Marco A. M. Marinho

A Signal Adaptive Array Interpolation Approach with Reduced Transformation Bias for DOA estimation of Highly Correlated Signals

Sensor arrays with Vandermonde or centro-hermitian responses cannot always be constructed. However, such array response structure can be achieved by means of a mapping which transforms the real array response to an array response with the desired properties by applying array interpolation algorithms. In this work a low-complexity, multi-sector, signal adaptive array interpolation approach that achieves low transformation bias in the presence of highly correlated signals is presented. Estimation of Signal Parameters via Rotational Invariance (ESPRIT) algorithm with Forward Backward Average (FBA) and Spatial Smoothing (SPS) as well as model order estimation is applied after array interpolation in conjunction with the Vandermonde Invariance Transformation (VIT) to obtain precise high resolution estimates in closed form. A set of numerical simulations show that the proposed approach provides precise estimates for arbitrary array responses in highly correlated signal signal environments.

Unscented Transformation based array interpolation

It is impossible to enforce exact responses for each sensor involved in an antenna array. Important signal processing techniques such as Estimation of Signal Parameters via Rotational Invariance (ESPRIT), Forward Backward Average (FBA) and Spatial Smoothing (SPS) rely on sensor arrays with Vandermonde or centro-hermitian responses. To achieve such responses array interpolation is often necessary. In this work a novel way of performing array interpolation while minimizing the transformation error using the Unscented Transformation (UT) is presented. The UT provides a different method for mapping interpolated regions and also exhibits a new insight into array interpolation and its current limitations. A set of numerical simulations presents promising results for array interpolation employing the UT.

Applying MIMO Techniques to Minimize Energy Consumption for Long Distances Communications in Wireless Sensor Networks

This paper explores the usage of cooperative multiple input multiple output (MIMO) technique to minimize energy consumption used to establish communications among distant nodes in a wireless sensor network (WSN). As energy depletion is an outstanding problem in WSN research field, a number of techniques aim to preserve such resource, especially by means of savings during communication among sensor nodes. One such wide used technique is multi-hop communication to diminish the energy required by a single node to transmit a given message, providing a homogeneous consumption of the energy resources among the nodes in the network. However, it is not the case that multi-hop is always more efficient than single-hop, even that it may represent a great depletion of a single node’s energy. In this paper a cooperative MIMO transmission technique for WSN is presented, which is compared to single-hop and multi-hop transmission ones, highlighting its advantages in relation to both. Simulation results support the statement about the utility in applying the proposed technique for energy saving purposes.

Energy harvesting photovoltaic system to charge a cell phone in indoor environments

Research advances in materials science improved gradually photovoltaic systems efficiency. However, such systems are limited to work in the presence of sun light, and they also depend on the geographic localization and on the period of the year, usually limited to 6 to 8 hours a day. In order to take maximum advantage of solar panels, it is crucial to use them also in cloudy weather or even at night. Therefore, in this paper, we propose to recycle light energy from artificial light sources to enable the use photovoltaic systems along 24 hours a day. We validate our proposal by means of measurements performed using artificial light in indoor environments. As a practical result, we show that 7 hours recharging in an indoor environments implies in 94.08 % of the overall cell phone battery capacity. Furthermore, we also propose a circuit for charging of a battery of a cell phone.

Using MIMO Techniques to Enhance Communication Among Static and Mobile Nodes in Wireless Sensor Networks

Wireless sensor networks are evolving to hybridnetworks in which static and mobile sensor nodes cooperate in order to address challenging requirements imposed by new emerging applications. However, due to the ad hoc nature of the network and especially to resources constraints of the sensor nodes, this cooperation is not trivial, requiring a number of retransmissions thus wasting precious resources. In this paper the use of cooperative multiple input multiple output (MIMO) techniques is proposed to overcome transmission problems, ensuring a reliable and more efficient communication link with less retransmissions. Extensive simulation experiments support the proposal, and the results highlight the benefits in using MIMO to deliver messages from static to mobile nodes in wireless sensor networks.

