Sensor array signal processing : two decades later

Caption title.Includes bibliographical references (p. 55-65).Supported by Army Research Office. DAAL03-92-G-115 Supported by the Air Force Office of Scientific Research. F49620-92-J-2002 Supported by the National Science Foundation. MIP-9015281 Supported by the ONR. N00014-91-J-1967 Supported by the AFOSR. F49620-93-1-0102Hamid Krim, Mats Viberg

Twenty-Five Years of Advances in Beamforming: From Convex and Nonconvex Optimization to Learning Techniques

Beamforming is a signal processing technique to steer, shape, and focus an electromagnetic wave using an array of sensors toward a desired direction. It has been used in several engineering applications such as radar, sonar, acoustics, astronomy, seismology, medical imaging, and communications. With the advances in multi-antenna technologies largely for radar and communications, there has been a great interest on beamformer design mostly relying on convex/nonconvex optimization. Recently, machine learning is being leveraged for obtaining attractive solutions to more complex beamforming problems. This article captures the evolution of beamforming in the last twenty-five years from convex-to-nonconvex optimization and optimization-to-learning approaches. It provides a glimpse of this important signal processing technique into a variety of transmit-receive architectures, propagation zones, paths, and conventional/emerging applications

Broadband, ultra-sparse array processing for low complexity multibeam sonar imaging

Imaging sonar systems have become increasingly popular in numerous applications associated with underwater imaging. Though multibeam sonar systems have been used in a variety of applications, the cost of these systems limits their use. The reason for the high costs has been identified to the use of large number of hydrophone array elements and hence large number of associated analogue channels and analogue-to-digital converters (ADC) that are required in high resolution imaging. In this thesis, an imaging sonar system has been developed with as few as four array elements to minimise cost. The inter-element spacing between any two array elements was chosen to be much greater than half the wavelength. In order to avoid phase ambiguity associated with wide array element spacing, the time difference of arrival is determined. Hence, for this purpose a wideband chirp signal was used. The return signals were divided into range cells to determine the target range. The time difference of arrival was obtained by correlating the range cells. Using the time difference of arrival, the direction of arrival (DOA) angle was calculated. The image of the target being illuminated was formed using the calculated range and the DOA values. The image pixel intensity at any pixel position was determined from the correlation result between the range cells. A simulation model was built to test the theory developed. Simulations were performed for various inter-element spacing and for four different target profiles types. Two objective metrics (signal to noise (SNR) ratio and peak signal to noise (PSNR) ratio) and a subjective metric (Structural Similarity (SSIM) index) were used to determine the performance of the algorithm and image quality. Image formed from the simulations using two hydrophone elements showed the presence of artefacts in the form of correlation sidelobes. The SNR metric showed a low gain of -5dB on comparison against a test image. PSNR and SSIM ratio showed a constant image quality over all the array spacing. The number of array elements was increased and linear operation like averaging was applied. The results showed no improvement in the gain and image quality. ii To overcome the problem of correlation sidelobes, a non-linear combining process has been proposed. Using the non-linear combining process it was found that the SNR showed an average gain of 10 dB on simulated data over the images formed without it. The PSNR and SSIM also showed a small increase in the image quality. The computational complexity of the proposed non-linear combining process was calculated by determining the number of multiplications and additions. The time taken to perform these operations on a SHARC ADSP 21261 chip was calculated theoretically. The calculations showed the feasibility of using this algorithm on a digital signal processing (DSP) hardware. An experimental prototype was built and performance was tested during sea trials. The data obtained was processed using a computer. The experimental results verified that the processing algorithm was effective in a practical system.EThOS - Electronic Theses Online ServiceUniversities UK : Newcastle UniversityGBUnited Kingdo

Imaging and counting of targets with a high resolution multibeam sonar

Includes abstract.Includes bibliographical references (p. 113-116).This dissertation pertains to the development of an imaging and counting system for a high resolution multibeam sonar. A mathematical model for the operation of the multibeam sonar is derived. The computational model is developed into a simulator for the multibeam sonar in MATLAB

Algorithms for propagation-aware underwater ranging and localization

Mención Internacional en el título de doctorWhile oceans occupy most of our planet, their exploration and conservation are one of the crucial research problems of modern time. Underwater localization stands among the key issues on the way to the proper inspection and monitoring of this significant part of our world. In this thesis, we investigate and tackle different challenges related to underwater ranging and localization. In particular, we focus on algorithms that consider underwater acoustic channel properties. This group of algorithms utilizes additional information about the environment and its impact on acoustic signal propagation, in order to improve the accuracy of location estimates, or to achieve a reduced complexity, or a reduced amount of resources (e.g., anchor nodes) compared to traditional algorithms. First, we tackle the problem of passive range estimation using the differences in the times of arrival of multipath replicas of a transmitted acoustic signal. This is a costand energy- effective algorithm that can be used for the localization of autonomous underwater vehicles (AUVs), and utilizes information about signal propagation. We study the accuracy of this method in the simplified case of constant sound speed profile (SSP) and compare it to a more realistic case with various non-constant SSP. We also propose an auxiliary quantity called effective sound speed. This quantity, when modeling acoustic propagation via ray models, takes into account the difference between rectilinear and non-rectilinear sound ray paths. According to our evaluation, this offers improved range estimation results with respect to standard algorithms that consider the actual value of the speed of sound. We then propose an algorithm suitable for the non-invasive tracking of AUVs or vocalizing marine animals, using only a single receiver. This algorithm evaluates the underwater acoustic channel impulse response differences induced by a diverse sea bottom profile, and proposes a computationally- and energy-efficient solution for passive localization. Finally, we propose another algorithm to solve the issue of 3D acoustic localization and tracking of marine fauna. To reach the expected degree of accuracy, more sensors are often required than are available in typical commercial off-the-shelf (COTS) phased arrays found, e.g., in ultra short baseline (USBL) systems. Direct combination of multiple COTS arrays may be constrained by array body elements, and lead to breaking the optimal array element spacing, or the desired array layout. Thus, the application of state-of-the-art direction of arrival (DoA) estimation algorithms may not be possible. We propose a solution for passive 3D localization and tracking using a wideband acoustic array of arbitrary shape, and validate the algorithm in multiple experiments, involving both active and passive targets.Part of the research in this thesis has been supported by the EU H2020 program under project SYMBIOSIS (G.A. no. 773753).This work has been supported by IMDEA Networks InstitutePrograma de Doctorado en Ingeniería Telemática por la Universidad Carlos III de MadridPresidente: Paul Daniel Mitchell.- Secretario: Antonio Fernández Anta.- Vocal: Santiago Zazo Bell