M-estimator based Chinese Remainder Theorem with few remainders using a Kroenecker product based mapping vector

Digital Signal Processing, April 1, 2019

The Chinese Remainder Theorem (CRT) explains how to estimate an integer valued number from the knowledge of the remainders obtained by dividing such unknown integer by co-prime integers. As an algebraic theorem, CRT is the basis for several techniques concerning data processing. For instance, considering a single-tone signal whose frequency value is above the sampling rate, the respective peak in the DFT informs the impinging frequency value modulo the sampling rate. CRT is nevertheless sensitive to errors in the remainders, and many efforts have been developed in order to improve its robustness. In this paper, we propose a technique to estimate real-valued numbers by means of CRT, employing for this goal a Kroenecker based M-Estimation (ME), specially suit- able for CRT systems with low number of remainders. Since ME schemes are in general computationally expensive, we propose a mapping vector obtained via Kroenecker products which considerably reduces the computational complexity. Furthermore, our proposed technique enhances the probability of estimating an unknown number accurately even when the errors in the remainders surpass 1/4 of the greatest common divisor of all moduli. We also provide a version of the mapping vectors based on tensorial n-mode products, delivering in the end the same information of the original method. Our approach outperforms the state-of-the-art CRT methods not only in terms of percentage of successful estimations but also in terms of smaller average error.

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Performance Assessment for Distributed Broadband Radio Localization

2018 52nd Asilomar Conference on Signals, Systems, and Computers, Oct. 28, 2018

Various emerging technologies, such as autonomous vehicles and fully autonomous flying, require precision positioning. This work presents a localization and tracking method based on joint direction of arrival (DOA), time delay, and range estimation using the SAGE algorithm. The proposed method does not rely on external sources of information such as global navigation satellite systems (GNSS). The method is opportunistic and does not require any location-based data exchange. A set of numerical simulations is presented to assess the performance of the proposed method.

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Array Processing Techniques for Direction of Arrival Estimation, Communications, and Localization in Vehicular and Wireless Sensor Networks

PhD Dissertation, March 11, 2018

Array signal processing in wireless communication has been a topic of interest in research for over three decades. In the fourth generation (4G) of the wireless communication systems, also known as Long Term Evolution (LTE), multi antenna systems have been adopted according to the Release 9 of the 3rd Generation Partnership Project (3GPP). For the fifth generation (5G) of the wireless communication systems, hundreds of antennas should be incorporated to the devices in a massive multi-user Multiple Input Multiple Output (MIMO) architecture. The presence of multiple antennas provides array gain, diversity gain, spatial gain, and interference reduction. Furthermore, arrays enable spatial filtering and parameter estimation, which can be used to help solve problems that could not previously be addressed from a signal processing perspective. The aim of this thesis is to bridge some gaps between signal processing theory and real world applications. Array processing techniques traditionally assume an ideal array. Therefore, in order to exploit such techniques, a robust set of methods for array interpolation are fundamental and are developed in this work. In this dissertation, novel methods for array interpolation are presented and their performance in real world scenarios is evaluated. Problems in the field of wireless sensor networks and vehicular networks are also addressed from an array signal processing perspective. Signal processing concepts are implemented in the context of a wireless sensor network. These concepts provide a level of synchronization sufficient for distributed multi antenna communication to be applied, resulting in improved lifetime and improved overall network behavior. Array signal processing methods are proposed to solve the problem of radio based localization in vehicular network scenarios with applications in road safety and pedestrian protection.

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Robust nonlinear array interpolation for direction of arrival estimation of highly correlated signals

Signal Processing, March 1, 2018

Important signal processing techniques need that the response of the different elements of a sensor array have specific characteristics. For physical systems this often is not achievable as the array elements’ responses are affected by mutual coupling or other effects. In such cases, it is necessary to apply array interpolation to allow the application of ESPRIT, Forward Backward Averaging (FBA), and Spatial Smoothing (SPS). Array interpolation provides a model or transformation between the true and a desired array response. If the true response of the array becomes more distorted with respect to the desired one or the considered region of the field of view of the array increases, nonlinear approaches become necessary. This work presents two novel methods for sector discretization. An Unscented Transform (UT) based method and a principal component analysis (PCA) based method are discussed. Additionally, two novel nonlinear interpolation methods are developed based on the nonlinear regression schemes Multivariate Adaptive Regression Splines (MARS) and Generalized Regression Neural Networks (GRNNs). These schemes are extended and applied to the array interpolation problem. The performance of the proposed methods is examined using simulated and measured array responses of a physical system used for research on mutual coupling in antenna arrays.

