scholarly journals Joint Sparsity for TomoSAR Imaging in Urban Areas Using Building POI and TerraSAR-X Staring Spotlight Data

Sensors ◽  
2021 ◽  
Vol 21 (20) ◽  
pp. 6888
Author(s):  
Lei Pang ◽  
Yanfeng Gai ◽  
Tian Zhang
Keyword(s):  
Urban Areas ◽  
Super Resolution ◽  
Likelihood Estimation ◽  
Satellite Orbit ◽  
Synthetic Aperture ◽  
Estimation Methods ◽  
Spectrum Estimation ◽  
Sar Images ◽  
Dense Point ◽  
Very High

Synthetic aperture radar (SAR) tomography (TomoSAR) can obtain 3D imaging models of observed urban areas and can also discriminate different scatters in an azimuth–range pixel unit. Recently, compressive sensing (CS) has been applied to TomoSAR imaging with the use of very-high-resolution (VHR) SAR images delivered by modern SAR systems, such as TerraSAR-X and TanDEM-X. Compared with the traditional Fourier transform and spectrum estimation methods, using sparse information for TomoSAR imaging can obtain super-resolution power and robustness and is only minorly impacted by the sidelobe effect. However, due to the tight control of SAR satellite orbit, the number of acquisitions is usually too low to form a synthetic aperture in the elevation direction, and the baseline distribution of acquisitions is also uneven. In addition, artificial outliers may easily be generated in later TomoSAR processing, leading to a poor mapping product. Focusing on these problems, by synthesizing the opinions of various experts and scholarly works, this paper briefly reviews the research status of sparse TomoSAR imaging. Then, a joint sparse imaging algorithm, based on the building points of interest (POIs) and maximum likelihood estimation, is proposed to reduce the number of acquisitions required and reject the scatterer outliers. Moreover, we adopted the proposed novel workflow in the TerraSAR-X datasets in staring spotlight (ST) work mode. The experiments on simulation data and TerraSAR-X data stacks not only indicated the effectiveness of the proposed approach, but also proved the great potential of producing a high-precision dense point cloud from staring spotlight (ST) data.

Markovian Change Detection of Urban Areas Using Very High Resolution Complex SAR Images

2014 ◽  
Vol 11 (5) ◽  
pp. 995-999 ◽  
Author(s):  
Fabio Baselice ◽  
Giampaolo Ferraioli ◽  
Vito Pascazio
Keyword(s):  
High Resolution ◽  
Change Detection ◽  
Urban Areas ◽  
Sar Images ◽  
Very High

scholarly journals ANALYSIS OF SCATTERING COMPONENTS FROM FULLY POLARIMETRIC SAR IMAGES FOR IMPROVING ACCURACIES OF URBAN DENSITY ESTIMATION

2016 ◽  
Vol III-7 ◽  
pp. 219-226
Author(s):  
J. Susaki
Keyword(s):  
Normal Distribution ◽  
Urban Areas ◽  
Synthetic Aperture ◽  
Sar Image ◽  
Polarimetric Sar ◽  
Sar Images ◽  
Polarimetric Synthetic Aperture Radar ◽  
Urban Density ◽  
Concrete Blocks ◽  
Image Pixels

In this paper, we analyze probability density functions (PDFs) of scatterings derived from fully polarimetric synthetic aperture radar (SAR) images for improving the accuracies of estimated urban density. We have reported a method for estimating urban density that uses an index <i>T</i><sub><i>v</i>+<i>c</i></sub> obtained by normalizing the sum of volume and helix scatterings <i>P</i><sub><i>v</i>+<i>c</i></sub>. Validation results showed that estimated urban densities have a high correlation with building-to-land ratios (Kajimoto and Susaki, 2013b; Susaki et al., 2014). While the method is found to be effective for estimating urban density, it is not clear why <i>T</i><sub><i>v</i>+<i>c</i></sub> is more effective than indices derived from other scatterings, such as surface or double-bounce scatterings, observed in urban areas. In this research, we focus on PDFs of scatterings derived from fully polarimetric SAR images in terms of scattering normalization. First, we introduce a theoretical PDF that assumes that image pixels have scatterers showing random backscattering. We then generate PDFs of scatterings derived from observations of concrete blocks with different orientation angles, and from a satellite-based fully polarimetric SAR image. The analysis of the PDFs and the derived statistics reveals that the curves of the PDFs of <i>P</i><sub><i>v</i>+<i>c</i></sub> are the most similar to the normal distribution among all the scatterings derived from fully polarimetric SAR images. It was found that <i>T</i><sub><i>v</i>+<i>c</i></sub> works most effectively because of its similarity to the normal distribution.

scholarly journals A Low-Cost Active Reflector for Interferometric Monitoring Based on Sentinel-1 SAR Images

