308 results about "Weighted least squares method" patented technology

A method, system and computer program product for inverting boundary conditions for rock mass field in-situ stress computation for a geologic structure are disclosed. According to an embodiment, the current invention includes a method for inverting boundary conditions for rock mass field in-situ stress computation for a geologic structure, the method comprising: considering physical constraint of the geological structure; deriving and solving normal equations of penalized weighted least squares, said normal equations of penalized weighted least squares partially representing said physical constraint of the geological structure; and outputting boundary conditions and reproducing the rock mass field in-situ stress based on the result of said solved normal equations of penalized weighted least squares.

The present invention relates to a three-lane detection method based on image morphological segmentation and region growing. The method comprises: a method for, by using a shape of a lane mark and a relative gray level of a roadway, performing segmentation on the lane mark by means of image morphology; a method for fitting a vanishing point by using a weighted least square method; and a method for forming a region of interest (ROI) of the lane mark by a region growing method and iteratively searching for a feature point of the lane mark. According to the three-lane detection method based on image morphological segmentation and region growing, aimed at the problem of perception of a vehicle-mounted visual system of an intelligent vehicle to a multi-lane road in a process of driving on the urban structural multi-lane road, a method of carrying out image morphology preprocessing and carrying out iterative solution on the lane mark is adopted to adapt to a multi-lane environment. The method is novel in algorithm, high in adaptability, relatively high in illumination robustness, small in computation amount and easy to implement by programming, so that a module of the vehicle-mounted visual system is improved, and the efficiency and environmental adaptability of an intelligent vehicle environment sensing module are further improved.

The invention discloses a method for defending false-data injection attacks in the direct-current state estimation of an electrical power system, which belongs to the technical fields of electrical-power system safety and control and comprises the following steps of: estimating the real-time state of a direct-current system by a weighted least square method, and filtering measuring noise and random disturbance; processing a state-estimating result by a maximum standard residual-error detecting method, and detecting and identifying bad data in quantity measurement; and calculating the sensor quantity-measuring combination which is most easily destroyed by the false-data injection attacks by a heuristic algorithm, carrying out encryption protection for a group of sensors, and blocking the false-data injection attacks from occurring from a source. The method can be used for accurately and rapidly defending the false-data injection attacks in the state estimation of the electrical power system, and the state-estimating accuracy and safety of the electrical power system are improved.

The invention relates to a robust state estimation method in an electric power system based on exponential type objective function, belonging to the field of electric power system dispatching automation. The method comprises the following steps: building a new state estimation mathematical model of the exponential type objective function according to the electric network model of the actual electric network and real-time measuring data; estimating the busbar voltage and phase angle of the electric network, thus calculating the active power and reactive power of the circuit, a transformer, a generator, loads and other devices. The invention can automatically realize that the impact of measurement with big errors on the objective function tends to zero, while the impact of correct measurement on the objective function tends to one. Therefore, the state estimation algorithm proposed in the invention can process in the absence of bad data identification, thus the invention has convenient realization and high computing efficiency; furthermore, if the system is absent of bad data, the estimated performance in the invention is similar to the classical weighted least squares method.

The invention discloses a method and a system for ultra wide band positioning in a coal mine. The method is based on a nonparametric non line of sight (NLOS) identification and ultra wide band (UWB) positioning technology of a weighted least square method, a nonparametric NLOS identification method is used for performing NLOS identification, corresponding weighting factors are distributed according to NLOS identification results, a novel weighted least square method positioning algorithm is constructed, and the algorithm is used for estimating the position of a goal node. The system comprises a browser server of a remote monitoring layer, a data server, a ground monitoring terminal, a switch, a goal node of an on-site monitoring layer, a reference node, a gateway and a base station, wherein devices applied in the mine are all safe in nature. The method and the system for the ultra wide band positioning in the coal mine has the advantages of being strong in anti-interference capacity, high in positioning accuracy, low in cost, simple in system device structure, low in energy consumption and suitable for roadway working environment.

