Applications of Array Signal Processing
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Design and Simulation of Smart Antenna Array Using Adaptive Beam Forming Method R
ISSN: 2319-5967 ISO 9001:2008 Certified International Journal of Engineering Science and Innovative Technology (IJESIT) Volume 3, Issue 6, November 2014 Design and Simulation of Smart Antenna Array Using Adaptive Beam forming Method R. Evangilin Beulah, N.Aneera Vigneshwari M.E., Department of ECE, Francis Xavier Engineering College, Tamilnadu (India) Abstract— This paper presents design of a smart antenna system based on direction-of-arrival estimation and adaptive beam forming. In order to obtain the antenna pattern synthesis for a ULA (uniform linear array) we use Dolph Chebyshev method. For the estimation of Direction-of-arrival (DOA) MUSIC algorithm (Multiple User Signal Classification) is used in order to identify the directions of the source signals incident on the antenna array comprising the smart antenna system. LMS algorithm is used for adaptive beam forming in order to direct the main beam towards the desired source signals and to adaptively move the nulls towards the unwanted interference in the radiation pattern. Thereby increasing the channel capacity to accommodate a higher number of users. The implementation of LMS algorithm helps in improving the following parameters in terms of signal to noise ration, convergence rate, increased channel capacity, average bit error rate. In this paper, we will discuss and analyze about the DolphChebyshev method for antenna pattern synthesis, MUSIC algorithm for DOA (Direction of Arrival) estimation and least mean squares algorithm for Beam forming. Index Terms—Uniform Linear Array (ULA), Direction of Arrival (DOA), Multiple User Signal Classification (MUSIC), Least Mean Square (LMS). I. INTRODUCTION A smart antenna has the ability to diminish noise, increase signal to noise ratio and enhance system competence [1]. -
Coarrays, MUSIC, and the Cramér Rao Bound
1 Coarrays, MUSIC, and the Cramer´ Rao Bound Mianzhi Wang, Student Member, IEEE, and Arye Nehorai, Life Fellow, IEEE Abstract—Sparse linear arrays, such as co-prime arrays and ESPRIT [17]) via first-order perturbation analysis. However, nested arrays, have the attractive capability of providing en- these results are based on the physical array model and hanced degrees of freedom. By exploiting the coarray structure, make use of the statistical properties of the original sample an augmented sample covariance matrix can be constructed and MUSIC (MUtiple SIgnal Classification) can be applied to covariance matrix, which cannot be applied when the coarray identify more sources than the number of sensors. While such model is utilized. In [18], Gorokhov et al. first derived a a MUSIC algorithm works quite well, its performance has not general MSE expression for the MUSIC algorithm applied been theoretically analyzed. In this paper, we derive a simplified to matrix-valued transforms of the sample covariance matrix. asymptotic mean square error (MSE) expression for the MUSIC While this expression is applicable to coarray-based MUSIC, algorithm applied to the coarray model, which is applicable even if the source number exceeds the sensor number. We show that its explicit form is rather complicated, making it difficult to the directly augmented sample covariance matrix and the spatial conduct analytical performance studies. Therefore, a simpler smoothed sample covariance matrix yield the same asymptotic and more revealing MSE expression is desired. MSE for MUSIC. We also show that when there are more sources In this paper, we first review the coarray signal model than the number of sensors, the MSE converges to a positive commonly used for sparse linear arrays. -
Prof. Peter Westervelt WHOI Ocean Acoustics Nov. 15, 2006
Prof. Peter Westervelt WHOI Ocean Acoustics Nov. 15, 2006 PART 1 Intro-This is a weekly gathering of the Ocean Acoustics Laboratory; this is a part of the Department Applied Ocean Physics and Engineering here at the Institution. Of course this is a very special occasion; I'm very pleased to welcome you to our Institution. Glad to be here. Don't recognize it but I was here very early on, forty years ago, when they dedicated one of the labs. Intro-This is the first and the oldest of the buildings, we have of the order of sixty buildings at the Institution, but Bigelow Laboratory is the first, built in 1930 and apparently the donors, the Rockefeller Brothers, were later asked about the donation to the Institution and they expressed surprise, they didn't recall it, they didn't know why they were asked! The influence of Brown University has been genuinely profound in many ways, it continues to be and there was a celebration of Brown University Physics at the Acoustical Society of America meeting in Providence in June, quite a turn out. Of course the Physics Department is also a profound personal influence for several of us and many colleges that we work with also. Your work has already been described to the group. But, its actually been very enlightening to take a ramble through some of the literature you're responsible for concerned with scattering with sound by sound and parametric acoustic array, absorption of sound by sound. A favorite later theme of course was non-scattering of sound by sound. -
