João Paulo Carvalho Lustosa da Costa | Universidade de Brasília - UnB (original) (raw)
Papers by João Paulo Carvalho Lustosa da Costa
Finding the number of signals is crucial to parametric direction-ofarrival (DOA) estimation metho... more Finding the number of signals is crucial to parametric direction-ofarrival (DOA) estimation methods such as MUSIC and ESPRIT. In challenging scenarios such as low signal-to-noise ratio (SNR) and/or presence of closely-spaced sources, only part of the parameters can be accurately estimated while others cannot. The number of former estimates is termed as the effective model order (EMO). We first propose a procedure to determine the EMO via Monte Carlo simulation. Ideally an order selection rule should return a source number estimate equal to EMO, since using an overestimated signal number larger than the EMO in a parameter estimator introduces inaccurate parameter estimates, which is a waste of resources in some applications, while using an underestimate renders some strong signals being treated as noise, which causes an accuracy loss in their parameter estimates. We propose to combine an under-enumerator with an over-enumerator for accurate parameter estimation in the threshold region. Simulations results using the combination of the Baysian information criterion with Akaike information criterion in ESPRIT show that our proposal retains the benefit of the under-enumerators with only accurate estimates while remarkably improves the estimation accuracy.
Lecture Notes in Computer Science, 2013
The application of Wireless Sensor Networks (WSNs) is hindered by the limited energy budget avail... more 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.
Sensors, 2014
The percentage of elderly people in European countries is increasing. Such conjuncture affects so... more The percentage of elderly people in European countries is increasing. Such conjuncture affects socio-economic structures and creates demands for resourceful solutions, such as Ambient Assisted Living (AAL), which is a possible methodology to foster health care for elderly people. In this context, sensor-based devices play a leading role in surveying, e.g., health conditions of elderly people, to alert care personnel in case of an incident. However, the adoption of such devices strongly depends on the comfort of wearing the devices. In most cases, the bottleneck is the battery lifetime, which impacts the effectiveness of the system. In this paper we propose an approach to reduce the energy consumption of sensors' by use of local sensors' intelligence. By increasing the intelligence of the sensor node, a substantial decrease in the necessary communication payload can be achieved. The Sensors 2014, 14 4933
Microwave and Optical Technology Letters, 2003
is much larger than that for the proposed antenna in free space (Figs. 3 and 4). This behavior is... more is much larger than that for the proposed antenna in free space (Figs. 3 and 4). This behavior is largely because the large metal plate placed behind the proposed antenna acts as a reflector, which decreases the undesired backward radiation and improves the directivity of the antenna. This characteristic is an advantage for practical applications of the proposed antenna. (a) and (b) shows the measured peak antenna gain for frequencies across the 5.2-and 5.8-GHz WLAN bands. The results show that, for the proposed antenna in free space, a high antennagain level of larger than 4.0 dBi is obtained across both the 5.2and 5.8-GHz bands. For the proposed antenna with a large metal plate in close proximity (also 1-mm behind the antenna), an even higher antenna gain level (Ͼ 5.0 dBi) is measured. This result makes the proposed antenna very attractive for applications in which it is required that the antenna be placed at narrow spaces with a large metal plate in close proximity.
In sensor array processing it is often required to know the number of signals received by an ante... more In sensor array processing it is often required to know the number of signals received by an antenna array, since in practice only a limited number of observations is available. Robust techniques for the estimation of the model order are needed.
R-dimensional parameter estimation problems are common in a variety of signal processing applicat... more R-dimensional parameter estimation problems are common in a variety of signal processing applications. In order to solve such problems, we propose a robust multidimensional model order selection scheme and a robust multidimensional parameter estimation scheme using the closed-form PARAFAC algorithm, which is a recently proposed way to compute the PARAFAC decomposition based on several simultaneous diagonalizations.
