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3789 results about "Least squares" patented technology

The method of least squares is a standard approach in regression analysis to approximate the solution of overdetermined systems, i.e., sets of equations in which there are more equations than unknowns. "Least squares" means that the overall solution minimizes the sum of the squares of the residuals made in the results of every single equation.

Method and apparatus of a self-configured, model-based adaptive, predictive controller for multi-zone regulation systems

A control system simultaneously controls a multi-zone process with a self-adaptive model predictive controller (MPC), such as temperature control within a plastic injection molding system. The controller is initialized with basic system information. A pre-identification procedure determines a suggested system sampling rate, delays or “dead times” for each zone and initial system model matrix coefficients necessary for operation of the control predictions. The recursive least squares based system model update, control variable predictions and calculations of the control horizon values are preferably executed in real time by using matrix calculation basic functions implemented and optimized for being used in a S7 environment by a Siemens PLC. The number of predictions and the horizon of the control steps required to achieve the setpoint are significantly high to achieve smooth and robust control. Several matrix calculations, including an inverse matrix procedure performed at each sample pulse and for each individual zone determine the MPC gain matrices needed to bring the system with minimum control effort and variations to the final setpoint. Corrective signals, based on the predictive model and the minimization criteria explained above, are issued to adjust system heating/cooling outputs at the next sample time occurrence, so as to bring the system to the desired set point. The process is repeated continuously at each sample pulse.

Remote high-precision independent combined navigation locating method

The invention relates to a remote high precision autonomous integrated navigation and positioning method, which is characterized in that a Strapdown Inertial Navigation System (SINS) is used as a main navigation system during the whole flight course of the aircraft, assisted by 3D high precision position and attitude angle information provided by celestial navigation system (CNS) based on the least square differential correction in boost phase (or middle segment). In reentry phase (terminal), using the characteristics of synthetic aperture radar (SAR), such as strong penetration capability, high resolving precision and all-weather, the SINS can be corrected through accurate location information and course information provided by SAR scene matching after motion compensation when the aircraft reentry into atmospheres, so the impact point (hit) accuracy of the aircraft can be increased and the invention has remarkable effects of eliminating or decreasing non-guidance error. The invention has advantages of autonomy and high precision, which can be used for improving remote ballistic missile, remote cruise missile, navigation and positioning accuracy of remote aircraft, such as long-endurance unmanned aerial vehicle, etc.

Circular target circular center positioning method

The invention discloses a circle center locating method of a circular target, mainly relating to a great deal of target identification and target location. Firstly, rough circle center location is carried out to an image by using a simple contour centroid method, a key square region is extracted as a region of interest according to the information of a rough location circle center and a rough location radius, and pixel-level edge location is carried out to the circular target in the region of interest by a canny operator; then sub-pixel location is carried out to the circular target according to the geometric features and the gray information of the circle, therefore, a precise coordinate of sub-pixel edge points is obtained; after that, a curvature filtering method and an average filtering method are respectively used for filtering 'isolated points' and noise occurring in the sub-pixel edge points; finally, a least squares method is utilized to fit a circle to the filtered sub-pixel edge points so as to obtain the final circular center and radius. The method not only effectively improves the precision of circle center location, but also improves the robustness thereof, thus further improving the measurement precision of a measurement system and perfecting the stability of the measurement system.
Owner:南通欧特建材设备有限公司 +1

SAR image registration method based on SIFT and normalized mutual information

ActiveCN103839265AImage analysisFeature vectorNormalized mutual information
The invention provides an SAR image registration method based on SIFT and normalized mutual information. The method includes the steps that firstly, a standard image I1 and an image to be registered I2 are input and are respectively pre-processed; secondly, features of the pre-processed image I1 and features of the pre-processed image I2 are extracted according to the MM-SIFT method to acquire initial feature point pairs Fc and SIFT feature vectors Fv1 and Fv2; thirdly, initial matching is carried out through the Fv1 and the Fv2; fourthly, the Fc is screened for the second time according to the RANSAC strategy of a homography matrix model, final correct matching point pairs Fm are acquired, and a registration parameter pr is worked out according to the least square method; fifthly, I2 is subjected to space conversion through affine transformation, and a roughly-registered image I3 is acquired through interpolation and resampling; sixthly, pr serves as the initial value of normalization information registration, I1 and I2 are subjected to fine registration through the normalized mutual information method, a final registration parameter pr1 is worked out, and a registered image I4 is output. The method can be quickly, effectively and stably carried out, and SAR image registration precision and robustness are improved.

Method for improving earth surface shape change monitoring precision of InSAR (Interferometric Synthetic Aperture Radar) technology based on high-precision DEM (Digital Elevation Model)

The invention discloses a method for improving earth surface shape change monitoring precision of an InSAR (Interferometric Synthetic Aperture Radar) technology based on a high-precision DEM (Digital Elevation Model). The method comprises five steps below: step 1, generating an interferogram by using radar data; step 2, generating a differential interference phase diagram; step 3, establishing error phases and performing feature analysis; step 4, establishing an error phase optimal function calibration model; step 5, recovering earth surface shape change information of a monitoring region based on results of steps 2 and 4. According to the invention, the error phases and elevation values or the error phases, the elevations and coordinate values along a distance/azimuth of different regions of a research region are extracted, the optimal function calibration models of the error phases of corresponding regions are established respectively based on a least square method, and a simulative error phase is finally removed from the differential interference phase diagram to further recover shape change information along a direction of a sight line of a radar in the monitoring region. The method for improving the earth surface shape change monitoring precision of the InSAR technology based on the high-precision DEM has practical value and wide application foreground in the application field of a satellite borne synthetic aperture radar monitoring technology for earth surface shape change.

Method for optimizing WLAN (Wireless Local Area Network) indoor ANN (Artificial Neural Network) positioning based on FCM (fuzzy C-mean) and least-squares curve surface fitting methods

InactiveCN101778399ARealize terminal location positioningNetwork topologiesPhysical realisationAlgorithmEuclidean distance
The invention discloses a method for optimizing WLAN (Wireless Local Area Network) indoor ANN (Artificial Neural Network) positioning based on FCM (fuzzy C-means) and least-squares curve surface fitting methods, relating to an indoor positioning method used for indoor positioning and aiming to solve generalization capability reduction of an ANN system caused by singular reference points existing in a training sample space. The method comprises the following steps of carrying out clustering on pre-labeled reference points based on the FCM method to confirm corresponding clustering centers and membership degree of different reference points to clustering centers thereof; obtaining the space position of the singular reference points in a target positioning area on the basis of carrying out quantitative processing and similarity calculation on the membership degree of the reference points; updating positioning fingerprint database by utilizing the least-squares curve surface fitting method to reject abrupt change points in an intensity distribution chart; estimating the cluster of a terminal on the basis of calculating the Euclidean distance between signal intensity samples collected online and different clustering centers; and finally accurately estimating the terminal by utilizing corresponding ANN subsystems.
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