A rise in interest for service robotic rovers produces a need for a low-cost method for source localization in order for a prospective robotic unit to engage with a human operator. This study examines the use of the LMS algorithm for constructing a beamformer using an optimized Weiner filter solution for this source localization application and evaluates the robustness of a developed characterization method for assuring that a proper approximation for the desired signal is achieved. The method presented in this paper encompasses using a filter and sum method in which the sums are generated for a selected set of filter angles, and this set of sums are compared and characterized to produce a selection for an approximate arrival angle from the sound source to the microphone array. These filters are adaptively trained offline using a generated desired signal chirp to represent the average human whistle and a training data set for each of the four possible room configurations. This method was tested to determine if a selected filter configuration could still produce viable outputs for scenarios in which the testing room had been changed, whether noise was injected into the testing environment, if two or three microphones were used in testing process, and whether the filter angles are aligned with the arrival angles of the signal. Results on the robustness of the adaptive LMS beamformer are presented. Limitations of the system performance are discussed and possible solutions for results that have undesired performance are given in future work. / Master of Science

A radio direction finding (DF) system uses a multiple-element antenna array coupled with one or more receivers to estimate the direction-of-arrival (DOA) of a targeted emitter using characteristics of the signal received at each of the antennas in the array. In general, DF systems can be classified both by the number of receivers employed as well as which characteristics of the received signal are used to produce the DOA estimate, such as the signal's amplitude, phase, or time of arrival. This work centers on the development and implementation of a novel single-channel direction finding system based on the differential phase of the target signal received by a uniform circular antenna array with a commutative switch. The algorithm is called the PLL DF Method and differs from older single-channel DF techniques in that it is a digital algorithm intended for implementation on a software-defined radio (SDR) platform with a custom-designed antenna array and RF switching network. It uses a bank of parallel software PLLs to estimate the phase of the signal received at each element of the multi-antenna array. Theses estimated phase values are then fed to a specialized signal processing block that estimates the DOA of the received signal. This thesis presents the details of the initial version of the PLL algorithm which was used to produce a proof-of-concept system with an eight-element circular array. It then discusses various technical challenges uncovered in the initial implementation and presents numerous enhancements to the algorithm to overcome these challenges, such as a modification to the PLL model to offer increased estimator robustness in the presence of a frequency offset between the transmitter and receiver, revisions of the software implementation to reduce the algorithm's processing requirements, and the adaptation of the DF algorithm for use with a 16-element circular array. The performance of the algorithm with these modifications under various conditions are simulated to investigate their impact on the DOA estimation process and the results of their implementation on an SDR are considered. / Master of Science

This thesis describes the challenges involved in detecting sources of acoustic noise using an autonomous underwater vehicle (AUV) in real world environments. The initial part of this thesis describes the developments made for redesigning an acoustic sensing system that can be used to estimate the relative bearing between a source of acoustic noise and an AUV. With an estimate of the relative bearing, the AUV can maneuver toward the source of noise. The class of algorithms that are used to estimate bearing angle are known as beamforming algorithms. A comparison of the performance of a variety of beamforming algorithms is presented. When estimating the bearing to a source of noise from a small AUV, the noise of the AUV, especially its propulsor, pose significant challenges. Toward the goal of active cancellation of AUV self-noise, we propose placing an additional hydrophone inside the AUV in order to estimate the AUV self-noise that appears on the exterior hydrophones that are used for bearing estimation. / Master of Science / A real world application using an autonomous underwater vehicle (AUV) is presented in this thesis. The application deals with detecting and estimating the relative location (bearing angle) between sources of acoustic noise and the AUV. The thesis starts by describing design changes made to target data sensing system inside the AUV for collecting and estimating the bearing angle. The estimation of bearing angle is done with a class of algorithms called beamforming algorithms whose performance comparison is presented on real world data. Operating the AUV propulsor yields inaccurate bearing angle estimations and thus presents a huge challenge for bearing estimation. We propose measuring AUV self-noise using additional sensors to move towards the goal of cancelling AUV self-noise and recovering target signal for accurate bearing estimation.

