Compressive techniques for sub-Nyquist data acquisition & processing in vibration-based structural health monitoring of engineering structures

Vibration-based structural health monitoring (VSHM) is an automated method for assessing the integrity and performance of dynamically excited structures through processing of structural vibration response signals acquired by arrays of sensors. From a technological viewpoint, wireless sensor networks (WSNs) offer less obtrusive, more economical, and rapid VSHM deployments in civil structures compared to their tethered counterparts, especially in monitoring large-scale and geometrically complex structures. However, WSNs are constrained by certain practical issues related to local power supply at sensors and restrictions to the amount of wirelessly transmitted data due to increased power consumptions and bandwidth limitations in wireless communications. The primary objective of this thesis is to resolve the above issues by considering sub-Nyquist data acquisition and processing techniques that involve simultaneous signal acquisition and compression before transmission. This drastically reduces the sampling and transmission requirements leading to reduced power consumptions up to 85-90% compared to conventional approaches at Nyquist rate. Within this context, the current state-of-the-art VSHM approaches exploits the theory of compressive sensing (CS) to acquire structural responses at non-uniform random sub-Nyquist sampling schemes. By exploiting the sparse structure of the analysed signals in a known vector basis (i.e., non-zero signal coefficients), the original time-domain signals are reconstructed at the uniform Nyquist grid by solving an underdetermined optimisation problem subject to signal sparsity constraints. However, the CS sparse recovery is a computationally intensive problem that strongly depends on and is limited by the sparsity attributes of the measured signals on a pre-defined expansion basis. This sparsity information, though, is unknown in real-time VSHM deployments while it is adversely affected by noisy environments encountered in practice. To efficiently address the above limitations encountered in CS-based VSHM methods, this research study proposes three alternative approaches for energy-efficient VSHM using compressed structural response signals under ambient vibrations. The first approach aims to enhance the sparsity information of vibrating structural responses by considering their representation on the wavelet transform domain using various oscillatory functions with different frequency domain attributes. In this respect, a novel data-driven damage detection algorithm is developed herein, emerged as a fusion of the CS framework with the Relative Wavelet Entropy (RWE) damage index. By processing sparse signal coefficients on the harmonic wavelet transform for two comparative structural states (i.e., damage versus healthy state), CS-based RWE damage indices are retrieved from a significantly reduced number of wavelet coefficients without reconstructing structural responses in time-domain. The second approach involves a novel signal-agnostic sub-Nyquist spectral estimation method free from sparsity constraints, which is proposed herein as a viable alternative for power-efficient WSNs in VSHM applications. The developed method relies on Power Spectrum Blind Sampling (PSBS) techniques together with a deterministic multi-coset sampling pattern, capable to acquire stationary structural responses at sub-Nyquist rates without imposing sparsity conditions. Based on a network of wireless sensors operating on the same sampling pattern, auto/cross power-spectral density estimates are computed directly from compressed data by solving an overdetermined optimisation problem; thus, by-passing the computationally intensive signal reconstruction operations in time-domain. This innovative approach can be fused with standard operational modal analysis algorithms to estimate the inherent resonant frequencies and modal deflected shapes of structures under low-amplitude ambient vibrations with the minimum power, computational and memory requirements at the sensor, while outperforming pertinent CS-based approaches. Based on the extracted modal in formation, numerous data-driven damage detection strategies can be further employed to evaluate the condition of the monitored structures. The third approach of this thesis proposes a noise-immune damage detection method capable to capture small shifts in structural natural frequencies before and after a seismic event of low intensity using compressed acceleration data contaminated with broadband noise. This novel approach relies on a recently established sub-Nyquist pseudo-spectral estimation method which combines the deterministic co-prime sub-Nyquist sampling technique with the multiple signal classification (MUSIC) pseudo-spectrum estimator. This is also a signal-agnostic and signal reconstruction-free method that treats structural response signals as wide-sense stationary stochastic processes to retrieve, with very high resolution, auto-power spectral densities and structural natural frequency estimates directly from compressed data while filtering out additive broadband noise