The invention discloses an adaptive Kalman filtering method oriented for WiFi / PDR indoor integrated positioning. The method comprises: first, holding by a user a terminal device in a targeted area to receive the RSSI from each AP; in a lognormal distribution path loss model, using the weighted least squares method to obtain the location of the user and at the same time, through the estimation model in the PDR algorithm, obtaining the location of the user; then using the adaptive Kalman filtering to integrate the positioning information based on the propagation model with the positioning information from PDR for multiple times to obtain the best location of the user, wherein the adaptive Kalman filtering is reflected in the feedback mechanism, that is, each integration positioning result dynamically corrects the path loss index and other parameters of the weighted least squares method so as to ultimately make the propagation model more in line with the indoor environment. The method solves the problems of low positioning accuracy of only using the WiFi and of the cumulative errors existing in PDR under an indoor environment, and the method also can track the path loss index of the propagation model in real time and enhances the stability of positioning performance.

Methods for reducing the resources needed to detect and identify faulty pseudorange measurements in a GNSS receiver are described. In a Receiver Autonomous Integrity Monitoring (RAIM) method, a position solution is calculated using a weighted least squares method on measurements from satellites of one or more GNSS constellations. A test statistic is calculated from residuals and a threshold is calculated based on a probability function. If the test statistic is greater than or equal to the threshold, a subset is selected from the set of pseudorange measurements using a metric indicative of possible measurement error. A measurement is selected from the subset using a metric indicative of signal strength or some other metric and discarded from the set of pseudorange measurements. If the number of measurements remaining in the set of pseudorange measurements is greater than five, the method loops back to the step of calculating a position solution.

The invention relates to a method for combined compensating the sampling frequency bias and the carrier wave frequency bias, used in the orthogonal frequency division multiplexing system, and a relative device, wherein based on the phase bias of pilot sub carrier wave, the invention uses the weight least square method and another two simplify methods to estimate the slope and intercept of phase bias curvature of sub carrier wave, whose weight is decided by the increment function or signal / noise ratio of pilot channel; compensates the phase bias of data sub carrier wave via the estimated phase bias curvature; and supports the accurate estimated value of FFT window drift based on the curvature slop, to adjust the position of FFT window by FFT window controller, to compensate the sampling frequency bias; then based on the curvature intercept, supports the estimated value of carrier wave frequency bias, to feedback and compensate the carrier wave frequency bias. The invention can improve the compensate accuracy of sampling frequency bias and carrier wave frequency bias under multi-path condition.

The invention provides a five-axis side milling machining cutter path smoothing method. The method comprises calculating the initial cutter location, and calculating the machine tool turning axle angle corresponding to the direction of a cutter axis through a dynamitic model of a specific machine tool; performing interpolation for the machine tool turning axle angle of the initial cutter location and the cutter nose point location, and obtaining a cutter nose point location trajectory and a machine tool rotation angle change curve; according to the cutter nose point location trajectory and the cutter axis vector, showing a side milling machining cutter path; calculating the rigidity matrix, corresponding to the cutter path, of the machine tool rotation angle curve; according to a differential evolution algorithm, calculating the point that the distance between the point to the cutter enveloping surface is shortest among the points on the design surface; and according to a weighted least square method, establishing a five-axis side milling machining cutter path smoothing model, and obtaining an optimized the initial cutter location and the cutter nose point location curve and a smooth machine tool rotation angle curve after solution. The five-axis side milling machining cutter path smoothing method solves the problem about smoothing and geometric deviation control of the five-axis side milling machining cutter path, and is suitable for five-axis side milling machining on a free form surface, a ruled surface or a curved surface similar to the ruled surface.

