scholarly journals Airborne Radar Super-Resolution Imaging Based on Fast Total Variation Method

2021 ◽  
Vol 13 (4) ◽  
pp. 549
Author(s):  
Qiping Zhang ◽  
Yin Zhang ◽  
Yongchao Zhang ◽  
Yulin Huang ◽  
Jianyu Yang
Keyword(s):  
Computational Complexity ◽  
Total Variation ◽  
Super Resolution ◽  
Real Data ◽  
Radar Imaging ◽  
Matrix Inversion ◽  
Variation Method ◽  
Airborne Radar ◽  
The Matrix ◽  
Very High

Total variation (TV) is an effective super-resolution method to improve the azimuth resolution and preserve the contour information of the target in airborne radar imaging. However, the computational complexity is very high because of the matrix inversion, reaching O(N3). In this paper, a Gohberg–Semencul (GS) representation based fast TV (GSFTV) method is proposed to make up for the shortcoming. The proposed GSFTV method fist utilizes a one-dimensional TV norm as the regular term under regularization framework, which is conducive to achieve super-resolution while preserving the target contour. Then, aiming at the very high computational complexity caused by matrix inversion when minimizing the TV regularization problem, we use the low displacement rank feature of Toeplitz matrix to achieve fast inversion through GS representation. This reduces the computational complexity from O(N3) to O(N2), benefiting efficiency improvement for airborne radar imaging. Finally, the simulation and real data processing results demonstrate that the proposed GSFTV method can simultaneously improve the resolution and preserve the target contour. Moreover, the very high computational efficiency of the proposed GSFTV method is tested by hardware platform.

scholarly journals Fast Split Bregman Based Deconvolution Algorithm for Airborne Radar Imaging

2020 ◽  
Vol 12 (11) ◽  
pp. 1747 ◽  
Author(s):  
Yin Zhang ◽  
Qiping Zhang ◽  
Yongchao Zhang ◽  
Jifang Pei ◽  
Yulin Huang ◽  
...  
Keyword(s):  
Real Time ◽  
Computing Time ◽  
Real Data ◽  
Radar Imaging ◽  
Matrix Inversion ◽  
Airborne Radar ◽  
Split Bregman ◽  
Regularization Problem ◽  
Azimuth Resolution ◽  
Split Bregman Algorithm

Deconvolution methods can be used to improve the azimuth resolution in airborne radar imaging. Due to the sparsity of targets in airborne radar imaging, an L 1 regularization problem usually needs to be solved. Recently, the Split Bregman algorithm (SBA) has been widely used to solve L 1 regularization problems. However, due to the high computational complexity of matrix inversion, the efficiency of the traditional SBA is low, which seriously restricts its real-time performance in airborne radar imaging. To overcome this disadvantage, a fast split Bregman algorithm (FSBA) is proposed in this paper to achieve real-time imaging with an airborne radar. Firstly, under the regularization framework, the problem of azimuth resolution improvement can be converted into an L 1 regularization problem. Then, the L 1 regularization problem can be solved with the proposed FSBA. By utilizing the low displacement rank features of Toeplitz matrix, the proposed FSBA is able to realize fast matrix inversion by using a Gohberg–Semencul (GS) representation. Through simulated and real data processing experiments, we prove that the proposed FSBA significantly improves the resolution, compared with the Wiener filtering (WF), truncated singular value decomposition (TSVD), Tikhonov regularization (REGU), Richardson–Lucy (RL), iterative adaptive approach (IAA) algorithms. The computational advantage of FSBA increases with the increase of echo dimension. Its computational efficiency is 51 times and 77 times of the traditional SBA, respectively, for echoes with dimensions of 218 × 400 and 400 × 400 , optimizing both the image quality and computing time. In addition, for a specific hardware platform, the proposed FSBA can process echo of greater dimensions than traditional SBA. Furthermore, the proposed FSBA causes little performance degradation, when compared with the traditional SBA.

scholarly journals Fast Total Variation Method Based on Iterative Reweighted Norm for Airborne Scanning Radar Super-Resolution Imaging

2020 ◽  
Vol 12 (18) ◽  
pp. 2877
Author(s):  
Xingyu Tuo ◽  
Yin Zhang ◽  
Yulin Huang ◽  
Jianyu Yang
Keyword(s):  
Total Variation ◽  
Structural Characteristics ◽  
Super Resolution ◽  
Variation Method ◽  
High Dimensional ◽  
Imaging Method ◽  
Lp Norm ◽  
L2 Norm ◽  
The Matrix ◽  
Resolution Imaging