Smart antenna systems are employed to overcome multipath fading, extend range, and increase capacity by using diversity or beamforming techniques in wireless communication systems. Understanding of the smart base antenna performance mechanisms for various environments is important to design cost effective systems and network. This dissertation focuses on the experimental characterization and modeling of the smart base station antenna performance for various propagation environment scenarios. An eight-channel Virginia Tech smart base station antenna testbed was developed to investigate performances of three reverse link diversity methods. The experiment campaign resulted in 245 sets of collected data over 83 measurement sites, which were used to compare the performance of space, polarization, and angle diversity under identical conditions. Measured propagation path loss, envelope correlation coefficients, power imbalances, and mean effective gain (MEG) are characterized as a function of distance between the base station and the mobile terminal to illustrate the diversity performance mechanisms over different propagation environments. The performance of the three base station diversity methods with selection combining (SC), maximal ratio combining (MRC), and equal gain combining (EGC) techniques for both urban and suburban non-line-of-sight (NLOS) environments are presented and summarized using the measured data. Forward-link performance of a twelve-fixed narrow-beam base station antenna system for urban NLOS environments is investigated using the same measured data. A new procedure is introduced to experimentally model the forward-link performance of muitlple-fixed narrow-beam (MFNB) antennas using the measured reverse-link vector channel response. The experimentally calculated lower bound performance result shows that it achieves 2.5 to 2.8 times higher average RF SIR compared to the conventional three-sector base station system for typical urban NLOS multipath fading environment conditions. Also, a new mobile user angle estimation algorithm using the muitlple-fixed narrow-beam antennas for NLOS multipath fading environment conditions is developed and the experiment results are presented. / Ph. D.

Wireless sensor networks has been one of the major research topics in recent years because of its great potential for a wide range of applications. In some application scenarios, sensor nodes intend to report the sensing data to a far-field destination, which cannot be realized by traditional transmission techniques. Due to the energy limitations and the hardware constraints of sensor nodes, distributed transmit beamforming is considered as an attractive candidate for long-range communications in such scenarios as it can reduce energy requirement of each sensor node and extend the communication range. However, unlike conventional beamforming, which is performed by a centralized antenna array, distributed beamforming is performed by a virtual antenna array composed of randomly located sensor nodes, each of which has an independent oscillator. Sensor nodes have to coordinate with each other and adjust their transmitting signals to collaboratively act as a distributed beamformer. The most crucial problem of realizing distributed beamforming is to achieve carrier phase alignment at the destination. This thesis will investigate distributed beamforming from both theoretical and practical aspects. First, the bit error ratio performance of distributed beamforming with phase errors is analyzed, which is a key metric to measure the system performance in practice. We derive two distinct expressions to approximate the error probability over Rayleigh fading channels corresponding to small numbers of nodes and large numbers of nodes respectively. The accuracy of both expressions is demonstrated by simulation results. The impact of phase errors on the system performance is examined for various numbers of nodes and different levels of transmit power. Second, a novel iterative algorithm is proposed to achieve carrier phase alignment at the destination in static channels, which only requires one-bit feedback from the destination. This algorithm is obtained by combining two novel schemes, both of which can greatly improve the convergence speed of phase alignment. The advantages in the convergence speed are obtained by exploiting the feedback information more efficiently compared to existing solutions. Third, the proposed phase alignment algorithm is modified to track time-varying channels. The modified algorithm has the ability to detect channel amplitude and phase changes that arise over time due to motion of the sensors or the destination. The algorithm can adjust key parameters adaptively according to the changes, which makes it more robust in practical implementation.

