120 results about "Non-linear least squares" patented technology

The invention discloses a fuel cell output voltage control method and system based on fuzzy neural network PID, and the method comprises the steps: building an air-cooled fuel cell voltage model based on an MATLAB / Simulink simulation platform, and obtaining the temperature changes of an air-cooled fuel cell under different working conditions; establishing an air-cooled fuel cell test bench, and obtaining a polarization curve of output voltage changing along with current; according to experimental data, calibrating the semi-empirical equation by adopting a nonlinear least square method, and comparing experimental results to verify the accuracy of the model; the input hydrogen flow is changed through the PID controller, so that stable control of the output voltage of the galvanic pile is realized, and the power generation performance of the battery is improved; a fuzzy neural network is adopted to optimize a PID controller, control parameters of PID are adjusted in a self-adaptive mode according to the error between expected voltage and actual voltage and the error change rate, and therefore a better temperature control effect is achieved. The method has the advantages of high robustness, high response speed and the like, and ensures that the voltage output of the fuel cell stack is maintained at a fixed preset value.

The invention relates to a wide-area coverage area high-precision deformation monitoring method based on an InSAR technology, and the method comprises the steps: obtaining the InSAR monitoring data of a plurality of data sources for a wide-area coverage area, carrying out the registration of the InSAR monitoring data, screening interference pairs according to the coherence, carrying out the interference pair combination of a single-view complex image set obtained through registration, and obtaining a single-view complex image set; performing time sequence analysis according to the interference pair combination result to generate a time sequence interference image; performing phase filtering and phase unwrapping on the time sequence interference image; for the time sequence interference image after phase unwrapping, baseline parameters are corrected based on a nonlinear least square method, and atmospheric delay errors are corrected based on a GACOS atmospheric delay model; according to the processed image, constructing a wide-area surface deformation rate map and a preset application scene surface deformation rate map, and analyzing the spatio-temporal evolution law of the wide-area surface deformation rate map and the preset application scene surface deformation rate map; and finally, visually displaying the wide-area surface deformation rate diagram, the preset application scene surface deformation rate diagram and the spatio-temporal evolution law analysis result.

A calibration method of the magnetic field model and a controller for electromagnetic positioning are provided. In the method, a magnetic field is established through a magnetic field transmitter; measurement data is obtained through a magnetic field sensor, where the measurement data includes the amplitude of induced voltage at multiple measurement positions in the magnetic field; and the magnetic field model is corrected according to the error between the measurement data and simulated data correction, where the magnetic field model is used to generate simulation data corresponding to multiple measurement locations. The steps of modifying the magnetic field model include: establishing one or more objective functions through the nonlinear least squares method based on the error between the measured data and the simulated data; and determining the modified magnetic field model based on one or more solutions of the objective function. Therefore, positioning accuracy can be improved.

The invention relates to an automatic test method and system for the zero offset of a hemispherical resonator gyroscope. The automatic test system composed of a double-shaft servo turntable control module, a gyroscope control module and a PC (Personal Computer) upper computer is built; a servo turntable control instruction and a gyroscope control instruction are sent through a serial port according to a certain program through an automatic test logic built in a PC upper computer, a gyroscope vibration mode angle is controlled to be automatically switched from 0 degree to 360 degrees (the step length can be set), and turntable angle and gyroscope vibration mode angle data under each vibration mode angle are synchronously collected; and substituting the acquired data into the error model, completing zero offset error parameter identification by adopting a nonlinear least square method, generating an error compensation formula, and writing the error compensation formula into a gyroscope control unit in real time to realize compensation.