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Antenna Array Based Localization Scheme for Vehicular Networks

2017 IEEE International Conference on Computer and Information Technology (CIT), Sept. 10, 2017

Vehicular ad hoc networks (VANETs) are emerging as the possible solution for multiple concerns in road traffic such as mobility and safety. One of the main concerns present in VANETs is the localization and tracking of vehicles. This work presents a passive vehicle localization and tracking method based on direction of arrival (DOA) estimation. The proposed method does not rely on external sources of information such as Global Navigation Satellite Systems (GNSS) and can be used to mitigate the possibility of spoofing or to provide a second independent source of position estimation for integrity purposes. The proposed algorithm uses array signal processing techniques to estimate not only the position but also the direction of other vehicles in network. Furthermore, it is a fully passive method and can alleviate the network load since it does not require any location based data exchange and can be performed by any listening vehicle using the signal of any data transmission. A set of numerical simulations is used to validate the proposed method and the results are shown to be more precise than the average accuracy of Global Position System (GPS) receivers.

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Direction of arrival estimation performance for compact antenna arrays with adjustable size

2017 IEEE MTT-S International Microwave Symposium (IMS), June 4, 2017

The quest for compact antenna arrays able to perform robust beamforming and high resolution direction of arrival (DOA) estimation is pushing the antenna array dimensions to progressively shrink, with effects in terms of reduced performance not only for the antenna but also for beam forming and DOA estimation algorithms, for which their assumptions about the antenna properties do not hold anymore. This work shows the design and development of an antenna array with adjustable mutual distance between the single elements: such setup will allow to scientifically analyze the effects that progressive miniaturization, i.e. progressively smaller mutual distances between the antennas, have on the DOA estimation algorithms,as well as show the improvements obtained by using array interpolation methods, i.e. techniques able to create a virtual array response out of the actual array one, such as to comply with the algorithms’ requirements on the antenna response.

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Adaptive communication and cooperative MIMO cluster formation for improved lifetime in wireless sensor networks

2016 IEEE International Conference on Wireless for Space and Extreme Environments (WiSEE), Sept. 26, 2016

One of the main limitations that still keeps WirelessSensor Networks (WSNs) from being adopted in a large scaleis the limited energy supply, i.e. the lifetime of the nodes thatconstitute the network. The wireless communication betweennodes is responsible for most of the energy consumed in WSNs.A promising method to improve the energy efficiency is theusage of a Cooperative Multiple Input Multiple Output (CO-MIMO) scheme, where nodes form clusters to transmit andreceive signals using a virtual antenna array. This work presentsa study on the energy consumption of multi-hop and single-hop transmission compared to CO-MIMO and how to select themost efficient method. It also proposes a method for adaptivelychoosing the number of nodes that form a CO-MIMO clusterin order to maximize the lifetime of the network and to avoiddisconnections. The proposed method takes into account not onlythe total energy consumption but also the distribution of energywithin the network, aiming to keep the energy distribution acrossthe network as uniform as possible. The effects of the proposedmethods in the total available energy of the network and in thedistribution of the energy is presented by means of numerical simulations.

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Array interpolation based on multivariate adaptive regression splines

2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM), July 10, 2016

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.

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Multi-hop Cooperative XIXO Transmission Scheme for Delay Tolerant Wireless Sensor Networks

WSA 2016; 20th International ITG Workshop on Smart Antennas, March 9, 2016

Delay Tolerant Wireless Sensor Networks (DT-WSN) are sensor networks sparsely populated where connectivity between sensor nodes is intermittent. The energy consumption is critical to the performance of these networks, since nodes have to carry data for a long period of time due to opportunistic transmissions. This work presents a multi-hop cooperative multiple/ single input multiple/single output (C-XIXO) transmission scheme for DT-WSN in order to achieve longer communication ranges and consequently reduce the message delivery time to the sink, maximizing the energy efficiency. Simulations results suggest that the proposed scheme provides higher message propagation speed and reduced energy consumption compared to a state-of-the-art scheme for DT-WSN.