A room acoustics measurement system using non-invasive microphone arrays

This thesis summarises research into adaptive room correction for small rooms and pre-recorded material, for example music of films. A measurement system to predict the sound at a remote location within a room, without a microphone at that location was investigated. This would allow the sound within a room to be adaptively manipulated to ensure that all listeners received optimum sound, therefore increasing their enjoyment. The solution presented used small microphone arrays, mounted on the room's walls. A unique geometry and processing system was designed, incorporating three processing stages, temporal, spatial and spectral. The temporal processing identifies individual reflection arrival times from the recorded data. Spatial processing estimates the angles of arrival of the reflections so that the three-dimensional coordinates of the reflections' origin can be calculated. The spectral processing then estimates the frequency response of the reflection. These estimates allow a mathematical model of the room to be calculated, based on the acoustic measurements made in the actual room. The model can then be used to predict the sound at different locations within the room. A simulated model of a room was produced to allow fast development of algorithms. Measurements in real rooms were then conducted and analysed to verify the theoretical models developed and to aid further development of the system. Results from these measurements and simulations, for each processing stage are presented

Short-Range Millimeter-Wave Sensing and Imaging: Theory, Experiments and Super-Resolution Algorithms

Recent advancements in silicon technology offer the possibility of realizing low-cost and highly integrated radar sensor and imaging systems in mm-wave (between 30 and 300 GHz) and beyond. Such active short-range mm-wave systems have a wide range of applications including medical imaging, security scanning, autonomous vehicle navigation, and human gesture recognition. Moving to higher frequencies provides us with the spectral and spatial degrees of freedom that we need for high resolution imaging and sensing application. Increased bandwidth availability enhances range resolution by increasing the degrees of freedom in the time-frequency domain. Cross-range resolution is enhanced by the increase in the number of spatial degrees of freedom for a constrained form factor. The focus of this thesis is to explore system design and algorithmic development to utilize the available degrees of freedom in mm-wave frequencies in order to realize imaging and sensing capabilities under cost, complexity and form factor constraints. We first consider the fundamental problem of estimating frequencies and gains in a noisy mixture of sinusoids. This problem is ubiquitous in radar sensing applications, including target range and velocity estimation using standard radar waveforms (e.g., chirp or stepped frequency continuous wave), and direction of arrival estimation using an array of antenna elements. We have developed a fast and robust iterative algorithm for super-resolving the frequencies and gains, and have demonstrated near-optimal performance in terms of frequency estimation accuracy by benchmarking against the Cramer Rao Bound in various scenarios.Next, we explore cross-range radar imaging using an array of antenna elements under severe cost, complexity and form factor constraints. We show that we must account for such constraints in a manner that is quite different from that of conventional radar, and introduce new models and algorithms validated by experimental results. In order to relax the synchronization requirements across multiple transceiver elements we have considered the monostatic architecture in which only the co-located elements are synchronized. We investigate the impact of sparse spatial sampling by reducing the number of array antenna elements, and show that ``sparse monostatic'' architecture leads to grating lobe artifact, which introduces ambiguity in the detection/estimation of point targets in the scene. At short ranges, however, targets are ``low-pass'' and contain extended features (consisting of a continuum of points), and are not well-modeled by a small number of point scatterers. We introduce the concept of ``spatial aggregation,'' which provides the flexibility of constructing a dictionary in which each atom corresponds to a collection of point scatterers, and demonstrate its effectiveness in suppressing the grating lobes and preserving the information in the scene.Finally, we take a more fundamental and systematic approach based on singular decomposition of the imaging system, to understand the information capacity and the limits of performance for various geometries. In general, a scene can be described by an infinite number of independent parameters. However, the number of independent parameters that can be measured through an imaging system (also known as the degrees of freedom of the system) is typically finite, and is constrained by the geometry and wavelength. We introduce a measure to predict the number of spatial degrees of freedom of 1D imaging systems for both monostatic and multistatic array architectures. Our analysis reveals that there is no fundamental benefit in multistatic architecture compared to monostatic in terms of achievable degrees of freedom. The real benefit of multistatic architecture from a practical point of view, is in being able to design sparse transmit and receive antenna arrays that are capable of achieving the available degrees of freedom. Moreover, our analytical framework opens up new avenues to investigate image formation techniques that aim to reconstruct the reflectivity function of the scene by solving an inverse scattering problem, and provides crucial insights on the achievable resolution

