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In this article, we propose a novel method utilizing iterative semidefinite relaxation for geolocation of stationary uncooperative radars. In our scenario, the geolocation is to be performed in a receiver located on a moving platform. The proposed method uses frequency measurements that are Doppler-shifted due to the platform motion. First, constructed nonconvex maximum likelihood cost function for position estimation is relaxed to a convex optimization problem by applying linearization to range variables. Then, at each iteration of the method, carrier frequency and position of the radar are estimated jointly. Conducted experiments show that a few iterations are enough for convergence to accurate estimates. The proposed method is computationally less expensive compared to traditional techniques, which require extensive grid search procedures in either position or carrier frequency parameter space. In the experiments, the performance of the proposed method is compared to the state-of-the-art techniques and the Cramer–Rao lower bound (CRLB). It is observed that the proposed method attains the CRLB at low noise levels while still providing accurate solutions at high noise cases. Furthermore, it is also seen that platform-radar geometry has an impact on the proposed method's performance. If the radar lies in the convex hull of the receiver path, the proposed method performs significantly better due to improvement in the linearization of range values. [ABSTRACT FROM AUTHOR]

Simulation of radar sounder (RS) data is important for understanding the radar response of subsurface features to facilitate the interpretation of the real data. Conventional electromagnetic simulators require the definition of complex geoelectrical models of the investigated targets. They also involve time-complex solutions of Maxwell’s equations for computing the received electric field, which leads to very high computation time. Furthermore, the simulated radargrams are often not realistic as it is very difficult to model all the variables involved in the data acquisition. In this paper, we propose a novel simulation approach that exploits the data available from existing RSs in geologically analogous terrains, to produce realistic simulations of the investigated RS target. This simulation strategy is based on minimizing the difference between the analog and the investigated acquisition scenarios. This is done by applying a series of corrections, which depend on the relation between the radargram characteristics and the physical variables describing the acquisition process. The aim is to produce radargrams that resemble the investigated scenario in terms of the echo magnitude, bandwidth, range resolution, and along-track resolution. Experimental results present three case studies for different possibilities of the analog and the investigated scenarios. The validation of the simulated radargrams with actual data demonstrates the effectiveness of the proposed approach. Finally, we also present a real application of this approach for the simulation of Radar for Icy Moon Exploration (RIME) radargrams for a combination of instrument and target parameters, using the SHAllow RADar (SHARAD) radargram acquired over the geological analog of a selected RIME target. [ABSTRACT FROM AUTHOR]

The improved ground resolution of state-of-the-art synthetic aperture radar (SAR) sensors suggests utilizing SAR data for the analysis of urban areas. The appearance of buildings in SAR or interferometric SAR (InSAR) data is characterized by the consequences of the inherent oblique scene illumination, such as layover, occlusion by radar shadow, and multipath signal propagation. Therefore, particularly in dense built-up areas, building reconstruction is often impossible from a single SAR or InSAR measurement alone. But, the reconstruction quality can be significantly improved by a combined analysis of multi-aspect data. In this paper, two approaches are proposed to detect and reconstruct buildings of different size from multi-aspect high-resolution InSAR data sets. Both approaches focus on the recognition of buildings supported by knowledge-based analysis considering the mentioned SAR-specific effects observed in urban areas. Building features are extracted independently for each direction from the magnitude and phase information of the interferometric data. Initial primitives are segmented and afterward projected from slant-range into the world coordinate system. From the fused set of primitives of both flight directions, building hypotheses are generated. The first approach exploits the frequently observed lines of bright double-bounce scattering, which are used for building reconstruction in residential districts. In the case of larger buildings, such as industrial halls, often additional features of roof and façade elements are visible. Therefore, in a second approach, extended buildings are extracted by grouping primitives of different kinds. The two approaches are demonstrated in an urban environment for an InSAR data set, which has spatial resolution of about 30 cm and was taken from two orthogonal flight directions. [ABSTRACT FROM AUTHOR]

