43 results about "Weighted least squares algorithm" patented technology

A system and method for monitoring a patient includes a sensor configured to acquire physiological data from a patient and a processor configured to receive the physiological data from the at least one sensor. The processor is also configured to apply a spectral estimation framework that utilizes structured time-frequency representations defined by imposing, to the physiological data, a prior distributions on a time-frequency plane that enforces spectral estimates that are smooth in time and sparse in a frequency domain. The processor is further configured to perform an iteratively re-weighted least squares algorithm to perform yield a denoised time-varying spectral decomposition of the physiological data and generate a report indicating a physiological state of the patient.

A method of calculating position data for an airborne aircraft using a GPS-based airborne navigation system includes the processing of a position component of a relative state function by fusing a plurality of different types of measurement data available in the GPS-based system into a weighted least squares algorithm to determine an appropriate covariance matrix for the plurality of different types of measurement data.

The invention relates to the space cruising autonomous navigation method based on plural globe route sign. It includes the following steps: programming the navigation using minor planet table, processing navigation minor planet image, and determine the autonomous path. The center of figure of plural minor planet determines the path of craft. The error of craft path is very low. The location error could be closed to 100Km and the speed error could be bellow 0.3m / s. It could satisfy the path accuracy request of the detector.

The invention belongs to the field of seismic signal processing in seismic exploration technologies, and specifically discloses a primary wave and multiple wave separation method based on an alternative splitting Bregman iterative algorithm. With regard to a multiple wave self-adaptive subtraction method based on a 3D matched filter, the primary wave and multiple wave separation method utilizes the alternative splitting Bregman iterative algorithm to solve an optimization problem of applying sparsity constraint on primary waves, achieves the estimation of the 3D matched filter, and utilizes the estimated 3D matched filter to separate the primary waves and the multiple waves in a 3D data window in a self-adaptive manner. Compared with the traditional iterative reweighted least squares algorithm, the alternative splitting Bregman iterative algorithm adopted by the primary wave and multiple wave separation method only needs to calculate matrix-matrix multiplication and matrix inversion once when estimating the 3D matched filter at each 3D data window, can effectively reduce the calculation complexity of solving the optimization problem, and improves the calculating efficiency of primary wave and multiple wave self-adaptive separation.

The invention discloses an improved positioning method based on multi-beacon arrival time differences. The method specifically comprises the steps of: (1) obtaining position information of a sensor in a multi-beacon arrival time difference positioning scene; (2) taking a target position and distances between a plurality of beacons and the target as unknown quantities, deriving a corresponding pseudo-linear equation group according to a non-linear measuring equation group of the multi-beacon arrival time differences; (3) according to a weighted least square algorithm, estimating the target position and the distances between the plurality of beacons and the target; and (4) according to the coupling relation between the target position and the distances between the plurality of beacons and the target, updating the estimation of the target position. According to the invention, the precision of the linear closed passive target positioning aimed at multi-beacon arrival time differences is improved. The plurality of beacons and the coupling relation between the target position and the distances between the plurality of beacons and the target are utilized to increase the positioning information amount and improve the positioning precision.

The invention relates to an RSSI (Received Signal Strength Indicator) ranging based WLS (WebLogic Server) node self-positioning method in a wireless sensor network, which comprises the following steps that: firstly, in a positioning process, a channel fading factor n is calculated by weighting; secondly, a distance between an unknown node and a beacon node is measured by RSSI ranging; and finally, a coordinate of the unknown node is estimated by a weighted least squares algorithm (WLS). Based on the same hardware complexity of the positioning algorithm and the least squares (LS) estimation algorithm, the positioning accuracy is greatly enhanced, therefore, the method provided by the invention is simple and easy to implement, and has a stronger practical value.

The invention relates to a method and a system for fixing integer ambiguity. The method comprises the steps of: S1, obtaining a measurement value of satellite and correcting constant term of the double-difference carrier phase observation equation of the satellite according to the measurement value of the satellite; S2, obtaining a wide-lane double-difference observation equation based on the corrected constant term; S3, solving the coefficient matrix of unknown parameters in the wide-lane double-difference observation equation using a weighted least squares algorithm and solving the variance-covariance matrix and the ambiguity floating point solution of output parameters of the wide-lane double-difference observation equation; S4, performing full rank decomposition on the variance-covariance matrix Qw to obtain a B matrix; and S5, performing ambiguity fixing on the ambiguity floating point solution by replacing the variance-covariance matrix with the B matrix to obtain an ambiguity fixing solution. According to the integer ambiguity fixing method, the precision of the ambiguity can be improved and the search range of the integer ambiguity can be narrowed.