The invention discloses an offshore wind power typical fault transient waveform rapid simulation method and system, and relates to the technical field of offshore wind power unit grid connection and power grid fault simulation, and the method comprises the steps: obtaining an original typical fault voltage transient waveform at an offshore wind power unit grid connection point; a wavelet analysis method is adopted to carry out filtering processing on the fault voltage transient waveform, decomposition is carried out to obtain an approximate signal and a detail signal, a fundamental wave and a main oscillation waveform in the detail signal are extracted, an RLC second-order fault simulation circuit is established, waveform superposition is carried out to form a reconstructed waveform, a reconstructed waveform analytic expression is obtained, and fault transient characteristic parameters needing to be solved are determined; preliminarily fitting the initial values of the characteristic parameters, and iteratively solving the final values of the characteristic parameters by adopting a nonlinear least square method; fitting and solving equivalent line parameter values in combination with a fault feature expression; and substituting the waveform into a fault simulation circuit, and carrying out analog simulation to generate a reproduction waveform. According to the method, the typical fault transient waveform of offshore wind power can be rapidly and accurately reproduced.

The invention discloses a real-time thunder and lightning positioning method. A plurality of observation station GNSS (Global Navigation Satellite System) synchronously acquire thunder and lightning signals to obtain waveform data; performing FFT band-pass filtering and denoising processing on the lightning signal waveform data; a sliding window dynamic threshold is adopted to extract peak value characteristics, peak value characteristics (tp, Ap and Wp) of a waveform in different time windows are obtained, a local noise standard deviation is calculated, only an effective peak value is reserved, and real-time return of lightning data is realized while positioning precision is ensured. The calculation center reconstructs the waveform based on the peak value characteristics (tp, Ap, Wp), the reconstructed waveform more accurately reflects the characteristics of the lightning signal, and the time delay measurement error caused by signal distortion is reduced. And calculating the mutual correlation of the reconstructed lightning waveform data of every two observation stations, extracting the maximum correlation time delay, calculating a TDOA equation set by adopting a weighted nonlinear least square method according to the signal time delay information, and outputting a three-dimensional lightning positioning result. And evaluating the reliability of the positioning result through residual analysis and geometric accuracy factors.

The invention discloses a lithium battery remaining service life prediction method based on an intelligent hybrid drive model, and the method comprises the steps: carrying out the modeling of a long-term degradation trend of a target system through a double-index degradation model (DEDM), and fitting model parameters through a nonlinear least square method; performing dynamic learning on the residual fluctuation of the actual observation data and the degradation trend through a fuzzy random configuration network (F-SCN); and finally, integrating trend prediction and residual prediction results through Gaussian process regression (GPR) to realize high-precision residual life prediction. According to the method, through collaborative optimization of the physical model and the data-driven model, the problem that trend fitting and local fluctuation are difficult to consider under limited data in a traditional method is solved, and the prediction precision and reliability are remarkably improved.

The invention relates to the technical field of river ice disaster prevention, and discloses a river freeze-up state prediction method under a multi-flow condition, which comprises the following steps: calculating the flat beach flow at the early stage of river freeze-up; calculating the river sealing volume at the early stage of riverway freezing; obtaining the cooling intensity of the river channel in the cooling process; after correlation analysis is carried out on the accumulated negative air temperature in the time period from the flow to the river closure, the flat beach flow, the river closure flow and the cooling intensity, an accumulated negative air temperature prediction model in the time period from the flow to the river closure is established, a nonlinear least square method is adopted for solving, an optimal fitting coefficient is obtained, and an optimal accumulated negative air temperature prediction model is generated; the accumulated negative air temperature of the current year is obtained, the accumulated negative air temperature is predicted, and the riverway freezing-up state of the current year is obtained through comparison; according to the method, the accumulated negative temperature of the frozen river channel can be accurately obtained by establishing the nonlinear relation between the factors such as the river channel condition (flat beach flow), the sealed river flow and the cooling intensity and the accumulated negative temperature, so that the frozen state of the river reach is accurately judged.

