; the side length relation is simplified through algebraic calculation, and the precondition of the geometric theorem is further provided; and finally, backtracking the reasoning path, and generating a proof process. According to the algebraic derivation and geometric derivation interaction method provided by the invention, the reasoning process strictly complies with the geometric theorem and the algebraic operation rule, and the correctness of the obtained result is ensured.

The invention discloses a method for detecting the position of a chairlift of a roundabout station of a skiing chairlift, and relates to the field of roundabout safe operation control, and the method comprises the steps: carrying out the nonlinear chairlift dynamics modeling of the chairlift, obtaining a correction envelope, carrying out the topological feature analysis of the chairlift based on the correction envelope, and obtaining a topological detection result. The method comprises the following steps: acquiring a geometric relationship of a hanging chair, laser installation parameters and a laser detection signal to carry out tensor risk fusion decision making to obtain a safety control instruction, carrying out fractional order optimal braking analysis based on the safety control instruction to obtain a structured data frame, acquiring hanging chair displacement, hanging chair motion manifold and laser signal parameters of the hanging chair, and carrying out conformal geometric maintenance to obtain the safety control instruction. Maintenance operation guidance is obtained, wind vibration dynamics, laser detection and safety control parameter space-time coupling modeling and detection precision guarantee under wind and snow interference can be achieved, the offside risk can be perceived in the early stage, the equipment state is judged based on a dynamic threshold value, the trend of dynamic degradation is considered, and maintenance decision response is timely.

The invention discloses a non-repeated scanning point cloud registration method based on energy consistency, and particularly relates to the technical field of three-dimensional point cloud processing. According to the method, a unified energy model fusing a scale normalization robust data item, an entropy regularization optimal transmission item, a normal consistency item and a spherical normal distribution alignment item is constructed aiming at the problems that the inherent geometrical relationship of a point cloud is damaged due to random sampling of a non-repeated scanning laser radar and a traditional registration method is easy to fail. Registration solution adopts a three-stage strategy: in a bootstrap stage, a high-quality initial pose is quickly obtained through spherical normal distribution alignment and robust translation estimation; in the main processing stage, the soft corresponding relation and the geometric increment are alternately optimized, and non-monotone line search is combined to ensure energy convergence; fine adjustment is conducted in the polishing stage to improve the final precision. According to the method, the matching problem in non-repeated scanning point clouds is effectively solved, and high-precision and high-robustness registration is realized in a scene with weak geometric features and repeated structures.

A computing system is provided, which receives a molecular graph at a message passing graph neural network (MPGNN), and produces scalar embeddings representing features of nodes and edges of the graph and vector embeddings representing geometric relationships of the graph. The system processes the scalar embeddings via a vector scalar interactive message passing mechanism of a message passing sub-block of theMPGNN to generate and pass scalar information from the scalar embeddings to an embedding space containing the vector embeddings. The system updates the vector embeddings based on the embedding space containing the scalar information and the vector embeddings. The system updates the scalar embeddings based on run-time geometry calculations of the geometric relationships encoded in the vector embeddings. The system computes an updated molecular graph based on the updated scalar and vector embeddings and outputs a target molecular property value based on the updated molecular graph.

The invention discloses a geometric topology fusion-based part assembly method, which comprises the following steps of: acquiring boundary representation models of at least two to-be-assembled CAD parts, and converting the boundary representation model of each CAD part into a structured heterogeneous geometric topology graph; performing feature coding on each node in the heterogeneous geometric topological graph to form node feature representation; inputting the node feature representation into a graph attention reasoning module, and obtaining a node embedding representation representing a geometrical relationship and a topological relationship in the CAD part through multi-layer residual graph structure information propagation and feature aggregation; based on the node embedding representations of the different parts, calculating association scores of node pairs among the different parts; and performing supervised training on the feature coding module and the graph attention reasoning module by using the labeled assembly constraint sample data. According to the method, fine geometric features can be extracted from a boundary representation B-Rep model, and a complex topological dependency relationship is inferred, so that robust assembly constraint inference is realized.

The invention relates to the technical field of urban planning and spatial information, in particular to an urban landscape style assessment method and system based on three-dimensional reconstruction, and the method comprises the following steps: S1, generating a live-action three-dimensional model of a target urban area; s2, dividing the target urban area into a plurality of space grid units on a horizontal plane; s3, extracting three-dimensional visual feature parameters in each vision field range; s4, calculating a visual space oppression index according to the geometrical relationship of the buildings in the visual field range; s5, calculating a landscape style and feature comprehensive evaluation value of the space grid unit; and S6, mapping the comprehensive evaluation value of the landscape style to the geographic position of the landscape style, and generating an urban landscape style evaluation thermodynamic diagram. According to the method, through three-dimensional modeling, visual feature extraction and comprehensive quantitative evaluation, three-dimensional, standardized and visual evaluation of urban landscape styles and features is realized, and scientific support is provided for urban planning and styles and features management.

The invention relates to the technical field of computer aided design and manufacturing, and provides a batch modification method and system.The method includes the steps that all parts of a current model are traversed, and according to parameter information of all the parts, the parts with the section types being circular rings and meeting preset parameter requirements are screened as a first part set; further identifying the arc-shaped parts of which the center lines are fixed in curvature in the first part set; and geometric relationship judgment is conducted on all the arc-shaped parts, and all the screened arc-shaped parts are modified into linear parts by moving part control points. According to the full-automatic batch processing method, the arc-shaped parts are automatically recognized and screened according to the machining requirements, and the arc-shaped parts are modified into the linear parts, and the problems that in an existing scheme, arc-shaped part through opening machining depends on manpower, and the batch processing efficiency is low during part modification are solved.

