Efficient Robust Adaptive Beamforming Algorithms for Sensor Arrays

Sensor array processing techniques have been an important research area in recent years. By using a sensor array of a certain configuration, we can improve the parameter estimation accuracy from the observation data in the presence of interference and noise. In this thesis, we focus on sensor array processing techniques that use antenna arrays for beamforming, which is the key task in wireless communications, radar and sonar systems. Firstly, we propose a low-complexity robust adaptive beamforming (RAB) technique which estimates the steering vector using a Low-Complexity Shrinkage-Based Mismatch Estimation (LOCSME) algorithm. The proposed LOCSME algorithm estimates the covariance matrix of the input data and the interference-plus-noise covariance (INC) matrix by using the Oracle Approximating Shrinkage (OAS) method. Secondly, we present cost-effective low-rank techniques for designing robust adaptive beamforming (RAB) algorithms. The proposed algorithms are based on the exploitation of the cross-correlation between the array observation data and the output of the beamformer. Thirdly, we propose distributed beamforming techniques that are based on wireless relay systems. Algorithms that combine relay selections and SINR maximization or Minimum Mean-Square- Error (MMSE) consensus are developed, assuming the relay systems are under total relay transmit power constraint. Lastly, we look into the research area of robust distributed beamforming (RDB) and develop a novel RDB approach based on the exploitation of the cross-correlation between the received data at the relays and the destination and a subspace projection method to estimate the channel errors, namely, the cross-correlation and subspace projection (CCSP) RDB technique, which efficiently maximizes the output SINR and minimizes the channel errors. Simulation results show that the proposed techniques outperform existing techniques in various performance metrics

Adaptive interference suppression algorithms for DS-UWB systems

In the time-domain, symbol by symbol transmission multiuser DS-UWB systems are considered. We first investigate a generic reduced-rank scheme based on the concept of joint and iterative optimization (JIO) that jointly optimizes a projection vector and a reduced-rank filter by using the minimum mean-squared error (MMSE) criterion. A low-complexity scheme, named Switched Approximations of Adaptive Basis Functions (SAABF), is proposed as a modification of the generic scheme, in which the complexity reduction is achieved by using a multi-branch framework to simplify the structure of the projection vector. Adaptive implementations for the SAABF scheme are developed by using least-mean squares (LMS) and recursive least-squares (RLS) algorithms. We also develop algorithms for selecting the branch number and the model order of the SAABF scheme. Secondly, a novel linear reduced-rank blind adaptive receiver based on JIO and the constrained constant modulus (CCM) design criterion is proposed that offers higher spectrum efficiency. Adaptive implementations for the blind JIO receiver are developed by using the normalized stochastic gradient (NSG) and RLS algorithms. In order to obtain a low-complexity scheme, the columns of the projection matrix with the RLS algorithm are updated individually. Blind channel estimation algorithms for both versions (NSG and RLS) are implemented. Assuming the perfect timing, the JIO receiver only requires the knowledge of the spreading code of the desired user and the received data. In the frequency-domain, we propose two adaptive detection schemes based on singlecarrier frequency domain equalization (SC-FDE) for the block by block transmission multiuser DS-UWB systems, which are termed structured channel estimation (SCE) and direct adaptation (DA). Both schemes use the MMSE linear detection strategy and employ a cyclic prefix. In the SCE scheme, we perform the adaptive channel estimation in the frequency-domain and implement the despreading in the time-domain after the FDE. In this scheme, the MMSE detection requires the knowledge of the number of users and the noise variance. For this purpose, we propose low-complexity algorithms for estimating these parameters. In the DA scheme, the interference suppression task is fulfilled with only one adaptive filter in the frequency-domain and a new signal expression is adopted to simplify the design of such a filter. LMS, RLS and conjugate gradient (CG) adaptive algorithms are then developed for both schemes. Another strand of investigation considers adaptive detectors and frequency domain equalization for multiuser DS-UWB systems with block transmissions and biased estimation methods. Biased estimation techniques can provide performance improvements to the existing unbiased estimation algorithms. In this work, biased adaptive estimation techniques based on shrinkage estimators are devised and incorporated into RLS-type algorithms. For the SCE scheme, automatic shrinkage factor mechanisms are proposed and incorporated into RLS estimators, obtaining a lower MSE of the channel estimation. For the DA scheme, the automatic shrinkage factors are incorporated directly to the adaptive receiver weights. The results show that a shorter data support is required by the proposed biased DA-RLS technique. An analysis of fundamental estimation limits of the proposed frequency domain biased estimators is included along with the derivation of appropriate Cramer-Rao lower bounds (CRLB)