The invention discloses an automatic circuit modeling method and system in electrochemical impedance spectroscopy analysis of a lithium ion battery. The method comprises the following steps: 1) acquiring electrochemical impedance spectroscopy data of the lithium ion battery to be analyzed; (2) deleting data with positive imaginary parts in the obtained electrochemical impedance spectroscopy Nyquist diagram of the lithium ion battery to be analyzed, and reserving other impedance spectroscopy data; and 3) calculating a fitting precision part in the fitness of the equivalent circuit model by using the retained impedance spectrum data, and obtaining a total fitness evaluation result of the single equivalent circuit model by combining the complexity of the equivalent circuit model. The system comprises a data acquisition module, a data processing module and a calculation module. According to the method, the circuit model can be quickly selected by using the genetic algorithm, and the circuit element parameter identification is performed by using the nonlinear least square method.

The invention relates to a shallow coal seam stope face oxygen concentration dynamic distribution model construction and real-time updating method, belongs to the technical field of coal mine safety monitoring, and aims to solve the technical problems that a traditional monitoring means cannot obtain an oxygen concentration space full view and a static model is difficult to track a dynamic mining environment. According to the technical scheme, at least four sensors are arranged on a coal face to form a gradient monitoring network, and oxygen concentration data of multiple positions are collected in real time; constructing an exponential decay function to characterize the distribution rule of the concentration along the tendency; solving an undetermined coefficient based on a nonlinear least square method with space-time constraint; and dynamically calculating a model updating period t through an environment complexity index ECI, and triggering model iteration. Working face oxygen concentration global dynamic sensing, low-oxygen risk area accurate early warning and ventilation decision intelligence are achieved, and the mine safety prevention and control capacity is remarkably improved.

The invention belongs to the technical field of gas detection and mode recognition, and particularly provides a smell classification electronic nose system based on a multi-sensor array and mode recognition, which is used for solving the problems of poor generalization and low classification precision of a traditional gas sensor on complex smells. The method comprises the following steps that (1) an embedded electronic nose system platform is built, data of five smells of mint sugar, coffee, chrysanthemum tea leaves, orange peel and apples are collected, and the platform comprises (1) a Raspberry Pi 4B main controller used for running of a main program; (2) four BME680 sensor arrays used for collecting multiple non-specific responses of the gas to be detected; (3) the speed-adjustable gas circuit module is used for driving a micro diaphragm gas pump through PWM (Pulse-Width Modulation), and the extraction rate of 0-0.8 L / min can be realized; (2) carrying out a data sampling experiment, and constructing a multi-scene data set; (3) establishment of a pattern recognition model: (1) data processing: performing data enhancement on originally acquired data, fitting a response curve through a nonlinear least square method, extracting characteristics such as slope, curvature and the like, and expanding characteristic dimensions of the original data; (2) carrying out principal component analysis on dimension-reduced data; and (3) model training: establishing a classifier model through various machine learning algorithms to obtain an optimal model. And the accuracy rate can reach 81.7%.

The invention discloses an aerodynamic damping rapid estimation method for a rotating blade, and the method comprises the steps: selecting a test impeller, obtaining an attenuation signal of a blade of the test impeller based on an impact test, and obtaining a structural damping ratio of the blade according to the attenuation signal through a free attenuation method and a nonlinear least square method; a BTT test technology is introduced, and the total damping ratio of the blade is obtained based on the BTT test technology and a nonlinear least square method; based on the structural damping ratio and the total damping ratio of the blade, an aerodynamic damping estimated value of the blade is obtained, and estimation of aerodynamic damping is achieved; according to the method, the BTT data analysis technology and the free vibration attenuation theory are combined, quantitative estimation of the aerodynamic damping ratio of the rotating blade is achieved, and the aerodynamic damping ratios of all the blades under different vibration pitch diameters can be determined; the pneumatic damping contribution of the rotating blade is quantitatively expressed, the vibration response mechanism of the blade in the service state can be deeply understood, and long-acting safe operation of a unit is guaranteed.

