Novel implementation technique for a wavelet-based broadband signal detection system

This thesis reports on the design, simulation and implementation of a novel Implementation for a Wavelet-based Broadband Signal Detection System. There is a strong interest in methods of increasing the resolution of sonar systems for the detection of targets at sea. A novel implementation of a wideband active sonar signal detection system is proposed in this project. In the system the Continuous Wavelet Transform is used for target motion estimation and an Adaptive-Network-based Fuzzy inference System (ANFIS) is adopted to minimize the noise effect on target detection. A local optimum search algorithm is introduced in this project to reduce the computation load of the Continuous Wavelet Transform and make it suitable for practical applications. The proposed system is realized on a Xilinx University Program Virtex-II Pro Development System which contains a Virtex II pro XC2VP30 FPGA chip with 2 powerPC 405 cores. Testing for single target detection and multiple target detection shows the proposed system is able to accurately locate targets under reverberation-limited underwater environment with a Signal-Noise-Ratio of up to -30db, with location error less than 10 meters and velocity estimation error less than 1 knot. In the proposed system the combination of CWT and local optimum search algorithm significantly saves the computation time for CWT and make it more practical to real applications. Also the implementation of ANFIS on the FPGA board indicates in the future a real-time ANFIS operation with VLSI implementation would be possible

Novel implementation technique for a wavelet-based broadband signal detection system

This thesis reports on the design, simulation and implementation of a novel Implementation for a Wavelet-based Broadband Signal Detection System. There is a strong interest in methods of increasing the resolution of sonar systems for the detection of targets at sea. A novel implementation of a wideband active sonar signal detection system is proposed in this project. In the system the Continuous Wavelet Transform is used for target motion estimation and an Adaptive-Network-based Fuzzy inference System (ANFIS) is adopted to minimize the noise effect on target detection. A local optimum search algorithm is introduced in this project to reduce the computation load of the Continuous Wavelet Transform and make it suitable for practical applications. The proposed system is realized on a Xilinx University Program Virtex-II Pro Development System which contains a Virtex II pro XC2VP30 FPGA chip with 2 powerPC 405 cores. Testing for single target detection and multiple target detection shows the proposed system is able to accurately locate targets under reverberation-limited underwater environment with a Signal-Noise-Ratio of up to -30db, with location error less than 10 meters and velocity estimation error less than 1 knot. In the proposed system the combination of CWT and local optimum search algorithm significantly saves the computation time for CWT and make it more practical to real applications. Also the implementation of ANFIS on the FPGA board indicates in the future a real-time ANFIS operation with VLSI implementation would be possible.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Single- and multi-microphone speech dereverberation using spectral enhancement

In speech communication systems, such as voice-controlled systems, hands-free mobile telephones, and hearing aids, the received microphone signals are degraded by room reverberation, background noise, and other interferences. This signal degradation may lead to total unintelligibility of the speech and decreases the performance of automatic speech recognition systems. In the context of this work reverberation is the process of multi-path propagation of an acoustic sound from its source to one or more microphones. The received microphone signal generally consists of a direct sound, reflections that arrive shortly after the direct sound (commonly called early reverberation), and reflections that arrive after the early reverberation (commonly called late reverberation). Reverberant speech can be described as sounding distant with noticeable echo and colouration. These detrimental perceptual effects are primarily caused by late reverberation, and generally increase with increasing distance between the source and microphone. Conversely, early reverberations tend to improve the intelligibility of speech. In combination with the direct sound it is sometimes referred to as the early speech component. Reduction of the detrimental effects of reflections is evidently of considerable practical importance, and is the focus of this dissertation. More specifically the dissertation deals with dereverberation techniques, i.e., signal processing techniques to reduce the detrimental effects of reflections. In the dissertation, novel single- and multimicrophone speech dereverberation algorithms are developed that aim at the suppression of late reverberation, i.e., at estimation of the early speech component. This is done via so-called spectral enhancement techniques that require a specific measure of the late reverberant signal. This measure, called spectral variance, can be estimated directly from the received (possibly noisy) reverberant signal(s) using a statistical reverberation model and a limited amount of a priori knowledge about the acoustic channel(s) between the source and the microphone(s). In our work an existing single-channel statistical reverberation model serves as a starting point. The model is characterized by one parameter that depends on the acoustic characteristics of the environment. We show that the spectral variance estimator that is based on this model, can only be used when the source-microphone distance is larger than the so-called critical distance. This is, crudely speaking, the distance where the direct sound power is equal to the total reflective power. A generalization of the statistical reverberation model in which the direct sound is incorporated is developed. This model requires one additional parameter that is related to the ratio between the direct sound energy and the sound energy of all reflections. The generalized model is used to derive a novel spectral variance estimator. When the novel estimator is used for dereverberation rather than the existing estimator, and the source-microphone distance is smaller than the critical distance, the dereverberation performance is significantly increased. Single-microphone systems only exploit the temporal and spectral diversity of the received signal. Reverberation, of course, also induces spatial diversity. To additionally exploit this diversity, multiple microphones must be used, and their outputs must be combined by a suitable spatial processor such as the so-called delay and sum beamformer. It is not a priori evident whether spectral enhancement is best done before or after the spatial processor. For this reason we investigate both possibilities, as well as a merge of the spatial processor and the spectral enhancement technique. An advantage of the latter option is that the spectral variance estimator can be further improved. Our experiments show that the use of multiple microphones affords a significant improvement of the perceptual speech quality. The applicability of the theory developed in this dissertation is demonstrated using a hands-free communication system. Since hands-free systems are often used in a noisy and reverberant environment, the received microphone signal does not only contain the desired signal but also interferences such as room reverberation that is caused by the desired source, background noise, and a far-end echo signal that results from a sound that is produced by the loudspeaker. Usually an acoustic echo canceller is used to cancel the far-end echo. Additionally a post-processor is used to suppress background noise and residual echo, i.e., echo which could not be cancelled by the echo canceller. In this work a novel structure and post-processor for an acoustic echo canceller are developed. The post-processor suppresses late reverberation caused by the desired source, residual echo, and background noise. The late reverberation and late residual echo are estimated using the generalized statistical reverberation model. Experimental results convincingly demonstrate the benefits of the proposed system for suppressing late reverberation, residual echo and background noise. The proposed structure and post-processor have a low computational complexity, a highly modular structure, can be seamlessly integrated into existing hands-free communication systems, and affords a significant increase of the listening comfort and speech intelligibility