Audio source separation for music in low-latency and high-latency scenarios

Aquesta tesi proposa mètodes per tractar les limitacions de les tècniques existents de separació de fonts musicals en condicions de baixa i alta latència. En primer lloc, ens centrem en els mètodes amb un baix cost computacional i baixa latència. Proposem l'ús de la regularització de Tikhonov com a mètode de descomposició de l'espectre en el context de baixa latència. El comparem amb les tècniques existents en tasques d'estimació i seguiment dels tons, que són passos crucials en molts mètodes de separació. A continuació utilitzem i avaluem el mètode de descomposició de l'espectre en tasques de separació de veu cantada, baix i percussió. En segon lloc, proposem diversos mètodes d'alta latència que milloren la separació de la veu cantada, gràcies al modelatge de components específics, com la respiració i les consonants. Finalment, explorem l'ús de correlacions temporals i anotacions manuals per millorar la separació dels instruments de percussió i dels senyals musicals polifònics complexes.Esta tesis propone métodos para tratar las limitaciones de las técnicas existentes de separación de fuentes musicales en condiciones de baja y alta latencia. En primer lugar, nos centramos en los métodos con un bajo coste computacional y baja latencia. Proponemos el uso de la regularización de Tikhonov como método de descomposición del espectro en el contexto de baja latencia. Lo comparamos con las técnicas existentes en tareas de estimación y seguimiento de los tonos, que son pasos cruciales en muchos métodos de separación. A continuación utilizamos y evaluamos el método de descomposición del espectro en tareas de separación de voz cantada, bajo y percusión. En segundo lugar, proponemos varios métodos de alta latencia que mejoran la separación de la voz cantada, gracias al modelado de componentes que a menudo no se toman en cuenta, como la respiración y las consonantes. Finalmente, exploramos el uso de correlaciones temporales y anotaciones manuales para mejorar la separación de los instrumentos de percusión y señales musicales polifónicas complejas.This thesis proposes specific methods to address the limitations of current music source separation methods in low-latency and high-latency scenarios. First, we focus on methods with low computational cost and low latency. We propose the use of Tikhonov regularization as a method for spectrum decomposition in the low-latency context. We compare it to existing techniques in pitch estimation and tracking tasks, crucial steps in many separation methods. We then use the proposed spectrum decomposition method in low-latency separation tasks targeting singing voice, bass and drums. Second, we propose several high-latency methods that improve the separation of singing voice by modeling components that are often not accounted for, such as breathiness and consonants. Finally, we explore using temporal correlations and human annotations to enhance the separation of drums and complex polyphonic music signals

