Learning based approaches have witnessed great successes in blind single image super-resolution (SISR) tasks, however, handcrafted kernel priors and learning are typically required. In this paper, we propose a Meta-learning Markov Chain Monte Carlo SISR approach to learn from organized randomness. concrete, lightweight network is adopted as generator, optimized via the MCMC simulation on random Gaussian distributions. This procedure provides an approximation for rational blur kernel,...

Despite the remarkable progress in synthetic aperture radar automatic target recognition (SAR ATR), recent efforts have concentrated on detecting and classifying a specific category, e.g., vehicles, ships, airplanes, or buildings. One of fundamental limitations top-performing SAR ATR methods is that learning paradigm supervised, task-specific, limited-category, closed-world learning, which depends massive amounts accurately annotated samples are expensively labeled by expert analysts limited...

A super-resolution imaging technique based on the vortex electromagnetic (EM) wave, which carries orbital angular momentum (OAM), is reported in this paper. The proof-of-concept experiment for EM conducted. An processing method real-world OAM radar data proposed to obtain target profile. Experimental results validate effectiveness of and demonstrate that wave can be exploited image targets with high-resolution beyond limit array aperture. This breakthrough Rayleigh paves way innovative...

Motivated by classical coincidence imaging which has been realized in optical systems, an instantaneous microwave-radar technique is proposed to obtain focused high-resolution images of targets without motion limitation. Such a radar method resolves target scatterers based on measuring the independent waveforms their echoes, quite different from conventional techniques where are derived depending time-delay and Doppler analysis. Due peculiar features imaging, there two potential advantages...

In this paper, we propose novel l <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> -regularized space-time adaptive processing (STAP) algorithms with a generalized sidelobe canceler architecture for airborne radar applications. The proposed methods suppose that number of samples at the output blocking process are not needed canceling, which leads to sparsity STAP filter weight vector. core idea is impose sparse regularization (l -norm...

Autofocusing technology is an essential step of Inverse Synthetic Aperture Radar (ISAR) imaging, whose performance has great influence on the quality radar image. As far as existed autofocusing methods are concerned, based minimum entropy criterion robust and have been widely applied in both (SAR) ISAR imaging. However, Minimum Entropy (MEA) usually suffer from heavy computation burden because complex formula image optimal search phase error. In this paper, a novel fast MEA method Newton...

In inverse synthetic aperture radar (ISAR) imaging of targets with complex motion such as the high maneuvering airplanes and fluctuating ships oceanic waves, azimuth echo signals can be modeled cubic chirps after translational compensation, then, focusing quality will deteriorated by time-varying chirp rate. this paper, a parameter estimation method is proposed based on discrete Fourier transform (DCFT), which generated from DCFT for quadratic chirps. Several properties are derived, we show...

Recently, millimeter-wave 3D holography techniques employing a scanning 1D multiple input output (MIMO) array have shown several superiorities for short-range applications than traditional single ones. However, current imaging algorithms this emerging regime are not satisfied, either too slow as back projection manner is used or of poor quality since steps approximations introduced. In paper, two fast fully focused developed towards fixing these drawbacks. Both based on the assumption that...

Sparse aperture ISAR autofocusing and imaging is generally achieved by methods of compressive sensing (CS), or, sparse signal recovery, because non-uniform sampling disables fast Fourier transform (FFT)-the core traditional algorithms. Note that the CS based are often computationally heavy to execute, which limits their applications in real-time systems. The improvement computational efficiency either necessary or at least highly desirable promote practical usage. This paper proposes an...

Sparse aperture radar imaging is generally achieved by methods of compressive sensing (CS), or, sparse signal recovery (SSR). However, most the traditional SSR cannot produce focused image stably, which limits their applications. l <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> regularization and alternating direction method multipliers(ADMM) are applied to problem, but its performance sensitive selection model parameters. This paper...

Aircraft target detection in SAR images is a challenging task due to the discrete scattering points and severe background clutter interference. Currently, methods with convolution-based or transformer-based paradigms cannot adequately address these issues. In this letter, we explore diffusion models for image aircraft first time propose novel Diffusion-based Detection network (DiffDet4SAR). Specifically, proposed DiffDet4SAR yields two main advantages detection: 1) maps denoising process of...