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Robust Multi-Antenna GNSS Receiver for Maritime Applications

DLR Kongress, Sept. 1, 2015

In this work algorithms for radio interference (RFI), multipath, and spoofing mitigation in a multi-antenna GNSS receiver for maritime applications are derived. For joint multipath and RFI mitigation a prewhitening approach followed by a space-time adaptive Principle Component Analysis (PCA) using a compression method based on Canonical Components (CC) with a bank of signal matched correlators is presented. For attitude and spoofing detection a scheme based on direction-of-arrival (DOA) estimation of the satellites in view and positioning information is derived. Furthermore, a complete design of a robust multi-antenna GNSS receiver test platform for maritime applications is presented. Its detailed design is outlined and trade-offs are discussed. The proposed algorithms for RFI and multipath mitigation are tested by computer simulations. The proposed algorithms for RFI and multipath mitigation are capable of suppressing strong RFI and separating highly correlated and even coherent signals and achieve improved time-delay and pseudorange estimation performance for safety-critical applications.

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A Practical Implementation of a Cooperative Antenna Array for Wireless Sensor Networks

Internet of Things, Smart Spaces, and Next Generation Networks and Systems, Aug. 26, 2015

Energy consumption is a key issue to be handled in Wireless Sensor Networks, especially considering low-end sensor nodes, i.e. sensor with severe energy resources limitations. When sensor nodes have their energy resources depleted, they stop working which can compromise the whole network functioning, thus its lifetime. As communication is the most energy- consumption task, enhancements in communication that diminish the amount of messages lost and the need for retransmissions are very important to preserve energy resources and extend the network lifetime. Considering the impact of the energy preservation and the opportunity to exploit it in terms of communication, this paper discusses the practical implementation of a cooperative MIMO scheme based on virtual antenna array using sensor nodes in order to enhance data communication in wireless sensor networks. The conducted experiments present evidence of the feasibility of the proposed approach highlighting performance aspects.

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Continuous authentication via localization using triangulation of directions of arrival of line of sight components

Forensic Computer Science-ICoFCS 2015, The Ninth International Conference on, June 6, 2015

A larger number of users work from a desktop computer and use their smartphones, tablets, and home computers to communicate, buy, organize, and store sensitive information. With the growth of the adoption of the Internet for tasks such as online banking and shopping, an increased focus has been given on the development of tools that enable secure transactions. This manuscript proposes the usage of direction of arrival estimation tools to provide continuous authentication. The location of a user within the network can be estimated by using triangulation of the user's wireless signal. The location estimates can be used to track a user's movement within a wireless network. The movement pattern can then be analyzed for possible indicators of fraud.

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Unscented transformation based array interpolation

2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), April 19, 2015

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.

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Multidimensional array interpolation applied to direction of arrival estimation

WSA 2015; 19th International ITG Workshop on Smart Antennas, March 3, 2015

n MIMO communications systems, the data has a natural multidimensional structure composed of time, frequency and space dimensions. Recently, multidimensional techniques that take into account the data multidimensional structure have been proposed for model order selection, parameter estimation and prewhitening. These multidimensional techniques require an array with a PARAFAC structure. However, in practice,building antenna arrays with precise geometries is not feasible.In this paper, we propose a multidimensional array interpolation scheme that forces a real imperfect array to become a PARAFAC array. Once the multidimensional interpolation is successfully performed, advantages such as increased identifiability, separation without imposing additional constraints and improved accuracy can be exploited. Numerical simulations show that the proposed method provides improved DOA estimation accuracy when a PARAFAC technique is applied to an originally non-PARAFAC array.

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

KMIS, June 15, 2014

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.

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Sensor Localization Via Diversely Polarized Antennas

2014 IEEE International Conference on Distributed Computing in Sensor Systems, June 11, 2014

Wireless sensor networks (WSNs) are currently employed in a vast number of different applications ranging from home automation and health care to military systems. Although their application may vary greatly, WSNs share a common set of characteristics such as a limited energy supply and simple hardware. A common issue related with the application of WSNs is sensor localization, for some types of applications it is important that the sensors know the relative or absolute position of other sensors in the network, such as surveillance of monitoring networks. If sensors are randomly placed they may resort a wide range of methods such as Global Navigation Satellite Systems (GNSS) or received signal strength indicators (RSSI). In this work we present an alternative to relative sensor localization by employed a crossed dipole antenna in the reception and a known polarization in the transmission. The accuracy of the proposed methods is measured trough numerical simulations and results are presented.