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2008
Author(s):  
Guido Luzi ◽  
Pedro F. Espín-López ◽  
Fermín Mira Pérez ◽  
Oriol Monserrat ◽  
Michele Crosetto
Keyword(s):  
Urban Areas ◽  
Low Cost ◽  
Cost Benefit ◽  
Weather Conditions ◽  
Severe Weather ◽  
Synthetic Aperture ◽  
Stable Phase ◽  
Dense Network ◽  
Sar Images ◽  
Active Reflector

The effectiveness of radar interferometric techniques in non-urban areas can often be compromised due to the lack of stable natural targets. This drawback can be partially compensated through the installation of reference targets, characterized by a bright and stable radar response. The installation of passive corner reflectors (PCR) often represents a valid aid, but these objects are usually cumbersome, and suffer from severe weather conditions; furthermore, the installation of a PCR can be difficult and costly, especially in places with hard accessibility. Active reflectors (AR) represent a less cumbersome alternative to PCRs, while still providing a stable phase response. This paper describes the design, implementation, and test of an AR prototype, designed to operate with the Sentinel-1 synthetic aperture radar (SAR), aimed at providing a fair performance/cost benefit. These characteristics, obtained through a tradeoff between the use of off-the-shelf components and a simple architecture, can make the setup of a dense network (i.e., tens of devices) in the monitored areas feasible. The paper reports the design, implementation, and the analysis of different tests carried out in a laboratory, and in a real condition in the field, to illustrate AR reliability and estimate its phase stability.

scholarly journals PRE-PROCESSES FOR URBAN AREAS DETECTION IN SAR IMAGES

2017 ◽  
Vol XLII-4/W6 ◽  
pp. 15-17
Author(s):  
S. Altay Açar ◽  
Ş. Bayır
Keyword(s):  
Experimental Study ◽  
Synthetic Aperture Radar ◽  
Urban Areas ◽  
Binary Image ◽  
Synthetic Aperture ◽  
Image Smoothing ◽  
Sar Images ◽  
Aperture Radar

In this study, pre-processes for urban areas detection in synthetic aperture radar (SAR) images are examined. These pre-processes are image smoothing, thresholding and white coloured regions determination. Image smoothing is carried out to remove noises then thresholding is applied to obtain binary image. Finally, candidate urban areas are detected by using white coloured regions determination. All pre-processes are applied by utilizing the developed software. Two different SAR images which are acquired by TerraSAR-X are used in experimental study. Obtained results are shown visually.

scholarly journals ANALYSIS OF SCATTERING COMPONENTS FROM FULLY POLARIMETRIC SAR IMAGES FOR IMPROVING ACCURACIES OF URBAN DENSITY ESTIMATION

2016 ◽  
Vol III-7 ◽  
pp. 219-226
Author(s):  
J. Susaki
Keyword(s):  
Normal Distribution ◽  
Urban Areas ◽  
Synthetic Aperture ◽  
Sar Image ◽  
Polarimetric Sar ◽  
Sar Images ◽  
Polarimetric Synthetic Aperture Radar ◽  
Urban Density ◽  
Concrete Blocks ◽  
Image Pixels

In this paper, we analyze probability density functions (PDFs) of scatterings derived from fully polarimetric synthetic aperture radar (SAR) images for improving the accuracies of estimated urban density. We have reported a method for estimating urban density that uses an index &lt;i&gt;T&lt;/i&gt;&lt;sub&gt;&lt;i&gt;v&lt;/i&gt;+&lt;i&gt;c&lt;/i&gt;&lt;/sub&gt; obtained by normalizing the sum of volume and helix scatterings &lt;i&gt;P&lt;/i&gt;&lt;sub&gt;&lt;i&gt;v&lt;/i&gt;+&lt;i&gt;c&lt;/i&gt;&lt;/sub&gt;. Validation results showed that estimated urban densities have a high correlation with building-to-land ratios (Kajimoto and Susaki, 2013b; Susaki et al., 2014). While the method is found to be effective for estimating urban density, it is not clear why &lt;i&gt;T&lt;/i&gt;&lt;sub&gt;&lt;i&gt;v&lt;/i&gt;+&lt;i&gt;c&lt;/i&gt;&lt;/sub&gt; is more effective than indices derived from other scatterings, such as surface or double-bounce scatterings, observed in urban areas. In this research, we focus on PDFs of scatterings derived from fully polarimetric SAR images in terms of scattering normalization. First, we introduce a theoretical PDF that assumes that image pixels have scatterers showing random backscattering. We then generate PDFs of scatterings derived from observations of concrete blocks with different orientation angles, and from a satellite-based fully polarimetric SAR image. The analysis of the PDFs and the derived statistics reveals that the curves of the PDFs of &lt;i&gt;P&lt;/i&gt;&lt;sub&gt;&lt;i&gt;v&lt;/i&gt;+&lt;i&gt;c&lt;/i&gt;&lt;/sub&gt; are the most similar to the normal distribution among all the scatterings derived from fully polarimetric SAR images. It was found that &lt;i&gt;T&lt;/i&gt;&lt;sub&gt;&lt;i&gt;v&lt;/i&gt;+&lt;i&gt;c&lt;/i&gt;&lt;/sub&gt; works most effectively because of its similarity to the normal distribution.