The total variation (TV) method has been applied to realizing airborne scanning radar super-resolution imaging while maintaining the outline of the target. The iterative reweighted norm (IRN) approach is an algorithm for addressing the minimum Lp norm problem by solving a sequence of minimum weighted L2 norm problems, and has been applied to solving the TV norm. However, during the solving process, the IRN method is required to update the weight term and result term in each iteration, involving multiplications and the inversion of large matrices. Consequently, it suffers from a huge calculation load, which seriously restricts the application of the TV imaging method. In this work, by analyzing the structural characteristics of the matrix involved in iteration, an efficient method based on suitable matrix blocking is proposed. It transforms multiplications and the inversion of large matrices into the computation of multiple small matrices, thereby accelerating the algorithm. The proposed method, called IRN-FTV method, is more time economical than the IRN-TV method, especially for high dimensional observation scenarios. Numerical results illustrate that the proposed IRN-FTV method enjoys preferable computational efficiency without performance degradation.

scholarly journals Impact of Stair and Diagonal Matrices in Iterative Linear Massive MIMO Uplink Detectors for 5G Wireless Networks

Symmetry ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 71 ◽  
Author(s):  
Mahmoud A. Albreem ◽  
Mohammed H. Alsharif ◽  
Sunghwan Kim
Keyword(s):  
Computational Complexity ◽  
Iterative Methods ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Low Complexity ◽  
Matrix Inversion ◽  
Multiple Input ◽  
The Matrix ◽  
Input Multiple Output ◽  
The Impact

In massive multiple-input multiple-output (M-MIMO) systems, a detector based on maximum likelihood (ML) algorithm attains optimum performance, but it exhaustively searches all possible solutions, hence, it has a very high complexity and realization is denied. Linear detectors are an alternative solution because of low complexity and simplicity in implementation. Unfortunately, they culminate in a matrix inversion that increases the computational complexity in high loaded systems. Therefore, several iterative methods have been proposed to approximate or avoid the matrix inversion, such as the Neuamnn series (NS), Newton iterations (NI), successive overrelaxation (SOR), Gauss–Siedel (GS), Jacobi (JA), and Richardson (RI) methods. However, a detector based on iterative methods requires a pre-processing and initialization where good initialization impresses the convergence, the performance, and the complexity. Most of the existing iterative linear detectors are using a diagonal matrix ( D ) in initialization because the equalization matrix is almost diagonal. This paper studies the impact of utilizing a stair matrix ( S ) instead of D in initializing the linear M-MIMO uplink (UL) detector. A comparison between iterative linear M-MIMO UL detectors with D and S is presented in performance and computational complexity. Numerical Results show that utilization of S achieves the target performance within few iterations, and, hence, the computational complexity is reduced. A detector based on the GS and S achieved a satisfactory bit-error-rate (BER) with the lowest complexity.

scholarly journals Infrared Image Super-Resolution Reconstruction Based on Quaternion and High-Order Overlapping Group Sparse Total Variation

Sensors ◽  
2019 ◽  
Vol 19 (23) ◽  
pp. 5139 ◽  
Author(s):  
Xingguo Liu ◽  
Yingpin Chen ◽  
Zhenming Peng ◽  
Juan Wu
Keyword(s):  
Total Variation ◽  
Super Resolution ◽  
High Order ◽  
Practical Significance ◽  
Variation Method ◽  
Reconstruction Method ◽  
Infrared Images ◽  
Denoising Method ◽  
Image Structure ◽  
Imaging Characteristics

Owing to the limitations of imaging principles and system imaging characteristics, infrared images generally have some shortcomings, such as low resolution, insufficient details, and blurred edges. Therefore, it is of practical significance to improve the quality of infrared images. To make full use of the information on adjacent points, preserve the image structure, and avoid staircase artifacts, this paper proposes a super-resolution reconstruction method for infrared images based on quaternion total variation and high-order overlapping group sparse. The method uses a quaternion total variation method to utilize the correlation between adjacent points to improve image anti-noise ability and reconstruction effect. It uses the sparsity of a higher-order gradient to reconstruct a clear image structure and restore smooth changes. In addition, we performed regularization by using the denoising method, alternating direction method of multipliers, and fast Fourier transform theory to improve the efficiency and robustness of our method. Our experimental results show that this method has excellent performance in objective evaluation and subjective visual effects.

