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Spectral refinement to speech enhancementUnknown Date (has links)
The goal of a speech enhancement algorithm is to remove noise and recover the original signal with as little distortion and residual noise as possible. Most successful real-time algorithms thereof have done in the frequency domain where the frequency amplitude of clean speech is estimated per short-time frame of the noisy signal. The state of-the-art short-time spectral amplitude estimator algorithms estimate the clean spectral amplitude in terms of the power spectral density (PSD) function of the noisy signal. The PSD has to be computed from a large ensemble of signal realizations. However, in practice, it may only be estimated from a finite-length sample of a single realization of the signal. Estimation errors introduced by these limitations deviate the solution from the optimal. Various spectral estimation techniques, many with added spectral smoothing, have been investigated for decades to reduce the estimation errors. These algorithms do not address significantly issue on quality of speech as perceived by a human. This dissertation presents analysis and techniques that offer spectral refinements toward speech enhancement. We present an analytical framework of the effect of spectral estimate variance on the performance of speech enhancement. We use the variance quality factor (VQF) as a quantitative measure of estimated spectra. We show that reducing the spectral estimator VQF reduces significantly the VQF of the enhanced speech. The Autoregressive Multitaper (ARMT) spectral estimate is proposed as a low VQF spectral estimator for use in speech enhancement algorithms. An innovative method of incorporating a speech production model using multiband excitation is also presented as a technique to emphasize the harmonic components of the glottal speech input. / The preconditioning of the noisy estimates by exploiting other avenues of information, such as pitch estimation and the speech production model, effectively increases the localized narrow-band signal-to noise ratio (SNR) of the noisy signal, which is subsequently denoised by the amplitude gain. Combined with voicing structure enhancement, the ARMT spectral estimate delivers enhanced speech with sound clarity desirable to human listeners. The resulting improvements in enhanced speech are observed to be significant with both Objective and Subjective measurement. / by Werayuth Charoenruengkit. / Vita. / Thesis (Ph.D.)--Florida Atlantic University, 2009. / Includes bibliography. / Electronic reproduction. Boca Raton, Fla., 2009. Mode of access: World Wide Web.
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Automated Launch and Recovery of an Autonomous Underwater Vehicle from an Unmanned Surface VesselUnknown Date (has links)
Research on collaboration among unmanned platforms is essential to improve the applications for autonomous missions, by expanding the working environment of the robotic systems, and reducing the risks and the costs associated with conducting manned operations. This research is devoted to enable the collaboration between an Unmanned Surface Vehicle (USV) and an Autonomous Underwater Vehicle (AUV), by allowing the first one to launch and recover the second one. The objective of this dissertation is to identify possible methods to launch and recover a REMUS 100 AUV from a WAM-V 16 USV, thus developing this capability by designing and implementing a launch and recovery system (LARS). To meet this objective, a series of preliminary experiments was first performed to identify two distinct methods to launch and recover the AUV: mobile and semi-stationary. Both methods have been simulated using the Orcaflex software. Subsequently, the necessary control systems to create the mandatory USV autonomy for the purpose of launch and recovery were developed. Specifically, a series of low-level controllers were designed and implemented to enable two autonomous maneuvers on the USV: station-keeping and speed & heading control. In addition, a level of intelligence to autonomously identify the optimal operating conditions within the vehicles' working environment, was derived and integrated on the USV. Lastly, a LARS was designed and implemented on the vehicles to perform the operation following the proposed methodology. The LARS and all subsystems developed for this research were extensively tested through sea-trials. The methodology for launch and recovery, the design of the LARS and the experimental findings are reported in this document. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2016. / FAU Electronic Theses and Dissertations Collection
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A high-level fuzzy logic guidance system for an unmanned surface vehicle (USV) tasked to perform an autonomous launch and recovery (ALR) of an unmanned underwater vehicle (UUV)Unknown Date (has links)
There have been much technological advances and research in Unmanned Surface
Vehicles (USV) as a support and delivery platform for Autonomous/Unmanned
Underwater Vehicles (AUV/UUV). Advantages include extending underwater search and
survey operations time and reach, improving underwater positioning and mission
awareness, in addition to minimizing the costs and risks associated with similar manned
vessel operations. The objective of this thesis is to present the design and development a
high-level fuzzy logic guidance controller for a WAM-V 14 USV in order to
autonomously launch and recover a REMUS 100 AUV. The approach to meeting this objective is to develop ability for the USV to intercept and rendezvous with an AUV that is in transit in order to maximize the probability of a final mobile docking maneuver. Specifically, a fuzzy logic Rendezvous Docking controller has been developed that generates Waypoint-Heading goals for the USV to minimize the cross-track errors between the USV and AUV. A subsequent fuzzy
logic Waypoint-Heading controller has been developed to provide the desired heading
and speed commands to the low-level controller given the Waypoint-Heading goals.
