Random Actuation Pattern Optimization by Genetic Algorithm for Ultrasonic Structural Health Monitoring of Plates

The objective of this research is to investigate an optimized two-dimensional random pattern of uniformly excited points using the Genetic Algorithm (GA) technique for structural health monitoring. The point excitations generate ultrasonic waves in both isotropic and anisotropic materials that can be effective in diagnosing structural defects. The formed ultrasonic waves can constructively interfere and send out an intense wave beam to a predetermined target. The constructed wave beams can be steered to different directions with variable target distances. In the GA, the cost function is constructed to reduce main lobe beamwidth, eliminate grating lobes and suppress sidelobes’ levels. Mathematical modelling, finite element simulations, and optimizations are successively performed to achieve the objectives. Secondly Firstly, a mathematical beamforming model is developed to describe the excitation pattern of which each point is excited at the same time delay with a uniform weighting factor. The derived methodology accounts for enclosing all excitations within a certain aperture. The centroid of the emitting sources is also kept at the origin of the Cartesian coordinate within a slight tolerance range. For the near field, in isotropic materials, the excitation points lay on equally spaced circular arcs centered at the target point. In anisotropic materials, such as composites, the wave amplitude and phase velocity are highly dependent on fiber directions. Because of anisotropic nature, the excitation geometry becomes quite complicated. Secondly, finite element models for aluminum and composite plates are simulated to extract wave characteristics, such as displacement amplitudes, phase velocity profiles and slowness curves. These data are implemented later in the optimization algorithm. A quarter plate of radius 150mm and 1.125mm thickness is modelled as a three-dimensional solid part. A concentrated force with a 2.5 cycle-Hanning window sinusoidal signal is applied at the center of the plate and the boundaries are chosen to be symmetrical. Radial sensors at 5 degrees increments are positioned at 50mm from the excitation source to measure wave properties. The simulation results show that the amplitude and velocity are uniform for isotropic materials whereas the waves propagate rapidly with higher amplitudes along the fibers in anisotropic materials. Thirdly, after collecting all the required information, a GA optimization technique is applied to generate the excitation population of x- and y-coordinates. The pre-determined population is permutated, cross-overed and mutated so that additional possibilities are produced. The same process is repeated for many generations until the local optimum result is obtained. Finally, the near field beamforming is plotted in MATLAB at different actuation point numbers for the isotropic and anisotropic materials. The results are then compared to other linear, circular and planar patterns found in literature

Solving “Antenna Array Thinning Problem” Using Genetic Algorithm

Thinning involves reducing total number of active elements in an antenna array without causing major degradation in system performance. Dynamic thinning is the process of achieving this under real-time conditions. It is required to find a strategic subset of antenna elements for thinning so as to have its optimum performance. From a mathematical perspective this is a nonlinear, multidimensional problem with multiple objectives and many constraints. Solution for such problem cannot be obtained by classical analytical techniques. It will be required to employ some type of search algorithm which can lead to a practical solution in an optimal. The present paper discusses an approach of using genetic algorithm for array thinning. After discussing the basic concept involving antenna array, array thinning, dynamic thinning, and application methodology, simulation results of applying the technique to linear and planar arrays are presented

Advances in Evolutionary Algorithms

With the recent trends towards massive data sets and significant computational power, combined with evolutionary algorithmic advances evolutionary computation is becoming much more relevant to practice. Aim of the book is to present recent improvements, innovative ideas and concepts in a part of a huge EA field

Journal of Telecommunications and Information Technology, 2022, nr 3

kwartalni

Optimisation of wireless communication system by exploitation of channel diversity

Communication systems are susceptible to degradation in performance because of interference received through their side lobes. The interference may be deliberate electronic counter measure (ECM), Accidental RF Interference (RFI) or natural noise. The growth of interference communication systems have given rise to different algorithms, Adaptive array techniques offer a possible solution to this problem of interference received through side lobes because of their automatic null steering in both spatial and frequency domains. Key requirement for space-time architecture is to use robust adaptive algorithms to ensure reliable operation of the smart antenna. Space division multiple access (SDMA) involves the use of adaptive nulling to allow two or more users (mobiles) in the same cell to share same frequency and time slot. One beam is formed for each user with nulls in the direction of other users. Different approaches have been used to identify the interferer from desired user. Thus a basic model for determining the angle of arrival of incoming signals, an appropriate antenna beam forming and adaptive algorithms are used for array processing. There is an insatiable demand for capacity in wireless data networks and cellular radio communication systems. However the RF environment that these systems operate in is harsh and severely limits the capacity of traditional digital wireless networks. With normal wireless systems this limits the data rate in cellular radio environments to approximately 200 kbps whereas much higher data rates in excess of 25Mbps are required. A common wireless channel problem is that of frequency selective multi-path fading. To combat this problem, new types of wireless interface are being developed which utilise space, time and frequency diversity to provide increasing resilience to the channel imperfections. At any instant in time, the channel conditions may be such that one or more of these diversity methods may offer a superior performance to the other diversity methods. The overall aim of the research is to develop new systems that use a novel combination of smart antenna MIMO techniques and an advanced communication system based on advanced system configuration that could be exploited by IEEE 802.20 user specification approach for broadband wireless networking. The new system combines the Multi-input Multi-output communication system with frequency diversity in the form of an OFDM modulator. The benefits of each approach are examined under similar channel conditions and results presented.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Orthogonal frequency division multiplexing multiple-input multiple-output automotive radar with novel signal processing algorithms