scholarly journals Συστήματα ραντάρ τύπου αντίστροφου συνθετικού ανοίγματος (ISAR)

2013 ◽  
Author(s):  
Ευάγγελος Καλλίτσης
Keyword(s):  
Synthetic Aperture Radar ◽  
Super Resolution ◽  
Synthetic Aperture ◽  
Spectrum Estimation ◽  
Inverse Synthetic Aperture Radar ◽  
Aperture Radar

Αντικείμενο της διατριβής αποτελεί η μελέτη των συστημάτων ραντάρ αντίστροφου συνθετικού ανοίγματος (ISAR, Inverse Synthetic Aperture Radar), καθώς και η ανάπτυξη καινοτόμων αλγορίθμων απεικόνισης στόχων ραντάρ. Η σπουδαιότερη καινοτομία της διατριβής αυτής είναι ο προτεινόμενος πλήρης αυτοματοποιημένος αλγόριθμος αυτοεστίασης για την μετεπεξεργασμένη εικόνα του ραντάρ αντίστροφου συνθετικού ανοίγματος (ISAR) που βασίζεται στην ελαχιστοποίηση της εντροπίας, καθώς και η μέθοδος που αφορά την ακριβή ευθυγράμμιση της απόστασης για την αντιστάθμιση της περιστροφικής κίνησης στην οριζόντια διεύθυνση με εφαρμογή στο ραντάρ ISAR (τρίτο και τέταρτο κεφάλαιο). Στην παρούσα έρευνα συγκριτικά με αντίστοιχες δημοσιευμένες εργασίες, ο μεν προτεινόμενος αλγόριθμος για την αυτοεστίαση της εικόνας ISAR είναι ευριστικός και βασίζεται στον διαχωρισμό του συμφασικού διαστήματος επεξεργασίας (CPI) σε βαθμίδες, η δε μέθοδος της ευθυγράμμισης της απόστασης που βασίζεται στην τεχνική της υπεραναλυμένης φασματικής εκτίμησης με υποδιπλασιασμό (Super-resolution DESED-decimative Spectrum Estimation) χρησιμοποιεί έναντι των κλασικών μεθόδων ευθυγράμμισης της απόστασης, την τεχνική της κλασματικής διόρθωσης του κελιού απόστασης (fractional range bin correction) ανά σκεδαστή. Για την εγκυρότητα και αποδοτικότητα των μεθόδων που αναπτύσσονται στην παρούσα διατριβή περιλαμβάνονται ακριβείς μαθηματικές αναλύσεις καθώς και τα αποτελέσματα προσομοίωσης με συνθετικά δεδομένα ISAR κάτω από ρεαλιστικά σενάρια για την ομοιόμορφη και μη ομοιόμορφη περιστροφική κίνηση.

scholarly journals Towards a 20 m Global Building Map from Sentinel-1 SAR Data

2018 ◽  
Vol 10 (11) ◽  
pp. 1833 ◽  
Author(s):  
Marco Chini ◽  
Ramona Pelich ◽  
Renaud Hostache ◽  
Patrick Matgen ◽  
Carlos Lopez-Martinez
Keyword(s):  
Arid Regions ◽  
Synthetic Aperture ◽  
False Alarms ◽  
Satellite Mission ◽  
Sar Images ◽  
Multi Temporal ◽  
Interferometric Sar ◽  
Very High ◽  
Urban Footprint ◽  
Wide Swath

This study introduces a technique for automatically mapping built-up areas using synthetic aperture radar (SAR) backscattering intensity and interferometric multi-temporal coherence generated from Sentinel-1 data in the framework of the Copernicus program. The underlying hypothesis is that, in SAR images, built-up areas exhibit very high backscattering values that are coherent in time. Several particular characteristics of the Sentinel-1 satellite mission are put to good use, such as its high revisit time, the availability of dual-polarized data, and its small orbital tube. The newly developed algorithm is based on an adaptive parametric thresholding that first identifies pixels with high backscattering values in both VV and VH polarimetric channels. The interferometric SAR coherence is then used to reduce false alarms. These are caused by land cover classes (other than buildings) that are characterized by high backscattering values that are not coherent in time (e.g., certain types of vegetated areas). The algorithm was tested on Sentinel-1 Interferometric Wide Swath data from five different test sites located in semiarid and arid regions in the Mediterranean region and Northern Africa. The resulting building maps were compared with the Global Urban Footprint (GUF) derived from the TerraSAR-X mission data and, on average, a 92% agreement was obtained.

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