Simulation and analysis of measurement techniques for the fast acquisition of head-related transfer functions

DFG, 174776315, FOR 1557: Simulation and Evaluation of Acoustical Environments (SEACEN

Beiträge zu breitbandigen Freisprechsystemen und ihrer Evaluation

This work deals with the advancement of wideband hands-free systems (HFS’s) for mono- and stereophonic cases of application. Furthermore, innovative contributions to the corr. field of quality evaluation are made. The proposed HFS approaches are based on frequency-domain adaptive filtering for system identification, making use of Kalman theory and state-space modeling. Functional enhancement modules are developed in this work, which improve one or more of key quality aspects, aiming at not to harm others. In so doing, these modules can be combined in a flexible way, dependent on the needs at hand. The enhanced monophonic HFS is evaluated according to automotive ITU-T recommendations, to prove its customized efficacy. Furthermore, a novel methodology and techn. framework are introduced in this work to improve the prototyping and evaluation process of automotive HF and in-car-communication (ICC) systems. The monophonic HFS in several configurations hereby acts as device under test (DUT) and is thoroughly investigated, which will show the DUT’s satisfying performance, as well as the advantages of the proposed development process. As current methods for the evaluation of HFS’s in dynamic conditions oftentimes still lack flexibility, reproducibility, and accuracy, this work introduces “Car in a Box” (CiaB) as a novel, improved system for this demanding task. It is able to enhance the development process by performing high-resolution system identification of dynamic electro-acoustical systems. The extracted dyn. impulse response trajectories are then applicable to arbitrary input signals in a synthesis operation. A realistic dynamic automotive auralization of a car cabin interior is available for HFS evaluation. It is shown that this system improves evaluation flexibility at guaranteed reproducibility. In addition, the accuracy of evaluation methods can be increased by having access to exact, realistic imp. resp. trajectories acting as a so-called “ground truth” reference. If CiaB is included into an automotive evaluation setup, there is no need for an acoustical car interior prototype to be present at this stage of development. Hency, CiaB may ease the HFS development process. Dynamic acoustic replicas may be provided including an arbitrary number of acoustic car cabin interiors for multiple developers simultaneously. With CiaB, speech enh. system developers therefore have an evaluation environment at hand, which can adequately replace the real environment.Diese Arbeit beschäftigt sich mit der Weiterentwicklung breitbandiger Freisprechsysteme für mono-/stereophone Anwendungsfälle und liefert innovative Beiträge zu deren Qualitätsmessung. Die vorgestellten Verfahren basieren auf im Frequenzbereich adaptierenden Algorithmen zur Systemidentifikation gemäß Kalman-Theorie in einer Zustandsraumdarstellung. Es werden funktionale Erweiterungsmodule dahingehend entwickelt, dass mindestens eine Qualitätsanforderung verbessert wird, ohne andere eklatant zu verletzen. Diese nach Anforderung flexibel kombinierbaren algorithmischen Erweiterungen werden gemäß Empfehlungen der ITU-T (Rec. P.1110/P.1130) in vorwiegend automotiven Testszenarien getestet und somit deren zielgerichtete Wirksamkeit bestätigt. Es wird eine Methodensammlung und ein technisches System zur verbesserten Prototypentwicklung/Evaluation von automotiven Freisprech- und Innenraumkommunikationssystemen vorgestellt und beispielhaft mit dem monophonen Freisprechsystem in diversen Ausbaustufen zur Anwendung gebracht. Daraus entstehende Vorteile im Entwicklungs- und Testprozess von Sprachverbesserungssystem werden dargelegt und messtechnisch verifiziert. Bestehende Messverfahren zum Verhalten von Freisprechsystemen in zeitvarianten Umgebungen zeigten bisher oft nur ein unzureichendes Maß an Flexibilität, Reproduzierbarkeit und Genauigkeit. Daher wird hier das „Car in a Box“-Verfahren (CiaB) entwickelt und vorgestellt, mit dem zeitvariante elektro-akustische Systeme technisch identifiziert werden können. So gewonnene dynamische Impulsantworten können im Labor in einer Syntheseoperation auf beliebige Eingangsignale angewandt werden, um realistische Testsignale unter dyn. Bedingungen zu erzeugen. Bei diesem Vorgehen wird ein hohes Maß an Flexibilität bei garantierter Reproduzierbarkeit erlangt. Es wird gezeigt, dass die Genauigkeit von darauf basierenden Evaluationsverfahren zudem gesteigert werden kann, da mit dem Vorliegen von exakten, realen Impulsantworten zu jedem Zeitpunkt der Messung eine sogenannte „ground truth“ als Referenz zur Verfügung steht. Bei der Einbindung von CiaB in einen Messaufbau für automotive Freisprechsysteme ist es bedeutsam, dass zu diesem Zeitpunkt das eigentliche Fahrzeug nicht mehr benötigt wird. Es wird gezeigt, dass eine dyn. Fahrzeugakustikumgebung, wie sie im Entwicklungsprozess von automotiven Sprachverbesserungsalgorithmen benötigt wird, in beliebiger Anzahl vollständig und mind. gleichwertig durch CiaB ersetzt werden kann