Convolutional Neural Network (CNN) still suffers from overfitting problems caused by limited samples in SAR target classification. Few-shot learning (FSL) aims to learn a classifier classify images when only few training examples are available for each class. Recent works on FSL demonstrate that using local descriptor representations can lead more informative than image-level representations. However, descriptors typically capture information an image, while disregarding global contextual...

This paper analyzes the influence of typical target micromotions on synthetic aperture radar (SAR) images, azimuth resolution limit, SAR/ground moving indication (GMTI), and MTI. According to micromotion periods contained in coherent processing interval, a new range model expansion generalized paired echo principle are proposed applied underlie analysis. Several kinds image characteristics including gray strips, ghost points, fences reported, which sheerly distinct from those slow movers....

The interrupted sampling repeater jamming (ISRJ) is an effective deception method for coherent radar, especially the wideband linear frequency modulation (LFM) radar. An electronic counter-countermeasure (ECCM) scheme proposed to remove ISRJ-based false targets from pulse compression result of de-chirping Through time-frequency (TF) analysis radar echo signal, it can be found that TF characteristics ISRJ signal are discontinuous in duration because jammer needs short durations receive...

The intricate vibration of a working vehicle provides an important signature to the type. Small vibrations introduce phase modulation in radar echoes, which is referred as micro-Doppler (m-D) phenomenon and can be modeled sinusoidal frequency-modulated (SFM) signal. Such induced by consists multiple frequency components; moreover, usually rather weak. Present parametric estimators are difficult estimate so many parameters every component, while nonparametric approaches suffer from low...

Sparsity and Shannon entropy have been widely used in inverse synthetic aperture radar (ISAR) imaging. The minimum criterion is usually applied the translational motion compensation sparse constraint azimuth In this paper, we combine these two criteria to develop a novel autofocusing algorithm for ISAR (SA-ISAR) First, Laplace approximation-based variational Bayesian inference with Laplacian scale mixture prior proposed SA-ISAR Then, accomplished by minimizing image of reconstructed within...

A novel interferometry technique is proposed and introduced into active millimeter-wave (MMW) holography. Different from optical holographic interferometry, which relies on a reference light source or the interferometric synthetic aperture radar where data apertures of different elevations are interfered, interfered between frequencies in method. Higher ranging accuracy achieved, since residual phase information always neglected utilized by manner. The method also avoids interpolations...

Recently, deep unfolded networks have been widely utilized in direction of arrival (DOA) estimation due to the reduced computational complexity and improved accuracy. However, few consider nested array for off-grid DOA estimation, where estimated DOAs are not on prespecified grids. In this article, we propose a FOCal underdetermined system solver network alternating method multiplies address problem, which respectively aim improve accuracy further reduce complexity. We first apply...

The electronic counter-countermeasures capabilities of staggered pulse repetition interval (PRI) signal is limited by its repetitive character, and a random PRI radar an alternative to improve the range velocity coverage. However, high sidelobe pedestal target Doppler spectrum caused randomness prevents development. In this paper, based on compressed sensing theory, we present novel framework in generate with low for moving detection. As precondition, equivalent matrix proved satisfy...

A novel cylindrical millimeter-wave holography regime using a multi-input-multi-output (MIMO) array is first introduced. More importantly, an accurate and fast 3-D imaging algorithm developed for this regime. Although many efficient algorithms synthetic aperture radar (SAR) or circular SAR have been developed, they can hardly be used new due to the compound effects of spherical wavefront, MIMO geometry, observation aperture. In paper, we develop mainly based on ideas wave decomposition,...

The vortex electromagnetic (EM) wave carrying orbital angular momentum (OAM) has been found great potential to improve radar imaging performance. However, achieve high-resolution image, a large number of OAM modes should be applied in the existing EM methods, which seriously limits improvement resolution practice. orthogonality eigenmodes enables reconstruction targets with limited measurements. Thus, and reduce measurements, sparse Bayesian learning (SBL) is introduced reconstruct for...