ISAR motion compensation method based on design structuration Gram matrix

Abstract

The invention discloses an ISAR motion compensation method based on a design structuration Gram matrix, which belongs to the technical field of radar imaging. Motion compensation is an important step in an ISAR imaging algorithm. According to the invention, motion compensation is attributed to a multi parameter estimation problem. An optimization theory based on the design structuration Gram matrix provides a new motion compensation method. The method can be divided into two parts of range alignment and phase compensation. According to a range alignment algorithm, the correlations between all range profiles approach the maximum at the same time to realize offset estimation. According to a phase compensation algorithm, by analyzing a signal model, an optimal matrix is derived, and an optimization method is used to extract a phase error. According to the invention, the correlations between echo pulses are fully used; high precision estimation is carried out on the range offset and the phase error; the algorithms have high robustness, and are suitable for the condition of echo random sampling; and a compression sensing technology has a practical application prospect in the field of ISAR imaging.

Description

technical field [0001] The invention relates to an ISAR motion compensation method based on a designed structured Gram matrix, belonging to the technical field of radar imaging. Background technique [0002] In general, the movement of non-cooperative targets relative to the radar is unpredictable. Generally, the relative motion between the radar and the target can be decomposed into translation and rotation components, of which only the rotation component plays a role in the reconstruction of the target image, while the translation component is unfavorable for imaging. Therefore, it is usually necessary to perform a motion compensation operation on each range image to remove the translational component before imaging. Motion compensation is a key technology of ISAR imaging, and its performance will directly affect the quality of final imaging. [0003] Since the motion parameters such as motion attitude and track of non-cooperative targets cannot be accurately known, the ...

AI Technical Summary

Problems solved by technology

Among them, the first two algorithms obtain the phase error by estimating the phase gradient of two adjacent range images, because there is an error accumulation effect in the process of estimating the phase error, which leads to the loss of algorithm accuracy; while the MLE algorithm obtains the phase error by solving the range image correlation The eigenvectors of the variance matrix directly estimate the phase error

Relatively speaking, the estimation accuracy of the MLE algorithm is higher than that of the first two algorithms, but because the algorithm needs to decompose the covariance matrix eigenvalues, the algorithm is limited by the dimension of the matrix and is difficult to apply in engineering practice

Images