The invention discloses a geospatial data geometric topological relation evaluation method and system based on a large language model, and belongs to the technical field of spatio-temporal information processing, and the method comprises the following steps: S1, data preprocessing and model construction: processing a training data set containing geospatial data and a corresponding geometric topological relation thereof, and constructing a model; the geometric topological relation of the geographic space data is coded into text or vector representation which can be understood by a large language model; the coded training data is utilized to finely adjust a pre-trained large language model, so that the pre-trained large language model can evaluate a topological relation according to input geographic space data description; s2, geographic space data input and feature extraction; and S3, large language model reasoning and topological relation evaluation. According to the method, by combining the language understanding ability of the large model and the spatial topology calculation technology, intelligent and high-precision evaluation of the geographic spatial data geometrical relationship is achieved, and a brand-new and self-adaptive evaluation technology is provided for the field of geographic spatial data processing.

The invention discloses a battery module welding quality detection method and related equipment, and the method comprises the steps: carrying out the time sequence observation of a welding spot array in a preset time window after the welding is completed, and generating a to-be-detected welding spot set; acquiring three-dimensional shape data of a welding spot to be detected, setting a non-welding reference ring on the outer side of the welding spot according to a lap joint geometrical relationship between a battery cell tab and a busbar, and extracting a welding pit opening boundary and a welding pit bottom area through a robust separation method; fitting a local reference surface by using data in a range of the non-welded reference ring, and calculating the depth of the welding pit and the upheaval volume of the ring area; a plurality of welding spots in the same busbar are subjected to statistical analysis, a judgment interval is dynamically generated in combination with a historical rhythm trend, and the welding quality is judged according to parameters of all the welding spots and array consistency. According to the technical scheme, key geometric features can be stably extracted under the high-speed production condition, errors caused by warping and material differences are reduced, and efficient quantitative detection of micron-sized welding spot defects is achieved.

The invention discloses an object tiny deformation measurement method and system based on interference fringe analysis, and belongs to the technical field of optical measurement. The method comprises the following steps: acquiring an interference fringe image and probe position and direction data; carrying out phase demodulation and sensitivity vector calculation on the surface of a measured object; obtaining the local phase number of each probe according to the interference image; calculating sensitivity vector data through a geometrical relationship; obtaining global phase and sensitivity data, obtaining initial full-field phase data through a weighted fusion method based on a geometrical relationship between a sensitivity vector and a deformation direction, calculating a consistency error, judging whether the consistency error exceeds a threshold value or not, if so, updating a deformation direction estimation value, and executing fusion processing again; and solving and obtaining three-dimensional deformation field data through a linear relation until the error meets the requirement or reaches the maximum number of iterations. According to the invention, the reliability and early warning capability of structural safety assessment in long-term monitoring can be improved.

This invention discloses a parking trajectory evaluation method, comprising: generating multiple candidate obstacle avoidance paths represented by fourth-order Bézier curves; utilizing the convex hull property of Bézier curves, a graded collision detection mechanism is used to screen candidate paths with no collision risk through preliminary axial bounding box judgment and precise judgment using the separating axis theorem; for safe candidate paths, regression gravity cost, ride comfort cost, and comprehensive safety cost are calculated by analyzing the geometric relationship of control points, wherein the regression gravity cost is based on the alignment degree between the control point evaluation at the curve endpoint and the heading and curvature of the reference path, and the ride comfort cost is calculated based on the discrete bending energy model of the control polygon; the comprehensive evaluation cost is obtained by weighted summation of the costs of the above three dimensions, and the path with the minimum cost is selected as the execution trajectory, wherein the weight coefficients are dynamically adjusted according to the width of the lateral passable space and the vehicle speed. This invention reduces the computational power consumption of planning and achieves smooth regression with the memorized path after obstacle avoidance.

The invention discloses an industrial control software-oriented AI intelligent software evaluation index system construction method, and relates to the technical field of index system construction, and the method comprises the steps of obtaining a semantic time period according to log data of an industrial control task; grouping the multi-period coordinate semantic record table corresponding to the semantic period and determining a geometrical relationship to obtain a geometrical relationship signature table; obtaining a target task combination based on the geometrical relationship signature table, and obtaining an extended task record table based on the target task combination; calculating a success rate index based on the extended task record table, and generating an index table of the semantic evaluation unit based on the success rate index; according to the method, stable and reliable data support can be provided for industrial control software version selection, upgrading decision and operation optimization.

The invention relates to a method for training a machine learning model to predict a geometric relationship between anomalies. The invention further relates to a computer program, a device, and a storage medium for this purpose.

The invention discloses a system and a method for realizing positioning in a carriage based on point cloud plane extraction. According to the method, point clouds in a carriage are collected through a laser radar, and after the point clouds of a robot are filtered out, a RANSAC algorithm is used for extracting and matching parallel wall surface planes on the left side and the right side; further generating an anti-interference inner side envelope plane by counting and analyzing point residual errors in the plane; and finally, calculating the transverse position and the course angle of the robot in the carriage based on the plane-to-geometry relationship. According to the invention, for the environment with scarce characteristics and serious reflection in the closed compartment, the positioning is realized by using the inherent parallel structure without depending on GNSS or IMU, and the method has the characteristics of strong robustness, high precision and good real-time performance, and is suitable for autonomous positioning of automatic loading and unloading robots and unmanned forklifts in closed spaces such as containers, trucks and the like.

This invention discloses a positioning method based on single-station ranging with bias reduction using multidimensional scaling analysis. The method first establishes a multidimensional similarity pseudolinear model based on the geometric relationship between the observation station and the target in the measured values; then, it sets an optimization function; and finally, it solves the model using Newton's iterative algorithm. This invention provides a general positioning method based on single-station ranging, achieving higher positioning accuracy compared to traditional pseudolinear and maximum likelihood methods.