Improved high-resolution SAR (synthetic aperture radar) imaging self-focusing method

Abstract

The invention discloses an improved high-resolution SAR (synthetic aperture radar) imaging self-focusing method. The method mainly comprises the following steps that: range pulse compression, preliminary movement compensation and range direction FFT are sequentially performed on radar echo signals, so that movement compensated radar echo signals and the simplified form of the movement compensated radar echo signals can be obtained sequentially; the simplified form of the movement compensated radar echo signals is multiplied by an azimuth Dechirp function; two-dimension interpolation is performed along the range and azimuth directions respectively; after two-dimension interpolated radar echo signals are obtained, IFFT is performed along the range direction, so that phase history-domain data can be obtained; envelope error compensation of the phase history-domain data can be accomplished through adopting an image shift SAR self-focusing algorithm, the phase error of the phase history-domain data of which the envelope error compensation has been completed can be solved through utilizing a conjugate gradient algorithm; after the phase history-domain data of which the envelope error compensation and phase error compensation have been completed are obtained, IFFT is performed along the azimuth direction, so that a high-resolution SAR image with an excellent focusing effect can be obtained.

Description

technical field [0001] The invention belongs to the technical field of radar imaging, in particular to an improved self-focusing method for high-resolution SAR imaging, which is suitable for motion error compensation of airborne SAR imaging. Background technique [0002] The self-focusing method starts from the data itself, estimates the non-spatial variable phase error data that affects the imaging result, and compensates the non-spatial variable phase error data, so as to obtain good imaging results. [0003] Existing autofocus methods can be roughly divided into three categories, specifically: methods based on image offset, methods based on Phase Gradient Autofocus (PGA) and methods based on cost functions. Although the method based on image migration is easy to implement, when estimating complex motion errors in high-resolution SAR imaging, the estimation accuracy of motion errors cannot meet the requirements; the phase gradient self-focusing method is a motion compensat...

AI Technical Summary

Problems solved by technology

Although the method based on image migration is easy to implement, when estimating complex motion errors in high-resolution SAR imaging, the estimation accuracy of motion errors cannot meet the requirements; the phase gradient self-focusing method is a motion compensation process in SAR imaging The most commonly used self-focusing method, this method can accurately estimate any form of motion error for data containing isolated scattering points, but for data with low signal-to-noise ratio and no obvious strong scattering points in the scene, such as The motion error estimation performance of this method is also poor for the data obtained in desert and sea conditions; the calculation amount of the method based on the cost function is generally relatively large, and this method is easily affected by the characteristics of the cost function itself. less than good focus

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