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Regularization technology can be utilized to improve the azimuth resolution for forward-looking scanning radar (FLSR). Among various regularization methods, L1 norm constrained method is usually adopted for its strong ability in resolving the sparse targets. Nevertheless, the solution of L1-norm constrained regularization method (L1-CRM) is sensitive to noise and the iterations would quickly diverge...
Angular super-resolution imaging plays a significant role in the area of the scanning radar imaging. Some deconvolution methods are used to realize the angular super-resolution on scanning radar. However, the ill-posed nature of the deconvolution problem means difficulties and inaccuracies in the search for the solution. In this paper, we present a novel method for angular super-resolution imaging...
Convergence speed is quite important for a iterative superresolution algorithm, especially in real time processing. A vector extrapolation acceleration maximum a posteriori (VEAMAP) superresoltuion algorithm is proposed in this paper. In the algorithm a predicted point is made before initial multiplicative iteration and this can make the iterations go faster along the convergence path. As the prediction...
Deconvolution techniques can be utilized to realize angular resolution enhancement for real-beam scanning radar (RBSR). However, most deconvolution algorithms are sensitive to noise and time consuming. In this paper, an accelerated iterative shrinkage/thresholding (AIST) algorithm is proposed to overcome these disadvantages. AIST is developed from iterative shrinkage/thresholding (IST) algorithm which...
Ship detection in sea clutter environment using scanning radar is of vital importance, but with challenges due to low angular resolution. To solve the problem, an angular superresolution algorithm for radar imaging based on Bayesian deconvolution theory is proposed. Firstly, the statistic characteristics of the sea clutter are modeled using compound K-distribution. Then the signal model of radar echo...
The angular superresolution is of great significance for scanning radar in forward-looking imaging. There are many techniques documented in literature to enhance the angular resolution, of which deconvolution method and power spectral density(PSD)methods are favored and attain many interests. In this paper, we focus on analyzing the advantages and challenges of PSD methods in comparison with the deconvolution...
Angular super-resolution of scanning radar is an important problem in radar system. Some deconvolution methods are used to realize the angular super-resolution in scanning radar. However, the ill-posed nature of the deconvolution problem leads to the noise amplification in the angular super-resolution image. This phenomenon brings the difficulty in signal detection and tracking. In this paper, a deconvolution...
To obtain high resolution image for real beam scanning radar, angular superresolution is studied, and a two-step scheme is proposed in this paper. In the scheme, using the threshold determined by CFAR-OSTU, the real beam data is divided into two parts firstly, and then maximum likelihood deconvolution with different number of iterations is conducted on the two parts of data. At last, the superresolution...
This paper presents a deconvolution algorithm based on the Maximum likelihood (ML) criterion to realize azimuth angular superresolution of sea-surface target in the background of sea clutter. Firstly, the received signal of real-beam image in azimuth dimension was modeled as the convolution of antenna pattern and target scattering. Then the ML objective function was built according to the assumption...
Radar image resolution is a controlling factor in the radar imaging application. In this paper, we propose an approach to radar angular super-resolution through sparse deconvolution, which is able to increase the resolution of radar image beyond the limitation of system parameters. It relies on the optimization approach that enables to incorporate the prior information about the system and the statistical...
This paper present a superresolution algorithm for forward-looking imaging of scanning radar based on weighted least squares method. This algorithm utilized the weighted vectors to structure the objective function, and introduced the diagonal loading technique to obtain more robust superresolution result. Simulation results verified the performance of our algorithm.
Angular super-resolution performance is the key problem in the field of radar imaging. In this paper, we propose an approach to radar angular super-resolution through deconvolution, which is able to increase the resolution of radar image beyond the limitation of system parameters. It relies on the Bayesian formulation approach that enables to incorporate the prior information about the system and...
The traditional Richardson-Lucy (R-L) algorithm has a strong ability to realize super-resolution. However, it always suffers from noise amplification. In this paper, an improved R-L algorithm is proposed to solve the real-beam scanning radar angular super-resolution problem, which relies on both the traditional R-L deconvolution algorithm and the regularization term. We first describe the angular...
Iterative deconvolution is an effective method of achieving high azimuth resolution in real aperture scanning radar. However, the performance is seriously limited when SNR is low. The application area and processing efficiency are affected by unreasonable iterative. Therefore, correct understanding the ability of super-resolution signal recovery is the premise to achieve super-resolution at low SNR...
The problem of angular super-resolution has attracted significant attention over the last decades. The difficultly and keystone of implementation of the angular super-resolution however, lies in how to cope with the ill-posed nature of these problems. Independently, there has been a surge in algorithms for angular super-resolution in optical and microwave imaging field. These algorithms are supported...
Angular resolution is crucial for scanning radar system. Angular resolution of real aperture radar (RAR) is decided by the size of the antenna aperture. In this paper, a novel method of improving angular resolution based on maximum a posteriori (MAP) framework is proposed. Firstly, scanning radar signal model is illustrated, and then an iterative deconvolution based on MAP algorithm that improves...
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