No description available.

No description available.

Sensor arrays are used in many applications where their ability to localize signal sources is essential. For many applications, it is necessary to estimate the direction-of-arrival (DOA) of target sources. Although there are many DOA estimation methods available, most of them are valid only for narrowband signals where time delay can be approximated as a phase shift. This thesis focuses on DOA estimation algorithms for wideband sources. Specifically, this thesis proposes the pruned fast beamformer which can reduce the number of computations of Delay-and-Sum (DS) beamforming by using a multi-resolution structure. For high resolution methods, signal subspace methods are required. Most of the subspace techniques for wideband signals decompose the received wideband signals into several bands of narrowband signals through bandpass filtering. Then, there are two different ways of processing decomposed signals. The incoherent methods process each band independently by a given narrowband method and average the results. The coherent methods attempt to modulate the signals in each band so that they can be combined coherently. In this thesis, a new DOA estimator, which is called TOPS, is developed to avoid disadvantages of both the incoherent and the coherent methods. The new method which can be categorized as a non-coherent method is tested and compared with other methods. It exhibits many desirable features for a number of applications where the sources are wideband such as acoustic direction finding.

Recent years have brought many new developments in the processing of speech and acoustic signals. Yet, despite this, the process of acquiring signals has gone largely unchanged. Adding spatial diversity to the repertoire of signal acquisition has long been known to offer advantages for processing signals further. The processing capabilities of mobile devices had not previously been able to handle the required computation to handle these previous streams of information. But current processing capabilities are such that the extra workload introduced by the addition of mutiple sensors on a mobile device are not over-burdensome. How these extra data streams can best be handled is still an open question. The present work deals with the examination of one type of spatial processing technique, known as beamforming. A microphone array test platform is constructed and verified through a number of beamforming agorithms. Issues related to speech acquisition through microphones arrays are discussed. The algorithms used for verification are presented in detail and compared to one another.

This work introduces new binaural beamforming algorithms for hearing aids, with a robustness to errors in the estimate of the target speaker direction of arrival (DOA) and a good trade-off between noise reduction and preservation of the noise/interferers spatial impression. Three robust designs are proposed, and their robustness is confirmed by simulation results. These robust designs are a combination of binaural and monaural beamformers using two different microphone configurations: one for low frequency components and one for high frequency components. The robust designs are also found to be robust to mismatch between the anechoic propagation models used for the beamformers designs and the reverberant propagation models used to generate the signals at the microphones in the simulations. To preserve the binaural cues of the noise/interferers in the binaural beamformer outputs, a method based on a mixing/selection of different available binaural signals is proposed, using a classification from the phase and magnitude of a complex coherence function. This method is added as a post processor to the beamforming designs robust to target DOA mismatch. Simulation results show that the resulting mixed binaural output signals have a good binaural cues preservation level that outperform the benchmark design, with significant noise reduction and low target distortion. Since knowledge of source DOAs is important for beamforming noise reduction, a beamformer-based broadband multi-source DOA detection system is also developed in the thesis, using information from different frequencies or sub‐bands to obtain global estimates of sources DOAs. Simulation results shows that using one beamformer on each side is capable of detecting the DOAs of active sources under several acoustic scenarios, including scenarios with one, two, or three sources, and with or without the presence of some level of diffuse noise.

In certain applications involving direction of arrival (DOA) estimation the operator may have a-priori information on some of the DOAs. This information could refer to a target known to be present at a certain position or to a reflection. In this study, the authors investigate a methodology for array processing that exploits the information on the known DOAs for estimating the unknown DOAs as accurately as possible. Algorithms are presented that can efficiently handle the case of both correlated and uncorrelated sources when the receiver is a uniform linear array. The authors find a major improvement in estimator accuracy in feasible scenarios, and they compare the estimator performance to the corresponding theoretical stochastic Cramer-Rao bounds as well as to the performance of other methods capable of exploiting such prior knowledge. In addition, real data from an ultra-sound array is applied to the investigated estimators. / <p>QC 20130107</p>

No description available.