Development of tangible acoustic interfaces for human computer interaction

Tangible interfaces, such as keyboards, mice, touch pads, and touch screens, are widely used in human computer interaction. A common disadvantage with these devices is the presence of mechanical or electronic devices at the point of interaction with the interface. The aim of this work has been to investigate and develop new tangible interfaces that can be adapted to virtually any surface, by acquiring and studying the acoustic vibrations produced by the interaction of the user's finger on the surface. Various approaches have been investigated in this work, including the popular time difference of arrival (TDOA) method, time-frequency analysis of dispersive velocities, the time reversal method, and continuous object tracking. The received signal due to a tap at a source position can be considered the impulse response function of the wave propagation between the source and the receiver. With the time reversal theory, the signals induced by impacts from one position contain the unique and consistent information that forms its signature. A pattern matching method, named Location Template Matching (LTM), has been developed to identify the signature of the received signals from different individual positions. Various experiments have been performed for different purposes, such as consistency testing, acquisition configuration, and accuracy of recognition. Eventually, this can be used to implement HCI applications on any arbitrary surfaces, including those of 3D objects and inhomogeneous materials. The resolution with the LTM method has been studied by different experiments, investigating factors such as optimal sensor configurations and the limitation of materials. On plates of the same material, the thickness is the essential determinant of resolution. With the knowledge of resolution for one material, a simple but faster search method becomes feasible to reduce the computation. Multiple simultaneous impacts are also recognisable in certain cases. The TDOA method has also been evaluated with two conventional approaches. Taking into account the dispersive properties of the vibration propagation in plates, time-frequency analysis, with continuous wavelet transformation, has been employed for the accurate localising of dispersive signals. In addition, a statistical estimation of maximum likelihood has been developed to improve the accuracy and reliability of acoustic localisation. A method to measure and verify the dispersive velocities has also been introduced. To enable the commonly required "drag & drop" function in the operation of graphical user interface (GUI) software, the tracking of a finger scratching on a surface needs to be implemented. To minimise the tracking error, a priori knowledge of previous measurements of source locations is needed to linearise the state model that enables prediction of the location of the contact point and the direction of movement. An adaptive Kalman filter has been used for this purpose.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Development of tangible acoustic interfaces for human computer interaction