Dislocation structures around SiO2 Particles in aged Cu-Cr-SiO2

1978 ◽  
Vol 36 (1) ◽  
pp. 594-595
Author(s):  
N.J. Long ◽  
M.H. Loretto ◽  
C.H. Lloyd
Keyword(s):  
Flow Stress ◽  
Single Crystals ◽  
Room Temperature ◽  
Thin Foil ◽  
Age Hardening ◽  
Dispersion Strengthening ◽  
Accurate Picture ◽  
The Matrix ◽  
Very High ◽  
Good Agreement

IntroductionThere have been several t.e.m. studies (1,2,3,4) of the dislocation arrangements in the matrix and around the particles in dispersion strengthened single crystals deformed in single slip. Good agreement has been obtained in general between the observed structures and the various theories for the flow stress and work hardening of this class of alloy. There has been though some difficulty in obtaining an accurate picture of these arrangements in the case when the obstacles are large (of the order of several 1000's Å). This is due to both the physical loss of dislocations from the thin foil in its preparation and to rearrangement of the structure on unloading and standing at room temperature under the influence of the very high localised stresses in the vicinity of the particles (2,3).This contribution presents part of a study of the Cu-Cr-SiO2 system where age hardening from the Cu-Cr and dispersion strengthening from Cu-Sio2 is combined.

Da eine oder mehrere betroffen …

2020 ◽  
Vol 48 (1) ◽  
pp. 47-100
Author(s):  
Melitta Gillmann
Keyword(s):  
High Frequency ◽  
Formal Language ◽  
Subordinate Clause ◽  
Matrix Clause ◽  
Very High Frequency ◽  
Corpus Study ◽  
Causal Relations ◽  
Legal Texts ◽  
The Matrix ◽  
Very High

AbstractBased on a corpus study conducted using the GerManC corpus (1650–1800), the paper sketches the functional and sociosymbolic development of subordinate clause constructions introduced by the subjunctor da ‘since’ in different text genres. In the second half of the 17th and the first half of the 18th century, the da clauses were characterized by semantic vagueness: Besides temporal, spatial and causal relations, the subjunctor established conditional, concessive, and adversative links between clauses. The corpus study reveals that different genres are crucial to the readings of da clauses. Spatial and temporal usages, for example, occur more often in sermons than in other genres. The conditional reading, in contrast, strongly tends to occur in legal texts, where it displays very high frequency. This could be the reason why da clauses carry indexical meaning in contemporary German and are associated with formal language. Over the course of the 18th century, the causal usages increase in all genres. Surprisingly, these causal da clauses tend to be placed in front of the matrix clause despite the overall tendency of causal clauses to follow the matrix clause.

scholarly journals The Role of Exopolysaccharides in Oral Biofilms

2019 ◽  
Vol 98 (7) ◽  
pp. 739-745 ◽  
Author(s):  
C. Cugini ◽  
M. Shanmugam ◽  
N. Landge ◽  
N. Ramasubbu
Keyword(s):  
Biofilm Formation ◽  
Bacterial Colonization ◽  
Super Resolution ◽  
Extracellular Proteins ◽  
Extracellular Polysaccharides ◽  
Oral Biofilms ◽  
The Matrix ◽  
Oral Microbes ◽  
Biofilm Development

The oral cavity contains a rich consortium of exopolysaccharide-producing microbes. These extracellular polysaccharides comprise a major component of the oral biofilm. Together with extracellular proteins, DNA, and lipids, they form the biofilm matrix, which contributes to bacterial colonization, biofilm formation and maintenance, and pathogenesis. While a number of oral microbes have been studied in detail with regard to biofilm formation and pathogenesis, the exopolysaccharides have been well characterized for only select organisms, namely Streptococcus mutans and Aggregatibacter actinomycetemcomitans. Studies on the exopolysaccharides of other oral organisms, however, are in their infancy. In this review, we present the current research on exopolysaccharides of oral microbes regarding their biosynthesis, regulation, contributions to biofilm formation and stability of the matrix, and immune evasion. In addition, insight into the role of exopolysaccharides in biofilms is highlighted through the evaluation of emerging techniques such as pH probing of biofilm colonies, solid-state nuclear magnetic resonance for macromolecular interactions within biofilms, and super-resolution microscopy analysis of biofilm development. Finally, exopolysaccharide as a potential nutrient source for species within a biofilm is discussed.

Sign in / Sign up

Export Citation Format

Share Document