Advanced driver assistance systems that actively assist the driver based on environment perception achieved significant advances in recent years. Along with this development, autonomous driving became a major research topic that aims ultimately at development of fully automated, driverless vehicles. Since such applications rely on environment perception, their ever increasing sophistication imposes growing demands on environmental sensors. Specifically, the need for reliable environment sensing necessitates the development of more sophisticated, high-performance radar sensors. A further vital challenge in terms of increased radar interference arises with the growing market penetration of the vehicular radar technology. To address these challenges, in many respects novel approaches and radar concepts are required. As the modulation is one of the key factors determining the radar performance, the research of new modulation schemes for automotive radar becomes essential. A topic that emerged in the last years is the radar operating with digitally generated waveforms based on orthogonal frequency division multiplexing (OFDM). Initially, the use of OFDM for radar was motivated by the combination of radar with communication via modulation of the radar waveform with communication data. Some subsequent works studied the use of OFDM as a modulation scheme in many different radar applications - from adaptive radar processing to synthetic aperture radar. This suggests that the flexibility provided by OFDM based digital generation of radar waveforms can potentially enable novel radar concepts that are well suited for future automotive radar systems. This thesis aims to explore the perspectives of OFDM as a modulation scheme for high-performance, robust and adaptive automotive radar. To this end, novel signal processing algorithms and OFDM based radar concepts are introduced in this work. The main focus of the thesis is on high-end automotive radar applications, while the applicability for real time implementation is of primary concern. The first part of this thesis focuses on signal processing algorithms for distance-velocity estimation. As a foundation for the algorithms presented in this thesis, a novel and rigorous signal model for OFDM radar is introduced. Based on this signal model, the limitations of the state-of-the-art OFDM radar signal processing are pointed out. To overcome these limitations, we propose two novel signal processing algorithms that build upon the conventional processing and extend it by more sophisticated modeling of the radar signal. The first method named all-cell Doppler compensation (ACDC) overcomes the Doppler sensitivity problem of OFDM radar. The core idea of this algorithm is the scenario-independent correction of Doppler shifts for the entire measurement signal. Since Doppler effect is a major concern for OFDM radar and influences the radar parametrization, its complete compensation opens new perspectives for OFDM radar. It not only achieves an improved, Doppler-independent performance, it also enables more favorable system parametrization. The second distance-velocity estimation algorithm introduced in this thesis addresses the issue of range and Doppler frequency migration due to the target’s motion during the measurement. For the conventional radar signal processing, these migration effects set an upper limit on the simultaneously achievable distance and velocity resolution. The proposed method named all-cell migration compensation (ACMC) extends the underlying OFDM radar signal model to account for the target motion. As a result, the effect of migration is compensated implicitly for the entire radar measurement, which leads to an improved distance and velocity resolution. Simulations show the effectiveness of the proposed algorithms in overcoming the two major limitations of the conventional OFDM radar signal processing. As multiple-input multiple-output (MIMO) radar is a well-established technology for improving the direction-of-arrival (DOA) estimation, the second part of this work studies the multiplexing methods for OFDM radar that enable simultaneous use of multiple transmit antennas for MIMO radar processing. After discussing the drawbacks of known multiplexing methods, we introduce two advanced multiplexing schemes for OFDM-MIMO radar based on non-equidistant interleaving of OFDM subcarriers. These multiplexing approaches exploit the multicarrier structure of OFDM for generation of orthogonal waveforms that enable a simultaneous operation of multiple MIMO channels occupying the same bandwidth. The primary advantage of these methods is that despite multiplexing they maintain all original radar parameters (resolution and unambiguous range in distance and velocity) for each individual MIMO channel. To obtain favorable interleaving patterns with low sidelobes, we propose an optimization approach based on genetic algorithms. Furthermore, to overcome the drawback of increased sidelobes due to subcarrier interleaving, we study the applicability of sparse processing methods for the distance-velocity estimation from measurements of non-equidistantly interleaved OFDM-MIMO radar. We introduce a novel sparsity based frequency estimation algorithm designed for this purpose. The third topic addressed in this work is the robustness of OFDM radar to interference from other radar sensors. In this part of the work we study the interference robustness of OFDM radar and propose novel interference mitigation techniques. The first interference suppression algorithm we introduce exploits the robustness of OFDM to narrowband interference by dropping subcarriers strongly corrupted by interference from evaluation. To avoid increase of sidelobes due to missing subcarriers, their values are reconstructed from the neighboring ones based on linear prediction methods. As a further measure for increasing the interference robustness in a more universal manner, we propose the extension of OFDM radar with cognitive features. We introduce the general concept of cognitive radar that is capable of adapting to the current spectral situation for avoiding interference. Our work focuses mainly on waveform adaptation techniques; we propose adaptation methods that allow dynamic interference avoidance without affecting adversely the estimation performance. The final part of this work focuses on prototypical implementation of OFDM-MIMO radar. With the constructed prototype, the feasibility of OFDM for high-performance radar applications is demonstrated. Furthermore, based on this radar prototype the algorithms presented in this thesis are validated experimentally. The measurements confirm the applicability of the proposed algorithms and concepts for real world automotive radar implementations