The invention provides a wireless channel modeling method based on human body shielding and surface waves, and the method comprises the steps: setting a receiving and transmitting end system with an adjustable distance dtr, and erecting a metal tube right above the receiving and transmitting end; carrying out joint calibration on the transmitting end surface wave exciter and the receiving end surface wave exciter, and establishing a surface wave transmission reference link; dynamically adjusting the coupling distance between the two exciters and the metal tube, and fully exciting a surface wave transmission mode; a movable human body model is arranged at the midpoint of a transmitting-receiving link, a measuring range is set to adjust the vertical distance dhv of a human body-metal pipe, and multiple groups of path loss samples are obtained through stepping measurement; constructing a path loss relation matrix containing dhv / dtr double variables through repeated measurement under a multi-distance dtr condition; and performing bivariate joint fitting on the measured data by adopting a nonlinear least square method, and establishing a path loss model with human body shielding compensation. The invention also provides an application of the wireless channel modeling method based on human body shielding and surface waves.

The invention provides a receiver autonomous integrity monitoring method, device and equipment and a storage medium, and the method comprises the steps: obtaining satellite observation data and 5G base station observation data, and carrying out the preprocessing; performing weighted nonlinear least square method solution based on the satellite observation data and the 5G base station observation data, and determining an observation value residual error; performing fault detection and fault identification on the satellite system according to the observation value residual error; and performing autonomous integrity monitoring availability judgment based on a fault-free satellite in the satellite system to obtain a judgment result. According to the invention, the positioning precision of the low-altitude aircraft is greatly improved, the integrity monitoring level can be remarkably improved, and the problem of poor monitoring precision in the prior art is solved.

The invention provides an ultra-short baseline calibration method, device and system, and belongs to the technical field of underwater acoustic measurement, and the ultra-short baseline calibration method comprises the following steps: according to an antenna phase center position, a carrier instantaneous attitude, a distance and azimuth information at each observation moment, and installation parameters of an ultra-short baseline acoustic transducer relative to an inertial navigation system, carrying out calibration on the ultra-short baseline; establishing a distance equation between the ultra-short baseline acoustic transducer and the ultra-short baseline acoustic beacon at each observation moment; establishing a residual equation of each distance equation; and solving the residual equation through a nonlinear least square method to obtain installation parameters. According to the method, the installation parameters of the ultra-short baseline acoustic beacon can be efficiently and accurately calibrated, and the problems that beacon laying and recycling operation is complex, cost is high, the operation period is long, efficiency is low, and the beacon is prone to drifting due to the influence of ocean currents are effectively solved.

The invention relates to the technical field of functional group analysis, and discloses an adsorption material surface functional group analysis method and system based on a Gaussian function model.According to the method, proton binding isotherm data of an adsorption material under different pH conditions are obtained through an incremental titration method, and the proton binding isotherm data are input into a Gaussian function model; the method comprises the following steps: carrying out characterization analysis on different types of functional groups, fitting experimental data by using a nonlinear least square method to obtain optimized parameters, verifying the accuracy of the optimized parameters by using a preparatory test means, analyzing the proportions of various functional groups in the adsorption material based on the verified optimized parameters, and generating a surface functional group distribution map. According to the method, distribution of different functional groups is accurately analyzed through the Gaussian function model, the defect that quantitative analysis of a traditional method is not accurate is overcome, high accuracy of a result is ensured, detailed data support is provided for design and optimization of an adsorption material, and the problem that in the prior art, when multiple functional groups coexist, the detection effect is not accurate is solved.

The invention relates to the technical field of radars, in particular to a weather radar distance resolution calibration method and system. The method comprises the following steps: collecting oversampling original baseband I / Q data of a point target in a plurality of continuous pulse periods; determining a pulse signal-to-noise ratio, and screening out effective pulses according to a threshold value; carrying out sub-sampling stage time alignment on the effective pulses based on cross-correlation analysis, and carrying out incoherent averaging on power module values of all the aligned pulses to generate an average pulse power envelope; converting the average pulse power envelope to a logarithm domain, and selecting discrete data points in a main lobe region; according to the discrete data points, a nonlinear least square method is adopted to carry out iterative fitting on the generalized Gaussian mathematical model, and a continuous analytic function describing the pulse envelope is obtained; according to the continuous analytic function, determining a pulse time width when the power is reduced to a peak value of-6dB; and determining the real distance resolution according to the pulse time width. The measurement robustness is improved, and sub-meter calibration precision is achieved.