Time-Frequency (TF) masking is an audio processing technique useful for isolating an audio source from interfering sources. TF masking has been applied and studied in monaural and binaural applications, but has only recently been applied to distributed microphone arrays. This work focuses on evaluating the TF masking technique's ability to isolate human speech and improve speech intelligibility in an immersive "cocktail party" environment. In particular, an upper-bound on TF masking performance is established and compared to the traditional delay-sum and general sidelobe canceler (GSC) beamformers. Additionally, the novel technique of combining the GSC with TF masking is investigated and its performance evaluated. This work presents a resource-efficient method for studying the performance of these isolation techniques and evaluates their performance using both virtually simulated data and data recorded in a real-life acoustical environment. Further, methods are presented to analyze speech intelligibility post-processing, and automated objective intelligibility measurements are applied alongside informal subjective assessments to evaluate the performance of these processing techniques. Finally, the causes for subjective/objective intelligibility measurement disagreements are discussed, and it was shown that TF masking did enhance intelligibility beyond delay-sum beamforming and that the utilization of adaptive beamforming can be beneficial.

This thesis is about the researching for 5th generation (5G) communication system, which focus on the improvement of 3D beamforming technology in the antenna array using in the Full Dimension Multiple-Input Multiple-Output (FD-MIMO) system and Millimeter-wave (mm-wave) system. When the 3D beamforming technology has been used in 5G communication system, the beam needs a weighting matrix to direct the beam to cover the UEs, but some compromises should be considered. If the narrow beams are used to transmit signals, then more energy is focused in the desired direction, but this has a restricted coverage area to a single or few User Equipments (UEs). If the BS covers multiple UEs, then multiple beams need to be steered towards more groups of UEs, but there is more interference between these beams from their side lobes when they are transmitted at same time. These challenges are waiting to be solved, which are about interference between each beam when the 3D beamforming technology is used. Therefore, there needs to be one method to decrease the generated interference between each beam through directing the side lobe beams and nulls to minimize interference in the 3D beamforming system. Simultaneously, energy needs to be directed towards the desired direction. If it has been decided that one beam should covera cluster of UEs, then there will be a range of received Signal to Interference plus Noise Ratio (SINR) depending on the location of the UEs relative to the direction of the main beam. If the beam is directed towards a group of UEs then there needs be a clustering method to cluster the UEs. In order to cover multiple UEs, an improved K-means clustering algorithm is used to cluster the multiple UEs into different groups, which is based on the cosine distance. Itcan decrease the number of beams when multiple UEs need be covered by multiple beams at same time. Moreover, a new method has been developed to calculate the weighting matrix for beamforming. It can adjust the values of weighting matrix according to the UEs' location and direct the main beam in a desired direction whilst minimizing its side lobes in other undesired directions. Then the minimum side lobe beamforming system only needs to know the UEs' location and can be used to estimate the Channel State Information (CSI) of UEs. Therefore, the scheme also shows lower complexity when compared to the beamforming methods with pre-coding. In order to test the improved K-means clustering algorithm and the new weighting method that can enhance the performance for 3D beamforming system, the two simulation systems are simulated to show the results such as 3D beamforming LTE system and mm-wave system.

O estudo concentra-se na localização de fontes de ruídos em aeroacústica, através do processamento digital de sinais. O objetivo em aeroacústica é localizar fontes de ruído em estruturas aerodinâmicas (e.g.: aerofólios, slats, flaps e trens de pouso), motores e turbinas. Isto se faz possível utilizando arranjos de microfones, ou simplesmente arrays, cujos sinais são processados para localizar as fontes. Ao utilizar o beamforming clássico para processar os sinais vindos do array, este é incapaz de localizar as fontes de ruído de forma satisfatória. O 2D-ESPRIT é um método de alta resolução que é apresentado como alternativa. Nas simulações, é possível perceber que o 2D-ESPRIT tem melhor desempenho que o beamforming clássico, conseguindo localizar fontes próximas com arrays quadrados e com um número reduzido de amostras de sinal. / This study focuses on locating sources of noise in aeroacoustics, through digital signal processing. An objective in aeroacoustics is to locate sources of noise in aerodynamic structures (e.g.: airfoils, slats, flaps and landing gears), engines and fans. This is possible using microphone arrays, whose signals are processed to locate the sources. Using classical beamforming as the processing scheme for these signals, it is shown that it is incapable of locating sources satisfactorily in many of the practical scenarios. 2D-ESPRIT is a high resolution processing scheme that is presented as an alternative. Simulations show that 2D-ESPRIT outperfoms classical beamforming, locating closely positioned sources with the simple URA and with a reduced number of signal samples.