The invention relates to the field of SCARA robot kinetic parameter identification, and discloses an improved SCARA robot kinetic parameter identification method. A Lagrange method is adopted for establishing an SCARA robot integral kinetic model comprising a friction term, and the SCARA robot integral kinetic model is subjected to linearization. The five-order fourier series is adopted as the stimulation track basic form, the polynomial with 5 degree is used for replacing the constant term in the traditional fourier series, and the joint angular velocity and angular acceleration are zero at the track start and stop time; and the minimum observing matrix conditional number serves as the target, and to enhance the global optimization capability, various coefficients of the stimulation trackare optimized through the niched pareto genetic algorithm based on the crowding-out mechanism. To avoid the transmission error directly caused to the joint angle two-time differential, the sampled joint angular velocity data are fitted into the fourier series form, and a joint acceleration signal is obtained through the differential. Considering the measuring noise influence, the WLS is adopted as the parameter estimation method.

The invention discloses a measurement device and a measurement method of a torsional vibration modal of a numerical control machine. The measurement device comprises a Hall sensor, a data acquisition card, a high-resolution rotary encoder, a counter, a parametric recognition module and a computer. The measurement method comprises the following steps: generating a series of sinusoidal waves with the same vibration amplitude and the same variable frequency by utilizing a numerical control device; measuring the current signal of a servo motor to obtain the drive torque of the servo motor; measuring the rotational angular velocity of a screw rod through the high-precision rotary encoder; respectively carrying out Fourier transform on a sampled angle velocity signal and the motor torque, and solving the specific value of the sampled angle velocity signal to the motor torque; solving a transfer function between all measuring points on the motor torque and the screw rod; and identifying the torsional vibration modal parameter of a motor rotor-screw rod system by utilizing a weighted least squares method to obtain inherent frequency and a modal shape of each order of torsional vibration. By the measurement device and the measurement method, the torsional vibration modal of a ball screw feeding drive mechanism of the numerical control machine can be rapidly and accurately measured, andthe torsional dynamical characteristics are analyzed; the measurement device and the measurement method provide the scientific basis for the design of the ball-screw feeding drive mechanism and the vibration control, and are applied to the measurement of the torsional vibration modal of the numerical control machine.

For coherent fiber optic communications, the nonlinear XPolM impairment is the most important issue to realize over-100 Gbps high-speed transmissions. A method provides a way to cancel time-varying XPolM crosstalk by introducing multi-stage adaptive mechanism. In the method, a low-complexity adaptive filtering based on recursive least-squares (RLS) first tracks the time-varying crosstalk along with the per-survivor trellis-state decoding. The estimated channel and the decoded data are then used to calculate the empirical covariance, which is in turn exploited to obtain more accurate channel estimates by means of optimal-weighted least-squares. This is performed with a low-complexity processing over frequency domain with fast Fourier transform. The performance is significantly improved with turbo principle decoding, more specifically, iterative decoding and iterative estimation over a block.

The invention discloses a method for improving robot parameter identification accuracy and belongs to the field of industrial robot control. The method comprises optimizing stimulation trajectories through a genetic algorithm; stimulate a robot to perform cyclical movement according to the optimized stimulation trajectories; sampling actual joint positions and actual torque data during moving and processing the data to obtain torque values, joint positions, joint speeds and joint accelerated speeds which are high in signal to noise ratio; establishing a dynamic linear model, and identifying all parameters related to joint dynamics through a weighted least square method. By the aid of the method, the actual trajectory Fourier series form is fit through an inverse method, and accordingly, speeds and accelerated speeds which cannot be obtained directly in experiments can be obtained conveniently, noise signals in sampling position signals and torque signals can be eliminated through an equalization method, the signal to noise ratio is improved and the robot parameter identification accuracy is improved.

The invention discloses a blind camera shake deblurring method based on the L0 sparse prior, and belongs to the technical field of digital image processing. The blind camera shake deblurring method is a method for deblurring blurred images caused by camera shaking, and various space-unchanged camera shaking blurred kernels, namely the point spread functions, can be estimated. The blind camera shake deblurring method solves the problem that a current variational bayes estimation method is high in computing complexity and solves the problem that a current maximum posteriori estimation method lacks strict optimization theory supports. The blind camera shake deblurring method comprises the steps of firstly, introducing remarkable edge sparse prior based on the L0 norm, and using the iterative hard threshold compressed method to achieve recessive automatic prediction of remarkable edge characteristics, secondly, introducing camera shake blurred kernel sparse prior, and using the iterative repeated weighted least square method to achieve rapid estimation of the blurred kernels, and finally, using the image non-blind deblurring method based on super-Laplacian prior to obtain a high-quality deblurred image. The flow diagram of the blind camera shake deblurring method is shown in the figure 1.