Partial update blind adaptive channel shortening algorithms for wireline multicarrier systems

In wireline multicarrier systems a cyclic prefix is generally used to facilitate simple channel equalization at the receiver. The choice of the length of the cyclic prefix is a trade-off between maximizing the length of the channel for which inter-symbol interference is eliminated and optimizing the transmission efficiency. When the length of the channel is greater than the cyclic prefix, adaptive channel shorteners can be used to force the effective channel length of the combined channel and channel shortener to be within the cyclic prefix constraint. The focus of this thesis is the design of new blind adaptive time-domain channel shortening algorithms with good convergence properties and low computational complexity. An overview of the previous work in the field of supervised partial update adaptive filtering is given. The concept of property-restoral based blind channel shortening algorithms is then introduced together with the main techniques within this class of adaptive filters. Two new partial update blind (unsupervised) adaptive channel shortening algorithms are therefore introduced with robustness to impulsive noise commonly present in wireline multicarrier systems. Two further blind channel shortening algorithms are proposed in which the set of coefficients which is updated at each iteration of the algorithm is chosen deterministically. One of which, the partial up-date single lag autocorrelation maximization (PUSLAM) algorithm is particularly attractive due to its low computational complexity. The interaction between the receiver matched filter and the channel shortener is considered in the context of a multi-input single-output environment. To mitigate the possibility of ill-convergence with the PUSLAM algorithm an entirely new random PUSLAM (RPUSLAM) algorithm is proposed in which randomness is introduced both into the lag selection of the cost function underlying SLAM and the selection of the particular set of coefficients updated at each algorithm. This algorithm benefits from robust convergence properties whilst retaining relatively low computational complexity. All algorithms developed within the thesis are supported by evaluation on a set of eight carrier serving area test loop channels.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Partial update blind adaptive channel shortening algorithms for wireline multicarrier systems.

In wireline multicarrier systems a cyclic prefix is generally used to facilitate simple channel equalization at the receiver. The choice of the length of the cyclic prefix is a trade-off between maximizing the length of the channel for which inter-symbol interference is eliminated and optimizing the transmission efficiency. When the length of the channel is greater than the cyclic prefix, adaptive channel shorteners can be used to force the effective channel length of the combined channel and channel shortener to be within the cyclic prefix constraint. The focus of this thesis is the design of new blind adaptive time-domain channel shortening algorithms with good convergence properties and low computational complexity. An overview of the previous work in the field of supervised partial update adaptive filtering is given. The concept of property-restoral based blind channel shortening algorithms is then introduced together with the main techniques within this class of adaptive filters. Two new partial update blind (unsupervised) adaptive channel shortening algorithms are therefore introduced with robustness to impulsive noise commonly present in wireline multicarrier systems. Two further blind channel shortening algorithms are proposed in which the set of coefficients which is updated at each iteration of the algorithm is chosen deterministically. One of which, the partial up-date single lag autocorrelation maximization (PUSLAM) algorithm is particularly attractive due to its low computational complexity. The interaction between the receiver matched filter and the channel shortener is considered in the context of a multi-input single-output environment. To mitigate the possibility of ill-convergence with the PUSLAM algorithm an entirely new random PUSLAM (RPUSLAM) algorithm is proposed in which randomness is introduced both into the lag selection of the cost function underlying SLAM and the selection of the particular set of coefficients updated at each algorithm. This algorithm benefits from robust convergence properties whilst retaining relatively low computational complexity. All algorithms developed within the thesis are supported by evaluation on a set of eight carrier serving area test loop channels