Contribution of the Conditioning Stage to the Total Harmonic Distortion in the Parametric Array Loudspeaker
Universidad EAFIT Contribution of the conditioning stage to the Total Harmonic Distortion in the Parametric Array Loudspeaker Andrés Yarce Botero Thesis to apply for the title of Master of Science in Applied Physics Advisor Olga Lucia Quintero. Ph.D. Master of Science in Applied Physics Science school Universidad EAFIT Medellín - Colombia 2017 1 Contents 1 Problem Statement 7 1.1 On sound artistic installations . 8 1.2 Objectives . 12 1.2.1 General Objective . 12 1.2.2 Specific Objectives . 12 1.3 Theoretical background . 13 1.3.1 Physics behind the Parametric Array Loudspeaker . 13 1.3.2 Maths behind of Parametric Array Loudspeakers . 19 1.3.3 About piezoelectric ultrasound transducers . 21 1.3.4 About the health and safety uses of the Parametric Array Loudspeaker Technology . 24 2 Acquisition of Sound from self-demodulation of Ultrasound 26 2.1 Acoustics . 26 2.1.1 Directionality of Sound . 28 2.2 On the non linearity of sound . 30 2.3 On the linearity of sound from ultrasound . 33 3 Signal distortion and modulation schemes 38 3.1 Introduction . 38 3.2 On Total Harmonic Distortion . 40 3.3 Effects on total harmonic distortion: Modulation techniques . 42 3.4 On Pulse Wave Modulation . 46 4 Loudspeaker Modelling by statistical design of experiments. 49 4.1 Characterization Parametric Array Loudspeaker . 51 4.2 Experimental setup . 52 4.2.1 Results of PAL radiation pattern . 53 4.3 Design of experiments . 56 4.3.1 Placket Burmann method . 59 4.3.2 Box Behnken methodology . 62 5 Digital filtering techniques and signal distortion analysis. -
The Impact of Sensor Positioning on the Array Manifold Adham Sleiman, Student Member, IEEE, and Athanassios Manikas, Senior Member, IEEE
IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION, VOL. 51, NO. 9, SEPTEMBER 2003 2227 The Impact of Sensor Positioning on the Array Manifold Adham Sleiman, Student Member, IEEE, and Athanassios Manikas, Senior Member, IEEE Abstract—A framework is presented in this study which the importance or relevance of a sensor’s position in the array analyzes the importance of each sensor in an antenna array for an application-specific criterion in the area of detection and based on its location in the overall geometry. Moving away from resolution capabilities of the array have been investigated in [1], the conventional methods of measuring sensor importance by means of application-specific criteria, a new approach, based [2]. Other criteria have lead to the design of arrays with the aim on the array manifold and its differential geometry, is used to of maximizing the mainlobe to sidelobe ratio while minimizing measure the significance of each sensor’s position in an array. By the 3 dB range of the mainlobe through Fourier, Dolph–Cheby- considering two-dimensional manifolds (function of azimuth and shev, Taylor and other synthesis techniques [3]–[8]. elevation angles) of planar arrays of isotropic sensors, and by using previously established results on the differential geometry By realising that the performance of an array system under a of such manifolds, a sensitivity analysis is performed which specific application is closely related to the manifold subtended leads to characterization and quantification of sensor location by this array, it becomes apparent that the importance of a sensor importance in an array geometry. Based on this framework, a criterion is developed for assessing an overall geometry. -
University of Cincinnati
UNIVERSITY OF CINCINNATI _____________ , 20 _____ I,______________________________________________, hereby submit this as part of the requirements for the degree of: ________________________________________________ in: ________________________________________________ It is entitled: ________________________________________________ ________________________________________________ ________________________________________________ ________________________________________________ Approved by: ________________________ ________________________ ________________________ ________________________ ________________________ Digital Direction Finding System Design and Analysis A thesis submitted to the Division of Graduate Studies and Research of the University of Cincinnati in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE (M.S.) in the Department of Electrical & Computer Engineering and Computer Science of the College of Engineering 2003 by Huazhou Liu B.E., Xi’an Jiaotong University P. R. China, 2000 Committee Chair: Professor Howard Fan ABSTRACT Direction Finding (DF) system is used in many military and civilian operations such as surveillance, reconnaissance, and rescue, etc. In the past years, direction finding system is implemented usually using analog RF techniques such as Butler matrix and analog beamforming. Analog direction finding systems have drawbacks inherent from their analog properties such as expensive implementation, inflexibility to adjust or change functionality, intensive calibration procedures and -
Iterative Sparse Asymptotic Minimum Variance Based Approaches For
