Interpolation Method for Complex RCS Data Based on Compressed Sensing

A technology of data interpolation and compressed sensing, which is applied in the direction of complex mathematical operations, code conversion, electrical components, etc., can solve the problems of increasing algorithm noise, increasing the constraint space range, and increasing computing memory and time, so as to suppress algorithm noise and shorten Effects of test time, guaranteed equivalence

CN108647183BActive Publication Date: 2021-09-24BEIJING INST OF ENVIRONMENTAL FEATURES
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Publication Date
2021-09-24

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Abstract

The invention relates to a complex RCS data interpolation method based on compressed sensing, and belongs to the technical field of comprehensive testing. A specific implementation of the method includes: constructing a complex domain reconstruction model according to the RCS measurement data; solving the complex domain reconstruction model to obtain the sparse distribution of the RCS data; reconstructing target frequency domain data based on the sparse distribution , realize complex RCS data interpolation. Compared with the traditional method of simply diagonalizing complex matrices, the invention does not reduce or increase the original constraint range, has fast processing speed and high precision, and can effectively shorten measurement time to improve RCS measurement efficiency.
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Description

technical field

[0001] The invention relates to the technical field of comprehensive testing, in particular to a complex RCS data interpolation method based on compressed sensing. Background technique

[0002] Traditional interpolation algorithms mainly include spline interpolation and Fourier transform method. Spline interpolation is a real number method and a pure interpolation algorithm. For darkroom RCS measurement data, it lacks physical concept and physical meaning support. The Fourier transform method has two defects. One is limited by the Nyquist sampling theory. To make the target expansion unambiguous in the distance and azimuth directions, the amount of sampled data cannot be reduced. The second is that the Fourier transform method is an overall algorithm. Even if the target signal is only in a small section of the unambiguous window, it must be transformed as a whole, and the algorithm efficiency is low. The radar target mostly satisfies the scattering center mo...

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Embodiment Construction

[0043] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments It is a part of embodiments of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0044] At present, the commonly used compressed sensing algorithm reconstruction model, especially the reconstruction algorithm (convex optimization algorithm) is aimed at real number domain data, while the data obtained by RCS (radar cross section) measurement is generally complex data. Based on this, the present invention provides a complex...