The invention belongs to a multi-sensor passive positioning technology and provides a multi-station continuous positioning model based on TDOA / GROA (time different of arrival / gain ratio of arrival) for a fixed radiation source target. The limitation of an intermediate variable based traditional positioning model to a positioning scene is taken into consideration, and a positioning model only related to a target state vector is obtained by starting from measurement equations of TDOA and GROA, so that the introduction of an intermediate variable is avoided; an error term of the positioning model is deduced according to a measurement model, and target state estimation is calculated with a constrained weighted least squares algorithm finally. The positioning model is applicable to continuous positioning of the fixed radiation source target under a multi-sports-station scene.

The invention discloses a weight least square indoor positioning algorithm based on phase difference Euclidean distance measurement. The weight least square indoor positioning algorithm comprises the following steps: arranging a positioning RFID (Radio Frequency Identification Devices) reader and a reference marker; estimating the distance between the reader and the maker according to a phase difference received by the reader, equalizing a distance measurement error caused by a multipath effect and Gaussian white noise to be Gaussian distribution, and enabling mean values and variances of deviation of estimated distances between the reference marker and the readers and actual distances to form position parameters and scale parameters of Gaussian distribution parameters; estimating the distance between the reference marker and a marker to be positioned; by taking the reciprocal of the variance of an estimation error of the distance between the marker to be positioned and the reader and the reference marker as a weighting factor, solving a positioning problem by using a weight least square algorithm. The weight least square indoor positioning algorithm has the characteristics of being relatively high in precision.

The present invention provides an NLOS (non-line of sight) transmission base station identification and positioning method based on side length residual errors. The method comprises the following steps: firstly dividing base stations into groups, and ensuring that each group comprises two base stations, the group number is represented by a formula, and the base station number is N; then calculating the virtual side length by using collected TOA and AOA estimated values according to a cosine theorem, calculating the difference value between the virtual side length and a measuring distance, and calculating a threshold by taking the difference value as the side length residual error; and then identifying NLOS transmission base stations and LOS transmission base stations by comparing the residual errors and the threshold values, finally estimating the location of an MS by using parameter measurement values of the LOS transmission base stations, and ensuring that an estimation algorithm adopts a two-step weighted least square algorithm. According to the NLOS transmission base station identification and positioning method based on the side length residual error provided by the invention, the errors can be effectively reduced, and the positioning accuracy can be improved.

The invention discloses a mobile robot pose estimation method based on a RFID. The method mainly includes: step 100, receiving a robot position coordinate estimation algorithm of a wireless signal intensity based on the RFID; and step 200, estimating an azimuth theta of a mobile robot. According to the mobile robot pose estimation method based on the RFID, a robot positioning system based on the RFID signal intensity and a robot positioning algorithm based on maximum likelihood estimation are combined, the method of weighted least squares is applied to the solution of maximum likelihood equations of robot coordinates, the combination of two algorithms is realized, the positioning precision is effectively improved, the influence of the environment on the system is small, and the positioningerror is stable.

The invention discloses a robust depth map structure reconstruction and denoising method based on a guided filter. A structure error region is detected; detecting a place where the input depth map isgreatly different through the guided filtering of the large window and the guided filtering of the small window; an eclosion effect can be achieved due to guided filtering under a large window; the guide filtering of the small window only plays a smoothing role. Therefore,. Therefore, areas with large differences can be regarded as structure error areas. Marking as a potential structure error region, then constructing a weight based on an iterative reweighted least square algorithm, after the weight construction is completed, carrying out overall solution and updating the depth map, judging whether a set iteration frequency is reached or not according to a result, if so, outputting the depth map to end calculation, and otherwise, carrying out structure error region detection again. According to the method, strong noise can be suppressed, structure error regions of the depth map and the color map can be repaired, the consistency of the depth map and the color map is improved, a correctdepth map boundary is recovered, and the method has important guiding significance for improving the quality of the synthesized view.

