Linear array SAR fast auto-focusing imaging method based on maximum sharpness

Abstract

The invention provides a linear array SAR fast auto-focusing imaging method based on maximum sharpness. The method is based on the maximum sharpness criterion and backward projection imaging principleof a linear array SAR 3D image. First, a phase error estimation equation of backward projection auto-focusing imaging is constructed by using an image sharpness partial derivative. Then, the phase error estimation equation is quickly and approximately solved through a conjugate gradient method, and quick estimation of phase error in linear array SAR echo is realized. Finally, phase error compensation and backward projection imaging are carried out, and linear array SAR backward projection auto-focusing imaging is realized. The low-frequency, high-frequency and randomly distributed phase errors in linear array SAR echo data can be quickly estimated without knowing the prior information of phase error distribution. The linear array SAR fast auto-focusing imaging method based on maximum sharpness is suitable for linear array SAR fast auto-focusing imaging under complex motion trajectories.

Description

technical field [0001] The invention belongs to the field of radar technology, in particular to the field of synthetic aperture radar (SAR) imaging technology. Background technique [0002] Synthetic Aperture Radar (SAR), as an all-weather, all-weather, and information-rich remote sensing imaging technology, has become an important means of earth observation today. National economic and military fields such as exploration and natural disaster monitoring have been more and more widely used. Because of its three-dimensional imaging capability, linear array SAR (LASAR) is a new type of SAR imaging technology that has attracted widespread attention in recent years. In essence, linear array SAR is a SAR imaging technology that obtains the two-dimensional resolution of the observed target by controlling the linear array antenna to move in space to form a large virtual two-dimensional array, and combines pulse compression technology to achieve the third-dimensional resolution of t...

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Problems solved by technology

For the spotlight SAR imaging mode, the document "Ash, Joshua N. "An autofocus method for back projection imagery insynthetic aperture radar." IEEE Geoscience and Remote Sensing Letters, Vol.9, No.1, 104-108, 2012" proposed a A SAR back-projection self-focusing algorithm based on the maximum sharpness of the image, using eigendecomposition to estimate the phase error, but the self-focusing algorithm needs to construct the eigenmatrix and eigendecomposition, and use the whole scene resolution unit to construct the cost estimation function, the calculation is large and When imaging a large scene, the cost estimation function has many dimensions and is difficult to apply in practice

In the literature "Dai Y H, Kou C X. A nonlinear conjugate gradient algorithm with an optimal property and an improved Wolfe line search [J]. SIAM Journal on Optimization, 2013, 23(1): 296-320" proposed a semi-positive definite relaxation based on And the cone-optimized SAR self-focusing imaging algorithm, the measured data results show that the performance of this method is better than the PGA algorithm and the MEE self-focusing method under the condition of steep phase error, but this method also needs to build a larger dimension when imaging a large scene Cost function, which is computationally intensive and difficult to apply in linear array SAR 3D imaging

The literature "Yang Zemin. Research on Fast Time-Domain SAR Imaging and Three-dimensional SAR Motion Compensation [D]. Xidian University, 2016" proposed a linear array SAR fast back projection self-focusing imaging algorithm combined with multiple channel echo data , but this method does not consider the compensation of higher-order terms and random phase errors

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