Iterative heavy weighted blind deconvolution method of passive millimeter wave radar image

Abstract

The invention belongs to the radar image processing technology field and discloses an iterative heavy weighted blind deconvolution method of a passive millimeter wave radar image. The method comprises the following steps of (1) integrating an adaptive weight constructed based on a residual error into a data item; (2) integrating a spatial adaptive weight of a coefficient of an image under a bilateral total variational operator effect into an image regularization item; (3) applying a smoothness constraint under a Laplace operator effect on a passive millimeter wave imaging system point expansion function; (4) realizing image and point expansion function combination iteration blind deconvolution under a multi-scale coarse-to-fine framework; and (5) deriving an adaptive estimation formula of a model regularization parameter. In the prior art, during passive millimeter wave image blind deconvolution, a radar is sensitive to a loud noise and a mixing noise and can not recover image edge and detail information. By using the heavy weighted blind deconvolution method of the invention, the above problems are solved.

Description

technical field [0001] The invention belongs to the technical field of radar image processing, in particular to an iterative reweighted blind deconvolution method for passive millimeter-wave radar images. Background technique [0002] Passive mmWave can penetrate fog, cloud and rain, and can image 24 / 7, so it has a wide range of applications in navigation, guidance and surveillance. Passive mmWave images have relatively long wavelengths compared to visible and infrared images. In order to improve the spatial resolution, it is necessary to increase the aperture of the imaging antenna. However, due to platform constraints and many practical application requirements, large antenna apertures are subject to many limitations in practical applications. Therefore, the acquired observation images are generally highly blurred and have low spatial resolution. Furthermore, observation images inevitably suffer from degradation from systematic noise and natural clutter outliers. [00...

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Problems solved by technology

[0004] In view of the above problems, the present invention provides an iterative reweighted blind deconvolution method for passive millimeter-wave radar images, which solves the problem that the prior art is sensitive to strong noise and mixed noise during blind deconvolution of passive millimeter-wave images, and cannot recover The problem of image edge and detail information; it can restore the original high-resolution image from the degraded passive millimeter-wave image with strong blur and strong noise, and provide high-quality images for subsequent target detection and tracking

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