On the indoor beamformer design with reverberation

Beamforming remains to be an important technique for signal enhancement. For applications in open space, the transfer function describing waves propagation has an explicit expression, which can be employed for beamformer design. However, the function becomes very complex in an indoor environment due to the effects of reverberation. In this paper, this problem is discussed. A method based on the image source method (ISM) is applied to model the room impulse responses (RIRs), which will act as the transfer function between source and sensor. The indoor beamformer design problem is formulated as a minimax optimization problem. We propose and study several optimization models based on the -norm to design the beamformer. We found that it is advantageous to separate early and late reverberations in the design process and better designs can be achieved. Several numerical experiments are presented using both simulated data and real recordings to evaluate the proposed methods

Array signal processing for source localization and enhancement

“A common approach to the wide-band microphone array problem is to assume a certain array geometry and then design optimal weights (often in subbands) to meet a set of desired criteria. In addition to weights, we consider the geometry of the microphone arrangement to be part of the optimization problem. Our approach is to use particle swarm optimization (PSO) to search for the optimal geometry while using an optimal weight design to design the weights for each particle’s geometry. The resulting directivity indices (DI’s) and white noise SNR gains (WNG’s) form the basis of the PSO’s fitness function. Another important consideration in the optimal weight design are several regularization parameters. By including those parameters in the particles, we optimize their values as well in the operation of the PSO. The proposed method allows the user great flexibility in specifying desired DI’s and WNG’s over frequency by virtue of the PSO fitness function. Although the above method discusses beam and nulls steering for fixed locations, in real time scenarios, it requires us to estimate the source positions to steer the beam position adaptively. We also investigate source localization of sound and RF sources using machine learning techniques. As for the RF source localization, we consider radio frequency identification (RFID) antenna tags. Using a planar RFID antenna array with beam steering capability and using received signal strength indicator (RSSI) value captured for each beam position, the position of each RFID antenna tag is estimated. The proposed approach is also shown to perform well under various challenging scenarios”--Abstract, page iv

Reduced complexity adaptive filtering algorithms with applications to communications systems

This thesis develops new adaptive filtering algorithms suitable for communications applications with the aim of reducing the computational complexity of the implementation. Low computational complexity of the adaptive filtering algorithm can, for example, reduce the required power consumption of the implementation. A low power consumption is important in wireless applications, particularly at the mobile terminal side, where the physical size of the mobile terminal and long battery life are crucial. We focus on the implementation of two types of adaptive filters: linearly-constrained minimum-variance (LCMV) adaptive filters and conventional training-based adaptive filters. For LCMV adaptive filters, normalized data-reusing algorithms are proposed which can trade off convergence speed and computational complexity by varying the number of data-reuses in the coefficient update. Furthermore, we propose a transformation of the input signal to the LCMV adaptive filter, which properly reduces the dimension of the coefficient update. It is shown that transforming the input signal using successive Householder transformations renders a particularly efficient implementation. The approach allows any unconstrained adaptation algorithm to be applied to linearly constrained problems. In addition, a family of algorithms is proposed using the framework of set-membership filtering (SMF). These algorithms combine a bounded error specification on the adaptive filter with the concept of data-reusing. The resulting algorithms have low average computational complexity because coefficient update is not performed at each iteration. In addition, the adaptation algorithm can be adjusted to achieve a desired computational complexity by allowing a variable number of data-reuses for the filter update. Finally, we propose a framework combining sparse update in time with sparse update of filter coefficients. This type of partial-update (PU) adaptive filters are suitable for applications where the required order of the adaptive filter is conflicting with tight constraints for the processing power.reviewe

Abstracts on Radio Direction Finding (1899 - 1995)

The files on this record represent the various databases that originally composed the CD-ROM issue of "Abstracts on Radio Direction Finding" database, which is now part of the Dudley Knox Library's Abstracts and Selected Full Text Documents on Radio Direction Finding (1899 - 1995) Collection. (See Calhoun record https://calhoun.nps.edu/handle/10945/57364 for further information on this collection and the bibliography). Due to issues of technological obsolescence preventing current and future audiences from accessing the bibliography, DKL exported and converted into the three files on this record the various databases contained in the CD-ROM. The contents of these files are: 1) RDFA_CompleteBibliography_xls.zip [RDFA_CompleteBibliography.xls: Metadata for the complete bibliography, in Excel 97-2003 Workbook format; RDFA_Glossary.xls: Glossary of terms, in Excel 97-2003 Workbookformat; RDFA_Biographies.xls: Biographies of leading figures, in Excel 97-2003 Workbook format]; 2) RDFA_CompleteBibliography_csv.zip [RDFA_CompleteBibliography.TXT: Metadata for the complete bibliography, in CSV format; RDFA_Glossary.TXT: Glossary of terms, in CSV format; RDFA_Biographies.TXT: Biographies of leading figures, in CSV format]; 3) RDFA_CompleteBibliography.pdf: A human readable display of the bibliographic data, as a means of double-checking any possible deviations due to conversion