Single-layer earth surface dielectric parameter and roughness parameter fast inversion combined optimization algorithm based on measured radar back scattering data

Abstract

The invention discloses a combined optimization algorithm of an inheritance multi-output support vector machine. The combined optimization algorithm combines with measured radar back scattering data for fast inversion of single-layer earth surface (root-mean-square height ksigma<1.5, and root-mean-square slope s<0.3) dielectric parameters and roughness parameters. The algorithm includes: using single-layer earth surface HH and VV measured polarizing radar back scattering coefficient data to obtain homo-polarization ratio; using a rough earth surface electromagnetic scattering small slope approximation method to calculate back homo-polarization ratio; combining a genetic algorithm with the small slope approximation homo-polarization ratio and the measured data to invert the earth surface dielectric constant; substituting the inversion result into an electromagnetic scattering integral equation model to generate a data file of back scattering coefficient changing with roughness; combining two kinds of measured polarized radar back scattering data to form a target function, using M-SVR optimization algorithm to invert the earth surface roughness parameters, and evaluating inversion errors and efficiency. By the combined optimization algorithm, real-time prediction of earth surface parameters can be achieved while inversion precision is guaranteed.

Description

technical field [0001] The invention relates to the technical field of microwave remote sensing, in particular to a joint optimization algorithm for rapid inversion of single-layer surface dielectric parameters and roughness parameters based on radar actual measurement data. Background technique [0002] The study of electromagnetic scattering and electromagnetic inverse scattering plays an extremely important role in microwave remote sensing. The radar technology of microwave remote sensing of the earth has made great progress in recent years. It can observe all-weather and all-weather, and has a wide application prospect. In microwave remote sensing of typical surface such as land and ocean, the backscatter echo is closely related to the physical parameters of the surface and soil moisture, which contains a lot of surface information. For example, the moisture content of soil can be obtained by using surface microwave remote sensing technology. , crop maturity, sea state, ...

AI Technical Summary

Problems solved by technology

At present, there are four main paths for inversion research: one is the empirical formula method, such as Oh model, Dubois model and Shi model, etc., but their respective scope of application is limited

Second, the optimization algorithm combines the surface electromagnetic scattering model and radar measured data to invert the dielectric parameters and roughness parameters of the rough surface. When the electromagnetic scattering model is more complex, the calculation speed is quite slow

The traditional support vector machine (SVM) can only perform inversion of surface single parameters, so the total inversion accuracy of multiple parameters cannot be guaranteed. For the situation where multiple surface parameters are unknown at the same time, SVM becomes powerless

Compared with SVM, M-SVR has multi-parameter inversion capability, and has the advantages of high precision and fast speed. According to the current domestic and foreign data, the application of M-SVR to surface electromagnetic parameter inversion has not been reported.

Images