Opportunistic communications in large uncoordinated networks

(English) The increase of wireless devices offering high data rate services limits the coexistence of wireless systems sharing the same resources in a given geographical area because of inter-system interference. Therefore, interference management plays a key role in permitting the coexistence of several heterogeneous communication services. However, classical interference management strategies require lateral information giving rise to the need for inter-system coordination and cooperation, which is not always practical. Opportunistic communications offer a potential solution to the problem of inter-system interference management. The basic principle of opportunistic communications is to efficiently and robustly exploit the resources available in a wireless network and adapt the transmitted signals to the state of the network to avoid inter-system interference. Therefore, opportunistic communications depend on inferring the available network resources that can be safely exploited without inducing interference in coexisting communication nodes. Once the available network resources are identified, the most prominent opportunistic communication techniques consist in designing scenario-adapted precoding/decoding strategies to exploit the so-called null space. Despite this, classical solutions in the literature suffer from two main drawbacks: the lack of robustness to detection errors and the need for intra-system cooperation. This thesis focuses on the design of a null space-based opportunistic communication scheme that addresses the drawbacks exhibited by existing methodologies under the assumption that opportunistic nodes do not cooperate. For this purpose, a generalized detection error model independent of the null-space identification mechanism is introduced that allows the design of solutions that exhibit minimal inter-system interference in the worst case. These solutions respond to a maximum signal-to-interference ratio (SIR) criterion, which is optimal under non-cooperative conditions. The proposed methodology allows the design of a family of orthonormal waveforms that perform a spreading of the modulated symbols within the detected null space, which is key to minimizing the induced interference density. The proposed solutions are invariant within the inferred null space, allowing the removal of the feedback link without giving up coherent waveform detection. In the absence of coordination, the waveform design relies solely on locally sensed network state information, inducing a mismatch between the null spaces identified by the transmitter and receiver that may worsen system performance. Although the proposed solution is robust to this mismatch, the design of enhanced receivers using active subspace detection schemes is also studied. When the total number of network resources increases arbitrarily, the proposed solutions tend to be linear combinations of complex exponentials, providing an interpretation in the frequency domain. This asymptotic behavior allows us to adapt the proposed solution to frequency-selective channels by means of a cyclic prefix and to study an efficient modulation similar to the time division multiplexing scheme but using circulant waveforms. Finally, the impact of the use of multiple antennas in opportunistic null space-based communications is studied. The performed analysis reveals that, in any case, the structure of the antenna clusters affects the opportunistic communication, since the proposed waveform mimics the behavior of a single-antenna transmitter. On the other hand, the number of sensors employed translates into an improvement in terms of SIR.(Català) El creixement incremental dels dispositius sense fils que requereixen serveis d'alta velocitat de dades limita la coexistència de sistemes sense fils que comparteixen els mateixos recursos en una àrea geogràfica donada a causa de la interferència entre sistemes. Conseqüentment, la gestió d'interferència juga un paper fonamental per a facilitar la coexistència de diversos serveis de comunicació heterogenis. No obstant això, les estratègies clàssiques de gestió d'interferència requereixen informació lateral originant la necessitat de coordinació i cooperació entre sistemes, que no sempre és pràctica. Les comunicacions oportunistes ofereixen una solució potencial al problema de la gestió de les interferències entre sistemes. El principi bàsic de les comunicacions oportunistes és explotar de manera eficient i robusta els recursos disponibles en una xarxa sense fils i adaptar els senyals transmesos a l'estat de la xarxa per evitar interferències entre sistemes. Per tant, les comunicacions oportunistes depenen de la inferència dels recursos de xarxa disponibles que poden ser explotats de manera segura sense induir interferència en els nodes de comunicació coexistents. Una vegada que s'han identificat els recursos de xarxa disponibles, les tècniques de comunicació oportunistes més prominents consisteixen en el disseny d'estratègies de precodificació/descodificació adaptades a l'escenari per explotar l'anomenat espai nul. Malgrat això, les solucions clàssiques en la literatura sofreixen dos inconvenients principals: la falta de robustesa als errors de detecció i la necessitat de cooperació intra-sistema. Aquesta tesi tracta el disseny d'un esquema de comunicació oportunista basat en l'espai nul que afronta els inconvenients exposats per les metodologies existents assumint que els nodes oportunistes no cooperen. Per a aquest propòsit, s'introdueix un model generalitzat d'error de detecció independent del mecanisme d'identificació de l'espai nul que permet el disseny de solucions que exhibeixen interferències mínimes entre sistemes en el cas pitjor. Aquestes solucions responen a un criteri de màxima relació de senyal a interferència (SIR), que és òptim en condicions de no cooperació. La metodologia proposada permet dissenyar una família de formes d'ona ortonormals que realitzen un spreading dels símbols modulats dins de l'espai nul detectat, que és clau per minimitzar la densitat d’interferència induïda. Les solucions proposades són invariants dins de l'espai nul inferit, permetent suprimir l'enllaç de retroalimentació i, tot i així, realitzar una detecció coherent de forma d'ona. Sota l’absència de coordinació, el