6 results about "Data covariance matrix" patented technology

The application discloses a constant beam adaptive beam forming method and system based on frequency difference, and the method comprises the following steps: segmenting FFT of time domain data of a target signal, converting the time domain data into frequency domain data, and calculating a data covariance matrix for each frequency point; estimating the azimuth of the target by using the data covariance matrix of each frequency point to obtain an estimated value of the target azimuth; generating a Gaussian random sequence with the same length as the array receiving signal as a reference signal, and reconstructing the array output of the reference signal according to the target azimuth estimated value; performing conjugate multiplication on the array output containing the target signal and the reconstructed array output of the reference signal to obtain the array output based on the frequency difference, and calculating the covariance matrix of the frequency difference output; calculating the weight value of the adaptive beam according to the covariance matrix of the frequency difference output to form the constant beam width adaptive beam. The application is simple and convenient, has small calculation amount, and can improve practicability.

The invention provides a saline-alkali cultivated land quality evaluation method and system, and relates to the technical field of saline-alkali cultivated land quality evaluation method.The saline-alkali cultivated land quality evaluation method comprises the steps that a sodium ion concentration gradient coefficient of each grid point is calculated through a central difference method, and a chloride ion space variation coefficient of each grid point is constructed through a regional averaging method; constructing a data characteristic matrix by adopting a principal component analysis method, and determining a sodium ion concentration gradient coefficient and a weight coefficient occupied by values of grid points; and calculating the quality index of any position of the grid by adopting a bilinear interpolation method, and calculating the comprehensive quality index of the whole saline-alkali cultivated land by adopting a global weighted integral method. On the basis of characteristic decomposition of a data covariance matrix, principal component weights of sodium ion gradients and values are automatically extracted, and human intervention is eliminated; capturing spatial heterogeneity through a region averaging method, and identifying local salinization hotspots; and bilinear interpolation is adopted to ensure the continuity and smoothness of the quality index field.

The application provides an underwater DOA estimation method, system, device and medium based on SKLD convex modeling, which comprises the following steps: constructing a sensor array received signal model according to a steering vector of a signal source; based on the difference between an observation data covariance matrix and a parameterized model covariance matrix, selecting a symmetric divergence as an initial objective function for measuring the difference; imposing a sparsity constraint on the initial objective function to form a regularized optimization problem, introducing a linear matrix inequality constraint, equivalently reconstructing the regularized optimization problem into a convex semi-definite programming problem, and taking the convex semi-definite programming problem as an optimization objective function; based on the sensor array received signal model, constructing a positive definite matrix by using sampling data; inputting the positive definite matrix into the optimization objective function to obtain an optimal objective function, obtaining a spatial spectrum distribution result based on the optimal objective function, and taking a spectral peak value of the spatial spectrum distribution result as an estimation result of a target direction.

The application discloses an automatic history matching method based on improved ensemble smoother multiple data assimilation, and relates to the technical field of petroleum engineering.The application firstly constructs multiple reservoir models, sets prior models, real models and initial inflation factors, obtains the production of each reservoir model by using numerical simulation of the reservoir model, calculates the residual error, improves the ensemble smoother based on the singular value decomposition of the modified data covariance matrix, the disturbance enhancement of the production observation data, the adaptive learning rate matrix scaling and the geological boundary constraint, updates the permeability of each reservoir model and performs numerical simulation again, judges whether the inflation factor meets the preset condition after updating the inflation factor, continues iteration if the preset condition is met, uses the updated inflation factor of the current iteration if the preset condition is not met, and ends the iteration, and finally outputs the updated permeability field of each reservoir model, so that the problems of parameter overshoot, covariance statistical deviation and low calculation efficiency in reservoir history matching are solved, and the history matching of complex reservoir production parameters is facilitated.

This invention discloses a meshless DOA estimation method for coherent signals based on coprime matrices. The method first averages the diagonal elements of the covariance matrix of the received data from the array, then reconstructs the Toeplitz matrix based on this average, and finally reconstructs the low-rank matrix using its Toeplitz structure. Next, the trace norm of the positive semi-definite matrix is ​​used to relax the non-convex low-rank matrix reconstruction problem, and the rank recovery matrix is ​​obtained using the convex optimization CVX toolbox. Finally, the DOA is estimated using the ESPRIT algorithm. Compared with traditional methods, this method does not require mesh generation, has stronger decoherence capabilities, and can accurately estimate the azimuth of coherent signals even under conditions of low signal-to-noise ratio, few snapshots, and small signal incident angle intervals. It has significant application value in underwater moorings or mobile observation platforms for ocean observation.

The invention discloses a co-prime array-based suppression-deception mixed interference detection and suppression method, which comprises the following steps of: firstly, calculating a data covariance matrix after noise weakening based on the periodic stationary characteristic of a navigation signal, then, carrying out vectorization and redundancy elimination processing on the covariance matrix, and further constructing a virtual array equivalent receiving signal model; the method comprises the following steps of: selecting a continuous part of the matrix to carry out spatial solution smoothing operation to recover the rank of the matrix, and then taking the discrete condition of a characteristic value of the matrix as a deception jamming detection quantity, and finishing the detection and suppression of the suppressing jamming and the deception jamming in cooperation with a multiple signal classification (MUSIC) algorithm and a signal subspace projection algorithm. The method can give consideration to the detection and suppression of suppressing interference and deception interference in a suppressing-deception mixed interference scene, and has the advantages of high interference detection rate and high-precision DOA estimation.