A method for positioning a collection of nodes within a wireless sensor network in which each node measures Respective Strength of Signals (RSSs), from its neighboring nodes, and channels linking regular nodes and its neighboring nodes are classified into different categories and are allocated path loss parameters accordingly. Distances separating each regular node from each of its neighboring nodes, and respective variances thereof, are estimated on the basis of the measured RSSs and the allocated path loss parameters. The positions of the regular nodes are then estimated by Weighted Least Square, optimization where the distances to be matched and the variances used for the weighting are those previously estimated.

The invention discloses a device for identifying kinetic parameters of terminal loads of a six-degree-of-freedom robot. The device comprises a six-axis industrial robot, a plurality of loads of different masses and a real-time control system, wherein the plurality of loads of different masses are alternatively arranged on the terminal of the six-axis industrial robot, the real-time control system is used for implementing millisecond level real-time motion data collection of the robot, and collected real-time motion data include an encoder value and a torque value. The invention further discloses a method for identifying the kinetic parameters of the terminal loads of the six-degree-of-freedom robot. According to the device and the method, data sampling is performed by adopting an optimized excited track, a kinetic model is established according to a Lagrange equation, and identification parameters are solved by adopting a weighted least square method; a sensing system adopts the efficient real-time control system, the millisecond level real-time data collection of the robot including displacement, motor output and the like can be realized, the data collection quantity can be extended, the characteristic of variability is provided, and the identification of the kinetic parameters of the terminal loads of the industrial robot is satisfied.

The invention discloses a robust passive passiveness target positioning method based on multiple frequency points, and belongs to the technical field of target detection and positioning in a wireless network. The method detects an attenuation link through measurement of a variable quantity of an RSS value of a link on the multiple frequency points, deletes an interference link through coarse positioning of a target to obtain a shadow attenuation link set, and then performs accurate positioning on the target by utilizing a weighted least square method. Compared with attenuation link detection under a single frequency point, attenuation link detection adopted in the method based on the multiple frequency points has better performance in indoor multi-path environment, can improve detection performance and positioning precision of the target in a monitoring region, and can reduce the false alarm probability of a system.

The invention discloses a positioning method based on arrival time of unknown starting time in the non-line-of-sight environment. The method comprises steps of firstly establishing a model of a signal transmission distance between a target source and each sensor; obtaining a description of the measurement noise based on the model; according to the description of the measurement noise, using the robust weighted least squares method under the worst case to obtain the positioning problem in the environment of unknown signal transmission start time and non-line-of-sight errors, and converting the positioning problem into a non-convex positioning problem; by introducing auxiliary variables and using the second-order cone relaxation method, obtaining a second-order cone programming problem; and finally, using the interior point method to solve the second-order cone programming problem to get the final estimation value of the coordinate position of the target source in the reference coordinate system. The method has the advantages of being capable of simultaneously solving the problems of the unknown signal transmission start time and the non-line-of-sight errors so as to improve the positioning accuracy.

The invention discloses a method for defending a data integrity attack in direct state estimation of a power system. The method comprises the following steps: estimating a real-time state of a direct current system by using a weighted least square method; constructing a minimum cost data integrity attack model to simulate the behavior of an attacker; resolving the minimum cost data integrity attack by using an algorithm based on linear transformation to obtain an optimal attack vector at the moment; if the current optimal attack vector is obtained, realizing a PMU optimized configuration defense strategy based on a greedy algorithm, and after the configuration is completed, the occurrence of the data integrity attack is prevented from the source, and meanwhile, the complete observability of the system is guaranteed. By adopting the method disclosed by the invention, the data integrity attack in the direct state estimation of the power system can be accurately and quickly defended, and the accuracy and security of the state estimation of the power system are improved.