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Evaluation of space-time-frequency (STF)-coded MIMO-OFDM systems in realistic channel models

2014 28th International Conference on Advanced Information Networking and Applications Workshops, May 12, 2014

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.

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A signal adaptive array interpolation approach with reduced transformation bias for DOA estimation of highly correlated signals

2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), April 5, 2014

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.

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Reduced Rank TLS Array Interpolation for DOA Estimation

WSA 2014; 18th International ITG Workshop on Smart Antennas, March 12, 2014

Important array signal processing techniques such as Spatial Smoothing, Forward Backward Averaging and Root-MUSIC require arrays with precise and specific geometries and responses. However, building sensor arrays with such demanding characteristics is not always possible. To deal with these possible limitations the real array response can be interpolated into the desired response applying array interpolation methods. In this work we study array interpolation methods for cases where the knowledge of the real array response is incomplete or contains errors. To address these imperfections a novel Total Least Squares (TLS) approach for calculating the transformation matrices is presented. Furthermore, a novel reduced rank regression approach is used to reduce the bias introduced by the transformation matrix onto the final direction of arrival (DOA) estimation.

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

2014 International Conference on Composite Materials & Renewable Energy Applications (ICCMREA), Jan. 22, 2014

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.

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Improved array interpolation for reduced bias in DOA estimation for GNSS

Proc. of Institute of Navigation (ION) GNSS+, Jan. 1, 2014

The proposed method can be applied to the vast majority ofsystems that rely on sensor arrays, e.g, radar systems, chan-nel sounding and sonars. For this work we consider GlobalNavigation Satellite Systems (GNSS) and especially thecase that highly correlated multipath or spoofing is re-ceived. Based on precise DOA estimation of all impingingsignals specific Receiver Autonomous Integrity Monitoring (RAIM) algorithms allow reliable detection and mitigationof spoofing or coherent multipath signals in the receiver.Furthermore, precise DOA estimation also enables attitudeestimation with high accuracy.

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Applying cooperative MIMO technique in an adaptive routing mechanism for wireless sensor networks

2013 IEEE Conference on Wireless Sensor (ICWISE), Dec. 2, 2013

Energy consumption in Wireless Sensor Networks(WSNs) is a limiting factor that hinders the application of such networks into solving a broader set of problems. Various ways of saving energy have been proposed, from energy efficient processing to power aware cluster organization. With communication between nodes being responsible for a large part of the energetic demand, energy efficient methods of communication have been proposed, with multi-hop communication being a wide used technique, capable of minimizing energy consumption and spreading it among the network. However, multi-hop is not always more efficient and is prone to a high delay, due to the decode and forward mechanism usually employed. In this paper a cooperative MIMO technique is studied, its energy consumption analyzed, and a mechanism for integrating it in existing WSNs and allowing its coexistence with multi-hop communication is suggested. Energy efficiency, packet delivery delay and packet loss ratios are analyzed and the results compared to standard WSNs.

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Array Interpolation Methods with applications in Wireless Sensor Networks and Global Positioning Systems

Master Thesis, Dec. 1, 2013

In the last three decades the study of antenna array signal processing techniques has received significant attention. A large number of techniques have been developed with different purposes such as the estimation of the direction of arrival (DOA), filtering or spatial separation of received signals, estimation of time delay of arrival (TDOA), Doppler frequency estimation and precoding of transmitted signals to maximize the power received by a different array. DOA estimation techniques are of particular interest for positioning systems based on radio waves such as the global positioning system (GPS) and for sensor mapping in wireless sensor networks (WSNs). These applications have the particular requirement of demanding the estimations to be made in real time or with reduced computational complexity. DOA estimation techniques that fulfill these requirements demand very specific antenna array structures that cannot, in general, be obtained in real implementations. In this work a set of techniques is presented that allows the interpolation of signals received in arrays of arbitrary geometry into arrays of specific geometry efficiently and robustly to allow the application of efficient DOA estimation techniques in arrays of arbitrary geometry. As an application of the proposed techniques precise mapping for WSNs and precise positioning for GPS receivers is presented.

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Synchronization for cooperative MIMO in wireless sensor networks

Internet of Things, Smart Spaces, and Next Generation Networking, Aug. 28, 2013

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.

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Using MIMO techniques to enhance communication among static and mobile nodes in wireless sensor networks

2013 IEEE 27th International Conference on Advanced Information Networking and Applications (AINA), March 25, 2013

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.

