No abstract

Much interest has arisen in the problem of detecting weak optical subpixel objects in a sequence of images immersed in a heavy homogeneous Gaussian clutter background. In optical systems, the presence of the objects changes the background plus the channel noise covariance matrix. Hence, this matrix may be different under null and alternative hypotheses. Because the maximum likelihood estimate of the background covariance matrix is not available when using the primary data set, we use an approximate estimate of a certain number of eigenvalues of the background covariance matrix that are available for estimation. We derived the general likelihood ratio test for the problem at hand and obtained the modified spectrum matching detector (MSpMD). Using the simulation results, we contrast it with well-known spectrum matching detectors and the hypothesis-independent matched subspace detectors. We also present experimental results of small subpixel objects detection on an agitated sea surface, using digital optical experiments that demonstrate the validation of the simulating results. We show the advantage of the MSpMD that allows to detect small subpixel floating objects on an agitated sea surface even with the same means and variances of the reflected signals from the sea surface and the object. © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

Spectrum deployment scenarios and advanced functionalities development in WINNER.) project is a major European research activity to develop a flexible and scalable radio access system for 4G, which is addressing the challenging requirements for future systems such as those of the International Telecommunication Union (ITU) in terms of overall performance, flexibility, scalability and optimized spectrum usage. In this article, the Radio Resource Management (RRM) spectrum functionalities are defined and subsequently analyzed. The proposed RRM spectrum architecture developed will result in reducing the time required to tailor new services to network operators. Furthermore, the flexible spectrum access and usage leads to more capable and faster services with high Quality-of-Service (QoS) giving more user satisfaction than conventional networks. The inherent centralization and decentralization degree for the functionalities is outlined and

This paper proposes the study of a robust control scheme for an Unmanned Surface Vehicle (USV) in a urban waterway using Visual Odometry (VO) for position estimation of the vehicle instead of traditional sensors. For different applications, a USV is required to operate in autonomous navigation mode and under various disturbances inherent to its environment as currents and waves. To achieve efficient operation, a robust control scheme is required to cope with such disturbances. The autonomous navigation is achieved by using VO to estimate the vehicle’s position for denied Global Positioning Systems (GPS) environments. A robust control scheme based on Sliding Modes (SM) control theory is designed and its convergence is guaranteed by means of Lyapunov analysis. The tracking capabilities under disturbance conditions using VO for position estimation are verified in simulation using the virtual world tool from Matlab and Simulink.

Photovoltaic (PV) systems are among the most used alternatives for electrical power generation from renewable sources. To ensure that PV systems make the most of the available solar energy, maximum power point tracking (MPPT) schemes must be implemented, which usually require voltage and current sensors to track the PV power. This paper presents the design of a robust observer using the Attractive Ellipsoid Method to achieve a precise estimation of PV current under parametric uncertainty and output perturbations. The application of such an observer enables the PV generation system to operate in a current sensorless mode, which reduces the overall cost of the system and enhances its reliability. The convergence of the observer is guaranteed by solving an optimization problem which generates the optimal gains using Linear Matrix Inequalities (LMI). To prove the effectiveness of the proposed sensorless scheme, simulations are performed in Matlab under test profiles based on the EN50530 standard and parameter uncertainty conditions, obtaining an accurate estimation which is used for MPPT operation.