Zugl.: Hamburg, Techn. Univ., Diss., 2008

FundaÃÃo Cearense de Apoio ao Desenvolvimento Cientifico e TecnolÃgico / In this dissertation the problem of spatial signature and direction of arrival estimation in Linear 2L-Shape and Planar arrays is investigated Methods based on tensor decompositions are proposed to treat the problem of estimating blind spatial signatures disregarding the use of training sequences and knowledge of the covariance structure of the sources By assuming that the power of the sources varies between successive time blocks decompositions for tensors of third and fourth orders obtained from spatial and spatio-temporal covariance of the received data in the array are proposed from which iterative algorithms are formulated to estimate spatial signatures of the sources Then greater spatial diversity is achieved by using the Spatial Smoothing in the 2L-Shape and Planar arrays In that case the estimation of the direction of arrival of the sources can not be obtained directly from the formulated algorithms The factorization of the Khatri-Rao product is then incorporated into these algorithms making it possible extracting estimates for the azimuth and elevation angles from matrices obtained using this method A distinguishing feature of the proposed tensor methods is their efficiency to treat the cases where the covariance matrix of the sources is non-diagonal and unknown which generally happens when working with sample data covariances computed from a reduced number of snapshots / Nesta dissertaÃÃo o problema de estimaÃÃo de assinaturas espaciais e consequentemente da direÃÃo de chegada dos sinais incidentes em arranjos Linear 2L-Shape e Planar à investigado MÃtodos baseados em decomposiÃÃes tensoriais sÃo propostos para tratar o problema de estimaÃÃo cega de assinaturas espaciais desconsiderando a utilizaÃÃo de sequÃncias de treinamento e o conhecimento da estrutura de covariÃncia das fontes Ao assumir que a potÃncia das fontes varia entre blocos de tempos sucessivos decomposiÃÃes para tensores de terceira e quarta ordem obtidas a partir da covariÃncia espacial e espaÃo-temporal dos dados recebidos no arranjo de sensores sÃo propostas a partir das quais algoritmos iterativos sÃo formulados para estimar a assinatura espacial das fontes em seguida uma maior diversidade espacial à alcanÃada utilizando a tÃcnica Spatial Smoothing na recepÃÃo de sinais nos arranjos 2L-Shape e Planar Nesse caso as estimaÃÃes da direÃÃo de chegada das fontes nÃo podem ser obtidas diretamente a partir dos algoritmos formulados de forma que a fatoraÃÃo do produto de Khatri-Rao à incorporada a estes algoritmos tornando possÃvel a obtenÃÃo de estimaÃÃes para os Ãngulos de azimute e elevaÃÃo a partir das matrizes obtidas utilizando este mÃtodo Uma caracterÃstica marcante dos mÃtodos tensoriais propostos està presente na eficiÃncia obtida no tratamento de casos em que a matriz de covariÃncia das fontes à nÃo-diagonal e desconhecida o que geralmente ocorre quando se trabalha com covariÃncias de amostras reais calculadas a partir de um nÃmero reduzido de snapshots

Spectrum sharing has become increasingly important since the past decade due to the ongoing congestion of spectral resources. Higher data rates in wireless communications require expansion of existing frequency allocations. Significant research efforts have been made in the direction of cognitive radio to effectively manage the existing frequency usage. Recently, coexistence of multiple platforms within the same frequency bands is considered effective to mitigate spectral congestion. This requires both systems to work collaboratively to mitigate their mutual interference. This challenging problem can be significantly simplified if both systems are controlled by the same entity. Joint radar-communication (JRC) system is such an example where radar and communication system objectives are achieved by the same physical platform. In this dissertation, we consider three different types of JRC systems. These JRC systems respectively exploit a single transmit antenna, an antenna array for beamforming, and a distributed JRC network, and develop novel signal processing techniques to optimize the performance of these systems. Special attention is given to the resource optimization objectives and numerous resource allocation schemes are developed and investigated. First, we consider a single transmit antenna-based JRC system which exploits dual-purpose transmit orthogonal frequency division multiplexing (OFDM) waveforms to perform radar and communication objectives simultaneously. We optimize the power allocation of the OFDM subcarriers based on the frequency-sensitive target response and communication channel characteristics. For this purpose, we employ mutual information as the optimization metric. In the simulation examples considered for this system, we observed that the JRC system enjoys approximately 20\% improvement in the performance of communication subsystem with a mere 5\% reduction in radar subsystem performance. Second, we propose a quadratic amplitude modulation (QAM) based sidelobe modulation scheme for beamforming-based JRC systems which enhances the communication data rate by enabling a novel multiple access strategy. The main principle of this proposed strategy lies in enabling the beamformer to transmit signals with distinct amplitudes and phases in different directions. We also investigate optimal power allocation for such a spectrum sharing approach by employing a spatial power control-based beamforming approach. Furthermore, the robustness of these beamforming-based JRC systems is improved using chance constrained programming. In this context, we observe that the chance constrained optimization can be relaxed to form a deterministic and convex problem by employing the statistical profile of the communication channels. When dealing with JRC systems that are equipped with more antennas than the number of radio frequency chains, we perform the resource optimization in terms of minimized power usage and optimal selection of antennas resulting in an efficient utilization of hardware up-conversion chains. In the simulation examples considered for these schemes, we observe that, even with a reduction of nearly 30\% of the transmit antennas, the beamforming-based JRC system is able to perform the required radar and communication tasks without any disadvantage. Our last contribution is on a distributed JRC system, which is the first effort in this research direction, enabling spectrum sharing for networked radar systems coexisting with the communication systems. We devise a power allocation strategy for such a system by employing convex optimization techniques. In this strategy, the target localization error and the Shannon capacity are respectively considered as the optimization criteria for radar and communication systems. For the simulation example considered in this case, we observe that the proposed resource allocation strategy achieves a communication performance that was approximately 5 times greater than that achieved by the radar-only counterpart. Moreover, the target localization performance achieved by the JRC system using the proposed approach was approximately 4 times better than the performance achieved by the communication-only approach. / Electrical and Computer Engineering