50results about How to "Achieving High-Precision Estimation" patented technology

The invention discloses an interferometric synthetic aperture radar (InSAR) and global navigation satellite system (GNSS) weight determining method aiming at three-dimensional ground surface deformation estimation. The InSAR and GNSS weight determining method comprises the steps that 1, by utilizing ascending rail InSAR data and descending rail InSAR data of a to-be-monitored area and GNSS data ofthe to-be-monitored area, the function relationship between three-dimensional deformation d<0> of an unknown point and a certain quantity of the InSAR / GNSS data L of surrounding points is established based on a ground surface stress strain model and observed value imaging geometry; 2, K observed data in the ascending rail InSAR, descending rail InSAR and GNSS observed values L are subjected to relative weight determining, and an initial weight matrix W of all kinds of observed values of InSAR / GNSS is determined; 3, a precise weight matrix hat{W} between all kinds of observed values of InSAR / GNSS is estimated and determined through variance components, and high-precision three-dimensional deformation d<0> is solved based on the least squares criterion; and 4, as for each ground surface point, InSAR and GNSS fusion estimation of a high-precision three-dimensional ground surface deformation field is achieved through the step 1 to the step 3.

The invention discloses an ephemeris correction-based autonomous celestial navigation method for a deep space probe in a capturing stage. The method comprises the following steps: firstly, establishing an ephemeris error state model and an ephemeris error measurement model of a target celestial body, and measuring ephemeris error according to a position difference between a predicted celestial body image and an actual celestial body image; secondly, simultaneously taking the ephemeris error state model and an orbital dynamic model as a celestial navigation system state model, taking the ephemeris error measurement model and a starlight angular distance measurement model as measurement models of a celestial navigation system, estimating the position and speed of the probe and the ephemeris error of the target celestial body by a Unscented Kalman filtering method, feeding back the estimated ephemeris error to the state model, and correcting the ephemeris data of the target celestial body, thereby obtaining the position and speed of the probe, relative to the target celestial body and the heliocenter, after autonomously correcting the ephemeris error. The method provided by the invention belongs to the technical field of aerospace navigation, can perform on-line estimation on ephemeris error of celestial bodies and correct model error of the navigation system, and is suitable for the probe capturing stage.

The invention discloses a method for estimating the height and position of pedestrians in a multi-storey building based on a MEMS sensor, comprising: fixing a MEMS integrated sensing device on the pedestrian's lower limbs; the MEMS integrated sensing device collects acceleration data, angular velocity data and Pedestrian height data; multi-threshold detection method is used to determine the posture phase and swing phase of pedestrian gait motion; the vertical acceleration of the posture phase and swing phase is respectively corrected, and the speed of the posture phase is updated to zero, and the The corrected vertical acceleration is quadratically integrated to obtain the estimated height of the pedestrian's attitude phase and swing phase; it is judged whether there is a deviation between the estimated height data obtained by the attitude phase and the target height data measured by the microbarometer. If it is, the error linear compensation is performed on the estimated height obtained by the swing phase, and finally the updated pedestrian positioning data is obtained. The invention realizes the accurate estimation of pedestrian's height position based on one sensor node.

The invention belongs to the technical field of surveying science, and particularly discloses a steady parameter estimation method of a rational function model of a satellite remote sensing image. The method comprises the steps that a control point grid and a check point grid are established in the image coverage range by using a strict imaging geometric model and a global DEM; linearization is conducted on the RFM with parameters of the RFM serving as unknown numbers to obtain an error equation coefficient matrix, QR decomposition is conducted on the error equation coefficient matrix through the Householder conversion method, and a new parameter resolving equation is established; parameter resolving is conducted on the equation through the Levenberg-Marquardt method to obtain the needed parameters of the RFM; image coordinates corresponding to object space coordinates of the check point grid are calculated through the resolved RFM, the image coordinates are compared with original image coordinates in the check point grid, maximum errors, minimum errors and mean square errors in the row direction and the list direction of the image are counted, and the fitting precision of the model is estimated. By means of the method, the fitting precision which is superior to that obtained through the ridge estimation algorithm can be achieved.

A determining method for ultrahigh-accuracy attitude of a spacecraft multi-stage compound control system. The determining method comprises the following steps: (1) establishing an attitude constraintmodel between a star and a load as well as between the load and a fast reflective mirror of the spacecraft multi-stage compound control system; (2) establishing a relative attitude quaternion model between the star and the load as well as between the load and the fast reflective mirror; (3) judging whether a star guiding sensor has a measured value or not; (4) establishing a load attitude estimation error state equation if the star guiding sensor has no the measured value, estimating a load attitude by adopting a Kalman filtering method, and realizing determination on high accuracy of the loadattitude; (5) establishing a star attitude estimation error state equation, and realizing determination on high accuracy of a star attitude by adopting the Kalman filtering method; (6) estimating a load sight attitude by adopting a measured value qfm of the star guiding sensor if the star guiding sensor has the measured value; (7) establishing the load attitude estimation error state equation, estimating the load attitude by adopting the Kalman filtering method, and realizing the determination on high accuracy of the load attitude; (8) establishing the star attitude estimation error state equation.

The invention discloses a method for estimating the angle of arrival based on sparse Bayesian theory in the presence of mutual coupling, comprising: constructing a sparse signal model when there is mutual coupling of antenna arrays and a grid deviation of the arrival angle; initializing unknown parameters in the sparse signal model ;According to the current unknown parameter value, the joint probability distribution function is solved based on Bayesian theory, and the mean value and covariance matrix of the received signal are estimated; By maximizing the likelihood function, the variance of the noise and the variance of the received signal are estimated; the calculated The spatial spectrum of the received signal; by maximizing the likelihood function, estimating the grid deviation of the arrival angle, and updating the dictionary matrix when there is a grid deviation; estimating the variance of the mutual coupling vector of the array antenna and the mutual coupling vector of the array antenna; iteration The calculation stops until the set number of iterations is reached, and the spatial spectrum of the received signal and the solved angle of arrival of the received signal are output. The invention improves the performance of estimating the angle of arrival and realizes the high-precision estimation of the angle of arrival of the signal.