Real-time SAR (synthetic aperture radar) imaging method based on improved range migration algorithm

Abstract

The invention discloses a real-time SAR (synthetic aperture radar) imaging method based on an improved range migration algorithm and mainly solves the problem that imaging cannot be achieved in the prior art. The real-time SAR imaging method is implemented according to the steps of 1) performing preprocessing and range compression on a datum of the nth subaperture and estimating a kinematic error of the nth subaperture; 2) subjecting the datum of the (n+1)th subaperture to kinematic error estimation; 3) obtaining a linear term a1 and a constant term a0 of error difference according to respective kinematic errors of the nth subaperture and the (n+1)th subaperture; (4) compensating the kinematic error of the nth subaperture to the datum of the nth subaperture, and performing imaging to obtain a rough-focus image; (5) projecting the rough-focus image of the nth subaperture to a projection plane; (6) imaging the data of the left subapertures to obtain rough-focus images; (7) splicing all rough-focus images to form an integral aperture image so as to finish real-time imaging. The real-time SAR imaging method is capable of achieving real-time imaging of SAR echo data and applicable to real-time natural disaster evaluation and real-time territorial resource monitoring.

Description

technical field [0001] The invention belongs to the field of radar signal processing and relates to a real-time SAR imaging method, which can be used for real-time evaluation of natural disasters and real-time monitoring of land resources. Background technique [0002] As an active detector, synthetic aperture radar (SAR) can work day and night under all-weather conditions. In addition, SAR can work in different frequencies and different polarization modes. These characteristics make SAR have great applications in military and civilian fields. In recent years, a lot of research has been carried out on airborne synthetic aperture radar SAR. [0003] For the airborne SAR system, the non-ideal movement of the radar caused by atmospheric turbulence and the instability of the airborne platform velocity not only leads to serious blurring of SAR imaging results, but also makes the SAR image geometrically distorted. Although the motion error caused by the non-ideal motion of the ra...

AI Technical Summary

Problems solved by technology

As one of the most effective autofocus algorithms, phase gradient self-focusing PGA has many improved PGA algorithms, such as the PGA maximum likelihood phase estimation method, which can estimate phase errors of any order and has good robustness; there are also based on The weighted maximum norm self-focusing method estimates the target eigenvector by solving the optimization function of the two-norm maximization, avoiding the decomposition process of the eigenvalue; but these methods are based on the full aperture data, that is, Only after the full-aperture and complete azimuth data is received, the motion error is estimated and imaging processing is performed, which limits the real-time processing of SAR imaging and cannot meet the growing demand for real-time imaging

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