Signal processing techniques for enhancement of defect detection in ultrasonic guided waves inspection of pipelines

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University Londonpipelines are the main means of transferring oil and gas. In order to avoid failure, they require regular inspection to locate defects and repair them accordingly. Ultrasonic guided waves (UGW) allows long-range inspection of pipelines from one test point. Determining the location of defects is a challenging and manual process. The main aim of this thesis is to develop novel signal processing algorithms for enhancement of data interpretation of UGW tests. The first step of this thesis was to investigate the operation of the device and the existing sources of noise from the literature. Afterward, based on the literature, three different methods were investigated for approaching the inspection problem of UGW. The first one was to utilize the individual signals from the transducer array to develop a defect identification algorithm. Detection of defects was done based on the spatial differences in the received signals from each time sample. The second was to change the current processing algorithm of the device, in order to enhance the SNR of the results; therefore, an adaptive filtering algorithm was implemented in order to remove significant amount of coherent noise from the tests. The third method was to use the power spectrum to develop a defect identification algorithm; Hence, an algorithm was developed that allowed detection of defects based on a comparison between the power spectrum of the reference signal with the one gathered from each time sample of the results. All of the aforementioned algorithms were validated using simulated data generated by a finite element model as well as experimental trials on real pipes. It was demonstrated that not only the algorithms are capable of enhancing the defect detection, but also the current signal processing routine of the device can be modified to produce better results

Mathematics and Digital Signal Processing

Modern computer technology has opened up new opportunities for the development of digital signal processing methods. The applications of digital signal processing have expanded significantly and today include audio and speech processing, sonar, radar, and other sensor array processing, spectral density estimation, statistical signal processing, digital image processing, signal processing for telecommunications, control systems, biomedical engineering, and seismology, among others. This Special Issue is aimed at wide coverage of the problems of digital signal processing, from mathematical modeling to the implementation of problem-oriented systems. The basis of digital signal processing is digital filtering. Wavelet analysis implements multiscale signal processing and is used to solve applied problems of de-noising and compression. Processing of visual information, including image and video processing and pattern recognition, is actively used in robotic systems and industrial processes control today. Improving digital signal processing circuits and developing new signal processing systems can improve the technical characteristics of many digital devices. The development of new methods of artificial intelligence, including artificial neural networks and brain-computer interfaces, opens up new prospects for the creation of smart technology. This Special Issue contains the latest technological developments in mathematics and digital signal processing. The stated results are of interest to researchers in the field of applied mathematics and developers of modern digital signal processing systems

Design and implementation of adaptive baseband predistorter for OFDM nonlinear transmitter. Simulation and measurement of OFDM transmitter in presence of RF high power amplifier nonlinear distortion and the development of adaptive digital predistorters based on Hammerstein approach.

The objective of this research work is to investigate, design and measurement of a digital predistortion linearizer that is able to compensate the dynamic nonlinear distortion of a High Power Amplifier (PA). The effectiveness of the proposed baseband predistorter (PD) on the performance of a WLAN OFDM transmitter utilizing a nonlinear PA with memory effect is observed and discussed. For this purpose, a 10W Class-A/B power amplifier with a gain of 22 dB, operated over the 3.5 GHz frequency band was designed and implemented. The proposed baseband PD is independent of the operating RF frequency and can be used in multiband applications. Its operation is based on the Hammerstein system, taking into account PA memory effect compensation, and demonstrates a noticeable improvement compared to memoryless predistorters. Different types of modelling procedures and linearizers were introduced and investigated, in which accurate behavioural models of Radio Frequency (RF) PAs exhibiting linear and nonlinear memory effects were presented and considered, based on the Wiener approach employing a linear parametric estimation technique. Three new linear methods of parameter estimation were investigated, with the aim of reducing the complexity of the required filtering process in linear memory compensation. Moreover, an improved wiener model is represented to include the nonlinear memory effect in the system. The validity of the PA modelling approaches and predistortion techniques for compensation of nonlinearities of a PA were verified by several tests and measurements. The approaches presented, based on the Wiener system, have the capacity to deal with the existing trade-off between accuracy and convergence speed compared to more computationally complex behavioural modelling algorithms considering memory effects, such as those based on Volterra series and Neural Networks. In addition, nonlinear and linear crosstalks introduced by the power amplifier nonlinear behaviour and antennas mutual coupling due to the compact size of a MIMO OFDM transmitter have been investigated