In this paper, a novel method is proposed for retrieving 3-D topography of the ground surface by using a single-antenna squint-mode airborne synthetic aperture radar (SAR). The main idea of the method is based on the fact that the spatial 3-D location of a target can be found as the intersection of the range sphere, the Doppler cone, and the elevation plane of the antenna pattern. An accurate estimation of the Doppler centroid for each resolution cell is required to realize this method. Experimental results obtained with a Ku-band airborne SAR are presented. The method calls for using a precise calibrated attitude determination unit. [ABSTRACT FROM AUTHOR]

In this paper, we consider landmine detection using ultrawideband synthetic aperture radar, where the two main challenges are feature extraction and discriminator design. The space-wavenumber processing is proposed to retrieve the frequency- and aspect-angle-dependent scattering features of suspected objects. In order to reduce the dimensionality of the input feature vector for a discriminator, the sequential forward floating selection method is used to choose efficient features. Based on the obtained feature vector, a fuzzy hypersphere support vector machine is designed to deal with the problem of detecting landmines in an unconstrained environment. The experimental results show that the proposed method can achieve a significant improvement in detection performance for antitank mines. [ABSTRACT FROM AUTHOR]

Inverse synthetic aperture radar (ISAR) images are frequently used in target classification and recognition applications. Some classifiers often require features that can be more easily obtained by extracting scattering centers from ISAR data rather than by reconstructing ISAR images. An available method for scattering center extraction, namely, the CLEAN technique, was proposed in a recent paper by Yang et al. In this paper, an improvement of this CLEAN technique is proposed that introduces a new method for detecting scattering centers. The proposed technique is based on a Gaussianity test, and its effectiveness is first theoretically proven and then tested on real data. Moreover, a comparison with the technique proposed by Yang et al. is shown. [ABSTRACT FROM AUTHOR]

A dual-polarization radar system operating in simultaneous transmission mode of both horizontal and vertical polarization states is a viable implementation if only copolar measurements are needed. The simultaneous transmission of horizontal and vertical polarizations results in an arbitrary elliptical polarization state transmitted, whereas the reception states in horizontal and vertical polarizations are neither copolar nor cross-polar to the transmitted state. Because of this, it is often referred as the hybrid mode. Previous studies have shown that the hybrid mode in the linear horizontal and vertical polarization basis is capable of providing measurements similar to the alternate transmission mode for most measurement conditions. These findings are based on the assumption of perfect sensing systems. This paper presents the results of radar system limitations on hybrid mode measurements that in turn are converted to system requirements. It is shown that the polarization purity requirement is more stringent for the hybrid mode compared to the alternate mode of operation. [ABSTRACT FROM AUTHOR]

A method for segmentation and classification of Baltic Sea ice synthetic aperture radar (SAR) images, based on pulse-coupled neural networks (PCNN5), is presented. Also, automated training, which is based on decomposing the total pixel value distribution into a mixture of class distributions, is presented and discussed. The algorithms have been trained and tested using logarithmic scale Radarsat-1 ScanSAR Wide mode images over the Baltic Sea ice. Before the decomposition into mixture of class distributions, an incidence angle correction, specifically designed for these Baltic Sea ice SAR images, is applied. Because the data distributions in the uniform areas of these images are very close to Gaussian distributions, the data are decomposed into a mixture of Gaussian distributions, using the Expectation-Maximazation algorithm. Only uniform image areas are used in the decomposition phase. The mixture of distributions is compared to the distributions of the Baltic Sea ice classes, based on earlier scatterometer measurements and visual video interpretations of the sea ice classes. The parameter values for the PCNN segmentation are defined based on this mixture of distributions. The PCNN segmentation results are also compared to the operational sea ice information of digitized ice charts and to visual interpretation of the sea ice class. [ABSTRACT FROM AUTHOR]

Focuses on the variations of the radar sensitivity to soil moisture with the radar configuration parameters frequency, polarization and angle. What was shown by an analysis of variance.

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