2014 28th International Conference on Advanced Information Networking and Applications Workshops, 2014
Models and numerical simulations are used to understand concepts of electronic circuits as well a... more Models and numerical simulations are used to understand concepts of electronic circuits as well as to evaluate their performance without the actual need to build them. Today, they are mostly implemented by softwares that rely on numerical solutions of analytic models, which usually require a great amount of computational resources. In this paper, we propose an alternative particle dynamical system to model electronic circuits. Its main features are a very simple evolution rule, which resembles the principles of classical electrodynamics, and purely deterministic scenarios. A simulation method is also proposed to simulate such model in order to allow the easy comprehension of electronic properties and concepts. Also, as we show in this paper, simulations of the model succeeds in displaying electron tunneling events, even though no particle is defined in terms of quantum mechanics.
Eurasip Journal on Advances in Signal Processing, 2011
Multi-dimensional model order selection (MOS) techniques achieve an improved accuracy, reliabilit... more Multi-dimensional model order selection (MOS) techniques achieve an improved accuracy, reliability, and robustness, since they consider all dimensions jointly during the estimation of parameters. Additionally, from fundamental identifiability results of multi-dimensional decompositions, it is known that the number of main components can be larger when compared to matrix-based decompositions. In this article, we show how to use tensor calculus to extend matrix-based MOS schemes and we also present our proposed multi-dimensional model order selection scheme based on the closed-form PARAFAC algorithm, which is only applicable to multi-dimensional data. In general, as shown by means of simulations, the Probability of correct Detection (PoD) of our proposed multi-dimensional MOS schemes is much better than the PoD of matrix-based schemes.
Recently, the Sequential GSVD (S-GSVD) based prewhitening scheme has been proposed to improve R-d... more Recently, the Sequential GSVD (S-GSVD) based prewhitening scheme has been proposed to improve R-dimensional subspace-based parameter estimation schemes in the presence of colored noise or interference with Kronecker structure. To apply the S-GSVD, second order statistics of the noise should be estimated, e.g., via samples captured in the absence of the desired signal components.
The reconstruction of multi-dimensional magnetic resonsance imaging (MRI) data can be a computati... more The reconstruction of multi-dimensional magnetic resonsance imaging (MRI) data can be a computationally demanding task. Signal-to-noise ratio is also a concern, specially in high-resolution imaging. Data compression may be useful not only for reducing reconstruction complexity and memory requirements, but also for reducing noise, as it is capable of eliminating spurious components. This work proposes the use of SVD-based low-rank approximation for the reconstruction and denoising of MRI data. The Akaike information criterion is used to estimate the appropriate model order. The model order is used to remove noisy components and to reduce the amount of data to be stored and processed. The proposed method is evaluated using in vivo MRI data. We present images reconstructed using less than 20% visual inspection. A quantitative evaluation is also presented.
Frequently, R-dimensional subspace-based methods are used to estimate the parameters in multi-dim... more Frequently, R-dimensional subspace-based methods are used to estimate the parameters in multi-dimensional harmonic retrieval problems in a variety of signal processing applications. Since the measured data is multi-dimensional, traditional approaches require stacking the dimensions into one highly structured matrix. Recently, we have shown how an HOSVD based low-rank approximation of the measurement tensor leads to an improved signal subspace estimate, which can be exploited in any multi-dimensional subspace-based parameter estimation scheme. To achieve this goal, it is required to estimate the model order of the multi-dimensional data.
R-dimensional parameter estimation problems are common in a variety of signal processing applicat... more R-dimensional parameter estimation problems are common in a variety of signal processing applications. In order to solve such problems, we propose a robust multidimensional model order selection scheme and a robust multidimensional parameter estimation scheme using the closed-form PARAFAC algorithm, which is a recently proposed way to compute the PARAFAC decomposition based on several simultaneous diagonalizations.
R-dimensional parameter estimation problems are common in a variety of signal processing applicat... more R-dimensional parameter estimation problems are common in a variety of signal processing applications. In order to solve such problems, we propose a robust multidimensional model order selection scheme and a robust multidimensional parameter estimation scheme using the closed-form PARAFAC algorithm, which is a recently proposed way to compute the PARAFAC decomposition based on several simultaneous diagonalizations.