High-level mission control has been extensively simulated using Matlab and partially
characterized in real-time during testing. Detailed simulation, experimental results and
findings will be reported in this paper. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2014. / FAU Electronic Theses and Dissertations Collection
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Modelling, information capacity, and estimation of time-varying channels in mobile communication systemsSadeghi, Parastoo, School of Electrical Engineering And Telecommunications, UNSW January 2006 (has links)
In the first part of this thesis, the information capacity of time-varying fading channels is analysed using finite-state Markov channel (FSMC) models. Both fading channel amplitude and fading channel phase are modelled as finite-state Markov processes. The effect of the number of fading channel gain partitions on the capacity is studied (from 2 to 128 partitions). It is observed that the FSMC capacity is saturated when the number of fading channel gain partitions is larger than 4 to 8 times the number of channel input levels. The rapid FSMC capacity saturation with a small number of fading channel gain partitions can be used for the design of computationally simple receivers, with a negligible loss in the capacity. Furthermore, the effect of fading channel memory order on the capacity is studied (from first- to fourth-order). It is observed that low-order FSMC models can provide higher capacity estimates for fading channels than high-order FSMC models, especially when channel states are poorly observable in the presence of channel noise. To explain the effect of memory order on the FSMC capacity, the capacities of high-order and low-order FSMC models are analytically compared. It is shown that the capacity difference is caused by two factors: 1) the channel entropy difference, and 2) the channel observability difference between the high-order and low-order FSMC models. Due to the existence of the second factor, the capacity of high-order FSMC models can be lower than the capacity of low-order FSMC models. Two sufficient conditions are proven to predict when the low-order FSMC capacity is higher or lower than the high-order FSMC capacity. In the second part of this thesis, a new implicit (blind) channel estimation method in time- varying fading channels is proposed. The information source emits bits ???0??? and ???1??? with unequal probabilities. The unbalanced source distribution is used as a priori known signal structure at the receiver for channel estimation. Compared to pilot-symbol-assisted channel estimation, the proposed channel estimation technique can achieve a superior receiver bit error rate performance, especially at low signal to noise ratio conditions.
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Active Noise Control in Forest MachinesForsgren, Fredrik January 2011 (has links)
Achieving a low noise level is of great interest to the forest machine industry. Traditionally this is obtained by using passive noise reduction, i.e. by using materials for sound isolation and sound absorption. Especially designs to attenuate low frequency noise tend to be bulky and impractical from an installation point of view. An alternative solution to the problem is to use active noise control (ANC). The basic principle of ANC is to generate an anti-noise signal designed to destructively interfere with the unwanted noise. In this thesis two algorithms (Feedback FxLMS and Feedforward FxLMS) are implemented and evaluated for use in the ANC-system. The ANC-system is tuned to the specific environment in the driver’s cabin of a Komatsu forest machine. The algorithms are first tested in a simulated environment and then in real-time inside a forest machine. Simulations are made both in Matlab and in C using both generated signals and recorded signals. The C code is implemented on the Analog Devices Blackfin DSP card BF526. The result showed a significantly reduction of the sound pressure level (SPL) in the driver’s cabin. The noise attenuation obtained using the Feedback FxLMS was approximately 14 dB for a tonal 100 Hz signal and 11 dB using recorded engine noise from a forest machine at 850 rpm.