The invention relates to an S-G filtering ultrasonic signal noise reduction method, in particular to an S-G filtering ultrasonic signal noise reduction method based on nonlinear least square method guidance. The invention aims to solve the problem of effective signal distortion possibly existing in an ultrasonic signal noise reduction process. The method comprises the following steps of: 1, performing nonlinear least square waveform fitting processing; 2, performing multi-scale grading and reference signal guide regularization; and step 3, implementing multi-scale adaptive S-G filtering. The invention belongs to the technical field of ultrasonic signal noise reduction.

The invention provides a UWB multi-base-station circular station distribution structure and a positioning method, which are used for improving the regional three-dimensional positioning precision in an ultra wide band UWB system, and the positioning method comprises the steps: obtaining base station coordinates from a three-dimensional positioning region through a multi-base-station circular station distribution structure designed in a geometric circle; obtaining a timestamp, an arrival phase difference and CIR frame information through DS-TWR multi-base-station efficient communication between multiple base stations and a label; receiving distance and angle data of a plurality of UWB base stations, and introducing Kalman filtering to optimize a dynamic error; constructing an equation by using a nonlinear least square method, completing positioning coordinate calculation, and executing a multi-base-station data fusion positioning algorithm; high-precision three-dimensional positioning can be realized through an innovative circular station distribution structure and a positioning method, and the system has the advantages of simplicity and convenience in deployment, miniaturization, low power consumption, high precision and the like, adapts to variable and complex environments, and has a wide application prospect in regional three-dimensional positioning and connector automatic positioning systems.

Described herein is NLS using a bounded linear initial search space and a fixed grid with pre-calculated variables. Specifically, first and second signals with unknown first and second elevation angles, respectively, are received that have been reflected by an object, with the second signal also having been reflected off the ground. A line of second angles is then established as a function of first angles, a sensor height, and a range to the object. The first angles being bound by a function of the sensor height and the range and a function of the sensor height, the range, and the maximum height. A search algorithm is then used to search for an initial elevation angle pair along the line. The initial elevation angle pair may then be fed into a refinement algorithm (e.g., non-linear least squares) to determine the elevation angles associated with the first and second signals.

The invention discloses a transformer overheating fault prediction method and system based on a nonlinear degradation model, and the method comprises the steps: collecting the concentration data of gas dissolved in oil of a transformer in a set time period before a fault according to a sampling interval, and obtaining historical data after preprocessing; establishing an exponential degeneration orbit model based on a thermal aging equation, fitting the exponential degeneration orbit model with historical data by adopting a nonlinear least square method, and judging whether the equipment is in a stable degeneration stage or not according to a fitting result; when the equipment is in a stable degradation stage, original time is converted into an accumulated degradation amount by using a time scale conversion function, and linear processing of a historical data sequence is completed; solving a pre-established nonlinear degradation model based on the linearized data; and deducing the fault time probability density by using the solving result of the nonlinear degradation model, and predicting the overheating fault of the transformer. According to the invention, abnormal interference caused by random factors can be effectively identified, and the sensitivity and reliability of fault early warning are improved.

The invention discloses a multi-line laser radar SLAM point cloud densification method based on indoor environment characteristics, and the method comprises the steps: employing a first frame of corrected point cloud data as a reference point cloud, and constructing an initialized map: carrying out the feature extraction, data matching and feature fusion of each frame of corrected point cloud data, and then constructing a residual equation; according to the residual equation, iteration is carried out through a nonlinear least square method to optimize the residual of the line and the plane, and the final pose Ri needing to be optimized is output and obtained; performing domain point classification on point cloud data of each frame on each current scanning line according to the optimized pose Ri, dividing the point cloud data into plane points and corner points, obtaining a relation between the plane points of the current frame and surrounding domain points, and judging to execute straight line fitting and point cloud densification processing of the plane points on the current frame; according to the method, the problem that the density of multi-line laser radar data is rapidly reduced at the distance from the radar is solved, and uniform distribution of point clouds at different depths is ensured through an intelligent densification algorithm, so that the quality of a whole indoor environment model is improved.