The starting point of any derivation is a suitable representation of the given model. Hypercomple... more The starting point of any derivation is a suitable representation of the given model. Hypercomplex numbers sometimes provide a more compact representation and more insight into a problem's structure than the reals or the complex numbers. Hence, efficient filters are needed for hypercomplex numbers as well. As there is a large zoo of different hypercomplex numbers obeying different algebras it is cumbersome to do derivations for each of them individually.
Frequently, R-dimensional subspace-based methods are used to estimate the parameters in multidime... more Frequently, R-dimensional subspace-based methods are used to estimate the parameters in multidimensional harmonic retrieval problems in a variety of signal processing applications. Since the measured data is multi-dimensional, traditional approaches require stacking the dimensions into one highly structured matrix. Recently, we have proposed eigenvalue based multi-dimensional model order selection schemes, which exploit the multidimensional structure of the data in order to achieve a higher probability of correct detection. However, our proposed multi-dimensional schemes are restricted to white noise scenarios.
An accurate and updated estimate of the attitude of Unmanned Aerial Vehicles (UAVs) is crucial fo... more An accurate and updated estimate of the attitude of Unmanned Aerial Vehicles (UAVs) is crucial for their control and displacement. Errors in the attitude can cause a misuse of the limited energy sources of UAVs or accidents. For the estimation of the attitude, Inertial Measurement Units (IMUs) are widely applied; they are, however, susceptible to inertial guidance error. With antenna arrays currently being incorporated to UAVs to improve their communication with ground stations, we can take advantage of such an antenna array structure in order to estimate the attitude. In this paper, we therefore propose an attitude estimation system based on an antenna array which could be used to improve the estimates of IMUs. We deliver iterative expressions to compute the attitude under usage of the estimated phase delays of the impinging signals over the antenna array. By means of simulations, we show the feasibility of our proposed solution for different SNR levels as well as for multipath scenarios.
Research advances in materials science improved gradually photovoltaic systems efficiency. Howeve... more 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.
Finding the number of signals is crucial to parametric direction-ofarrival (DOA) estimation metho... more Finding the number of signals is crucial to parametric direction-ofarrival (DOA) estimation methods such as MUSIC and ESPRIT. In challenging scenarios such as low signal-to-noise ratio (SNR) and/or presence of closely-spaced sources, only part of the parameters can be accurately estimated while others cannot. The number of former estimates is termed as the effective model order (EMO). We first propose a procedure to determine the EMO via Monte Carlo simulation. Ideally an order selection rule should return a source number estimate equal to EMO, since using an overestimated signal number larger than the EMO in a parameter estimator introduces inaccurate parameter estimates, which is a waste of resources in some applications, while using an underestimate renders some strong signals being treated as noise, which causes an accuracy loss in their parameter estimates. We propose to combine an under-enumerator with an over-enumerator for accurate parameter estimation in the threshold region. Simulations results using the combination of the Baysian information criterion with Akaike information criterion in ESPRIT show that our proposal retains the benefit of the under-enumerators with only accurate estimates while remarkably improves the estimation accuracy.
Lecture Notes in Computer Science, 2013
The application of Wireless Sensor Networks (WSNs) is hindered by the limited energy budget avail... more 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.