1 Iterative Sparse Asymptotic Minimum Variance Based Approaches for Array Processing Habti Abeida∗, Qilin Zhangy, Jian Liz and Nadjim Merabtinex ∗Department of Electrical Engineering, University of Taif, Al-Haweiah, Saudi Arabia yDepartment of Computer Science, Stevens Institue of Technology, Hoboken, NJ, USA zDepartment of Electrical and Computer Engineering, University of Florida, Gainesville, FL, USA xDepartment of Electrical Engineering, University of Taif, Al-Haweiah, Saudi Arabia Abstract This paper presents a series of user parameter-free iterative Sparse Asymptotic Minimum Variance (SAMV) approaches for array processing applications based on the asymptotically minimum variance (AMV) criterion. With the assumption of abundant snapshots in the direction-of-arrival (DOA) estimation problem, the signal powers and noise variance are jointly estimated by the proposed iterative AMV approach, which is later proved to coincide with the Maximum Likelihood (ML) estimator. We then propose a series of power-based iterative SAMV approaches, which are robust against insufficient snapshots, coherent sources and arbitrary array geometries. Moreover, to over- come the direction grid limitation on the estimation accuracy, the SAMV-Stochastic ML (SAMV-SML) approaches are derived by explicitly minimizing a closed form stochastic ML cost function with respect to one scalar parameter, eliminating the need of any additional grid refinement techniques. To assist the performance evaluation, approximate solutions to the SAMV approaches are also provided at high signal-to-noise ratio (SNR) and low SNR, respectively. Finally, numerical examples are generated to compare the performance of the proposed approaches with existing approaches. Index terms: Array Processing, AMV estimator, Direction-Of-Arrival (DOA) estimation, Sparse parameter estima- tion, Covariance matrix, Iterative methods, Vectors, Arrays, Maximum likelihood estimation, Signal to noise ratio, SAMV approach. -
Directional Steering of Audio Signal Using Parametric Array in Air
International Journal of Engineering Research & Technology (IJERT) ISSN: 2278-0181 Vol. 3 Issue 1, January - 2014 Directional Steering of Audio Signal Using Parametric Array in Air Sreedhu T Sasi, Anaswara V Nath, Archana V R College of Engineering,Cherthala Abstract directly on the wall without the need for a mechanical pan-and-tilt system. Directional Audio is very recent technology that creates . focused beams of sound .By projecting sound to one location, 2. Prior art specific listeners can be targeted with sound without other In 1963, Westervelt described how an audible nearby hearing it.The parametric loudspeaker provides an difference frequency signal is generated from two high- effective means of projecting sound in a highly directional frequency collimated beams of sound. These high- manner without using large loudspeaker arrays to form sharp frequency sound beams are commonly referred to as primary waves. The nonlinear interaction of primary directional beams.Development of parametric loudspeaker in waves in mediums (such as air and water) produces an many public places reduce noise pollution.Digital Signal end-fire array of virtual acoustics sources that is Processing plays a significant role in enhancing the aural referred to as the parametric array. The primary interest quality of the parametric loudspeakers,and array processing for the parametric array focuses on the difference- can help to shape and steer the beam electronic electronically. frequency signal that is being created along the axis of the main beam (or virtual end-fire array) at the speed of 1. Introduction sound. This phenomenon results in a sharp directional he controllable audible sound can greatly reduce sound beam of audible signal. -
An Overview of Smart Antenna and a Survey on Direction of Arrival Estimation Algorithms for Smart Antenna
IOSR Journal of Electronics and Communication Engineering (IOSR-JECE) ISSN : 2278-2834, ISBN : 2278-8735, PP : 01-06 www.iosrjournals.org An Overview Of Smart Antenna And A Survey On Direction Of Arrival Estimation Algorithms For Smart Antenna 1 2 Mrs. Mane Sunita Vijay , Prof. Dr. Bombale U.L. 1(Assist. Prof., Electronics Department, KBP College of Engineering, Satara/ Shivaji University,India) 2(Associate Prof., Technology Department, Shivaji University, Kolhapur, India) ABSTRACT : Smart Antenna Systems is one of the most rapidly developing areas of communication. With effective direction of arrival (DOA) and Beam forming techniques Smart Antenna Systems prove to be most efficient in terms of quality of signals in wireless communication. In this paper a brief overview of Smart Antenna along with a survey on high resolution direction of arrival estimation algorithms for array antenna systems is presented and compared for different parameters. It can help one understand the effectiveness of the DOA algorithms over others under certain parametric conditions. Keywords - Antenna array, DOA estimation, ESPRIT, MUSIC ,Smart antenna. 1. INTRODUCTION 1.1 Smart Antenna System: A smart antenna system combines multiple antenna elements with a signal processing capability to optimize its radiation and/or reception pattern automatically in response to the signal environment. Smart Antenna systems are classified on the basis of their transmit strategy, into the following three types (“levels of intelligence”): • Switched Beam Antennas • Dynamically-Phased Arrays • Adaptive Antenna Arrays 1.1.1 Switched Beam Antennas: Switched beam or switched lobe antennas are directional antennas deployed at base stations of a cell. They have only a basic switching function between separate directive antennas or predefined beams of an array. -