The invention belongs to the field of traffic road environment sensing in the intelligent automobile technology, and relates to a road edge detection method based on three-dimensional laser radar, comprising the following steps: acquiring point cloud data of the surrounding road environment by using the three-dimensional laser radar installed on the vehicle, adopting a random sampling consistencyalgorithm to segment the ground; setting a wider threshold according to various geometric features of the road edge for judgment, and extracting the candidate points of the road edge by using the neighborhood relationship between the respective scanning points of the same scanning layer; clustering the candidate points of the road edge and removing the dense and isolated noise points by using a density-based clustering algorithm according to the continuous feature about density and rod direction of the data points of the road edge; and finally fitting the qualified candidate points of the roadedge by weighted least squares to improve the fitting accuracy. The method extracts candidate points of the road edge according to the plurality of features of the road edge, and comprehensively considers the continuous feature of the road edge in the density and the road direction to de-noise, so that the final detection error is small and the precision is high.

The invention discloses a cognitive radar optimal waveform design method suitable for parameter estimation. The cognitive radar optimal waveform design method suitable for parameter estimation comprises the steps of building a channel model by use of actual target impulse response more consistent with the actual situation, and obtaining the energy spectrum density of the desired waveform by use of a water injection method according to the channel model so that the maximum target information quantity can be obtained from echo, taking the energy spectrum density and time-domain complex waveform amplitude as constant constraint conditions and obtaining the time-domain complex waveform of constant amplitude by use of an iteratively weighted least square method without wasting the power of a transmitter, next, transmitting the designed time-domain complex waveform by use of a radar to obtain target echo and performing parameter estimation by use of the target echo, after the expiry of the accumulated time of estimation of one parameter, updating the target impulse response by use of the current target echo and carrying out waveform design and transmission again so that the waveform transmitted at present changes along with the change of the target and the environment, and guaranteeing that the target echo obtained at present always contains the maximum target information quantity so that target parameter estimation can be carried out favorably.

The invention puts forward a virtual studio mobile robot visual localization method based on improved Apriltag tags, comprising the following steps: adding four uniformly-sized ring markers at the appropriate length of quadrilateral diagonal extension cords of a tag; calibrating a camera; acquiring tag images: preprocessing the acquired images; carrying out threshold processing on ROI region extraction; identifying elliptical markers; extracting the ROI region; carrying out threshold processing on the minimum rectangular area surrounding the four points which is the ROI tag area of the tag images with the coordinates of four ellipse centers on the improved tags as the benchmark; extracting tag corner points and fitting the extracted straight lines by the weighted least square method, calculating intersection points of straight lines to obtain subpixel-level corner point coordinate, and extracting image coordinates of the tag corner points; reading the coded message of the tags according to the extracted image coordinates of the corner points, obtaining world coordinates of the corner points, and obtaining the pose of a robot by coordinate transformation. The method of the inventionhelps reduce the data size of the identification tags and improve the real-time performance of identification.

The invention discloses an image interpolation method capable of improving image resolution and a device utilizing the image interpolation method, aiming to overcome defects at boundaries of interpolated images in the prior art. The image interpolation method capable of improving image resolution includes steps of determining similarity probability weight between all pixels in a local window and the reference pixel, modulating contribution of each pixel to the integral error in optimization estimation according to the similarity probability weight, and finally calculating all the pixel values to be estimated in the local window by estimating according to the weighted least square process. Since the similarity probability weight is introduced to serve as the weight for estimation of high-resolution pixels, estimation error is minimized, and defects at the boundaries are reduced.

