Design method of weak cross-correlation observation matrix of troposphere chromatography model

By designing a weak cross-correlation observation matrix, the problem of unsuitability of equations in the troposphere chromatography model is solved, the uniqueness of the solution of sparse coefficients and the stability of the compression perception model are ensured, and high-precision acquisition of troposphere information is achieved.

CN119716930AActive Publication Date: 2025-03-28XIAN UNIV OF POSTS & TELECOMM
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Patent Information

Application Number
CN202411861530.5
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-12-17
Publication Date
2025-03-28
Estimated Expiration
2044-12-17

AI Technical Summary

Technical Problem

Due to the many parameters to be estimated and the strong correlation of the observation of the chromatography region, the existing convective chromatography model has severe unsuitability in the equation, making it difficult to ensure the uniqueness of the solution sparse coefficient and the stability of the compression perception model.

Method used

Design a weak cross-correlation observation matrix, and reduce the cross-correlationship of the observation matrix through steps such as tomography meshing, random matrix correction and cross-correlation function measurement, ensuring the uniqueness of solving sparse coefficients and the stability of the compressed perception model.

Benefits of technology

By designing the weak cross-correlation observation matrix, the problem of unsuitability of the tomography model equation is solved, ensuring the uniqueness of the solution of sparse coefficients and the stability of the compressively perceived convective chromatography model.

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Abstract

The invention discloses a method for designing a weak cross-correlation observation matrix of a troposphere chromatography model, which comprises the following steps of: 1, carrying out chromatography grid division, and constructing an observation matrix # imgabs0 # according to a satellite signal direction; a second step, selecting Gaussian, Radaache, Bernoulli and other random matrixes, dividing the random matrixes into a left module and a right module, mixing and splicing the left module and the right module into a matrix, and correcting the observation matrix by a new random matrix # imgabs 1 # to obtain # imgabs 2 #; and 3, measuring the cross-correlation degree between the observation matrix # imgabs3 # and the adaptive dictionary matrix # imgabs4 # by using a cross-correlation function, judging whether convergence is carried out or not, if not, reconstructing a random matrix to correct the observation matrix, and judging the cross-correlation degree again until the two matrixes are converged. According to the method, aiming at the problem that the equation is seriously improper due to the fact that the chromatography model has many to-be-estimated parameters and strong correlation of the observed quantity of the chromatography area, the observation matrix with weak cross correlation is designed, the fact that the sparse coefficient has a unique solution can be guaranteed, and the stable solution of the compressed sensing troposphere chromatography model can also be guaranteed.
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