The invention provides a radar positioning method and device and a storage medium, and relates to the technical field of radar positioning. The method comprises the following steps: acquiring reflective column information in a global landmark coordinate system and reflective column information in a local coordinate system under a current radar coordinate system; obtaining a matching relationship between the reflective column information in the global landmark coordinate system and the reflective column information in the local coordinate system under the radar coordinate system through a reflective column matching algorithm; and calculating and obtaining pose information of the radar through the matching relation and a weighted least square algorithm. The radar pose calculation is performed by using multiple pieces of matched reflective column information and the weighted least square algorithm, so that the problem that the radar positioning precision is greatly influenced when information of a single reflective column is inaccurately acquired at present is solved, and the radar pose calculation accuracy is improved.

The invention is applied to the technical field of image processing, and provides an ultrasound image denoising method and system. The method comprises steps as follows: feature information of an ultrasound image is extracted through multi-scale feature asymmetry metric; the ultrasound image finishing feature information extraction is denoised based on a phase weighted least-squares algorithm. With adoption of the method and the system, the feature information of the image can be reserved while ultrasound image noise is removed.

The invention discloses a fluidized bed boiler air input capacity control method based on model online identification. The method comprises the following steps that according to the actual running condition of a fluidized bed boiler, the air input capacity is selected to serve as input of an online identification model, and material bed temperature of the circulating fluidized bed boiler serves as output of the model; a mathematical model of a single-input and single-output linear constant stochastic system is set up to enable the quadratic sum of fitting residual to be minimum, the model is identified on the basis of a weighted least square method of a rolling time window, and a material bed temperature value is output; a fuzzy control strategy is adopted for controlling the air input capacity, the obtained material bed temperature value is compared with an expected material bed temperature value to obtain input of the fuzzy controller, output of the controller is obtained after fuzzy inference is carried out, and the air input capacity is adjusted according to the air input capacity. According to the method, the model set up on the basis of the weighted least square method of the rolling time window is online, and therefore in comparison with an offline model, the material bed temperature can be identified better and can be more accurate than that of traditional modeling.

The invention discloses an aircraft skin opposite joint gap calculation method based on end face extraction. The method specifically comprises the steps of acquiring aircraft skin actual measurement point cloud data; carrying out rasterization processing on the actual measurement point cloud data; calculating the planeness of the point cloud data in each grid through principal component analysis,extracting a plane grid in each grid, and fitting the point cloud data in the plane grids into a plane by adopting a weighted least square algorithm; extracting point cloud data of a skin plane area by adopting an area growth algorithm based on the fitted grid plane; and fitting a plane by adopting an iterative weighted least square algorithm, judging whether the fitted plane is an end face or not, and calculating a butt joint gap of the end face of the skin. According to the invention, the aircraft skin gap alignment gap can be accurately calculated, and the problem that the aircraft skin gapalignment gap is difficult to detect is solved.

The invention discloses a color map guide-based depth map restoration and view synthesis optimization method, which comprises the following steps: firstly, detecting inconsistent regions, detecting the edge of an input depth map, performing swelling processing on the edge, and marking the swelled edge as a potential inconsistent region; secondly, constructing a weight based on an iterative reweighting-based least squares algorithm, and after weight construction is completed, performing integral solving, and updating a depth map; judging whether the iteration is performed for set times or not according to a result; and if YES, outputting the depth map, and ending the calculation, or redetecting the inconsistent regions. The color map guide-based depth map restoration and view synthesis optimization method disclosed by the invention can suppress strong noise and restore inconsistent regions between the depth map and a color map to improve the consistency between the depth map and the color map and restore a correct boundary of the depth map, and has important guiding significance for improving the quality of a synthesized view. Meanwhile, the denoising and edge retaining capacity forconsistent regions is high; and an adopted matured iterative weighted least squares model is high in adaptability to parameters, and the robustness of the model is improved.

The invention belongs to the technical field of digital image processing, and discloses an impulse noise blurred image nonlinear restoration method and system, and the method specifically comprises the steps: building an impulse noise blurred image degradation mechanism model, and determining an optimization framework; constructing data items to model impulse noise; selecting an image prior item,and constructing a pulse noise blurred image non-blind deconvolution model in combination with the data item; and performing numerical optimization solution on the non-blind deconvolution model by using an iterative reweighted least square algorithm and a conjugate gradient method to obtain a restored image. According to the impulse noise blurred image nonlinear restoration method, properties of impulse noise are analyzed, a nonlinear deconvolution model is designed in a targeted mode, and the nonlinear degenerated impulse noise blurred image restoration problem is solved.