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Antenna array based positioning scheme for unmanned aerial vehicles

WSA 2013; 17th International ITG Workshop on Smart Antennas, March 13, 2013

Recently antenna arrays have been incorporated in Unmanned Aerial Vehicles (UAVs) in order to improve their communications capacities. Such antenna arrays can be further exploited in order to provide accurate estimation of a UAV pose and attitude which are necessary for the UAV movement and control. In this paper, we propose a pose estimation solution based on the 2-D Standard ESPRIT with Forward Backward Averaging (FBA) for determining the directions of arrival (DOAs) of the incoming signals. Moreover, by exploiting the geometry of the antenna array, it is possible to estimate the antenna positions, and then, by applying the TRIAD algorithm, it is possible to compute the attitude. We show, by means of simulations, that our proposed solution provides a very accurate pose estimation.

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Using cooperative MIMO techniques and UAV relay networks to support connectivity in sparse Wireless Sensor Networks

2013 International Conference on Computing, Management and Telecommunications (ComManTel), Jan. 21, 2013

One possible way to define the end of lifetime for a Wireless Sensor Network (WSN) is to set a threshold for the number of disconnections among the sensor nodes so that above this level the WSN becomes unable to provide the quality of services required by the users or even totally loses its ability to provide any service at all. Disconnections isolate sensors or group of sensors which cannot deliver their acquired data, thus constituting a sparse nonfunctional WSN, although some of its isolated or grouped sensors remain operational. A possible way to overcome such a problem is to provide an alternative reliable connection via other types of nodes to support the communication among isolated parts of a disconnected network. This paper proposes the use of cooperative multiple input multiple output (MIMO) techniques to support communication among static sensors in a sparse WSN and a relay network composed of Unmanned Aerial Vehicles (UAVs) keeping the WSN connected, thus extending its lifetime. Simulations of the proposed approach are performed and the acquired results highlight the benefits of this proposal.

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Intelligent and flexible manufacturing product line supported by agents and wireless sensor and actuator network

IFAC Proceedings Volumes, Jan. 1, 2013

The demand for highly decentralized control in factory automation is based on the current needs for flexibility and scalability in the production and assembly in product lines. On one hand, intelligent manufacturing systems, presenting holonic and multi-agent based approaches address these needs, providing the necessary decentralization in the manufacturing control. On the other hand, flexibility and scalability are also related to the disposition of the sensors and actuators devices in the factories, and how easily they can be displaced, introduced and reorganized. This second aspect is addressed by diminishing the needs for cabling to connect these devices, which is possible by using wireless connections instead. This paper explores these two aspects, by studying a flexible product line able to assemble different types of products in a production line by means of a multi-agent approach that drives the products through production units composed of a wireless sensor and actuator network,according to the specification of the products to be assembled. The feasibility of this approach is studied in the performed experiments by assessing timing properties of the proposed technique. This implies in how efficientis the combination of the multi-agent based factory control system with a wireless communication infrastructure in terms of timing.

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Cooperative MIMO for Wireless Sensor Network and Antenna Array based Solutions for Unmanned Aerial Vehicles

Bachelor Thesis, Dec. 11, 2012

The cheapening and increasing miniaturization of electronic components has enabled the use of wireless sensor networks for various purposes, from disaster prevention to patient monitoring in hospitals. These devices are generally battery powered and have great restrictions in its physical dimensions which makes it imperative that their energy efficiency is maximized. The use of unmanned aerial vehicles (UAVs) in conjunction with sensor networks has emerged as a viable solution for maintaining communication between network nodes. Techniques that use multiple antennas can be applied to minimize energy consumption in wireless sensor networks and assist in communication of such networks with groups of UAVs. The same set of antennas used for communication in UAVs can be used to provide other benefits, such as implementation of an altimeter and a precise positioning system that does not rely on external agents. This work presents a set of techniques for antenna arrays that can improve the efficiency of sensor networks, provide automated and safe control for UAVs and enable efficient interaction between these two systems.

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

2012 IV International Congress on Ultra Modern Telecommunications and Control Systems, Oct. 3, 2012

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.

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Applying MIMO techniques to minimize energy consumption for long distances communications in wireless sensor networks

Internet of Things, Smart Spaces, and Next Generation Networking, Aug. 27, 2012

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.

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