SAR imaging of buried objects from MoM modelled scattered field (original) (raw)
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IEEE Transactions on Instrumentation and Measurement, 2019
This contribution introduces three methodologies to improve Synthetic Aperture Radar (SAR)-based techniques used in Ground Penetrating Radar (GPR) systems. They consist of i) equalization of the frequency response of the transmitting (Tx) and receiving (Rx) antennas, ii) processing of SAR images using partially overlapped frequency sub-bands, and iii) imaging domain clustering. The goal is to combine ground penetration capabilities of lower frequency bands with the resolution achieved when increasing the overall frequency band, resulting in enhanced detection and imaging capabilities. Validation of these techniques has been done at three levels: first using simulations, next by means of measurements in a controlled scenario, and finally using a portable setup deployed in a realistic scenario.
Imaging targets embedded in a lossy half space with synthetic aperture radar
Geoscience and Remote Sensing IEEE International Symposium, 1994
This paper addresses theoretical aspects of forming images from an airborne synthetic aperture radar (SAR) of targets buried below the Earth's surface. Soil is generally a lossy, dispersive medium, with wide ranging variability in these attributes depending on soil type, moisture content, and a host of other physical properties. Focussing a SAR subsurface image presents new dimensions of complexity relative
Scattering-Based Model of the SAR Signatures of Complex Targets for Classification Applications
International Journal of Navigation and Observation, 2008
The modeling of complex target response in SAR imagery is the main subject of this paper. The analysis of a large database of SAR images with polarimetric and interferometric capabilities is used to accurately establish how the different structural parts of targets interact with the incident signal. This allows to relate the reflectivity information provided by SAR images with specific geometries and to fix variation reflectivity patterns in terms of different imaging parameters such as image resolution, incidence angle, or operating frequency. Most of the used images have been obtained from the SAR simulator of complex targets developed at UPC, which is able to generate realistic data for a wide range of observation and environmental conditions. The result is a precise scattering-based SAR model that opens the door, among others, to an alternative way for reliable geometry retrieval. Under this approach, a novel SAR classification method for ships has been proposed. The preliminary evaluation in simulated scenarios shows a notable classification capability even under strong clutter and ship motion conditions. Due to these promising results, the same methodology is intended to be applied to urban areas. Concerns about possible model limitations and required improvements are preliminarily treated.
SAR Processing for Buried Objects Detection using GPR
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Mine detection techniques require extremely high detection rates. In this paper, signal processing algorithm is introduced to be applied in the ground penetrating radar (GPR) which is more suitable for this application. In GPR microwave signals penetrate into the ground until a buried object reflects them back and the reflected signals are processed in order to extract information about the target. The proposed algorithm generates complex range profiles by applying Inverse Fast Fourier Transform (IFFT) and corrects phase shift due to the system delay. Afterwards in order to improve resolution, synthetic aperture radar (SAR) processing is applied and SAR matrix is formed as GPR moves to the next position. The results obtained show that this algorithm has overcome the problem of the strong reflected signals from the ground and also the other unwanted signals and clutter Keywords—GPR; Landmines; IFFT; SAR processing
Statistical Analysis of High-Resolution SAR Ground Clutter Data
IEEE Transactions on Geoscience and Remote Sensing, 2007
This paper deals with the problem of modeling highresolution synthetic aperture radar clutter data from different vegetated areas. We analyzed moving and stationary target recognition (MSTAR) data sets focusing on histograms, moments, and covariance of clutter amplitude, texture, and speckle. The most celebrated statistical models are tested on real data of grass field or wood and trees to validate the goodness of fit of the compound Gaussian model in different scenarios. The results demonstrate that for grass fields, the compound Gaussian model provides a good data fitting. This is not the case for woods images where the speckle is not more Gaussian distributed. Covariance analysis and concluding remarks complete this paper.
Microwave and Optical Technology Letters, 2006
and good performance was demonstrated in fabricated devices implemented by means of the dual transmission line concept 15], we have been pioneers in using the resonant-type approach in the design of these devices, and reasonable performance has been obtained. We have also explored the possibility of designing multifrequency couplers by using CSRRs. This paper has demonstrated that the resonant-type approach to left-handed lines is useful and promising, and it can be an alternative to the wellestablished dual-transmission-line approach in narrow-or moderate-bandwidth applications.
A model for forming airborne synthetic aperture radar images of underground targets
1994
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From Maxwell’s Equations to Polarimetric SAR Images: A Simulation Approach
Sensors, 2008
A new electromagnetic approach for the simulation of polarimetric SAR images is proposed. It starts from Maxwell's equations, employs the spectral domain full-wave technique, the moment method, and the stationary phase method to compute the far electromagnetic fields scattered by multilayer structures. A multilayer structure is located at each selected position of a regular rectangular grid of coordinates, which defines the scene area under imaging. The grid is determined taking into account the elementary scatter size and SAR operational parameters, such as spatial resolution, pixel spacing, look angle and platform altitude. A two-dimensional separable "sinc" function to represent the SAR spread point function is also considered. Multifrequency sets of single-look polarimetric SAR images are generated, in L-, C-and X-bands and the images are evaluated using several measurements commonly employed in SAR data analysis. The evaluation shows that the proposed simulation process is working properly, since the obtained results are in accordance with those presented in the literature. Therefore, this new approach becomes suitable for carrying out theoretical and practical studies using polarimetric SAR images.
IEEE Transactions on Geoscience and Remote Sensing, 2002
A rigorous three-dimensional (3-D) electromagnetic model is developed to analyze the scattering from anti-personnel (AP) nonmetallic mine-like target when it is buried near a clutter object under two-dimensional (2-D) random rough surfaces. The steepest descent fast multipole method (SDFMM) is implemented to solve for the unknown electric and magnetic surface currents on the ground surface, on the target and on the clutter object. A comprehensive numerical investigation of two clutter sources; the ground roughness and the nearby benign object, is presented based on using more than 800 random rough surface realizations which could not be achieved without using fast algorithms such as the SDFMM. The statistics of the scattered near-electric fields are computed using the Monte Carlo simulations for both polarizations. For the parameters used here, the results show that the average and the standard deviation of the target signature represent 5-7% and 3-3.5% of the total scattered signal, respectively, while they represent 16-20% and 7-12% of the signal for the clutter object, respectively. This study indicates the high possibility of a false alarm during the detection process when the target is located nearby a realistic object such as a piece of a tree root.