SAR image registration in the presence of rotation and translation : a constrained least squares approach

This letter proposes a coregistration algorithm to compensate for possible inaccuracy of trajectory sensor during the SAR image acquisition process. Such a misalignment can be modeled as a pure displacement in range and azimuth directions and a rotation effect due to different angle of sight. The approach is formalized as a Constrained Least Squares (CLS) optimization problem enforcing a constraint of absence of a zooming effect between the two SAR images. Moreover, system equations can optionally be weighted according to local properties between the extracted patches within the quoted couple. Interestingly, the solution can be obtained in closed-form, therefore with a low computational cost. The results of the tests conducted on the 9.6GHz Gotcha SAR data demonstrate the capability of the strategy to proper register the imagery

Sensor Failure Detection for TDOA-based Localization Systems

This paper outlines a strategy for identifying sensors in a passive locating system that are not functioning properly. The framework is based on the information extracted from delay estimation errors, obtained from solving a system of equations in which the cross- and cross-cross-correlation methods are both used. Hence, we remove equations with the highest errors and use a statistical test to identify which sensor is experiencing failure. Our approach is analyzed through numerical simulations and real-recorded data, and compared to heuristic and conventional methods to prove its advantages

Espacio-tiempo caótico

En este artículo se demuestra cómo la consideración de una mecánica caótica suministra una redefinición del  espacio-tiempo en la teoría de la relatividad especial. En particular, el tiempo caótico significa que no hay una  posibilidad de definir el ordenamiento temporal lo que implica una ruptura de la causalidad. Las nuevas  transformaciones caóticas entre las coordenadas espaciotemporales ‘indeterminadas’ no son más lineales y  homogéneas. Los principios de inercia y el impulso de la conservación de la energía ya no son bien definidos y  en todo caso no son más invariantes.In this paper we have shown how the consideration of a chaotic mechanics supplies a redefinition of  special‑relativistic space‑time. In particular chaotic time means no possibility of defining temporal ordering and  implies a breakdown of causality. The new chaotic transformations among ‘undetermined’ space‑time  coordinates are no more linear and homogeneous. The principles of inertia and of energy‑impulse conservation are no longer well defined and in any case no more invariant

User Localization for Rescue Operations Exploiting the Cross-Cross-Correlations of Signals from Multiple Sensors

Delay estimation of incoming signals in passive systems is still nowadays at the base of many signal processing applications ranging from passive radars to underwater acoustics, indoor acoustic positioning, and others. This paper aims at improving the estimation of the delays with respect to multiple sensing nodes for user localization for rescue operations under the unavailability of the base stations in the area of interest. To this end, it suitably exploits a method grounded on the computation of the cross-correlation between the cross-correlation estimates (say cross-cross-correlation) of the received signals. The estimation problem is formulated as a least squares (LS) optimization problem. As a consequence, the proposed method inherits an important feature of the LS approach, namely that is independent of the underlying data distributions. The performance assessment is conducted in comparison with its classic counterpart

Robust Target Localization for Multistatic Passive Radar Networks

Passive multistatic radar networks localize a non-cooperative target exploiting the bistatic measurements associated with signals emitted by several transmitters of opportunity and acquired by multiple receivers. However, in realistic scenarios, it might happen that one or more receivers are damaged and/or under malicious attacks with a consequent degradation of the system performance. This paper proposes a procedure to reveal sensors that return anomalous measurements due to an attack or a failure. Specifically, we first detect such measurements by solving a binary hypothesis test, then we cancel them and estimate the final delays as well as the target position. The performance of the overall architecture is assessed using both synthetic data and real-recorded data

Variable kinematic plate elements coupled via Arlequin method

In this work, plate elements based on different kinematic assumptions and variational principles are combined through the Arlequin method. Computational costs are reduced assuming refined models only in those zones with a quasi-three-dimensional stress field, whereas computationally cheap, low-order elements are used in the remaining parts of the plate. Plate elements are formulated on the basis of a unified formulation (UF). Via UF, higher-order, layer-wise and mixed theories can be easily formulated. Classical theories, such as Kirchhoff's and Reissner's models, can be obtained as particular cases. UF is extended to the Arlequin method to derive the matrices that account for the coupling between different theories. Multi-layered composite plates are investigated. Variable kinematic multiple models solutions are assessed towards mono-model results and three-dimensional exact results. Numerical investigation has shown that Arlequin method in the context of UF effectively couples sub-domains having finite elements based upon different theories, reducing the computational costs without loss of accurac

Subpixel SAR image registration through parabolic interpolation of the 2D cross-correlation

In this article, the problem of synthetic aperture radar (SAR) images coregistration is considered. In particular, a novel algorithm aimed at achieving a fine subpixel coregistration accuracy is developed. The procedure is based on the parabolic interpolation of the 2-D cross correlation computed between the two SAR images to be aligned. More precisely, from the 2-D cross correlation, a neighborhood of its peak value is extracted and the interpolation of both the 2-D paraboloid and the two alternative 1-D parabolas is computed to provide the finer misregistration estimation with subpixel accuracy. The main advantage of the proposed framework is that the overall computational burden is only due to the 2-D cross correlation estimation since the parabolic interpolation is calculated with a closed-form expression. The results obtained on real recorded unmanned aerial vehicle (UAV) SAR data highlight the effectiveness of the proposed approach as well as its capabilities to provide some benefits with respect to other available strategies

A FEM Free Vibration Analysis of Variable Stiffness Composite Plates through Hierarchical Modeling

Variable Angle Tow (VAT) laminates offer a promising alternative to classical straight-fiber composites in terms of design and performance. However, analyzing these structures can be more complex due to the introduction of new design variables. Carrera’s unified formulation (CUF) has been successful in previous works for buckling, vibrational, and stress analysis of VAT plates. Typically, one-dimensional (1D) and two-dimensional (2D) CUF models are used, with a linear law describing the fiber orientation variation in the main plane of the structure. The objective of this article is to expand the CUF 2D plate finite elements family to perform free vibration analysis of composite laminated plate structures with curvilinear fibers. The primary contribution is the application of Reissner’s mixed variational theorem (RMVT) to a CUF finite element model. The principle of virtual displacements (PVD) and RMVT are both used as variational statements for the study of monolayer and multilayer VAT plate dynamic behavior. The proposed approach is compared to Abaqus three-dimensional (3D) reference solutions, classical theories and literature results to investigate the effectiveness of the developed models. The results demonstrate that mixed theories provide the best approximation of the reference solution in all cases