A self-focusing method of ionospheric scintillation effect in low-frequency spaceborne SAR

Abstract

The invention provides a low-frequency-band satellite-borne SAR (Synthetic Aperture Radar) ionospheric scintillation effect self-focusing method. The technical scheme is characterized in that an SAR image polluted by a scintillation effect is divided into a plurality of sub-block SAR images along a distance direction; the size of the sub-block SAR images adopts a principle of limiting distance space variability of the scintillation effect in an acceptable range. Aiming at each sub-block SAR image, an optimization method is used for carrying out iterative optimization of entropy function of thesub-block SAR image, and the sub-block SAR image is subjected to phase compensation for one time in each iteration process. The method can be adapted to SAR images in any size scene; the calculationefficiency of algorithm is ensured; meanwhile, the SAR image self-focusing algorithm with good performance can still be maintained under the medium-intensity scintillation condition.

Description

technical field [0001] The invention relates to the technical field of microwave remote sensing, in particular to a self-focusing method for SAR (Synthetic Aperture Radar, Synthetic Aperture Radar) images affected by ionospheric scintillation effects. Background technique [0002] Spaceborne SAR is an important means of remote sensing observation. SAR operating in the low frequency band (P-band or L-band) has a strong penetrating ability and can penetrate densely vegetated rainforest and shallow surface soil. It is used in military reconnaissance, agricultural Detection, biomass measurement and geological observation and other fields have great application prospects. In recent years, major developed countries in the world are vigorously developing low-frequency spaceborne SAR. For example, the planned working frequency band of BIOMASS synthetic aperture radar of ESA (European Space Agency) is 435MHz, which is a typical P-band spaceborne SAR. The ALOS / PALSAR synthetic apertu...

AI Technical Summary

Problems solved by technology

Among them, the PGA algorithm is dependent on the strong point target in the image, and its robustness is poor

And the scintillation effect itself will cause the image to defocus in the azimuth direction, reducing the image contrast and making it more difficult to extract strong point information. Zhuo Li and JieChen have analyzed in "Performance Analysis of Phase Gradient Autofocus for Compensating Ionospheric Phase Scintillation in BIOMASS P-Band SAR Data" However, when the signal-to-noise ratio is less than 16dB, the PGA algorithm is invalid for medium-intensity flicker correction

The defect of the minimum entropy correction algorithm (see the literature "SAR image autofocus utilizing minimum-entropy criterion") is that it is dependent on the initial value, and it often fails to converge to the minimum value of the image entropy function

Images