A method of calculating position data for an airborne aircraft using a GPS-based airborne navigation system includes the processing of a position component of a relative state function by fusing a plurality of different types of measurement data available in the GPS-based system into a weighted least squares algorithm to determine an appropriate covariance matrix for the plurality of different types of measurement data.

An NLOS transmission base station identification and positioning method based on angle residual error comprises the following steps: firstly, N base stations need to be grouped in pairs, after the number of groups is set, a calculation angle value is obtained by utilizing the cosine law according to obtained TOA and AOA estimated values, then a difference value between the calculation angle value and a measured AOA value is obtained, the difference value is taken as the angle residual error, and an angle threshold value is obtained at the same time; and the NLOS transmission base station and the LOS transmission base station can be identified by comparing the residual error and the threshold, finally, the position of the MS is estimated by using the parameter measurement value of the LOS transmission base station, and the estimation algorithm adopts a two-step weighted least square algorithm. According to the NLOS transmission base station identification and positioning method based on the angle residual error, errors are effectively reduced, and the positioning precision is improved.

The present invention discloses a double base distance positioning method for the multi-radiating and multi-receiving external radiation source radar under clock deviation. The method comprises: performing linear processing according to the double base distance measurement equation of multi-radiating and multi-receiving external radiation source radar under the system deviation and the measurementerror, selecting the distance of the target from the receiving station as an auxiliary variable, and constructing a joint estimation linear model of the target position and the double base distance system deviation; eliminating and ignoring the influence of the correlation between the auxiliary variable and the target position on the target positioning by using a multi-stage weighted least squares algorithm so as to improve the joint estimation accuracy of the target position and the double base distance system deviation; and finally, using the double base distance system deviation to correctthe double base distance measurement value, and performing posterior iteration to further improve the target positioning performance.

The invention relates to a method of composing inversion digital elevation model of aperture radar image from single full-polarization by combining respective characteristics of radar polarization andradar angle-measurement technology. Polarization azimuth offset psi is estimated from polarization SAR data by using circular polarization method to build data relationship between polarization azimuth offset psi and range slope angle alpha and azimuth slope angle beta . Under the condition that there is only single full-polarization SAR image, suppose that imaging region satisfies conditions ofsurface covering homogeneity and little slope fluctuation and the technology from shadow to image in radar angle measurement is inducted to build data relationship of surface backward-scattering strength and surface geometric parameters (containing range slope angle alpha and azimuth slope angle beta ). In this way, by said data relationship range slope angle alpha and azimuth slope angle beta arecalculated. Weight graph is extracted from cross-polarization response signal graph and discrete poisson equation about ground elevation is solved by weighted least square algorithm to obtain DEM ininversion.

The invention discloses a complex fracture network oil reservoir flow simulation method which comprises the following steps: dispersing an oil reservoir into a series of nodes according to a complex fracture network distribution rule of a fractured horizontal well control area, and representing flow characteristics of fluid in media with different scales by adopting a flow path between the nodes; estimating a pressure Laplacian operator by utilizing the node physical property, the influence domain and a weighted least square algorithm, and giving a calculation method for the conductivity reflecting the seepage capacity of the connection unit and a calculation method for the communication volume of the attribute parameter of the material basis; with a connection unit as an object, solving the flow flux in the unit through node pressure equation, carrying out semi-analysis tracking of a saturation equation along the connection unit, calculating the output dynamic state, obtaining the production dynamic states of different perforation points, and realizing simulation of complex fracture network oil reservoir flow. The method has the advantages that the fracture form can be accurately described in a node form, and fracture network flow simulation can be rapidly and efficiently carried out.

The invention relates to a water quality monitoring network positioning method based on RSSI distance measurement. The method comprises the following steps: establishing RF communication modeling; obtaining path loss PL (d0) after the wireless signal passes through the reference distance d0; periodically measuring received signal strength RSSI between a node to be positioned and a neighbor reference node thereof, and then calculating a path loss index n in a current monitoring area by using an RF wireless signal propagation model; according to the known reference node coordinates, comparing the measured distance between the reference nodes with the actual distance to obtain the relative ranging error of the RSSI; establishing a distance equation of the monitoring nodes, carrying out Taylor series expansion, adopting a weighted least squares (WLS) algorithm for processing, and updating parameter vectors. The method can effectively reduce distance measurement errors, can enable the positioning method based on RSSI distance measurement to be suitable for water quality monitoring systems in various different environments, and can meet the positioning requirements of water quality online monitoring systems with complex and severe network environments and limited positioning cost.