According to the Vine Copula-based large-span roof structure wind pressure coherence probability modeling method, a large-span roof wind pressure coherence function considering different wind direction angles is put forward, generalized extreme value distribution is adopted to estimate marginal probability distribution of coherence function parameters, probability dependency of the coherence function parameters is quantized based on Vine Copula, and the probability dependency of the coherence function parameters is quantized based on Vine Copula. The wind pressure coherence of the large-span roof structure is effectively simulated by considering the uncertainty of the wind field. The specific implementation process is as follows: A, preprocessing wind pressure measurement data of the large-span roof structure, and establishing a wind pressure data set; b, deducing a wind pressure coherence function model considering wind directions, and fitting coherence functions of wind pressures measured under different wind directions through a nonlinear least square method; c, estimating marginal probability distribution of coherence function parameters according to the parameter samples of the fitted coherence function; d, on the basis of Vine Copula, constructing a probability dependency relationship among different coherence function parameters; and E, generating a random parameter sample by adopting a conditional sampling method, and substituting parameters into the proposed coherence function to obtain a simulated wind pressure coherence function of the large-span roof structure.

The invention provides a GNSS / VIO fusion high-precision positioning method based on graph optimization. A system is composed of a data acquisition module, a preprocessing module, a visual inertial odometer module and a graph optimization fusion module. The system integrates a monocular camera, an IMU (inertial measurement unit) and a GNSS-RTK (global navigation satellite system-real-time kinematic) receiver, and establishes a unified multi-factor graph optimization model by constructing a visual re-projection factor, an IMU pre-integration factor and a GNSS-RTK factor. The core innovation point of the method is that local estimation of the visual inertial odometer is corrected in real time in a sliding window by utilizing global absolute position constraint provided by a GNSS (Global Navigation Satellite System), so that the increase of accumulative errors of VIO (Visual Inertial Odometer) is effectively inhibited. The back end of the system adopts a nonlinear least square method to optimize and solve the pose, the speed and the IMU zero offset of the carrier in real time; and when the GNSS signal is shielded or lock losing occurs, high-precision positioning output is still kept depending on the continuity of the VIO. In conclusion, through collaborative modeling and joint optimization of the multi-source sensor, the limitations of insufficient precision, signal interruption and the like of a single sensor in a complex shielding environment are overcome, and high-precision and high-robustness continuous positioning is realized.

The application belongs to the field of curved surface body positioning reference plane adjustment and discloses a curved surface body positioning reference plane adjustment method based on nonlinear least squares, which aims to provide an improved curved surface body positioning reference plane adjustment method based on nonlinear least squares. After the curved surface body is fixed on a workbench, the coordinates of the registration control points on the curved surface body are measured and obtained by a laser tracker. In the Boolean sand model, the two coordinate system origins are translated to the center positions of the reference control points to establish a center auxiliary conversion coordinate system. Seven parameters are solved based on the nonlinear least squares method and the Gauss-Newton iteration method, and the adjustment is performed based on the offset and the scaling ratio. The corresponding displacement and deflection angle values are compensated to the reference plane, and the curved surface body is moved to the optimal working position. The application is applied to the field of curved surface body reference plane positioning.