Beam Forming in Smart Antenna with Improved Gain and Suppressed Interference Using Genetic Algorithm
Cent. Eur. J. Comp. Sci. • 2(1) • 2012 • 1-14 DOI: 10.2478/s13537-012-0001-0 Central European Journal of Computer Science Beam forming in smart antenna with improved gain and suppressed interference using genetic algorithm Research Article T. S. Ghouse Basha1∗, M. N. Giri Prasad2, P.V. Sridevi3 1 K.O.R.M.College of Engineering, Kadapa, Andhra Pradesh, India 2 J.N.T.U.College of Engineering, Anantapur, Andhra Pradesh, India 3 Department of ECE, AU College of Engineering, Andhra University, Visakha Patnam, Andhra Pradesh, India Received 21 September 2011; accepted 18 November 2011 Abstract: The most imperative process in smart antenna system is beam forming, which changes the beam pattern of an antenna for a particular angle. If the antenna does not change the position for the specified angle, then the signal loss will be very high. By considering the aforesaid drawback, here a new genetic algorithm based technique for beam forming in smart antenna system is proposed. In the proposed technique, if the angle is given as input, the maximum signal gain in the beam pattern of the antenna with corresponding position and phase angle is obtained as output. The length of the beam, interference, phase angle, and the number of patterns are the factors that are considered in our proposed technique. By using this technique, the gain of the system gets increased as well as the interference is reduced considerably. The implementation result exhibits the efficiency of the system in beam forming. Keywords: smart antenna • beam forming • genetic algorithm (GA) • phase angle • main beam © Versita Sp. -
Frontmatter: SENSOR ARRAY SIGNAL PROCESSING
SENSOR ARRAY SIGNAL PROCESSING SENSOR ARRAY SIGNAL PROCESSING Prabhakar S. Naidu CRC Press Boca Raton London New York Washington, D.C. 1195/Disclaimer Page 1 Monday, June 5, 2000 3:20 PM Library of Congress Cataloging-in-Publication Data Naidu, Prabhakar S. Sensor array signal processing / Prabhakar S. Naidu. p. cm. Includes bibliographical references and index. ISBN 0-8493-1195-0 (alk. paper) 1. Singal processing–Digital techniques. 2. Multisensor data fusion. I. Title. TK5102.9.N35 2000 621.382'2—dc21 00-030409 CIP This book contains information obtained from authentic and highly regarded sources. Reprinted material is quoted with permission, and sources are indicated. A wide variety of references are listed. Reasonable efforts have been made to publish reliable data and information, but the author and the publisher cannot assume responsibility for the validity of all materials or for the consequences of their use. Neither this book nor any part may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, microfilming, and recording, or by any information storage or retrieval system, without prior permission in writing from the publisher. The consent of CRC Press LLC does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific permission must be obtained in writing from CRC Press LLC for such copying. Direct all inquiries to CRC Press LLC, 2000 N.W. Corporate Blvd., Boca Raton, Florida 33431. Trademark Notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation, without intent to infringe. -
Evaluation of MUSIC Algorithm for DOA Estimation in Smart Antenna
IARJSET ISSN (Online) 2393-8021 ISSN (Print) 2394-1588 International Advanced Research Journal in Science, Engineering and Technology Vol. 3, Issue 5, May 2016 Evaluation of MUSIC algorithm for DOA estimation in Smart antenna Banuprakash.R1, H.Ganapathy Hebbar2, Sowmya.M3, Swetha.M4 Assistant Professor, Department of TE, BMS Institute of Technology and Management, Bengaluru, India1,2 Final Year Students, Department of TE, BMS Institute of Technology and Management, Bengaluru, India3,4 Abstract: This paper presents a simulation study of a smart antenna system on basis of direction-of-arrival estimation for identifying the direction of desired signal using Multiple Signal Classification (MUSIC) algorithm. In recent times smart antennas are gaining more popularity by increasing user capacity, achieved by effectively reducing interference. In this paper, performance and resolution analysis of the algorithm is made. Its sensitivity to various perturbations and the effect of parameters such as the number of array elements and the spacing between them which are related to the design of the array sensor are investigated. The analysis is based on uniform linear array antenna and the calculation of the pseudo spectrum function of the algorithm. MATLAB is used for simulating the algorithm. Keywords: Smart antenna, DOA, MUSIC, Pseudo spectrum, MATLAB. I. INTRODUCTION 1.1 DOA ESTIMATION ALGORITHM DOA is a research area in array signal processing and The requirement of mobile communication resources has many engineering application such as radar, radio been increased rapidly over few years. The smart astronomy, sonar and other emergency assistance devices techniques or adaptive beamforming techniques have been that need to be supported by estimation of DOA[2].