The invention relates to an RSSI (Received Signal Strength Indicator) ranging based WLS (WebLogic Server) node self-positioning method in a wireless sensor network, which comprises the following steps that: firstly, in a positioning process, a channel fading factor n is calculated by weighting; secondly, a distance between an unknown node and a beacon node is measured by RSSI ranging; and finally, a coordinate of the unknown node is estimated by a weighted least squares algorithm (WLS). Based on the same hardware complexity of the positioning algorithm and the least squares (LS) estimation algorithm, the positioning accuracy is greatly enhanced, therefore, the method provided by the invention is simple and easy to implement, and has a stronger practical value.

The invention provides a method and system for orthogonal anisotropy velocity inversion. The method comprises the steps that an imaging point gather and superposition data are collected; cross-correlation calculation is conducted in a user-defined processing time window through a model trace and each seismic data trace in the imaging point gather; cross-correlation calculation is conducted on eachcross-correlation time window of current seismic data; all the seismic data traces in the current imaging point gather are processed; according to residual time difference data and correlation coefficient data of the current imaging point gather and pre-stack time migration velocity field data, HTI anisotropy velocity parameters of the current imaging point gather on all zero offset data sample points are obtained through calculation by means of a weighted least square algorithm; VTI anisotropy velocity parameters are obtained according to HTI anisotropy velocities and residual time difference parts; and each imaging point gather is processed, and orthogonal anisotropy velocity inversion results of all the seismic data are obtained. The method has the advantages that the calculation efficiency is high, and the calculation result precision is high.

The present invention provides an NLOS (non-line of sight) transmission base station identification and positioning method based on side length residual errors. The method comprises the following steps: firstly dividing base stations into groups, and ensuring that each group comprises two base stations, the group number is represented by a formula, and the base station number is N; then calculating the virtual side length by using collected TOA and AOA estimated values according to a cosine theorem, calculating the difference value between the virtual side length and a measuring distance, and calculating a threshold by taking the difference value as the side length residual error; and then identifying NLOS transmission base stations and LOS transmission base stations by comparing the residual errors and the threshold values, finally estimating the location of an MS by using parameter measurement values of the LOS transmission base stations, and ensuring that an estimation algorithm adopts a two-step weighted least square algorithm. According to the NLOS transmission base station identification and positioning method based on the side length residual error provided by the invention, the errors can be effectively reduced, and the positioning accuracy can be improved.

The invention discloses a dynamic magnetic resonance rapid reconstruction method, which comprises the following steps: a first frame adopts high-precision sampling as a reference frame, and the firsttwo frames are rapidly reconstructed by adopting a DTV algorithm; CFT data fusion is carried out on a subsequent frame and a reconstructed second frame before reconstruction to generate a high-precision prediction image for the current frame, and then rapid reconstruction is carried out by using a total variation algorithm by using a residual image of the first frame and the prediction image. According to the invention, the redundancy characteristic of dMRI in the time-space domain is utilized; a weighted least square algorithm is optimized by adopting a PPCG technology; the sampling data of the k space is aggregated by using a CFT prediction algorithm; high-precision prediction is provided for a current frame, high-precision sampling of a first frame is combined as a reference image, rapid high-definition reconstruction of a dMRI imaging sequence is realized, and by supporting an online parallel reconstruction frame structure, the method can be easily combined with a multi-coil parallel imaging technology, and the reconstruction speed is further improved.

The invention provides an intelligent substation sampling data quality comprehensive evaluation method and system, and the method comprises the steps: obtaining merging unit data, measurement and control device data and PMU data in a substation, and forming multi-source redundant three-phase measurement under a unified time scale in the substation; three-phase linear state estimation of the transformer substation is carried out by adopting three-phase measurement of multi-source redundancy in the transformer substation and real-time on-off states of a transformer substation model and a circuit breaker, and a state estimation problem is solved by using a weighted least square algorithm; and performing comprehensive comparison according to a state estimation result, detecting and judging whether bad data exist in the measurement quantity by using Chii-square, and identifying the most probable bad measurement quantity by using a maximum normalized residual LNR method to obtain a data quality comprehensive analysis result. Based on the multi-interval, multi-type and available sampling data in the existing integrated monitoring system in the substation, the quality analysis and comprehensive evaluation of the sampling data of the intelligent substation are realized, and the operation reliability of the substation is improved.