The present invention discloses a method for evaluating the dielectric loss factor of power equipment under the action of an oscillating wave high voltage, which is applied to the field of high voltage test technology. In addition to evaluating the oscillating wave voltage information in the traditional dielectric loss factor evaluation method, the oscillating wave current is evaluated. Through mathematical deduction, a mathematical expression for the relationship between the dielectric loss factor and the oscillating wave voltage and current waveform parameters is obtained; based on an algorithm combining phase-shifted fast Fourier transform and nonlinear least squares method, the oscillating wave voltage and current sequence is processed to obtain waveform parameter estimates, and then an estimated value of the dielectric loss factor is obtained. The dielectric loss factor evaluation algorithm of the present invention has good anti-noise interference capabilities, and at the same time, the dielectric loss factor estimation accuracy is high.

The present invention provides a positioning and timing method, system, device and readable storage medium based on PPP-B2b, which relates to the field of information technology. The method includes receiving PPP-B2b messages and GNSS raw observation data, extracting key features from the self-matched PPP-B2b messages, and using a support vector machine to learn and match the key features; using PPP-B2b orbit and clock offset correction data to calculate satellite positions and satellite clock offsets, constructing an error model including error terms, and optimizing the error model by using the nonlinear least squares method; and using the calculated satellite positions and satellite clock offsets to establish a dual-frequency ionosphere-free combination model; and performing parameter estimation by using Kalman filtering to complete real-time positioning and timing. Without being connected to the network, the present invention not only realizes single-station real-time high-precision positioning, but also realizes the synchronization of the local clock with the satellite system clock by means of phase modulation.

The invention relates to the technical field of sensor calibration, in particular to a calibration method based on laser radar and camera external parameters, and the method comprises the steps: obtaining laser observation data and camera observation data; constructing a plane constraint equation of a laser point on the two-dimensional code calibration plate through a conversion relation among a calibration plate coordinate system, a laser coordinate system and a camera coordinate system; constructing a linear equation set based on the plane constraint equation, and performing singular value decomposition and rotation matrix orthogonalization on the linear equation set to obtain an external parameter initial value; and optimizing the initial values of the external parameters by adopting a nonlinear least square method to obtain optimal estimated values of the external parameters, and completing calibration of the external parameters of the laser radar and the camera. According to the method, the angular point information of the camera is rapidly extracted by using the high contrast of the two-dimensional code and the regular pattern, and the precision and robustness of external parameter calibration are improved in cooperation with the laser radar data of the plane constraint.

The application discloses a two-step method for accurately correcting GNSS-IR abnormal phase, and belongs to the technical field of microwave remote sensing. The method is characterized in that: the GNSS observation data is preprocessed, and the modulation term in the signal-to-noise ratio is extracted; then, the nonlinear least square method is used to fit the modulation term, and the phase of each satellite is obtained; finally, the abnormal phase is accurately corrected through the two-step method: in the first step, a signal-to-noise ratio period method is constructed to correct the phase of the whole period and half period jump caused by the limitation of the nonlinear least square method itself; in the second step, the standard fraction method is combined with the Savitzky-Golay filter to accurately detect and repair the phase of less than half period jump caused by the multipath environmental factors. The method can effectively improve the phase quality of each satellite, improve the shortcomings of the traditional phase solving method, and solve the problems in the prior art.

The invention provides a commercial vehicle EBS road adhesion coefficient identification method, system and device and a storage medium, and the method comprises the following steps: building a current sample point based on the obtained current slip rate data and current adhesion coefficient under an ABS triggering condition, historical sample points are constructed based on the obtained multiple historical slip rates and the historical attachment coefficients of the corresponding historical slip rates; preprocessing the historical sample points, and constructing the historical sample points and the current sample points to obtain a two-dimensional data set; performing noise reduction fitting on the two-dimensional data set through an RANSAC (Random Sample Consensus) algorithm, and calculating to obtain a primary fitting model parameter and an interior point data set; secondary fitting is carried out on the primary fitting model parameters and the interior point data set through a nonlinear least square method, and secondary fitting model parameters are obtained through calculation; and a peak road surface coefficient is calculated based on the quadratic fitting model parameters, a current road surface adhesion coefficient is identified based on the peak road surface coefficient, and the road surface adhesion condition is determined. The method can accurately identify the road adhesion coefficient.