Remote Sensing

This dual conception of remote sensing brought us to the idea of preparing two different books; in addition to the first book which displays recent advances in remote sensing applications, this book is devoted to new techniques for data processing, sensors and platforms. We do not intend this book to cover all aspects of remote sensing techniques and platforms, since it would be an impossible task for a single volume. Instead, we have collected a number of high-quality, original and representative contributions in those areas

Signal processing with Fourier analysis, novel algorithms and applications

Fourier analysis is the study of the way general functions may be represented or approximated by sums of simpler trigonometric functions, also analogously known as sinusoidal modeling. The original idea of Fourier had a profound impact on mathematical analysis, physics and engineering because it diagonalizes time-invariant convolution operators. In the past signal processing was a topic that stayed almost exclusively in electrical engineering, where only the experts could cancel noise, compress and reconstruct signals. Nowadays it is almost ubiquitous, as everyone now deals with modern digital signals. Medical imaging, wireless communications and power systems of the future will experience more data processing conditions and wider range of applications requirements than the systems of today. Such systems will require more powerful, efficient and flexible signal processing algorithms that are well designed to handle such needs. No matter how advanced our hardware technology becomes we will still need intelligent and efficient algorithms to address the growing demands in signal processing. In this thesis, we investigate novel techniques to solve a suite of four fundamental problems in signal processing that have a wide range of applications. The relevant equations, literature of signal processing applications, analysis and final numerical algorithms/methods to solve them using Fourier analysis are discussed for different applications in the electrical engineering/computer science. The first four chapters cover the following topics of central importance in the field of signal processing: • Fast Phasor Estimation using Adaptive Signal Processing (Chapter 2) • Frequency Estimation from Nonuniform Samples (Chapter 3) • 2D Polar and 3D Spherical Polar Nonuniform Discrete Fourier Transform (Chapter 4) • Robust 3D registration using Spherical Polar Discrete Fourier Transform and Spherical Harmonics (Chapter 5) Even though each of these four methods discussed may seem completely disparate, the underlying motivation for more efficient processing by exploiting the Fourier domain signal structure remains the same. The main contribution of this thesis is the innovation in the analysis, synthesis, discretization of certain well known problems like phasor estimation, frequency estimation, computations of a particular non-uniform Fourier transform and signal registration on the transformed domain. We conduct propositions and evaluations of certain applications relevant algorithms such as, frequency estimation algorithm using non-uniform sampling, polar and spherical polar Fourier transform. The techniques proposed are also useful in the field of computer vision and medical imaging. From a practical perspective, the proposed algorithms are shown to improve the existing solutions in the respective fields where they are applied/evaluated. The formulation and final proposition is shown to have a variety of benefits. Future work with potentials in medical imaging, directional wavelets, volume rendering, video/3D object classifications, high dimensional registration are also discussed in the final chapter. Finally, in the spirit of reproducible research we release the implementation of these algorithms to the public using Github

Manipulador aéreo con brazos antropomórficos de articulaciones flexibles

[Resumen] Este artículo presenta el primer robot manipulador aéreo con dos brazos antropomórficos diseñado para aplicarse en tareas de inspección y mantenimiento en entornos industriales de difícil acceso para operarios humanos. El robot consiste en una plataforma aérea multirrotor equipada con dos brazos antropomórficos ultraligeros, así como el sistema de control integrado de la plataforma y los brazos. Una de las principales características del manipulador es la flexibilidad mecánica proporcionada en todas las articulaciones, lo que aumenta la seguridad en las interacciones físicas con el entorno y la protección del propio robot. Para ello se ha introducido un compacto y simple mecanismo de transmisión por muelle entre el eje del servo y el enlace de salida. La estructura en aluminio de los brazos ha sido cuidadosamente diseñada de forma que los actuadores estén aislados frente a cargas radiales y axiales que los puedan dañar. El manipulador desarrollado ha sido validado a través de experimentos en base fija y en pruebas de vuelo en exteriores.Ministerio de Economía y Competitividad; DPI2014-5983-C2-1-