Sensors, 2014
The percentage of elderly people in European countries is increasing. Such conjuncture affects so... more The percentage of elderly people in European countries is increasing. Such conjuncture affects socio-economic structures and creates demands for resourceful solutions, such as Ambient Assisted Living (AAL), which is a possible methodology to foster health care for elderly people. In this context, sensor-based devices play a leading role in surveying, e.g., health conditions of elderly people, to alert care personnel in case of an incident. However, the adoption of such devices strongly depends on the comfort of wearing the devices. In most cases, the bottleneck is the battery lifetime, which impacts the effectiveness of the system. In this paper we propose an approach to reduce the energy consumption of sensors' by use of local sensors' intelligence. By increasing the intelligence of the sensor node, a substantial decrease in the necessary communication payload can be achieved. The Sensors 2014, 14 4933
Microwave and Optical Technology Letters, 2003
is much larger than that for the proposed antenna in free space (Figs. 3 and 4). This behavior is... more is much larger than that for the proposed antenna in free space (Figs. 3 and 4). This behavior is largely because the large metal plate placed behind the proposed antenna acts as a reflector, which decreases the undesired backward radiation and improves the directivity of the antenna. This characteristic is an advantage for practical applications of the proposed antenna. (a) and (b) shows the measured peak antenna gain for frequencies across the 5.2-and 5.8-GHz WLAN bands. The results show that, for the proposed antenna in free space, a high antennagain level of larger than 4.0 dBi is obtained across both the 5.2and 5.8-GHz bands. For the proposed antenna with a large metal plate in close proximity (also 1-mm behind the antenna), an even higher antenna gain level (Ͼ 5.0 dBi) is measured. This result makes the proposed antenna very attractive for applications in which it is required that the antenna be placed at narrow spaces with a large metal plate in close proximity.
In sensor array processing it is often required to know the number of signals received by an ante... more In sensor array processing it is often required to know the number of signals received by an antenna array, since in practice only a limited number of observations is available. Robust techniques for the estimation of the model order are needed.
R-dimensional parameter estimation problems are common in a variety of signal processing applicat... more R-dimensional parameter estimation problems are common in a variety of signal processing applications. In order to solve such problems, we propose a robust multidimensional model order selection scheme and a robust multidimensional parameter estimation scheme using the closed-form PARAFAC algorithm, which is a recently proposed way to compute the PARAFAC decomposition based on several simultaneous diagonalizations.
2014 28th International Conference on Advanced Information Networking and Applications Workshops, 2014
Models and numerical simulations are used to understand concepts of electronic circuits as well a... more Models and numerical simulations are used to understand concepts of electronic circuits as well as to evaluate their performance without the actual need to build them. Today, they are mostly implemented by softwares that rely on numerical solutions of analytic models, which usually require a great amount of computational resources. In this paper, we propose an alternative particle dynamical system to model electronic circuits. Its main features are a very simple evolution rule, which resembles the principles of classical electrodynamics, and purely deterministic scenarios. A simulation method is also proposed to simulate such model in order to allow the easy comprehension of electronic properties and concepts. Also, as we show in this paper, simulations of the model succeeds in displaying electron tunneling events, even though no particle is defined in terms of quantum mechanics.
Eurasip Journal on Advances in Signal Processing, 2011
Multi-dimensional model order selection (MOS) techniques achieve an improved accuracy, reliabilit... more Multi-dimensional model order selection (MOS) techniques achieve an improved accuracy, reliability, and robustness, since they consider all dimensions jointly during the estimation of parameters. Additionally, from fundamental identifiability results of multi-dimensional decompositions, it is known that the number of main components can be larger when compared to matrix-based decompositions. In this article, we show how to use tensor calculus to extend matrix-based MOS schemes and we also present our proposed multi-dimensional model order selection scheme based on the closed-form PARAFAC algorithm, which is only applicable to multi-dimensional data. In general, as shown by means of simulations, the Probability of correct Detection (PoD) of our proposed multi-dimensional MOS schemes is much better than the PoD of matrix-based schemes.
Recently, the Sequential GSVD (S-GSVD) based prewhitening scheme has been proposed to improve R-d... more Recently, the Sequential GSVD (S-GSVD) based prewhitening scheme has been proposed to improve R-dimensional subspace-based parameter estimation schemes in the presence of colored noise or interference with Kronecker structure. To apply the S-GSVD, second order statistics of the noise should be estimated, e.g., via samples captured in the absence of the desired signal components.