The invention discloses a visible light image and high-spectrum image registering method which comprises the following steps: performing multi-scale decomposition on a visible light image to form a low-resolution visible light image; generating a high-spectrum image significant waveband image according to the high-spectrum image; extracting SIFT (scale invariant feature transform) features, multi-scale angular point features and surface point features from the low-resolution visible light image and high-spectrum image significant waveband image; matching the SIFT features and removing exterior points; obtaining a transformation model by use of the matched SIFT feature pair; extracting the multi-scale angular point features and surface point features based on an image block pair by taking a registered transformation model of the previous layer as an initial transformation model of the current layer on each layer of visible light image and high-spectrum image significant waveband image; selecting the transformation type and obtaining a transformation parameter according to the initial transformation and the multi-scale angular point features and surface point features in combination with an iteration re-weighted least square method; and transforming the high-spectrum image according to the transformation model to obtain the transformed high-spectrum image.

The invention provides an electric power system operation state detecting method based on dynamic partitioning. The method includes the following steps that a power grid is partitioned dynamically according to network topological changes; states of all partitions are estimated through a weighted least square method; the electric power system operation state is detected according to the state estimation results. The power grid system topological changes can be rapidly responded to achieve dynamic partitioning of the power grid, the influence on the state estimation results of other areas by measurement data errors in a certain area is reduced, and the accuracy of total state estimation of power grid operation basis data is improved, so that it is ensured that the detected the electric power system operation state is free of errors.

The invention belongs to the technical field of data fusion, and provides a data fusion method and device for multi-source heterogeneous sensors. The method comprises the steps that measurement data of the various sensors are acquired, and time alignment is carried out on measurement data which are asynchronous in time and inconsistent in frequency through the spline fitting method; the measurement data obtained after alignment are grouped according to the classes and precision of the sensors; intra-group or inter-group combination is carried out on the grouped data, integrated measurement data of a target are provided, and preliminary estimation is carried out on the position of the target; linear transformation is carried out on a measurement equation with the preliminary estimation value of the position of the target as a reference point, and secondary estimation is carried out on the position of the target based on the weighted least square method. According to the data fusion method and device for the multi-source heterogeneous sensors, the three-layer fusion locating strategy is adopted, a monitoring system can acquire a high-precision target location value quickly, various kinds of target information collected by the acoustic / optical / electric sensors or other types of sensors at the front end of the system are fused more efficiently, and therefore the monitoring and commanding efficiency is improved.

The present invention provides an improved DV-Hop positioning method based on the hop count threshold to optimize the average hop distance. Firstly, the hop count threshold is calculated, and considering the influence of other anchor nodes other than the nearest anchor node in the local and global ranges, the DV-Hop location is selected according to the threshold value. The optimal corrected average hop distance is used to estimate the distance, and after combined optimization of the anchor nodes within the single-hop communication radius participating in the positioning, the centroid algorithm is used to obtain an estimated coordinate, and the weighted least square method is used to obtain another estimated coordinate, and finally The arithmetic mean of the two estimated coordinates is used as the positioning coordinates of the unknown node. Simulation experiments show that the present invention can more effectively reduce the average node positioning error and improve the positioning accuracy.

The invention discloses an inertial navigation assisted Beidou three-frequency carrier phase whole-cycle ambiguity calculation method. The method comprises the steps of firstly determining BDS three-frequency combination carrier phase double difference and a pseudo-range double difference observation model, and obtaining pseudo-range and carrier phase observation values; then taking different scaling factor values, and performing linear combination on the pseudo-range observation quantity and the carrier phase observation quantity to obtain a narrow-lane, wide-lane and ultra-wide lane carrierphase and pseudo-range observation equation and a carrier phase and pseudo-range observation equation under an ionized layer independent and geometric independent model; obtaining an INS observation equation by using inertial navigation; and simultaneously setting the carrier phase and pseudo-rang observation equations and the INS observation equation, and solving the equations by using a weightedleast square method to obtain a floating point solution of the whole-cycle ambiguity; and finally solving an integer value of the whole-cycle ambiguity by using the LAMBDA. The method introduces theinertial navigation information and calculates the solution by using redundancy of the equations, thereby being capable of effectively improving the solving precision of the whole-cycle ambiguity value, and being applicable to a high-precision positioning system of the Beidou satellite system.