Beamforming considerando difração acústica em superfícies cilíndricas

Tese (doutorado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Engenharia Mecânica, Florianópolis, 2013.Beamforming é uma técnica de processamento de sinais já conhecida por suas aplicações em antenas e radioastronomia. É, essencialmente, uma técnica de localização de fontes baseada na conformação de feixes de onda de uma dada direção ou região no espaço. Sua aplicação em acústica foi iniciada de forma rústica na primeira grande guerra. Todavia, os avanços que propiciaram a criação das imagens acústicas são datados a partir dos anos setenta. Este trabalho propõe a aplicação desta técnica considerando que os sensores estão posicionados na superfície de uma estrutura rígida e cilíndrica, sendo que o campo externo é o objeto de interesse. Deste modo, fontes sonoras ao redor do cilindro serão detectáveis e passíveis de visualização. Para este propósito, diferente do comumente aplicado, não somente o campo livre é considerado, mas também o campo de difração que é criado pelo cilindro. A modelagem analítica do problema é desenvolvida e adaptada para a aplicação do algoritmo de beamforming. Esta é uma das contribuições desta pesquisa visto que, na maioria das aplicações, somente o campo incidente é considerado no pós-processamento. Além disso, para uma das geometrias estudadas, medições foram realizadas em ambiente anecoico para comparar os resultados com as simulações analítica e numérica.Outros métodos numéricos foram também empregados em duas frentes: para confirmar o significado físico e discutir resultados, e para encontrar uma geometria mais adequada. O Método de Elementos de Contorno (MEC ou BEM) é utilizado para avaliação do problema de maneira genérica, visto que quase todos os tipos de estruturas podem ser modelados em seu domínio. O objetivo é calcular as mesmas situações de difração com o modelo analítico e com o MEC e compará-las. O trabalho então apresenta um estudo correlacionando à malha do modelo 3D com os erros de localização nos mapas criados pelo beamforming. Em conseguinte, um método de otimização baseado em Algoritmo Genético (GA) é desenvolvido para posicionar os sensores na superfície do cilindro de modo a prevenir lóbulos laterais, lóbulos espelho e maximizar a faixa dinâmica.A aplicação dos métodos estudados junto ao beamforming criou novos aspectos em design de arrays. Ao longo do documento as discussões apontam os aprimoramentos e problemas relacionados ao desempenho na localização de fontes sonoras. Ao final, há um sumário acerca das contribuições da pesquisa e algumas ideias para trabalhos futuro. Abstract : Beamforming is a signal processing technique recognized for its applications in antennas and radio astronomy. It is essentially a technique to locate sources based on the conformation of wave beams from a given direction or region in space. Its application in acoustics originated rudimentarily during World War I. However, the advances that have led to the creation of acoustic images date from the early seventies.The present work proposes the application this technique considering the sensors are over a rigid cylindrical surface with the external field as the object of interest. Thus, sound sources anywhere around the cylinder become detectable and subject to viewing. For this purpose not only the free-field is considered, but also the diffraction acoustic field created by the cylinder. The problem?s analytical modelling is developed and adapted in order to apply the beamforming algorithm. This is one of the contributions of this research since in most applications only the incident field is considered in post-processing. In addition, measurements were carried out in an anechoic environment for one of the geometries studied to compare the results with the analytical and numerical simulations.Other numerical methods are also employed on two fronts: to confirm the physical meaning and discuss the results, and to search for a more suitable geometry. The Boundary Element Method (BEM) is used to generically review the problem, since the great majority of structures can be modelled in its domain. The objective is to calculate the same diffraction situations in the analytical model and the BEM for comparison. The work then presents a study on the mesh of the 3D model used correlated with beamforming sound source map location errors. Subsequently, an optimisation method based on the Genetic Algorithm (GA) is developed to place the sensors over the cylinder's surface in order to prevent sidelobes, grating lobes, and to maximize the dynamic range. The application of the methods studied together with beamforming has created new aspects in array design. This document then discusses and points out the improvements and problems with respect to sound source location performance. Finally, there is a summary concerning the research contributions and some thoughts for future work