Tangible interfaces, such as keyboards, mice, touch pads, and touch screens, are widely used in human computer interaction. A common disadvantage with these devices is the presence of mechanical or electronic devices at the point of interaction with the interface. The aim of this work has been to investigate and develop new tangible interfaces that can be adapted to virtually any surface, by acquiring and studying the acoustic vibrations produced by the interaction of the user's finger on the surface. Various approaches have been investigated in this work, including the popular time difference of arrival (TDOA) method, time-frequency analysis of dispersive velocities, the time reversal method, and continuous object tracking. The received signal due to a tap at a source position can be considered the impulse response function of the wave propagation between the source and the receiver. With the time reversal theory, the signals induced by impacts from one position contain the unique and consistent information that forms its signature. A pattern matching method, named Location Template Matching (LTM), has been developed to identify the signature of the received signals from different individual positions. Various experiments have been performed for different purposes, such as consistency testing, acquisition configuration, and accuracy of recognition. Eventually, this can be used to implement HCI applications on any arbitrary surfaces, including those of 3D objects and inhomogeneous materials. The resolution with the LTM method has been studied by different experiments, investigating factors such as optimal sensor configurations and the limitation of materials. On plates of the same material, the thickness is the essential determinant of resolution. With the knowledge of resolution for one material, a simple but faster search method becomes feasible to reduce the computation. Multiple simultaneous impacts are also recognisable in certain cases. The TDOA method has also been evaluated with two conventional approaches. Taking into account the dispersive properties of the vibration propagation in plates, time-frequency analysis, with continuous wavelet transformation, has been employed for the accurate localising of dispersive signals. In addition, a statistical estimation of maximum likelihood has been developed to improve the accuracy and reliability of acoustic localisation. A method to measure and verify the dispersive velocities has also been introduced. To enable the commonly required "drag & drop" function in the operation of graphical user interface (GUI) software, the tracking of a finger scratching on a surface needs to be implemented. To minimise the tracking error, a priori knowledge of previous measurements of source locations is needed to linearise the state model that enables prediction of the location of the contact point and the direction of movement. An adaptive Kalman filter has been used for this purpose

Detecção de novidade para sistemas de sonar passivo

Sound is a mechanical wave that propagates over great distances in the oceans and it can, therefore, be used for vessel detection and classification in underwater environments, which are basic sonar system tasks. The development of such systems is directly linked to the country defense, especially, in countries with continental dimensions, such as Brazil. Recently, the Brazilian Navy defined underwater acoustics as a strategic priority area. Passive sonar systems can be installed to monitor the Brazilian coast in a stealthy and efficient way. In addition, these are used in military submarines for different applications. As in this operating environment, each ship has a unique acoustic signature, and ships whose data have not been acquired can be observed, it is necessary to develop a novelty detector operating in conjunction with the contact classifiers implemented in Brazilian Navy systems. Because classification systems operate competing for computing resources with novelty detectors, they can impact in classification efficiency. The number of classes in this environment is very large, and because of this, specific performance indices were created to evaluate the developed model efficiency. In addition, different data compressors were developed to access relevant ship information of, among them can be cited PCD, kPCA, NLPCA and SAE. The novelty detection development was based on the operating environment of the Brazilian Navy and since it can have its operating conditions changed over time, a stationarity monitoring system based on higher order statistics was proposed. Both the novelty detector and the stationarity monitoring system were developed with experimental data provided by the Brazilian Navy.O som é uma onda mecânica que se propaga por grandes distâncias nos oceanos e, por essa razão, pode ser utilizado para a detecção e classificação de contatos em meios submarinos, tarefas básicas de um sistema sonar. O desenvolvimento de tais sistemas está diretamente ligado a defesa de um país com dimensões continentais, como o Brasil. Recentemente, a Marinha do Brasil definiu como prioridade estratégica a área de acústica submarina. Sistemas de sonar passivo podem ser instalados para monitorar a costa brasileira de maneira furtiva e eficiente. Ademais, estes são utilizados em submarinos militares para diferentes aplicações. Como neste ambiente de operação, cada navio possui uma assinatura acústica única, e navios cujos dados não foram adquiridos podem ser observados, faz-se necessário o desenvolvimento de um detector de novidade operando em conjunto com os classificadores de contatos implementados em sistemas da Marinha do Brasil. Como os classificadores operam competindo por recursos computacionais com os detectores de novidade, estes podem impactar na eficiência de classificação. A quantidade de classes, neste ambiente, ´e muito grande e, devido a isso, índices de desempenho específicos foram criados para avaliar a eficiência dos modelos desenvolvidos. Além disso, diferentes extratores de informação foram desenvolvidos para acessar informações relevantes dos navios em questão, dentre eles podem ser citados PCD, kPCA, NLPCA e SAE. O desenvolvimento deste modelo de detecção foi baseado no ambiente de operação da Marinha do Brasil e, como este pode ter suas condições operativas alteradas ao longo do tempo, um sistema de monitoramento da estacionaridade baseado em estatística de ordem superior foi proposto. Tanto o detector de novidade quanto o sistema de monitoramento de estacionaridade foram desenvolvidos com dados experimentais disponibilizados pela Marinha do Brasil