O estudo concentra-se na localização de fontes de ruídos em aeroacústica, através do processamento digital de sinais. O objetivo em aeroacústica é localizar fontes de ruído em estruturas aerodinâmicas (e.g.: aerofólios, slats, flaps e trens de pouso), motores e turbinas. Isto se faz possível utilizando arranjos de microfones, ou simplesmente arrays, cujos sinais são processados para localizar as fontes. Ao utilizar o beamforming clássico para processar os sinais vindos do array, este é incapaz de localizar as fontes de ruído de forma satisfatória. O 2D-ESPRIT é um método de alta resolução que é apresentado como alternativa. Nas simulações, é possível perceber que o 2D-ESPRIT tem melhor desempenho que o beamforming clássico, conseguindo localizar fontes próximas com arrays quadrados e com um número reduzido de amostras de sinal. / This study focuses on locating sources of noise in aeroacoustics, through digital signal processing. An objective in aeroacoustics is to locate sources of noise in aerodynamic structures (e.g.: airfoils, slats, flaps and landing gears), engines and fans. This is possible using microphone arrays, whose signals are processed to locate the sources. Using classical beamforming as the processing scheme for these signals, it is shown that it is incapable of locating sources satisfactorily in many of the practical scenarios. 2D-ESPRIT is a high resolution processing scheme that is presented as an alternative. Simulations show that 2D-ESPRIT outperfoms classical beamforming, locating closely positioned sources with the simple URA and with a reduced number of signal samples.

This thesis considers the design of a beamformer which can enhance desired signals in an environment consisting of broadband nearfield and/or farfield sources. The thesis contains: a formulation of a set of analysis tools which can provide insight into the intrinsic structure of array processing problems; a methodology for nearfield beamforming; theory and design of a general broadband beamformer; and a consideration of a coherent nearfield broadband adaptive beamforming problem. To a lesser extent, the source localization problem and background noise modeling are also treated. ¶: A set of analysis tools called modal analysis techniques which can be used to a solve wider class of array signal processing problems, is first formulated. The solution to the classical wave equation is studied in detail and exploited in order to develop these techniques. ¶: Three novel methods of designing a beamformer having a desired nearfield broadband beampattern are presented. The first method uses the modal analysis techniques to transform the desired nearfield beampattern to an equivalent farfield beampattern. A farfield beamformer is then designed for a transformed farfield beampattern which, if achieved, gives the desired nearfield pattern exactly. The second method establishes an asymptotic equivalence, up to complex conjugation, of two problems: (i) determining the nearfield performance of a farfield beampattern specification, and (ii) determining the equivalent farfield beampattern corresponding to a nearfield beampattern specification. Using this reciprocity relationship a computationally simple nearfield beamforming procedure is developed. The third method uses the modal analysis techniques to find a linear transformation between the array weights required to have the desired beampattern for farfield and nearfield, respectively. ¶: An efficient parameterization for the general broadband beamforming problem is introduced with a single parameter to focus the beamformer to a desired operating radius and another set of parameters to control the actual broadband beampattern shape. This parameterization is derived using the modal analysis techniques and the concept of the theoretical continuous aperture. ¶: A design of an adaptive beamformer to operate in a signal environment consisting of broadband nearfield sources, where some of interfering signals may be correlated with desired signal is also considered. Application of modal analysis techniques to noise modeling and broadband coherent source localization conclude the thesis.