The reconstruction of multi-dimensional magnetic resonsance imaging (MRI) data can be a computati... more The reconstruction of multi-dimensional magnetic resonsance imaging (MRI) data can be a computationally demanding task. Signal-to-noise ratio is also a concern, specially in high-resolution imaging. Data compression may be useful not only for reducing reconstruction complexity and memory requirements, but also for reducing noise, as it is capable of eliminating spurious components. This work proposes the use of SVD-based low-rank approximation for the reconstruction and denoising of MRI data. The Akaike information criterion is used to estimate the appropriate model order. The model order is used to remove noisy components and to reduce the amount of data to be stored and processed. The proposed method is evaluated using in vivo MRI data. We present images reconstructed using less than 20% visual inspection. A quantitative evaluation is also presented.
Frequently, R-dimensional subspace-based methods are used to estimate the parameters in multi-dim... more Frequently, R-dimensional subspace-based methods are used to estimate the parameters in multi-dimensional harmonic retrieval problems in a variety of signal processing applications. Since the measured data is multi-dimensional, traditional approaches require stacking the dimensions into one highly structured matrix. Recently, we have shown how an HOSVD based low-rank approximation of the measurement tensor leads to an improved signal subspace estimate, which can be exploited in any multi-dimensional subspace-based parameter estimation scheme. To achieve this goal, it is required to estimate the model order of the multi-dimensional data.
R-dimensional parameter estimation problems are common in a variety of signal processing applicat... more R-dimensional parameter estimation problems are common in a variety of signal processing applications. In order to solve such problems, we propose a robust multidimensional model order selection scheme and a robust multidimensional parameter estimation scheme using the closed-form PARAFAC algorithm, which is a recently proposed way to compute the PARAFAC decomposition based on several simultaneous diagonalizations.
R-dimensional parameter estimation problems are common in a variety of signal processing applicat... more R-dimensional parameter estimation problems are common in a variety of signal processing applications. In order to solve such problems, we propose a robust multidimensional model order selection scheme and a robust multidimensional parameter estimation scheme using the closed-form PARAFAC algorithm, which is a recently proposed way to compute the PARAFAC decomposition based on several simultaneous diagonalizations.
The starting point of any derivation is a suitable representation of the given model. Hypercomple... more The starting point of any derivation is a suitable representation of the given model. Hypercomplex numbers sometimes provide a more compact representation and more insight into a problem's structure than the reals or the complex numbers. Hence, efficient filters are needed for hypercomplex numbers as well. As there is a large zoo of different hypercomplex numbers obeying different algebras it is cumbersome to do derivations for each of them individually.
Frequently, R-dimensional subspace-based methods are used to estimate the parameters in multidime... more Frequently, R-dimensional subspace-based methods are used to estimate the parameters in multidimensional harmonic retrieval problems in a variety of signal processing applications. Since the measured data is multi-dimensional, traditional approaches require stacking the dimensions into one highly structured matrix. Recently, we have proposed eigenvalue based multi-dimensional model order selection schemes, which exploit the multidimensional structure of the data in order to achieve a higher probability of correct detection. However, our proposed multi-dimensional schemes are restricted to white noise scenarios.
An accurate and updated estimate of the attitude of Unmanned Aerial Vehicles (UAVs) is crucial fo... more An accurate and updated estimate of the attitude of Unmanned Aerial Vehicles (UAVs) is crucial for their control and displacement. Errors in the attitude can cause a misuse of the limited energy sources of UAVs or accidents. For the estimation of the attitude, Inertial Measurement Units (IMUs) are widely applied; they are, however, susceptible to inertial guidance error. With antenna arrays currently being incorporated to UAVs to improve their communication with ground stations, we can take advantage of such an antenna array structure in order to estimate the attitude. In this paper, we therefore propose an attitude estimation system based on an antenna array which could be used to improve the estimates of IMUs. We deliver iterative expressions to compute the attitude under usage of the estimated phase delays of the impinging signals over the antenna array. By means of simulations, we show the feasibility of our proposed solution for different SNR levels as well as for multipath scenarios.
Research advances in materials science improved gradually photovoltaic systems efficiency. Howeve... more 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.