disseny de la forma d'ona es basa únicament en la informació de l'estat de la xarxa detectada localment, induint un desajust entre els espais nuls identificats pel transmissor i receptor que pot empitjorar el rendiment del sistema. Tot i que la solució proposada és robusta a aquest desajust, també s'estudia el disseny de receptors millorats fent ús de tècniques de detecció de subespai actiu. Quan el nombre total de recursos de xarxa augmenta arbitràriament, les solucions proposades tendeixen a ser combinacions lineals d'exponencials complexes, proporcionant una interpretació en el domini freqüencial. Aquest comportament asimptòtic permet adaptar la solució proposada a entorns selectius en freqüència fent ús d'un prefix cíclic i estudiar una modulació eficient derivada de l'esquema de multiplexat per divisió de temps emprant formes d'ona circulant. Finalment, s’estudia l'impacte de l'ús de múltiples antenes en comunicacions oportunistes basades en l'espai nul. L'anàlisi realitzada permet concloure que, en cap cas, l'estructura de les agrupacions d'antenes tenen un impacte sobre la comunicació oportunista, ja que la forma d'ona proposada imita el comportament d'un transmissor mono-antena. D'altra banda, el nombre de sensors emprat es tradueix en una millora en termes de SIR.(Español) El incremento de los dispositivos inalámbricos que ofrecen servicios de alta velocidad de datos limita la coexistencia de sistemas inalámbricos que comparten los mismos recursos en un área geográfica dada a causa de la interferencia inter-sistema. Por tanto, la gestión de interferencia juega un papel fundamental para facilitar la coexistencia de varios servicios de comunicación heterogéneos. Sin embargo, las estrategias clásicas de gestión de interferencia requieren información lateral originando la necesidad de coordinación y cooperación entre sistemas, que no siempre es práctica. Las comunicaciones oportunistas ofrecen una solución potencial al problema de la gestión de las interferencias entre sistemas. El principio básico de las comunicaciones oportunistas es explotar de manera eficiente y robusta los recursos disponibles en una red inalámbricas y adaptar las señales transmitidas al estado de la red para evitar interferencias entre sistemas. Por lo tanto, las comunicaciones oportunistas dependen de la inferencia de los recursos de red disponibles que pueden ser explotados de manera segura sin inducir interferencia en los nodos de comunicación coexistentes. Una vez identificados los recursos disponibles, las técnicas de comunicación oportunistas más prominentes consisten en el diseño de estrategias de precodificación/descodificación adaptadas al escenario para explotar el llamado espacio nulo. A pesar de esto, las soluciones clásicas en la literatura sufren dos inconvenientes principales: la falta de robustez a los errores de detección y la necesidad de cooperación intra-sistema. Esta tesis propone diseñar un esquema de comunicación oportunista basado en el espacio nulo que afronta los inconvenientes expuestos por las metodologías existentes asumiendo que los nodos oportunistas no cooperan. Para este propósito, se introduce un modelo generalizado de error de detección independiente del mecanismo de identificación del espacio nulo que permite el diseño de soluciones que exhiben interferencias mínimas entre sistemas en el caso peor. Estas soluciones responden a un criterio de máxima relación de señal a interferencia (SIR), que es óptimo en condiciones de no cooperación. La metodología propuesta permite diseñar una familia de formas de onda ortonormales que realizan un spreading de los símbolos modulados dentro del espacio nulo detectado, que es clave para minimizar la densidad de interferencia inducida. Las soluciones propuestas son invariantes dentro del espacio nulo inferido, permitiendo suprimir el enlace de retroalimentación sin renunciar a la detección coherente de forma de onda. En ausencia de coordinación, el diseño de la forma de onda se basa únicamente en la información del estado de la red detectada localmente, induciendo un desajuste entre los espacios nulos identificados por el transmisor y receptor que puede empeorar el rendimiento del sistema. A pesar de que la solución propuesta es robusta a este desajuste, también se estudia el diseño de receptores mejorados usando técnicas de detección de subespacio activo. Cuando el número total de recursos de red aumenta arbitrariamente, las soluciones propuestas tienden a ser combinaciones lineales de exponenciales complejas, proporcionando una interpretación en el dominio frecuencial. Este comportamiento asintótico permite adaptar la solución propuesta a canales selectivos en frecuencia mediante un prefijo cíclico y estudiar una modulación eficiente derivada del esquema de multiplexado por división de tiempo empleando formas de onda circulante. Finalmente, se estudia el impacto del uso de múltiples antenas en comunicaciones oportunistas basadas en el espacio nulo. El análisis realizado revela que la estructura de las agrupaciones de antenas no afecta la comunicación oportunista, ya que la forma de onda propuesta imita el comportamiento de un transmisor mono-antena. Por otro lado, el número de sensores empleado se traduce en una mejora en términos de SIR.Postprint (published version

Very High Resolution Tomographic SAR Inversion for Urban Infrastructure Monitoring — A Sparse and Nonlinear Tour

The topic of this thesis is very high resolution (VHR) tomographic SAR inversion for urban infrastructure monitoring. To this end, SAR tomography and differential SAR tomography are demonstrated using TerraSAR-X spotlight data for providing 3-D and 4-D (spatial-temporal) maps of an entire high rise city area including layover separation and estimation of deformation of the buildings. A compressive sensing based estimator (SL1MMER) tailored to VHR SAR data is developed for tomographic SAR inversion by exploiting the sparsity of the signal. A systematic performance assessment of the algorithm is performed regarding elevation estimation accuracy, super-resolution and robustness. A generalized time warp method is proposed which enables differential SAR tomography to estimate multi-component nonlinear motion. All developed methods are validated with both simulated and extensive processing of large volumes of real data from TerraSAR-X