Efficient Raw Signal Generation Based on Equivalent Scatterer and Subaperture Processing for SAR with Arbitrary Motion

An efficient SAR raw signal generation method based on equivalent scatterer and subaperture processing is proposed in this paper. It considers the radar’s motion track, which can obtain the precise raw signal for the real SAR. First, the imaging geometry with arbitrary motion is established, and then the scene is divided into several equidistant rings. Based on the equivalent scatterer model, the approximate expression of the SAR system transfer function is derived, thus each pulse’s raw signal can be generated by the convolution of the transmitted signal and system transfer function, performed by the fast Fourier transform (FFT). To further improve the simulation efficiency, the subaperture and polar subscene processing is used. The system transfer function of pluses for the same subaperture is calculated simultaneously by the weighted sum of all subscenes’ equivalent backscattering coefficient in the same equidistant ring, performed by the nonuniform FFT (NUFFT). The method only involves the FFT, NUFFT and complex multiplication operations, which means the easier implementation and higher efficiency. Simulation results are given to prove the validity of this method

Monitoring of Collapsed Built-Up Areas with High Resolution SAR Images

A 16-year-old male with cystic fibrosis (CF) was admitted to hospital with a severe infective exacerbation. Despite standard management, including conventionally selected intravenous antibiotics for Pseudomonas aeruginosa chest physiotherapy, and institution of noninvasive ventilation (NIV) for progressive hypercapneic respiratory failure, he continued to deteriorate. Direct sputum sensitivity testing (DSST) revealed a novel combination of antibiotics that resulted in a rapid and remarkable clinical improvement. DSST is a form of "whole" sputum sensitivity testing that provides information on antibiotic synergy, and may more accurately reflect in vivo antibiotic sensitivity patterns in cystic fibrosis.</p

Modeling the Radar Return of Powerlines Using an Incremental Length Diffraction Coefficient Approach

A method for modeling the signal from cables and powerlines in Synthetic Aperture Radar (SAR) imagery is presented. Powerline detection using radar is an active area of research. Accurately identifing the location of powerlines in a scene can be used to aid pilots of low flying aircraft in collision avoidance, or map the electrical infrastructure of an area. The focus of this research was on the forward modeling problem of generating the powerline SAR signal from first principles. Previous work on simulating SAR imagery involved methods that ranged from efficient but insufficiently accurate, depending on the application, to more exact but computationally complex. A brief survey of the numerous ways to model the scattering of electromagnetic radiation is provided. A popular tool that uses the geometric optics approximation for modeling imagery for remote sensing applications across a wide range of modalities is the Digitial Imaging and Remote Sensing Image Generation (DIRSIG) tool. This research shows the way in which DIRSIG generates the SAR phase history is unique compared to other methods used. In particular, DIRSIG uses the geometric optics approximation for the scattering of electromagnetic radiation and builds the phase history in the time domain on a pulse-by-pulse basis. This enables an efficient generation of the phase history of complex scenes. The drawback to this method is the inability to account for diffraction. Since the characteristic diameter of many communication cables and powerlines is on the order of the wavelength of the incident radiation, diffraction is the dominant mechanism by which the radiation gets scattered for these targets. Comparison of DIRSIG imagery to field data shows good scene-wide qualitative agreement as well as Rayleigh distributed noise in the amplitude data, as expected for coherent imaging with speckle. A closer inspection of the Radar Cross Sections of canonical targets such as trihedrals and dihedrals, however, shows DIRSIG consistently underestimated the scattered return, especially away from specular observation angles. This underestimation was particularly pronounced for the dihedral targets which have a low acceptance angle in elevation, probably caused by the lack of a physical optics capability in DIRSIG. Powerlines were not apparent in the simulated data. For modeling powerlines outside of DIRSIG using a standalone approach, an Incremental Length Diffraction Coefficient (ILDC) method was used. Traditionally, this method is used to model the scattered radiation from the edge of a wedge, for example the edges on the wings of a stealth aircraft. The Physical Theory of Diffraction provides the 2D diffraction coefficient and the ILDC method performs an integral along the edge to extend this solution to three dimensions. This research takes the ILDC approach but instead of using the wedge diffraction coefficient, the exact far-field diffraction coefficient for scattering from a finite length cylinder is used. Wavenumber-diameter products are limited to less than or about 10. For typical powerline diameters, this translates to X-band frequencies and lower. The advantage of this method is it allows exact 2D solutions to be extended to powerline geometries where sag is present and it is shown to be more accurate than a pure physical optics approach for frequencies lower than millimeter wave. The Radar Cross Sections produced by this method were accurate to within the experimental uncertainty of measured RF anechoic chamber data for both X and C-band frequencies across an 80 degree arc for 5 different target types and diameters. For the X-band data, the mean error was 6.0% for data with 9.5% measurement uncertainty. For the C-band data, the mean error was 11.8% for data with 14.3% measurement uncertainty. The best results were obtained for X-band data in the HH polarization channel within a 20 degree arc about normal incidence. For this configuration, a mean error of 3.0% for data with a measurement uncertainty of 5.2% was obtained. The least accurate results were obtained for X-band data in the VV polarization channel within a 20 degree arc about normal incidence. For this configuration, a mean error of 8.9% for data with a measurement uncertainty of 5.9% was obtained. This error likely arose from making the smooth cylinder assumption, which neglects the semi-open waveguide TE contribution from the grooves in the helically wound powerline. For field data in an actual X-band circular SAR collection, a mean error of 3.3% for data with a measurement uncertainty of 3.3% was obtained in the HH channel. For the VV channel, a mean error of 9.9% was obtained for data with a measurement uncertainty of 3.4%. Future work for improving this method would likely entail adding a far-field semi-open waveguide contribution to the 2D diffraction coefficient for TE polarized radiation. Accounting for second order diffractions between closely spaced powerlines would also lead to improved accuracy for simulated field data