The electronically steerable parasitic array radiator antenna for wireless communications : signal processing and emerging techniques

Smart antenna technology is expected to play an important role in future wireless communication networks in order to use the spectrum efficiently, improve the quality of service, reduce the costs of establishing new wireless paradigms and reduce the energy consumption in wireless networks. Generally, smart antennas exploit multiple widely spaced active elements, which are connected to separate radio frequency (RF) chains. Therefore, they are only applicable to base stations (BSs) and access points, by contrast with modern compact wireless terminals with constraints on size, power and complexity. This dissertation considers an alternative smart antenna system the electronically steerable parasitic array radiator (ESPAR) which uses only a single RF chain, coupled with multiple parasitic elements. The ESPAR antenna is of significant interest because of its flexibility in beamforming by tuning a number of easy-to-implement reactance loads connected to parasitic elements; however, parasitic elements require no expensive RF circuits. This work concentrates on the study of the ESPAR antenna for compact transceivers in order to achieve some emerging techniques in wireless communications. The work begins by presenting the work principle and modeling of the ESPAR antenna and describes the reactance-domain signal processing that is suited to the single active antenna array, which are fundamental factors throughout this thesis. The major contribution in this chapter is the adaptive beamforming method based on the ESPAR antenna. In order to achieve fast convergent beamforming for the ESPAR antenna, a modified minimum variance distortionless response (MVDR) beamfomer is proposed. With reactance-domain signal processing, the ESPAR array obtains a correlation matrix of receive signals as the input to the MVDR optimization problem. To design a set of feasible reactance loads for a desired beampattern, the MVDR optimization problem is reformulated as a convex optimization problem constraining an optimized weight vector close to a feasible solution. Finally, the necessary reactance loads are optimized by iterating the convex problem and a simple projector. In addition, the generic algorithm-based beamforming method has also studied for the ESPAR antenna. Blind interference alignment (BIA) is a promising technique for providing an optimal degree of freedom in a multi-user, multiple-inputsingle-output broadcast channel, without the requirements of channel state information at the transmitters. Its key is antenna mode switching at the receive antenna. The ESPAR antenna is able to provide a practical solution to beampattern switching (one kind of antenna mode switching) for the implementation of BIA. In this chapter, three beamforming methods are proposed for providing the required number of beampatterns that are exploited across one super symbol for creating the channel fluctuation patterns seen by receivers. These manually created channel fluctuation patterns are jointly combined with the designed spacetime precoding in order to align the inter-user interference. Furthermore, the directional beampatterns designed in the ESPAR antenna are demonstrated to improve the performance of BIA by alleviating the noise amplification. The ESPAR antenna is studied as the solution to interference mitigation in small cell networks. Specifically, ESPARs analog beamforming presented in the previous chapter is exploited to suppress inter-cell interference for the system scenario, scheduling only one user to be served by each small BS at a single time. In addition, the ESPAR-based BIA is employed to mitigate both inter-cell and intracell interference for the system scenario, scheduling a small number of users to be simultaneously served by each small BS for a single time. In the cognitive radio (CR) paradigm, the ESPAR antenna is employed for spatial spectrum sensing in order to utilize the new angle dimension in the spectrum space besides the conventional frequency, time and space dimensions. The twostage spatial spectrum sensing method is proposed based on the ESPAR antenna being targeted at identifying white spectrum space, including the new angle dimension. At the first stage, the occupancy of a specific frequency band is detected by conventional spectrum-sensing methods, including energy detector and eigenvalue-based methods implemented with the switched-beam ESPAR antenna. With the presence of primary users, their directions are estimated at the second stage, by high-resolution angle-of-arrival (AoA) estimation algorithms. Specifically, the compressive sensing technology has been studied for AoA detection with the ESPAR antenna, which is demonstrated to provide high-resolution estimation results and even to outperform the reactance-domain multiple signal classification