scholarly journals Enhanced Passive GNSS-Based Radar Imaging Based on Coherent Integrated Multi-Satellite Signals

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 842 ◽  
Author(s):  
Yu Zheng ◽  
Zhuxian Zhang ◽  
Lu Feng ◽  
Peidong Zhu ◽  
Feng Zhou

Weak reflected signal is one of the main problems in a recent developing remote sensing tool—passive GNSS-based radar (GNSS radar). To address this issue, an enhanced GNSS radar imaging scheme on the basis of coherently integrating multiple satellites is proposed. In the proposed scheme, to avoid direct signal interference at surveillance antenna, the satellites that used as transmission of opportunity are in backscattering geometry model. To coherently accumulate echo signal magnitudes of the scene center in the targeted sensing region illuminated by the selected satellites, after performing the paralleled range compressions, a coordinates alignment operator is performed to the respective range domains, in which, pseudorandom noise (PRN) code phases are aligned. Thereafter, the coordinates aligned range compressed signals of the selected satellites are coherently integrated along azimuth domain so that imaging gain is improved and azimuth processing can be accomplished in only one state operation. The theoretical analysis and field proof-of-concept experimental results indicate that compared to both conventional bistatic imaging scheme and the state-of-the-art multi-image fusion scheme, the proposed scheme can provide a higher imaging gain; compared to the state-of-the-art multi-image fusion scheme, the proposed scheme has a less computational complexity and faster algorithm speed.

2021 ◽  
Vol 09 (06) ◽  
pp. 73-108
Author(s):  
Bing Li ◽  
Yong Xian ◽  
Daqiao Zhang ◽  
Juan Su ◽  
Xiaoxiang Hu ◽  
...  

2021 ◽  
Vol 5 (OOPSLA) ◽  
pp. 1-27
Author(s):  
Tian Tan ◽  
Yue Li ◽  
Xiaoxing Ma ◽  
Chang Xu ◽  
Yannis Smaragdakis

Traditional context-sensitive pointer analysis is hard to scale for large and complex Java programs. To address this issue, a series of selective context-sensitivity approaches have been proposed and exhibit promising results. In this work, we move one step further towards producing highly-precise pointer analyses for hard-to-analyze Java programs by presenting the Unity-Relay framework, which takes selective context sensitivity to the next level. Briefly, Unity-Relay is a one-two punch: given a set of different selective context-sensitivity approaches, say S = S1, . . . , Sn, Unity-Relay first provides a mechanism (called Unity)to combine and maximize the precision of all components of S. When Unity fails to scale, Unity-Relay offers a scheme (called Relay) to pass and accumulate the precision from one approach Si in S to the next, Si+1, leading to an analysis that is more precise than all approaches in S. As a proof-of-concept, we instantiate Unity-Relay into a tool called Baton and extensively evaluate it on a set of hard-to-analyze Java programs, using general precision metrics and popular clients. Compared with the state of the art, Baton achieves the best precision for all metrics and clients for all evaluated programs. The difference in precision is often dramatic — up to 71% of alias pairs reported by previously-best algorithms are found to be spurious and eliminated.


2020 ◽  
Vol 64 ◽  
pp. 71-91 ◽  
Author(s):  
Yu Liu ◽  
Lei Wang ◽  
Juan Cheng ◽  
Chang Li ◽  
Xun Chen

2007 ◽  
Vol 8 (2) ◽  
pp. 114-118 ◽  
Author(s):  
A. Ardeshir Goshtasby ◽  
Stavri Nikolov

2014 ◽  
Vol 19 ◽  
pp. 4-19 ◽  
Author(s):  
Alex Pappachen James ◽  
Belur V. Dasarathy

2020 ◽  
Vol 34 (07) ◽  
pp. 12797-12804 ◽  
Author(s):  
Hao Zhang ◽  
Han Xu ◽  
Yang Xiao ◽  
Xiaojie Guo ◽  
Jiayi Ma

In this paper, we propose a fast unified image fusion network based on proportional maintenance of gradient and intensity (PMGI), which can end-to-end realize a variety of image fusion tasks, including infrared and visible image fusion, multi-exposure image fusion, medical image fusion, multi-focus image fusion and pan-sharpening. We unify the image fusion problem into the texture and intensity proportional maintenance problem of the source images. On the one hand, the network is divided into gradient path and intensity path for information extraction. We perform feature reuse in the same path to avoid loss of information due to convolution. At the same time, we introduce the pathwise transfer block to exchange information between different paths, which can not only pre-fuse the gradient information and intensity information, but also enhance the information to be processed later. On the other hand, we define a uniform form of loss function based on these two kinds of information, which can adapt to different fusion tasks. Experiments on publicly available datasets demonstrate the superiority of our PMGI over the state-of-the-art in terms of both visual effect and quantitative metric in a variety of fusion tasks. In addition, our method is faster compared with the state-of-the-art.


2017 ◽  
Vol 33 ◽  
pp. 100-112 ◽  
Author(s):  
Shutao Li ◽  
Xudong Kang ◽  
Leyuan Fang ◽  
Jianwen Hu ◽  
Haitao Yin

Author(s):  
T. A. Welton

Various authors have emphasized the spatial information resident in an electron micrograph taken with adequately coherent radiation. In view of the completion of at least one such instrument, this opportunity is taken to summarize the state of the art of processing such micrographs. We use the usual symbols for the aberration coefficients, and supplement these with £ and 6 for the transverse coherence length and the fractional energy spread respectively. He also assume a weak, biologically interesting sample, with principal interest lying in the molecular skeleton remaining after obvious hydrogen loss and other radiation damage has occurred.


Sign in / Sign up

Export Citation Format

Share Document