Comparing Multistatic with Monostatic Super-Resolution Array Processing Techniques: Detection of Random Targets

2006 ◽  
Author(s):  
Minhtri Ho ◽  
H. Lev-Ari
Keyword(s):  
Array Processing ◽  
Super Resolution ◽  
Processing Techniques

scholarly journals Spatial Enhancement of AWiFS along Wider Swath using NSCT

2018 ◽  
Vol 7 (3.12) ◽  
pp. 474
Author(s):  
K S. R. Radhika ◽  
C V. Rao ◽  
V Kamakshi Prasad
Keyword(s):  
Temporal Resolution ◽  
Accuracy Assessment ◽  
Super Resolution ◽  
Computation Time ◽  
Processing Technique ◽  
Sensor Data ◽  
Liss Iii ◽  
Novel Processing ◽  
Single Image Super Resolution ◽  
Processing Techniques

Image acquisition in a wider swath, cannot assess the best spatial resolution (SR) and temporal resolution (TR) simultaneously, due to inherent limitations of space borne sensors. But any of the information extraction from remote sensed (RS) images demands the above characteristics. As this is not possible onboard, suitable ground processing techniques need to be evolved to realise the requirements through advanced image processing techniques. The proposed work deals with processing of two onboard sensor data viz., Resourcesat-1 (RS1): LISS-III, which has medium swath combined with AWiFS, which has wider swath data to provide high spatial and temporal resolution at the same instant. LISS-III at 23m and 24 days, AWiFS at 56m and 5 days spatial and temporal revisits acquire the data at different swaths. In the process of acquisition at the same time, the 140km swath of LISS-III coincides at the exact centre line 740km swath of AWiFS. If the non-overlapping area of AWiFS has same features of earth’s surface as of LISS-III overlapping area, it then provides a way to increase the SR of AWiFS to SR of LISS-III in the same non-overlapping area. Using this knowledge, a novel processing technique Fast One Pair Learning and Prediction (FOPLP) is developed in which time is optimized against the existing methods. FOPLP improves the SR of LISS-III in non-overlapping area using technique Single Image Super Resolution (SISR) with Non Sub sampled Contourlet Transforms (NSCT) method and is applied on different sets of images. The proposed technique resulting into an image having TR of 5 days, 740km swath at SR of 23m. Results have shown the strength of the proposed method in terms of computation time and prediction accuracy assessment.  

Array processing techniques for multiuser detection

1997 ◽  
Vol 45 (11) ◽  
pp. 1375-1378 ◽  
Author(s):  
J.B. Schodorf ◽  
D.B. Williams
Keyword(s):  
Multiuser Detection ◽  
Array Processing ◽  
Processing Techniques

scholarly journals Sparsity Based Full Rank Polarimetric Reconstruction of Coherence Matrix T

2019 ◽  
Vol 11 (11) ◽  
pp. 1288 ◽  
Author(s):  
Hossein Aghababaee ◽  
Giampaolo Ferraioli ◽  
Laurent Ferro-Famil ◽  
Gilda Schirinzi ◽  
Yue Huang
Keyword(s):  
Super Resolution ◽  
Full Rank ◽  
Real Data ◽  
Natural Environments ◽  
Data Sets ◽  
Scattering Pattern ◽  
Component Decomposition ◽  
Resolution Imaging ◽  
Processing Techniques ◽  
Physical Features

In the frame of polarimetric synthetic aperture radar (SAR) tomography, full-ranks reconstruction framework has been recognized as a significant technique for fully characterization of superimposed scatterers in a resolution cell. The technique, mainly is characterized by the advantages of polarimetric scattering pattern reconstruction, allows physical feature extraction of the scatterers. In this paper, to overcome the limitations of conventional full-rank tomographic techniques in natural environments, a polarimetric estimator with advantages of super-resolution imaging is proposed. Under the frame of compressive sensing (CS) and sparsity based reconstruction, the profile of second order polarimetric coherence matrix T is recovered. Once the polarimetric coherence matrices of the scatterers are available, the physical features can be extracted using classical polarimetric processing techniques. The objective of this study is to evaluate the performance of the proposed full-rank polarimetric reconstruction by means of conventional three-component decomposition of T, and focusing on the consistency of vertical resolution and polarimetric scattering pattern of the scatterers. The outcomes from simulated and two different real data sets confirm that significant improvement can be achieved in the reconstruction quality with respect to conventional approaches.

Improving Seismic Resolution Through Array Processing Techniques

2009 ◽  
Vol 30 (4-5) ◽  
pp. 271-299 ◽  
Author(s):  
Sebastian Rost ◽  
Christine Thomas
Keyword(s):  
Array Processing ◽  
Seismic Resolution ◽  
Processing Techniques
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