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Modelling, information capacity, and estimation of time-varying channels in mobile communication systemsSadeghi, Parastoo, School of Electrical Engineering And Telecommunications, UNSW January 2006 (has links)
In the first part of this thesis, the information capacity of time-varying fading channels is analysed using finite-state Markov channel (FSMC) models. Both fading channel amplitude and fading channel phase are modelled as finite-state Markov processes. The effect of the number of fading channel gain partitions on the capacity is studied (from 2 to 128 partitions). It is observed that the FSMC capacity is saturated when the number of fading channel gain partitions is larger than 4 to 8 times the number of channel input levels. The rapid FSMC capacity saturation with a small number of fading channel gain partitions can be used for the design of computationally simple receivers, with a negligible loss in the capacity. Furthermore, the effect of fading channel memory order on the capacity is studied (from first- to fourth-order). It is observed that low-order FSMC models can provide higher capacity estimates for fading channels than high-order FSMC models, especially when channel states are poorly observable in the presence of channel noise. To explain the effect of memory order on the FSMC capacity, the capacities of high-order and low-order FSMC models are analytically compared. It is shown that the capacity difference is caused by two factors: 1) the channel entropy difference, and 2) the channel observability difference between the high-order and low-order FSMC models. Due to the existence of the second factor, the capacity of high-order FSMC models can be lower than the capacity of low-order FSMC models. Two sufficient conditions are proven to predict when the low-order FSMC capacity is higher or lower than the high-order FSMC capacity. In the second part of this thesis, a new implicit (blind) channel estimation method in time- varying fading channels is proposed. The information source emits bits ???0??? and ???1??? with unequal probabilities. The unbalanced source distribution is used as a priori known signal structure at the receiver for channel estimation. Compared to pilot-symbol-assisted channel estimation, the proposed channel estimation technique can achieve a superior receiver bit error rate performance, especially at low signal to noise ratio conditions.
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Novas tecnicas de processamento espaço-temporal em transmissão conciliando diversidade e beamforming / New methods for transmit space-time processing combining diversity and beamformingZanatta Filho, Danilo 11 January 2006 (has links)
Orientador: João Marcos Travassos Romano / Tese (doutorado) - Universidade Estadual de Campinas. Faculdade de Engenharia Eletrica e de Computação / Made available in DSpace on 2018-08-07T23:30:42Z (GMT). No. of bitstreams: 1
ZanattaFilho_Danilo_D.pdf: 1987916 bytes, checksum: be6038a70235bda4b62a193a0296ffb7 (MD5)
Previous issue date: 2006 / Resumo: O presente trabalho trata da utilização, em transmissão, de um arranjo de antenas na estação rádio-base de um sistema de comunicação celular. Na recepção, as soluções para explorar o arranjo são atualmente bem estabelecidas na literatura. Por outro lado, na transmissão, o problema se mantém aberto. Duas abordagens são possíveis: explorar o arranjo de antenas em beamforming ou em diversidade. Essas duas abordagens se opõem pelas hipóteses sobre a correlação dos canais, o que implica um maior ou menor espaçamento entre as antenas, de acordo com o ambiente de propagação. Na prática, essas hipóteses são muito difíceis de se respeitar. Nesta dissertação, pretendemos tratar esta questão na sua globalidade, conciliando diversidade e beamforming para melhor explorar o arranjo de antenas. Consideramos o contexto monousuário, assim como o caso multiusuário. No caso monousuário, propomos uma estrutura de transmissão composta por uma técnica de diversidade de transmissão clássica aplicada a antenas virtuais diretivas e idealmente independentes. Essas antenas virtuais são fabricadas por meio de filtros puramente espaciais aplicados às antenas reais. O conjunto desses filtros é chamado precoder e se intercala entre a diversidade de transmissão e o arranjo de antenas utilizado em transmissão. Esse precoder desempenha um duplo papel, o de realizar o beamforming e o de criar a diversidade por meio de antenas virtuais idealmente independentes, conciliando assim diversidade de transmissão e beamforming em transmissão. Duas abordagens são propostas para se obter o precoder , uma baseada na minimização da variância da potência recebida pelo móvel e a segunda baseada diretamente na minimização da taxa de erro. Comparadas às técnicas clássicas, as novas técnicas apresentam melhores desempenhos. Em seguida, propomos uma extensão dessa estrutura ao contexto multiusuário, para o qual técnicas de diversidade de transmissão ainda não foram propostas na literatura. Propomos a adaptação conjunta dos precoders, buscando minimizar a potência total de transmissão, respeitando as BERs alvo dos usuários. De maneira análoga ao caso monousuário, os precoders permitem conciliar beamforming e diversidade de transmissão. Comparada às técnicas clássicas de beamforming multiusuário, a nova abordagem introduz diversidade de transmissão ao enlace, apresentando melhores desempenhos / Abstract: This work deals with the use of an antenna array at the base station of a mobile communication system for transmission. In reception, solutions that exploit the antenna array are now well established. In transmission, however, the problem remains open. Two approaches are possible: exploit the array by using beamforming techniques or by using diversity techniques. These two approaches are based on opposing assumptions about the channels correlation, which implies a greater or smaller distance between antennas, depending on the environment. In practice, these assumptions are not verified. Here, we