Electromagnetic Modelling for Information Extraction from High Resolution SAR Images of Urban Areas

Analysis, interpretation and feature extraction concerning High Resolution (HR) Synthetic Aperture Radar (SAR) images of urban areas urgently require support of sound and appropriate electromagnetic modelling. The modelling takes into consideration the radar geometry and the (geometric and electromagnetic) scene parameters but also the novelty brought by high resolution. In this paper, this way of developing suitable electromagnetic modelling for HR SAR images of urban areas is shown to be successful as able to interpret and retrieve, from these scenarios, new and interesting details that will certainly represent the main actor of next generation of applications for urban areas with SAR sensors

A SAR image-based tool for prompt and effective earthquake response

Recently, a new concept for detection of damaged infrastructure after earthquakes has been introduced, based on analysis of double reflection lines in SAR images. This paper describes the development of a processing step for extraction of double-reflection lines, and its implementation. In particular, an unsupervised bright line detector working on the ratio of pre- and post-event single look complex SAR data is introduced, and is demonstrated using COSMO-SkyMed SAR data from the 2009 L'Aquila earthquake

Towards a 20m global building map from Sentinel-1 SAR Data

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.Peer ReviewedPostprint (published version

An algorithm for operational flood mapping from Synthetic Aperture Radar (SAR) data using fuzzy logic

Abstract. An algorithm developed to map flooded areas from synthetic aperture radar imagery is presented in this paper. It is conceived to be inserted in the operational flood management system of the Italian Civil Protection and can be used in an almost automatic mode or in an interactive mode, depending on the user's needs. The approach is based on the fuzzy logic that is used to integrate theoretical knowledge about the radar return from inundated areas taken into account by means of three electromagnetic scattering models, with simple hydraulic considerations and contextual information. This integration aims at allowing a user to cope with situations, such as the presence of vegetation in the flooded area, in which inundation mapping from satellite radars represents a difficult task. The algorithm is designed to work with radar data at L, C, and X frequency bands and employs also ancillary data, such as a land cover map and a digital elevation model. The flood mapping procedure is tested on an inundation that occurred in Albania on January 2010 using COSMO-SkyMed very high resolution X-band SAR data