Abstract
When conventional motion compensation algorithms that are fit for a single target are applied to cooperative targets imaging, a well-focused image cannot be obtained due to the low correlation between adjacent returned signals. In this paper, a parametric compensation method is proposed for the imaging of cooperative targets. First, the problem of the imaging is formulated by analyzing the translational motion of the target moving along a rectilinear fight path and by assuming a signal model of cooperative targets imaging. A bulk image is then obtained by parametric compensation of the linear and quadratic phase terms, which is performed by means of estimating the translational motion parameters through the fractional Fourier transform. Next, the number of targets in the bulk image is estimated by clustering number estimation, and the segmented images from the bulk image are separated by the normalized cuts. Finally, well-focused images are obtained by refined parametric compensation of the residual quadratic and cubic phase terms, which is carried out by estimating the parameters through maximizing the image contrast. Simulation results demonstrate the effectiveness of the proposed method.
Highlights
High-resolution radar imaging has been a widely addressed topic in recent years [1-3]
In order to reconstruct a well-focused image of cooperative targets, this paper proposes an imaging method using parametric compensation
In order to obtain the bulk image of the cooperative targets, compensation of the linear and quadratic phase terms should be carried out to eliminate the influences of translational motion
Summary
High-resolution radar imaging has been a widely addressed topic in recent years [1-3]. When high-resolution radar imaging is applied to imaging of multiple targets moving in the same radar beam, the conventional motion compensation algorithms, which are suitable for a single moving target, cannot obtain a well-focused image due to the low correlation between adjacent returned signals [4-7]. The current techniques of multiple targets imaging can be categorized into two classes: direct imaging and separated imaging The former method is based on timefrequency transformation [2,8,9]. In order to reconstruct a well-focused image of cooperative targets, this paper proposes an imaging method using parametric compensation. The third step consists in refined parametric compensation In this step, well-focused images are obtained by refined compensation of the residual quadratic and cubic phase terms, which is carried out by estimating the parameters through maximizing the image contrast. Compared with the existing imaging methods by parameter separation, the proposed method can yield well-focused images of cooperative targets.
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