It is a feasible and promising way to utilize deep neural networks learn extract valuable features from synthetic aperture radar (SAR) images for SAR automatic target recognition (ATR). However, it too difficult effectively train the with limited raw images. In this paper, we propose new approach do ATR, in which multiview learning framework was employed. Based on ATR pattern, first present flexible mean generate adequate data, can guarantee large amount of inputs network training without...

Recently, the generalized sparse iterative covariance-based estimation algorithm was extended to allow for varying norm constraints in scanning radar applications. In this paper, further development, we introduce a wideband dictionary framework which can provide computationally efficient of signals. The technique is formed by initially introducing coarse grid constructed from integrating elements, spanning bands considered parameter space. After forming estimates activated bands, these are...

With appropriate geometry configurations, bistatic synthetic aperture radar (SAR) can break through the limitations of monostatic SAR on forward-looking imaging. Thanks to such a capability, (BFSAR) has extensive potential applications, as self-navigation and self-landing. In mode BFSAR with stationary transmitter (ST-BFSAR), two-dimensional spatial variation makes it difficult use traditional data focusing algorithms. this letter, an imaging algorithm based keystone transform nonlinear...

With the geosynchronous synthetic aperture radar (SAR) satellite as transmitter, unmanned aerial vehicle (UAV) can passively receive echo within illuminated ground area and achieve 2-D imaging of interested target. This SAR system, known GEO-UAV bistatic SAR, is capable autonomously accomplishing mission in rough terrain environments by prespecifying a path for UAV receiver. In this paper, system first investigated. The practical advantages spatial resolution are then analyzed detail....

High-resolution scanning radar mapping of the surface is an effective tool for addressing concerns in local environmental and social investigation fields. Regrettably, azimuth resolution a constrained by antenna beamwidth. Multiple super-resolution approaches have been applied to enhance resolution, but they suffer from limited improvement. In this paper, methodology derive estimates at improved proposed. We first consider truncated spectrum discarding unreliable frequencies suppress noise...

In synthetic aperture radar (SAR) imagery, images of ground moving targets (GMTs) are smeared, distorted, and shifted. Current GMT imaging methods mostly based on range-Doppler algorithms, which have two main drawbacks: 1) coupling between range cell migration correction (RCMC) Doppler parameter estimation 2) cross terms degrade the performance nonlinear methods. this paper, an optimal 2-D spectrum matching method for SAR is proposed. The innovation or advantage that problem transformed into...

Recently, a variety of super-resolution (SR) methods have been devoted to enhancing the angular resolution real beam mapping (RBM) imagery in modern microwave remote sensing applications. When addressing large-scale datasets, however, they suffer from notably high computational complexity due high-dimensional matrix inversion, multiplication, or singular value decomposition (SVD). To overcome this limitation, article presents low-complexity SR strategy based on adaptive low-rank...

Geosynchronous synthetic aperture radar (GEO-SAR) offers new opportunities for continuous Earth observation missions with large coverage and short revisit cycle. The unique features of GEO-SAR present huge potentials bistatic applications. In this paper, the concept advantages GEO SAR (GEO-BiSAR) are first investigated. system consists a illuminator an airborne receiver, such as airplane or near-space vehicle. Compared monostatic system, configuration can provide finer spatial resolution...

Because a scanning radar system works as noncoherent sensor, it is suitable for any geometry situation, and has significant extensive applications, such surveillance, autonomous landing of aircraft, navigation, guidance. After the pulse compression technique improving range resolution was presented, angular became crucial system. In this paper, scheme superresolution based on maximum posteriori (MAP) framework proposed. First, received signal in azimuth modeled mathematical convolution...

Scanning radar is of notable importance for ground surveillance, terrain mapping and disaster rescue. However, the angular resolution a scanning image poor compared to achievable range resolution. This paper presents deconvolution algorithm super-resolution in based on Bayesian theory, which states that can be realized by solving corresponding problem with maximum posteriori (MAP) criterion. The considers noise composed two mutually independent parts, i.e., Gaussian signal-independent...

Feature extraction from high-dimensional synthetic aperture radar images is one of the key steps for SAR automatic target recognition. In this paper, we propose a new approach to image feature that named neighborhood geometric center scaling embedding, which based on manifold learning theory. our framework, introduced construct relationships. The samples are endowed with clear clustering directions in dimensionality reduction, and classification better conducted space than original space....

Airborne forward-looking radar (AFLR) imaging has raised many concerns in fields of Earth observation, independent weather and daytime. Constrained by principles, conventional high-resolution techniques such as synthetic aperture (SAR) Doppler beam sharpening (DBS) are incapable AFLR imaging. The real (RAR) can obtain images using a scanning antenna, but suffers from coarse cross-range resolution. Recently, there been much attention paid to the iterative adaptive approach (IAA), which draws...

Bistatic forward-looking synthetic aperture radar (BFL-SAR) is a kind of bistatic SAR system that can image terrain in the flight direction an aircraft. Until now, BFL-SAR imaging theories and methods have been researched for stationary targets. Unlike target, motion ground-moving target (GMT) induces unknown range cell migration additional modulation azimuth signal. Thus, to finely GMT, one must obtain its velocity parameters accurately, but they are usually unknown. In this paper, novel...

Cross-resolution enhancement for airborne high-squint radar (AHSR) imagery is mathematically equivalent to the ill-conditioned problem of inverse-scattering reconstruction. Although a variety inversion methods with regularization can be introduced advance field AHSR imagery, they turn out computationally intensive when extended 2-D (range and cross-range dimension) image formulation due range-by-range calculation space-variant operators over full range swath. To tackle efficiency, this...

Convolutional neural networks (CNNs) have dominated the synthetic aperture radar (SAR) automatic target recognition (ATR) for years. However, under limited SAR images, width and depth of CNN-based models are limited, widening received field global features in images is hindered, which finally leads to low performance recognition. To address these challenges, we propose a Transformer (ConvT) ATR few-shot learning (FSL). The proposed method focuses on constructing hierarchical feature...

Maritime surveillance is indispensable for civilian fields, including national maritime safeguarding, channel monitoring, and so on, in which synthetic aperture radar (SAR) ship target recognition a crucial research field. The core problem to realizing accurate SAR the large inner-class variance inter-class overlap of features, limits performance. Most existing methods plainly extract multi-scale features network utilize equally each feature scale classification stage. However, shallow are...

In this study, the authors consider direction of arrival (DOA) estimation problem for a monostatic multiple-input multiple-output (MIMO) radar. A DOA algorithm MIMO radar using Capon and reduced-dimension transformation is proposed. The proposed can achieve lower computational complexity than algorithm, while not debasing performance angle estimation. has better signal parameters via rotational invariance techniques it close to Cramér–Rao bound (CRB). variance error CRB are derived....

Angular superresolution technique is of great significance in enhancing the azimuth resolution when real aperture constrained. Recently, based on weighted least squares (WLS), iterative adaptive approach (IAA) has been applied to scanning radar angular superresolution. The resulting estimates present noticeably superior performance compared with existing approaches. However, improved IAA comes at cost high computational complexity. In this paper, a scheme fast (IAA-F) proposed for mitigating...