Array interpolation based on multivariate adaptive regression splines

Many important signal processing techniques such as Spatial Smoothing, Forward Backward Averaging and Root-MUSIC, rely on antenna arrays with specific and precise structures. Arrays with such ideal structures, such as a centro-hermitian structure, are often hard to build in practice. Array interpolation is used to enable the usage of these techniques with imperfect (not having a centro-hermitian structure) arrays. Most interpolation methods rely on methods based on least squares (LS) to map the output of a perfect virtual array based on the real array. In this work, the usage of Multivariate Adaptive Regression Splines (MARS) is proposed instead of the traditional LS to interpolate arrays with responses largely different from the ideal.

Improved Business Intelligence Solution with Reimbursement Tracking System for the Brazilian Ministry of Planning, Budget and Management

Business Intelligence (BI) systems are crucial for assisting the decision making processes of private and governmental institutions. The Human Resources Auditing Department (CGAUD) of the Brazilian Ministry of Planning, Budget and Management (MP) has been developing its own BI for auditing the payroll of all federal employees since 2010. Given that the monthly payroll is approximately 12.5 billion reais, the initial version of the proposed BI system in 2012 was able to audit approximately 1.5 billion reais. In this paper, we propose an improved BI system, which can deal with an increased volume of data, a greater amount of monitoring trails and a higher granularity of the final reports. As consequence, the total audit value has increased to approximately 5 billion reais. In addition, our new BI system has incorporated a Reimbursement Tracking System for monitoring the payroll of federal employees who have to reimburse the Brazilian government. Around 4.5 million reais are automatically monthly tracked by our new BI system. Our proposed BI system has been validated using the real environment of the MP and the results are compared to the previous BI system.

Synchronization for Cooperative MIMO in Wireless Sensor Networks

The application of Wireless Sensor Networks (WSNs) is hindered by the limited energy budget available for the member nodes. Energy aware solutions have been proposed for all tasks involved in WSNs, such as processing, routing, cluster formation and communication. With communication being responsible for a large part of the energetic demand of WSNs energy efficient communication is paramount. The application of MIMO (Multiple-Input Multiple-Output) techniques in WSNs emerges as a efficient alternative for long range communications, however, MIMO communication require precise synchronization in order to achieve good performance. In this paper the problem of transmission synchronization for WSNs employing Cooperative MIMO is studied, the main problems and limitations are highlighted and a synchronization method is proposed.

Improved landing radio altimeter for unmanned aerial vehicles based on an antenna array

Unmanned aerial vehicles (UAVs) are used in various applications such as civil and military surveillance, law enforcement, and support in natural disasters as well as in hazardous environments. Approaching and landing are necessary steps for all UAVs, indicating that radio altimeters are needed. In this paper, a radio altimeter based on an antenna array is proposed. Our solution allows some improvements over the traditional radio altimeter such as more precise altitude estimation, ground imaging without the need of side looking radar, mapping the obstacles positions and detecting the ground inclination and topology. Another important contribution of this paper is a review of traditional radio altimeters along with a performance comparison between the level-crossing detection and the digital signal processing frequency detection - which is based on the fast Fourier transform algorithm.

Evaluation of Space-Time-Frequency (STF)-Coded MIMO-OFDM Systems in Realistic Channel Models

By taking into account several dimension of the transmitted signal, such as space, frequency, period and time, MIMO-OFDM systems allow an increased spectral efficiency and an improved identifiability in comparison to matrix solutions. In this paper, we evaluate MIMO-OFDM systems for geometric scenarios where the narrow band approximation is violated. To this end a new data model is proposed to better represent the behavior of the system in the presence of wide band signals. Moreover, we also relax the assumption that the amount of transmitted antennas is equal to the number of transmitted symbols.