aim to deal with the problem as a whole for better exploiting the antenna array. This work treats the single-user case, as well as the multiuser scenario. In the single-user case, we propose a transmission scheme composed of a classical transmit diversity technique applied to virtual antennas, which are directive and ideally independent. These virtual antennas are produced by means of purely spatial filters applied to the real antennas. This set of filters is called precoder, and acts as the interface between the transmit diversity technique and the transmit antenna array. The precoder function is twofold; to beamform the transmit signal, and to create diversity by means of ideally independent virtual antennas, thus combining transmit diversity and transmit beamforming. We propose two approaches to obtain this precoder, one based on the minimization of the variance of the received power at the mobile, and the other directly based on the minimization of the error rate. Compared to more classical approaches, the performance of the new methods reveals their advantage. Then, we extend this scheme to a multiuser context, for which transmit diversity techniques have not yet been developed. We propose to jointly adapt the precoders by minimizing the total transmit power while satisfying the users¿ target BER. Similarly to the single-user case, the precoders allow to combine beamforming and transmit diversity. Compared to classical multiuser beamforming techniques, the new approach adds diversity to the link and obtains in return better performances / Doutorado / Telecomunicações e Telemática / Doutor em Engenharia Elétrica
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The development and application of random matrix theory in adaptive signal processing in the sample deficient regimePajovic, Milutin January 2014 (has links)
Thesis: Ph. D., Joint Program in Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science; and the Woods Hole Oceanographic Institution), 2014. / This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. / Cataloged from student-submitted PDF version of thesis. / Includes bibliographical references (pages 237-243). / This thesis studies the problems associated with adaptive signal processing in the sample deficient regime using random matrix theory. The scenarios in which the sample deficient regime arises include, among others, the cases where the number of observations available in a period over which the channel can be approximated as time-invariant is limited (wireless communications), the number of available observations is limited by the measurement process (medical applications), or the number of unknown coefficients is large compared to the number of observations (modern sonar and radar systems). Random matrix theory, which studies how different encodings of eigenvalues and eigenvectors of a random matrix behave, provides suitable tools for analyzing how the statistics estimated from a limited data set behave with respect to their ensemble counterparts. The applications of adaptive signal processing considered in the thesis are (1) adaptive beamforming for spatial spectrum estimation, (2) tracking of time-varying channels and (3) equalization of time-varying communication channels. The thesis analyzes the performance of the considered adaptive processors when operating in the deficient sample support regime. In addition, it gains insights into behavior of different estimators based on the estimated second order statistics of the data originating from time-varying environment. Finally, it studies how to optimize the adaptive processors and algorithms so as to account for deficient sample support and improve the performance. In particular, random matrix quantities needed for the analysis are characterized in the first part. In the second part, the thesis studies the problem of regularization in the form of diagonal loading for two conventionally used spatial power spectrum estimators based on adaptive beamforming, and shows the asymptotic properties of the estimators, studies how the optimal diagonal loading behaves and compares the estimators on the grounds of performance and sensitivity to optimal diagonal loading. In the third part, the performance of the least squares based channel tracking algorithm is analyzed, and several practical insights are obtained. Finally, the performance of multi-channel decision feedback equalizers in time-varying channels is characterized, and insights concerning the optimal selection of the number of sensors, their separation and constituent filter lengths are presented. / by Milutin Pajovic. / Ph. D.
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Investigation of Coherent Reflections in GNSS-R using CYGNSSLoria, Eric Andrew 13 November 2020 (has links)
No description available.
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Combined spatial diversity and time equalization for broadband multiple channel underwater acoustic communicationsUnknown Date (has links)
High data rate acoustic communications become feasible with the use of communication systems that operate at high frequency. The high frequency acoustic transmission in shallow water endures severe distortion as a result of the extensive intersymbol interference and Doppler shift, caused by the time variable multipath nature of the channel. In this research a Single Input Multiple Output (SIMO) acoustic communication system is developed to improve the reliability of the high data rate communications at short range in the shallow water acoustic channel. The proposed SIMO communication system operates at very high frequency and combines spatial diversity and decision feedback equalizer in a multilevel adaptive configuration. The first configuration performs selective combining on the equalized signals from multiple receivers and generates quality feedback parameter for the next level of combining. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2015. / FAU Electronic Theses and Dissertations Collection
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